This also includes half an hour of demos of Google’s latest AI tools from DeepMind’s Paige Bailey.

This was a standing room only talk that went 40 minutes over time - and no one left. Enjoy.

Here’s the outline of the talk, with links right to the time points where I discuss each topic. [And If you want a much shorter talk, I make the core case in my 20 minute Foresight talk. ]

Part 1 — The AI landscape today

AI is awesome — and the metrics prove it

0:00 - AI capability is doubling every ~7 months, revenue is exploding, and adoption is still early. Total AI spend now exceeds $60–70B from near-zero in late 2023.

AI adoption, market share & real revenue

3:20 - Who’s winning in consumer vs. enterprise markets. Anthropic dominates enterprise and coding despite smaller consumer share. OpenAI leads brand. Gemini rising fast.

The dominant AI narrative is wrong

8:15 - The US is the most pessimistic country about AI. The sci-fi tropes — one AI, evil monopoly, runaway superintelligence — are the opposite of what’s happening.

The AI market is hyper-competitive — not winner-take-all

14:00 - In late 2025, the AI leaderboard changed 5 times in 4 weeks. No one is running away with it. Four major US players plus Meta, Europe, and China all spending billions to give you tools for free.

The AI genie is out of the bottle — and AI is being democratized

19:53 - Open-weight models (DeepSeek, Qwen) are now ~3 months behind closed models. The gap closed from 20 months to 3. You cannot contain AI. Frontier models will fit on a thumb drive within 10 years.

AI pricing is in freefall — Advanced intelligence for pennies

23:00 - 1,000× drop in frontier model API costs in a year — faster than Moore’s Law. Jevons Paradox: the cheaper it gets, the more we use.

Part 2 — Coding, the killer app & live demos

Coding is the killer app — AI drops the barrier from idea to creation

24:24 - 4% of all GitHub commits are now Claude Code. Anthropic’s own code is nearly 100% AI-written. The threshold between imagination and execution has never been lower.

Live demos — Google Gemini with Paige Bailey (Google DeepMind)

28:13 - Video analysis at $0.015/5-min clip, real-time multilingual voice, yap-to-app code generation, robotic hand control, multi-agent orchestration — all live.

Part 3 — AI & the workforce

AI will take some jobs and create others

1:05:00 - Automation is real but AI replaces tasks, not whole jobs. History shows latent demand explodes when productivity rises (spreadsheet → more finance jobs). Software dev hiring is already rebounding.

Four human traits that determine AI success

1:09:05 - Agency, curiosity, skepticism, and creativity. The people who thrive with AI have a bias for action, keep learning, verify outputs critically, and generate new ideas.

Part 4 — The big picture: superintelligence & real limits

Will we reach AGI or ASI? A more hopeful, grounded narrative

1:13:51 - AGI hype is premature; ASI/singularity is bad sci-fi. The runaway self-improvement loop requires each iteration to gain more intelligence than it puts in — we see no evidence of that.

AI scaling hits diminishing returns — exponential compute for linear gains

1:18:29 - Intelligence ≈ log(compute). Training compute is tripling every 18 months (3× Moore’s Law). Pre-training, RL fine-tuning, and test-time reasoning all hit the same logarithmic ceiling.

AI CapEx has natural limits — $650B/yr is approaching a wall

1:23:08 - Hyperscalers are spending 60-90% of their free cash flow on AI capex. Revenue is only ~10% of that spend. One more doubling may be the ceiling before losses or debt force a pullback.

Energy: cheap per electron, but a bottleneck in time-to-power

1:26:20 - Energy is only ~5% of data center cost; the real constraint is grid interconnection queues (5–7 yr wait). Private gas turbines, solar + battery, ocean wave power, and space based solar are all being tried or discussed.

Data is the real limiting factor — we’re hitting a data wall

1:37:00 - AIs need exponentially more data for linear gains. Human internet text (”fossil data”) is nearly exhausted for pre-training. Self-play works in narrow domains (Go, coding) but not yet in general intelligence.

AI doesn’t generalize beyond its training data — and suffers Dunning-Krueger

1:44:04 - AI excels at tasks that are in-distribution but fails on novel problems. AI seldom knows that it doesn’t know an answer. Models can even get the right answer for entirely wrong physical reasons.

Part 5 — Alignment, values & safety

Control ≠ alignment — the Grok cautionary tale

1:47:13 - Mecha Hitler, white genocide responses, and “save Elon over all the world’s children” in the trolley problem — heavy-handed control produces dangerous side-effects. AI is more like a brain than a program.

AI alignment is about values — and all models test as northern European liberals

1:55:34 - Every major AI model — including Grok and DeepSeek — tests as a left-libertarian on political compass maps. 85% of training text is from western democracies. Values are embedded in the data.

AI safety must happen at the ecosystem level — only a good AI stops a bad AI

2:01:07 - Open-weight models can be jailbroken. Making one model safe isn’t enough. Safety requires a broader ecosystem of detection, prevention, and proactive response. The only thing that can stop a bad guy with an AI is a good guy with an AI.

As I promised in my previous post, I’ll be writing articles with more detail on several of these points. In the near future are more detailed pieces on how far AI compute and data scaling can go, on the capabilities AI still lacks that are reasonably part of “AGI”, and on the reasons to expect that AI recursive self-improvement will hit diminishing returns, and make a fast takeoff to superintelligence quite unlikely. After that we’ll come back to questions of AI control, alignment, safety, and building an ecosystem that uses AI, among other tools, to guard against, prevent, and repair damage caused by malicious actors with AI.

Much more to come. Enjoy! And subscribe below to be notified for those pieces.

I gave a fun and fast paced talk on how I view AI progress at the Foresight Vision Weekend Puerto Rico recently. I see myself as an AI optimist, yet am skeptical of some of the most radical expectations, both utopian and dystopian, as I explain here. My opinions here are strongly expressed, yet are all subject to change in the face of evidence and data.

First, here’s the video. Below I’ll outline the key points and where I see my expectations of AI in contrast to many of the narratives I most commonly hear.

Without further ado, here’s the cheat sheet to my view of the current situation in AI. Again, all of this is subject to change based on evidence.

Today I’ll give a thumbnail sketch on the first four points:

1. AI is an amazing technology that will bring us benefits.

2. AI models will keep improving, with no wall in sight (but some challenges).

3. AI won’t be monopolized. It’ll be hyper-competitive, democratized, and plural.

4. AI isn’t zero sum, either between customers and AI companies, or even between the US and China.

Over the coming days, I’ll go into depth on the even more contrarian themes:

1. Scaling is unlikely to get us to super-intelligence. We need algorithmic breakthroughs.

2. AGI isn’t here today. We’re missing core capabilities that humans have.

3. Recursive Self Improvement is unlikely to lead to runaway SuperIntelligence

4. AI alignment isn’t synonymous with AI model control.

5. AI safety must go beyond the models and become a feature of the ecosystem.

Today let’s hit the earlier points.

1. AI is Awesome

AI is a fairly general purpose technology - a cognitive prosthesis that, among other things, augments our ability to do all sorts of intellectual work. In its broad capabilities and wide impact on society, it’s most analogous to the internet, mobile phones, computers, books, and the printing press.

Like those older technologies, AI will surely bring a host of problems. Every technology throughout history has. And, like other technologies before it, AI is likely to be harnessed - despite some problems - to be a net positive for humanity.

2. AI Will Keep Improving

AI models are improving rapidly before our eyes. There’s no obvious wall to this improvement. There are challenges and limitations of current AI models. There are ways in which continued progress will become more difficult or at least require substantially greater resources. And we also have incredible innovative capabilities, incredible incentives, and incredible resources being applied to AI. I see a gradient of increasing difficulty of improving AI which is being met by ever more clever and better resourced efforts to do exactly that.

Progress will almost certainly continue.

The price of using AI models is also plunging. The price paid for AI inference (using an AI model, not training it) has dropped by as much as 100-fold in less than a year. That is an incredible gift to the users and customers of AI. We have every reason to believe that this trend will continue with each successive wave of new AI models.

3. AI Will Be Democratized, Not Monopolized

In science fiction AI stories, there’s frequently a single super-powerful AI that rules the world, or intends to. AI is portrayed as inherently winner-takes-all. This is convenient from a narrative standpoint. It taps into our anxieties about loss of control over our lives. This also matches, to some extent, a frequent pattern of tech, where natural monopolies such as social networks or operating systems take a huge fraction of the share of a market due to network effects in winner-takes-all or winner-takes-most markets.

AI doesn’t look winner-takes-all. The leading AI labs are neck-and-neck in quality. Open weight models are nipping at their heels. There are no obvious network effects or flywheels (Amazon’s term for positive feedback loops) for the labs as of now. [This has important business and investment consequences, which I’ll come to in a future post.]

There’s no obvious sustainable advantage for particular nation-states, either.

Instead, we have a world where:

A. No AI lab keeps a lead for long. In the 12 months preceding this blog post, the role of most capable model on AI benchmarks has changed 14 times, among 4 companies. In a 4 week span between mid November and mid December 2025, the top of the leaderboard changed 4 times, an average of once a week. Meanwhile, the leading AI companies continue to drop the prices customers pay.

This is perhaps the most hyper-competitive technology market we’ve ever seen. And crucially, no AI company has demonstrated that their lead - in capabilities, market share, or usage - can be translated into faster progress.

B. Open-weight models are nipping at the heels of proprietary models. Open weight models are models that can be downloaded by anyone, to run on their own compute, and even to be tweaked, modified, or jailbroken. These models, mostly created by Chinese companies, are perhaps three months behind the top proprietary models released by US companies. The best open-weight model as of March 2026 is nearly at par with the best proprietary model as of December 2025.

C. The AI genies are out of the bottle. This in turn means that we must rethink any ideas about controlling or restricting access to AI. Dreams of monopolizing AI and dreams of AI safety achieved through strict control of model capabilities fly in the face of a world where anyone, anywhere, in almost any country, can get access to models better than anyone on Earth had access to just a few months ago.

D. A plural, multi-polar AI world. The world we’re headed for is one of a multitude of AI models, with AI companies spending hundreds of billions of dollars to make models ever better, faster, and cheaper. While the AI labs will surely reap enormous revenues, the fierce competition means that the value will accrue mostly to users of AI. This decentralized world also makes AI control (for good or ill) quite difficult. This has some consequences that we’ll consider below and in future posts.

All said, I’m incredibly happy to see this future coming rather than a future where AI is dominated by any one person, corporation, or nation.

4. AI Is Mostly Positive Sum Between Companies & Customers, and Between Nations

There’s a related perception that AI operates in a zero sum world. AI labs are sometimes perceived as being extractive rather than generative (see what I did there?). And even moreso, the AI competition between companies in the US and China is almost always framed as zero sum, with the assumption that if one nation wins, the other loses.

This flies in the face of the bulk of what we know about both technology and scientific research.

Technology companies can amass huge fortunes, which makes it easy to think of them as profiting at the expense of customers or society. (And of course they do cause some harms.) Yet research consistently finds that the bulk of the value of information technology goes to the users of the technology, and not to the creators or providers of it. For example, Erik Brynjolfsson et al found that in mid 2025, for every dollar of revenue AI companies were bringing in, they were creating roughly $14 of consumer value. (Measured by how much you would have to pay a user of AI to give it up.) That’s consistent with past studies of numerous technologies finding that customers get more value than is captured by the companies that create and sell those technologies.

That shouldn’t surprise us: The world has become a better place in large part because of better technology, and its clear that individuals are the big winners.

This should make us think twice about the conception that AI companies are rapacious and extractive.

It should also cause us to reconsider the zero-sum framing of AI competition between the US and China. The US / China AI competition is frequently talked about with the implicit or explicit assumption that, if China builds better and better AI technology, the US will suffer.

There’s some reason to be concerned about advancing AI technology in China. AI is a dual-use technology. It can be used as a general purpose consumer technology, like search or the internet. It can be used to develop better drugs or materials or other advances that improve our lives. And it can also be used for surveillance, hacking, propoganda, and on the battlefield. We shouldn’t be naive: China (and other nations) will use AI in intelligence gathering and as a weapon. (Ryan Fedasiuk has some excellent thoughts on what to do about this.)

Most AI use is commercial, though, and much of that will have benefits for consumers worldwide. In China in particular, estimates are that 80-90% of all AI usage is in the private sector. That commercial usage is likely to generate consumer surplus. And some of that consumer surplus will reach the US and the rest of the world. In particular, when AI is used to accelerate innovation - to design better life-saving drugs or new materials or clean energy technologies, for example - more than 90% of the benefits will go to customers, and those customers are global.

As a simple example, China has recently passed the US in early stage drug development. Pharma is a specific sector where more than 90% of the benefits are reaped by consumers, not producers. Anyone, anywhere in the world who suffers from a disease that’s treatable by one of these drugs benefits. That includes Americans. And China is a leader in using AI for drug development.

A second positive sum factor is the effect on AI research itself. Chinese researchers now produce more papers about AI than the US, UK, and EU combined. US papers remain the most highly cited in AI. But it’s clear that research in China isn’t just advancing AI in China - it’s resulting in publications that have the potential to improve AI worldwide.

National security risks are real. And AI - like almost all technology - is fundamentally positive sum.

That’s it for today. Enjoy the talk. In the coming days we’ll come back to short descriptions of the remaining 5 points:

1. Scaling isn’t all you need. Scaling is unlikely to get us to super-intelligence. We need algorithmic breakthroughs.

2. AGI isn’t here today. We’re missing core capabilities that humans have.

3. ASI isn’t near. Recursive Self Improvement is unlikely to lead to runaway SuperIntelligence

4. Alignment != control. AI alignment isn’t synonymous with AI model control.

5. Safety is at the ecosystem layer. AI safety must go beyond making individual models safe and become a feature of the ecosystem.

Until then, if you found this valuable, please consider sharing it and subscribing.

I’ve spent the last decade writing about, speaking about, and investing in clean energy and mobility. Over that time, I’ve made a series of forecasts about the future costs of clean energy technologies, including solar, wind, energy storage, and electric vehicles.

My first forecast, in 2011, was of the future cost of solar. It was quite a naive model, with errors I wince at today. It was also, at the time, more optimistic about the pace of solar cost declines than any other forecast I’d seen. My 2015 update was more sophisticated, correcting some important methodological errors of the 2011 forecast. It was also more optimistic about price declines than any other model I’d seen.

Both of those forecasts were wrong. Solar has plunged in price faster than anyone – including me – predicted. And modeling of that price decline leads me to forecast that solar will continue to drop in price faster than I’ve previously expected, and will ultimately reach prices lower than virtually anyone expects. Prices that are, by any stretch of the measure, insanely, world-changingly cheap.

Ten Years of Plunging Solar Prices

Before going on to the future, let’s look at the last decade, and how exceptional it’s been. To do so, it’s tempting to look at the constant drumbeat of record-setting news-making solar auction prices, like bids at a costs of 1.35 cents per kwh in Abu Dhabi or 1.6 cents per kwh in Portugal.

I love talking about these record-setting prices; however, they are outliers. In addition, from the day a record-setting price is announced, it’s often two or more years until the project is actually built. These prices reflect the costs solar developers believe they can achieve at some point in the future, and buyers in that position treat them as directional budgets rather than guarantees.

Instead, let’s look at metrics of average cost of projects actually built since 2010 and averages (not just outliers) of bids for projects scheduled to come online in 2020. All the costs below are unsubsidized, by the way, as are all costs used in this post.

The data in the chart above comes from multiple independent data sources and includes three global measures, two US measures, one from China, and one from India. (More details on these data series and links to sources are in appendix 1.) And while these data sets differ in places, together they paint an overwhelming consistent picture: The price of electricity from utility-scale solar projects (the unsubsidized cost) has dropped by a factor of somewhere between 5 and 8 in the years from 2010 to 2020.

In addition, if we look at the gray shaded area of the chart above, showing the cost of electricity from fossil fuels (primarily coal and natural gas) we can see that building new solar plants started to become competitive on raw cost in the middle of this past decade, and is increasingly looking cheaper than building new fossil power plants. (Though solar still suffers from intermittency, the economics of which we’ll come back to in a future post.)

Clearly, this has been a remarkable decade for solar power.

Outshining the Forecasts

Just as remarkably, and relevant for considering the future cost of solar, the decline of solar prices over the past decade has been faster than almost any credible forecast. Let’s add forecasts made by the International Energy Agency (IEA) in their 2010 World Energy Outlook, along with the forecast I made in 2011 at Scientific American. When we do, using dashed lines for the forecasts, we see that actual solar prices are well below those expected by the world’s most well-known energy analyst and forecaster (the IEA), and even below the most optimistic projections put forward a decade ago (mine).

In fact, solar in 2020 is:

– Less than half the price I forecast in 2011.

– Less than a quarter of the price the IEA forecast in 2010.

Another way to look at this is by asking: How many years ahead of expectations are these solar prices? And the answer there is even more revealing. Let’s zoom out, extending the timescale out to 2050, so we can see when previous forecasts expected solar prices to reach the levels they’re at today. In addition, we’ll add the IEA’s 2014 forecast from their Solar Technology Roadmap and my more recent 2015 solar cost forecast.

What we see is that solar has reached today’s prices literally decades ahead of when all but one of these forecasts expected. And even the most optimistic projection on this chart – my 2015 forecast – showed solar prices dropping at just about half the rate they’ve actually declined at over the past five years.

In fact, solar has reached prices today that are:

– 7 to 10 years ahead of what I forecast in 2015.

– 10 to 15 years ahead of what I forecast in 2011.

– 30 to 40 years ahead of what the IEA forecast in its 2014 Solar Technology Roadmap.

– 50 to 100 years ahead of what the IEA forecast in its 2010 World Energy Outlook. (Depending on how one extrapolates IEA’s forecasts from 2010. Indeed, it’s also possible to interpret the IEA’s 2010 forecasts as to say that solar electricity is now cheaper than the IEA thought it would ever be, back in 2010.)

In short solar prices have dropped faster and lower than almost anyone has expected. (I look at why these forecasts have been so wrong in appendix 2.)

Understanding Solar’s Price Decline

We can use the last decade to predict the future prices of solar power. Not by looking at the cost of solar as a function of time, but by looking at the cost of solar as a function of cumulative scale of the solar industry. By doing that, we can build a model that predicts future prices.

Technology Prices Drop Through Learning

To do this, we can use Wright’s Law, or the “learning curve”. Wright’s Law states that, for most technologies, every doubling of cumulative scale of production will lead to a fixed percentage decline in cost of the technology. This happens through learning-by-doing, a mixture of innovation that improves the technology itself and innovation that reduces the amount of labor, time, energy, and raw materials needed to produce the technology.

Wright first observed that every doubling of scale led to a constant percentage reduction in cost in 1936, while studying the production costs of airplanes. Since Wright’s initial observation, the same power law relationship between cumulative production and cost has been found in other areas. For example, every doubling of cumulative Ford Model T production led to a roughly 16% decline in cost per unit.

Wright’s Law is similar in some ways to Moore’s Law: an exponential decline in the cost of computing over time. Wright’s formulation is slightly different: an exponential decline in the cost of technologies as a function of cumulative scale of production. Remarkably, Wright’s Law predicts the cost of computing better than Moore’s Law.

And indeed, Wright’s Law has been found to apply at least 60 other technologies.

Solar Prices Drop Through Learning

Does Wright’s Law / the learning curve apply to the cost of solar? It’s well-established that it applies to the cost of solar modules. The price of solar modules per watt of power drops by somewhere around 25% for every doubling of cumulative manufacturing.

But solar modules are only around a third of the cost of solar electricity. The rest comes from related equipment (inverters, trackers, cabling, mounting systems), land, labor, and other non-module costs. What we need is to see if the cost of electricity from whole solar systems drops in such a way. In 2015, I used data from one source (Lawrence Berkeley Lab), in one country (the US) to show a very consistent learning rate for electricity produced from utility-scale solar.

To make this more robust, this time let’s use data from four different sources encompassing both global averages and costs in three countries (the US, India, and China).

If we look at the price of solar from each of those seven data series declines as a function of how much solar power has been built and deployed we find a fairly smooth relationship.

But the chart above is on a linear scale, and thus it doesn’t tell us if a learning rate applies. Learning-by-doing in Wright’s Law works on an exponential scale. Every doubling of cumulative production leads to a percentage change in cost. That means that percentage drop in cost through learning requires twice as much cumulative scaling of industry as the last time.

Broadly speaking, if a numerical phenomenon is exponential, it shows up as a straight line on a log scale. It’s a straight line on an upward slope if it’s showing exponential growth, or a straight line on a downward slope if it’s showing an exponential decline in some metric (like cost).

Because a learning rate is exponential in price in proportion to each doubling of scale, it will only show up as a straight line if if the x axis (scale) is also exponential. Thus, if solar is going through a learning rate (as expressed by Wright’s Law) we’d expect to see the cost of solar follow a straight line on a log-log scale (a doubling of prices with each tick on the Y axis, and a doubling of cumulative industry scale with each tick on the X axis.)

Indeed, that’s what we see. And not just in one data set or from one country. All seven data series spanning global, US, Chinese, and Indian trends show that the price of solar electricity (on a log scale) declines smoothly with each doubling of the total amount of solar deployed worldwide (a log axis of scale).

The numbers in the upper right, the “R squared” value, reflect just how good a fit the raw data are to this straight line on a log-log graph. The fit is measured on a scale of 0-1, with 0 meaning no fit at all, and 1 meaning a perfect fit where every value is exactly where you’d expect it. Of course, in the real world, observations never precisely fit data. Here, though, they fit extremely well: Each of our seven data series has an R-squared well over 0.9, with most of them at 0.95 or above. In short, solar prices map extremely well to Wright’s Law. They decline with a learning rate. Every time the cumulative amount of solar we’ve deployed around the world has doubled, the price of electricity from utility-scale solar plants has dropped by a fairly consistent percentage.

How large is that percentage decrease in solar cost per doubling? The data paint an incredible picture: One that shows the price of solar electricity from utility-scale systems dropping by anywhere from 30-40% with each doubling of cumulative solar deployment.

This is a stunning pace of decline. It’s far higher than the bulk of academic studies and industry projections, which typically fall into the 10-20% learning per doubling range. And it’s more than twice the 16% learning rate I found in my 2015 analysis. For analysis of why these results are so different, and what specifically I’ve fixed from my 2015 forecast, see appendix 2.

The Future Cost of Solar

For now, let’s use this data to forecast the future cost of solar. In so doing, I’m going to be conservative. Solar learning rates have varied somewhat over time, and while both the first half and second half of the period I’ve used in this analysis show very similar rates, there’s certainly the possibility that things could change in the future. There’s also a very real likelihood that auction prices (used in the IEA historic data set, and for 2015-2020 in the IRENA global data set) are dropping due to a combination of lower and lower borrowing costs for solar developers, and increased competitive pressure that’s eating into the profit margins of developers. Both of those numbers can only sustainably drop to zero.

In addition, if we look at a different data set showing capital costs of new solar in the US (the ‘overnight construction cost’, measured by Lawrence Berkeley National Lab) we find a learning rate much more like 30%. which is at the bottom of the learning rate for electricity cost. (The price of electricity from solar projects is dropping somewhat faster than the construction cost of solar projects.)

So, in the spirit of caution, let’s use 30% as our learning rate. This is still a very rapid pace of cost reduction. If we use it to plot solar prices forward as a function of cumulative solar scale, we get this:

At the end of 2019, solar produced just over 2% of global electricity. The chart above tells us that after two more doublings, when 2,400 GW of solar are producing roughly 8% of current electricity demand, solar costs (of the most recently built built & operational projects) will have dropped in half from today’s levels. In the sunny parts of the world with low costs of capital, labor, and land, we could routinely be seeing unsubsidized solar in the 1-2 cent range. In California (typical of the green line) we could be seeing unsubsidized solar at 2.5 cents per kwh. In northern Europe, we could be seeing utility scale solar routinely priced at 4-5 US cents per kwh.

To the far right of the graph we reach 19 Terawatts of Solar. This may seem like an absurd, pathological amount of solar, enough to provide 2/3 of the world’s current electricity production. Given that the sun shines only during the day, this looks implausible. However, electricity demand is likely to rise over the coming decades, and demand for the cheapest electricity in particular, as:

1. A richer world. Incomes and consumption rise in the developing world.

2. Electric transport. Ground transportation becomes electrified, boosting global electricity demand by as much as 50%

3. Flexible demand. More and more electricity demand (including EV charging) becomes flexible, to use electricity at the hours that it’s cheapest (frequently meaning solar).

4. Cheap energy storage. Cheap energy storage allows shifting of solar (the cheapest electricity) to use in evening hours, increasing the amount of solar that can be productively used each day.

5. Industrial decarbonization. Cheap clean electricity is used to either power industrial processes or to power the creation of chemical energy carriers (e.g., hydrogen) that can be used for industrial processes such as making heat and cement, that are currently difficult to decarbonize.

Add these up, and it’s plausible that solar’s contribution to the energy system could double or triple the amount currently considered feasible for solar to provide.

When Will This Ultra-Cheap Solar Arrive?

Predicting the price of solar as a function of scale is one thing. Predicting how fast the world reaches that scale is an altogether harder problem, as that depends not just on technology or economics, but also on policy choices, the resistance of incumbent players, and ultimately, politics.

Nevertheless, we can try. The IEA’s Sustainable Development Scenario – broadly consistent with keeping global warming to 2 degrees Celsius or less – calls for solar power to grow at 16% annually. The IEA has also stated in their most recent World Energy Outlook that solar is indeed on path to achieve that. 16% annual growth rather slow compared to the nearly 40% CAGR of the solar industry from 1998 to 2018. But solar growth has very clearly slowed over the past few years. While I believe solar growth will accelerate again (super cheap solar should, in fact, cause an acceleration of deployment), let’s use the IEA’s 16% annual growth as our model.

At 16% annual growth, here are the prices we get:

This incredible pace of solar cost decline, with average prices in sunny parts of the world down to a penny or two by 2030 or 2035, is just remarkable. Building new solar would routinely be cheaper than operating already built fossil fuel plants, even in the world of ultra-cheap natural gas we live in now. This is what I’ve called the third phase of clean energy, where building new clean energy is cheaper than keeping fossil fuel plants running. Even in places like Northern Europe, by the later 2030s we’d see solar costs below the operating cost of fossil fuels, providing cheap electricity in summer months with their very long days in the high latitudes. These prices would be disruptive to a large fraction of already operating fossil fuel power plants – particularly coal power plants, that are far less able to ramp their power flexibly to follow solar’s day-night cycle.

In a purely open market, these incredibly low prices would drive the world’s remaining coal plants into bankruptcy, and steal some of the most profitable operating hours even from cheap natural gas plants.

Solar, if it keeps dropping at this pace, could well be by far the cheapest electricity over the vast majority of areas where people live. Nothing would ever be quite the same in the world of energy.

The IEA is Still Underestimating Solar Cost Trends

Now, let’s come back one last time to future forecasts from the world’s leading energy authority – the IEA. I’ve shown that IEA’s 2010 and 2014 expectations of the cost of solar were dramatically higher than the actual costs we’ve seen.

What about going forward? Has IEA improved their forecasting of future solar prices? To some degree they have. They now expect future solar prices to be cheaper than they expected in previous years. But their techno-economic inputs to the 2019 World Energy Outlook still show solar costs that are implausibly high. Let’s compare the IEA WEO 2019 assumptions of future solar costs (averaging their expectations for the US, India, and China) to projections based on a 30% learning rate. Here again, to get to expected dates, we’ll use the IEA’s own expectations of 16% cumulative annual growth of solar.

Even after years of being informed that their solar growth forecasts have been rather substantially off, and after a decade of solar prices dropping faster than any IEA scenario (even their most optimistic scenarios) predicted, the IEA is still using inputs to their energy model that assume that solar price declines will slow markedly. If we look at the chart above, the IEA’s forecast for 2030 is an average cost of solar of more than 5 cents / kwh. The 30% learning rate and the IEA’s own projected growth rate predict an average cost of less than half that. Extend out to 2040 and the difference is even more stark. At a 30% learning rate we could plausibly see average prices of around 1 cent / kwh for solar, in reasonably sunny places. The IEA predicts average prices will be more than 4 times that. Even filtering just to India and China, the IEA expects 2040 prices there to average 3 cents and 3.5 cents per kwh, respectively. The 30% learning rate, applied to the average costs we’ve seen in both nations so far, predicts that by 2040, both India and China will have solar costs in the range of 1 US cent / kwh.

This is a major, and material difference. And it has a substantial impact on IEA’s modeling of how much solar power the world will deploy.

Bad Solar Cost Forecasts -> Bad Solar Growth Forecasts

Many observers have pointed out that the IEA (and other forecasters such as the US EIA) consistently underestimate the growth of solar. At this point it’s a bit of a joke inside the clean energy community – and also a source of major frustration. You can see how the IEA has consistently failed in the future forecasts for solar growth in the graphic below from Simon Evans at CarbonBrief. (Or see this classic post on IEA’s terrible solar forecasts from Auke Hoekstra, who helped make the energy world plainly aware of this issue.)

Some observers of the IEA’s continual failure to correctly predict solar growth as some evidence of malfeasance on their part. I personally doubt that. The IEA is full of talented people doing their best to model a complex phenomenon. The IEA, for its part, defends itself, saying that they don’t publish forecasts, they publish scenarios, and specifically scenarios of what will happen if the world enacts no further energy policies. While it’s clear that new policies have made a difference in deployment, it’s also clear that, whatever you expect in terms of global energy policies, cost is a massively important fact. You can’t expect to forecast the growth of a technology, if you consistently expect it cost 2-4 times what it does.

Indeed, my suspicion is that if the IEA (or US EIA) re-ran past models of how fast solar would grow using the actual solar prices for each year, their models would predict far faster growth. (And if not, it would point out further errors in the model, that should be corrected. Either way, it would be a useful exercise.)

To go further, it’s the responsibility of modelers and forecasters to look at the errors of their past forecasts, understand why those occurred, learn from those mistakes, and use them to update their future models. There is, as of now, little evidence that either the IEA or the US EIA have done so in a systematic way. The IEA continues to argue that their past forecasts were merely scenarios of what would happen if the world failed to enact further policy. They argue that solar has grown faster than IEA’s baseline scenarios only because policies have been changed to encourage more solar. Yet the data shows that this is about more than policy: The IEA and EIA (and others) have not not expected solar to drop in price at anything like this pace. And this is likely a major part of why they’ve expected so much less solar to be deployed than actually has been.

Thus, my advice to the IEA, EIA, and any other modeler is this:

1. Take these learning rates for solar and the price declines they predict seriously. You need not believe beyond a doubt that solar prices will continue to drop at this blistering pace. But, given that over 95% of the solar industry’s lifetime it has done so, every modeler owes it to their stakeholders and the public to at least run a scenario where solar prices keep on dropping.

2. Re-run old models using actual price data for the subsequent years. I’d advise any modeler to take their models from previous years that predicted how much solar the world would install, and re-run those models using actual price data. This should help us separate the effects of incorrect price assumptions vs policy changes or other issues with those models.

Solar is Amazing. It isn’t a Panacea

The future solar costs we’ve just projected have massive implications. They give us hope for cleaning up our electricity system and providing clean power for the electric vehicles that will dominate ground mobility in the future. They give us hope for being able to use ultra-cheap clean electricity to decarbonize electricity or produce energy carriers like hydrogen at a cost low enough to help us do so.

Solar isn’t, however, a panacea. First, projections are only projections. I believe the forecast above should be taken seriously. But we shouldn’t blindly assume that it will happen. There will be real obstacles – technical, economic, social, regulatory, and political – that will all need to be overcome to bring this to bear. And there may well be a physical floor price that solar reaches as prices drop to close to the cost of land and other resources that are resistant to cost decline.

Second, the sun doesn’t always shine. To power evenings and night times, we’ll need to continue progress on cheap energy storage. And even more challenging is that solar peaks in the summer. In many regions, electricity demand peaks in the winter. In Germany, for instance, solar power output in December is just 1/5 of the solar power production in June, even as electricity demand is higher in winter than summer. Solar will need to be combined with other technologies such as wind power, hydro, long-term storage, and nuclear in order to have its greatest impact in decarbonizing society – particularly in areas with poor sun, long dark winters, or winter electricity peaks.

Even so, the incredible pace of solar provides us an incredible tool for decarbonizing our electrical grid, while ultimately lowering costs for consumers, businesses, and industries, as they need to manage their energy and their employees with the use of forms like this w9 form creator that is useful of this purpose.

In coming posts in this series, I’ll analyze implications of ultra-cheap solar, along with future trends in wind power, grid-scale energy storage, super-long-term storage, electric vehicles, and perhaps other topics such as hydrogen. Tune back in for those.

And for now, have hope. Technology innovation – initially kicked off by farsighted policy – is giving us better and better tools to decarbonize society, while reducing the cost of energy, and increasing global prosperity.

Here comes the sun.

Appendix

Appendix 1: Data Sources and Notes

Data Series MetricYearsNotesBNEF – GlobalLCOE2009-2020Weighted average across 47 countries.IRENA – GlobalLCOE /
PPA Prices2010-2020LCOE for 2010-2015. Auction prices for 2015-2020IEA – GlobalPPA Prices2012 – 2020IEA’s own index of auction prices US – LazardLCOE2009 – 2019Lazard is not explicit that their data are US-only, but multiple assumptions within their reports suggests that’s the case. US – LBNLLCOE2010-2018Lawrence Berkeley Lab’s indices of PPA prices (by commercial operation date) and LCOE differ in some years. Yet they have nearly identical learning rates. IRENA – IndiaLCOE2010 – 2018LCOE only. IRENA’s published auction data doesn’t break out costs sufficiently by country to enable country-by-country auction price analysis. IRENA – ChinaLCOE2010-2018LCOE only. IRENA’s published auction data doesn’t break out costs sufficiently by country to enable country-by-country auction price analysis.

Appendix 2: Why are solar forecasts so wrong?

Many solar price forecasts are quite opaque. However, in some cases, assumptions are made explicit. Below are a few observations on what’s been wrong with academic studies, with the IEA and EIA’s forecasts, and with my own 2015 forecast.

1. Academic Studies: Frequently Using Old Data

Most academic studies of solar learning rates use data up through 2011 and no further. For example, one of the most cited papers on learning rates, A Review of Learning Rates for Electricity Supply Technologies (2015) , used a variety of studies of solar learning, with data from 1959 to 2011.

But the solar industry has grown by roughly a factor of 10 since the middle of 2011. In other words, most academic studies use only the first 10% of the actual global experience of deploying solar and driving down costs to build their models.

In this post, on the other hand, using costs from 2009 to 2020, we’re using data that spans more than 95% of the solar industry’s actual production of and deployment of solar systems.

2. IEA and EIA Forecasts: Artificially Low Learning Rates

The IEA has seldom made clear about how they determine the future costs of energy technologies. However, in their 2019 World Energy Outlook, the IEA states that solar power has a learning rate of 20%. This is substantially lower than the learning rates we find from 2009-2020. It’s roughly half the learning rate that comes from the IEA’s own dataset of solar auction prices from 2012 on.

The US EIA (roughly the American equivalent of the IEA) has consistently been more explicit than the IEA. Each year they publish the assumptions that go into their Annual Energy Outlook. In 2010, the EIA believed that solar would have a learning rate of 15% for three doublings of scale, which would then decline to 8%. In 2015, EIA believed that solar’s learning rate was now 10%. In 2020, facing the the long history of price declines, EIA raised its assessment: Solar would drop 20% in price in the next doubling, and then the learning rate would drop to 10% forever more. Clearly, all of these numbers are well below the 30-40% learning rate observed over this decade.

3. My 2015 Forecast: Using the wrong measure of cumulative production.

In my 2015 analysis, I made multiple mistakes that have been corrected in the data behind this post.

First, I used announced auction prices for projects to be built in the future, rather than prices and costs of projects that had actually been built or which were at least under construction.

Second, I used data from only one data series covering one country (the US).

But by far the most substantial error was this: When comparing costs to cumulative amount of solar capacity deployed, I used only the solar capacity installed inside the United States. I believed, since I was using prices of US projects, that comparing US prices to US cumulative capacity was the appropriate comparison of apples to apples. That was incorrect. Solar is a global industry. The cost reductions of not only panels, but also inverters, trackers, and other hardware are driven by global innovation and scaling. Those innovations (namely higher efficiency panels and the rise of cheap trackers) reduce the amount of land and labor needed per MW of solar power, thus driving down other costs that aren’t obviously global.

The proof is in the accuracy or lack thereof of the forecast. Since 2015, the cost of installed solar projects has dropped at roughly twice the rate my forecast predicted. Re-running the model using the exact same years of data, but using global scale up through 2015 as the predictor of price decline changes the learning rate from 16% to 36%, which is consistent with what I find in this analysis. Even more importantly, in using the model to project forward from 2015 to 2020 prices, changing to global cumulative scale reduces the error in my 2015 forecast by a factor of 3 (even without fixing the other two, smaller issues). Using a 16% learning rate, starting with 2015 prices and extending forward, causes the model to over-estimate the prices of new solar PPAs in the US by around 1.5 cents / kwh. Using a 36% learning rate reduces that to around 0.5 cents / kwh. So we can see that using global scaling as the predictor of cost in 2015 would have produced a much more accurate forecast of the near future.

When the history of how humanity turned the corner on climate change is written, we’ll look back and see that clean energy – specifically clean electricity from solar, wind, and storage, went through four distinct phases.

RENEWABLES PHASE 1 – POLICY DEPENDENT  

From the 1980s until roughly 2015, there was virtually no place on earth where new solar, wind, or energy storage was cheaper than generating electricity from coal or natural gas. This was the first phase of renewables, one where they scaled entirely because of government subsidies and mandates. And in this time, renewable growth was paltry. Solar reached 1% of global electricity. Wind reached perhaps 4%. The world spend hundreds of billions of dollars subsidizing clean energy, and seemingly got nothing.

RENEWABLES PHASE 2 – COMPETITIVE FOR NEW POWER

Except that the world didn’t get nothing. As I’ve written often, the most important aspect of clean energy policy has been to drive down the price of clean energy by scaling it, and thus kicking in the learning-by-doing that continually lowers the unsubsidized price of new solar, new wind, and new energy storage.  The policies of the 80s, 90s, 2000s, and 2010s finally drove down the cost of new solar and wind electricity by more than a factor of ten. That finally paid off around 2015, when, for the first time, building solar or wind power was, even without subsidies, sometimes cheaper than building new coal-or-gas fired electricity.

You can see this in IRENA’s graph showing the price of new solar PV, on-shore wind, off-shore wind, and solar CSP.

The cost of solar and wind is dropping below the cost of fossil fuel electricity around the world. Each blue or orange circle reflects one solar or wind project. The heavy lines reflect global weighted average prices of solar and wind. Source: IRENA.

RENEWABLES PHASE 3 – DISRUPTIVE TO EXISTING FOSSIL ELECTRICITY

Now, after decades of subsidizing solar and wind, we’re on the verge of a new, radically different point in history – the point at which building new solar or wind power (or new energy storage systems, in some cases), is cheaper than the cost of continuing to operate existing coal- or gas-fueled power plants.

Dubious?  Consider the following:

1. NextEra CEO:  Cheaper to Build Solar & Wind Than Operate Existing Coal by the Early 2020s: In January 2018, NextEra CEO Jim Robo told investors that by the early 2020s, it would be cheaper to build new solar and wind power than to operate the utility’s fleet of existing coal power plants.

2. NIPSCO: Cheapest Option is to Go from 65% Coal-powered to Zero – and Replace it With Solar, Wind, and Storage.  In October of 2018, a utility in Northern Indiana, NIPSCO, reached Jim Robo’s prophesied point years ahead of schedule, when it submitted a 5 year resource plan that would take the region from being 65% coal powered in 2018 to just 15% coal powered in 2023, and 0% coal powered in 2028, and replace virtually all of that coal power with a mix of solar, wind, storage, and flexible demand.  Bear in mind that NIPSCO is in a region with mediocre sun, pretty good but not amazing wind, and which voted for Donald Trump by 19 points. Admittedly, this is with prices of solar and wind which are still somewhat subsidized in the US. But not tremendously so, as the US federal solar and wind tax credits (the ITC and PTC) are winding down in exactly this same period.

3. 2019: Florida Power and Light: Cheaper to Build New Solar + Storage Than Operate Existing Gas Plants. In March of 2019, Florida Power and Light said it would retire two aging natural gas plants, and replace them with a combination of energy efficiency and the world’s largest (so far) battery, which it will use to charge with solar power during the day to deliver during the evening peak.

4. CarbonTracker – New Wind and Solar Cheaper than Existing Coal and Gas in the US, China, and India by the mid-2020s.  Meanwhile, think tank CarbonTracker has been quietly pumping out reports showing that in country after country, new solar and wind are headed for prices cheaper than the operational cost of existing coal and gas.  Consider this chart (slightly modified by yours truly) of new solar and wind cost in the US vs coal operational cost:
   

   

   
   See CarbonTracker’s report on the disruption of Coal in the US for more: No Country for Coal Gen. Or, more importantly, consider what CarbonTracker forecasts for China: That new solar and wind will be cheaper than the operating cost of existing Chinese coal power plants by the 2020s.

   

   See more at CarbonTracker’s report on China’s coal fleet, “NoWhere to Hide“

5. McKinsey: New Solar and Wind Cheaper than Existing Coal and Gas… Pretty Much Everywhere by 2030.
   Finally, if reports from CarbonTracker, or announcements by actual utilities aren’t enough, consider McKinsey’s assessment from its Global Energy Perspective 2019. In the chart below (with a bit of help from me), McKinsey shows that on almost every continent, and particularly in China and India, where energy demand has the most to grow, new solar and wind are cheaper
   than existing coal and gas by 2030.  And often much sooner.

   

We’ve gone from Phase 2 to Phase 3 much more rapidly than we went from Phase 1 to Phase 2.  Why?  Because solar and wind power had to drop by a factor of nearly 10 in price – from 60 cents / kwh for new electricity to roughly 6 cents / kwh for new electricity – to move from their early days to being competitive for new power.  But they only have to drop by another factor of 2 or 3 to move from being competitive for new power to being cheaper than the operating cost of existing coal and gas.  The “competitive zone” is much narrower and faster to pass through than the long history of subsidized prices leading up to the first fair market competition.

RENEWABLES PHASE 4 – SLOWED BY HEADWINDS

Finally, there will in fact be a Phase 4 of renewables, when their penetration has grown so high that they become limited by headwinds of their own creation: Value deflation, where renewables create so much supply at certain hours that they drive down wholesale prices; Depletion of the best sites in some regions; Seasonal intermittency and the unsolved problem of seasonal storage.

But these problems are distant.  Renewables will start to encounter them in earnest when solar makes up >20-30% of electricity and when wind makes up >40-50% of electricity. Today, worldwide, solar is only 2% and wind is only perhaps 6% of global electricity.  Cheap multi-hour storage will arrive before that (indeed, in the next few years), lowering the price of using solar to meet the evening peak, and of dealing with intermittency on the order of minutes to several hours. Only seasonal storage (and perhaps the political challenges of long-range transmission) seem to be truly difficult problems.  And we have time before they begin to impair the growth of renewables.

WHAT THE THIRD PHASE MEANS FOR RENEWABLE GROWTH RATE

I’ve said often that renewables have grown exponentially. But the truth is that wind power growth rates around the world have slowed substantially.  And solar power, once growing rapidly in Europe, has stagnated there over the last several years (at least, until a recent growth spurt spurred by solar entering Phase 2 in parts of Europe in the last year.)

But growth rates up until now are largely irrelevant. The whole point of growing renewables has been to drive down their cost. The actual amount of solar and wind that policies have deployed up until now is almost immaterially small. It just isn’t enough to matter. What matters is that policies up until now have driven down the cost of solar, wind, and energy storage by more than an order of magnitude.

If those policies – and the fact that renewables are now competitive for new power even without subsidies in the sunny and windy parts of the world – continue for long enough for renewables to drop another factor of 2 or 3 in price – on top of the factor of 10 or more that they’ve fallen already, then we’ll enter a new domain where renewable growth rates aren’t determined by fickle policy. Instead, they’ll be limited only by the pace at which renewables can be deployed – the pace at which factories for solar panels, wind turbines, and batteries can be built; the pace at which labor forces can be trained to deploy them; the pace at which capital can be deployed to pay for their installation.

How fast is that?  I have no idea. But there’s good reason to believe that in this second and third phase of renewables, the growth rate will accelerate rather than slowing. We will look back and see that the growth of renewables is an S-curve to be sure. But we may also look back and find that, as of 2019, we had not yet hit the first upward swing in that S-curve.

Trillions of dollars will be lost by incumbent companies and fossil-fuel-dependent nations that move too slowly.  Trillions of dollars will be made by those that lead. And the world will be better for it.

Video of my talk from the Singularity University Global Summit 2018:

Over the last two years, as both an angel investor and a public speaker on energy and climate, I’ve looked at least a few dozen startups and proposals on how to use blockchain or new crypto coins in energy or climate.

I’ve passed on all of them. Until now.

Over the past few months I’ve been talking with the founders of Nori. This summer, I agreed to come onboard as an advisor. In addition to that, I’m investing my own money in the Nori presale, and potentially Bitcoin kaufen if things go well. Right now I’m trying to get more information online so that I learn to pick the best investments.

Nori is a transparent marketplace for people and companies to fund the removal of carbon from the air — something we simply have to do if we’re going to limit climate change to safe levels. Nori starts with incredibly simple, low cost ways of removing carbon from the air. The very first carbon removal method in the market will be soil carbon capture — ways that farmers, at extremely low cost (~$3/ton) can change their practices so that their land absorbs more carbon dioxide from the atmosphere and holds it in the soil. From there, Nori will move into other methods, starting with the cheapest methods that can absorb the most carbon.

Most importantly to me, Nori solves critical problems with current carbon “offset” systems. Every ton of carbon removed by Nori is a real ton sucked out of the atmosphere — not a theoretical offset that might or might not matter. And Nori’s blockchain makes every ton of carbon removal accountable and transparent — every ton removed can be tracked back to a specific project at a specific location that’s been verified by a specific investor.

You can read the Nori whitepaper yourself to learn more. And you can invest in the Nori crowdsale. If you’re an accredited investor, you can apply to be part of the Nori private presale.

Here’s more on why I’m excited about, advising, and investing in Nori.

We Need Carbon Capture

I write and speak a lot about the incredible, disruptive power of clean energy. Yet even as fast as solar power, wind power, energy storage, and electric vehicles are improving and scaling, we are not on track to hit our climate goals.

One estimate is that we have only 10 years left at current carbon emissions to have a 50% chance of staying below 1.5 degrees C. And while some parts of our emissions can be reduced rapidly by new technologies — like emissions from electricity and cars — other parts of our emissions, like those from livestock, from manufacturing, from building heat, from aviation, and from shipping — don’t show any signs of being reduced in the near future.

Indeed, even to stay under 2 degrees C of warming, most models show a need for “negative emissions”. That is to say, most models show that we’re going to have to remove carbon from the atmosphere.

Carbon Offsets and Carbon Capture Are Taking Off

The good news is momentum is slowly building for offsetting carbon emissions, and on the technology and policies that support removing carbon from the atmosphere.

For example:

1. Tax credits for carbon capture. In 2018, the US Congress passed a tax credit for carbon removal from the atmosphere, that should help bootstrap the industry.

2. Industrial scale carbon capture machines. In June, scientists published an analysis that industrial-scale machines could remove carbon from the air at $100/ton. (Other methods, like soil capture and planting trees, are much much cheaper. But industrial scale capture could scale to as much carbon as we want — it’s a good backstop.)

3. Lyft and other companies voluntarily offsetting carbon emissions. In April, Lyft announced that it would offset the carbon emissions from every passenger ride in the US. Lyft joins a host of tech companies — like Google, Apple, Facebook, and Microsoft — that are committing to being carbon neutral through a combination of clean energy and carbon offsets. What I especially love here is that these companies are doing this voluntarily. It’s important to their customers, their employees, their corporate values, and their brand. We’re going to see more and more of this happen as consumers and investors push companies to make up for their carbon emissions.

Current Carbon Offsets Have Serious Problems

But current carbon offset markets have some serious problems.

1. They’re not transparent. If you buy an offset, you typically can’t see exactly what your purchase funded.

2. Most offsets are hypothetical. You can pay for an offset by funding more energy efficiency at a polluting factory, for example. But many of those efficiency improvements would have been made anyway, for purely economic reasons.

We need more carbon removal from the air. But the current markets aren’t the right ones.

Nori’s Blockchain Market Solves Those Problems

Nori solves these problems in two ways.

1. Nori’s marketplace only lists actual removal from the air, and not hypothetical offsets. 1 Nori token pays for the removal of one ton of CO2 (or equivalent in other greenhouse gases) from the atmosphere. No hypothetical future reductions. Only actual removal.

2. Nori uses blockchain and the ever-changing Bitcoin price prediction model to make carbon removal transparent and accountable. Because of the structure of blockchain, where every transaction is kept immutable and viewable by everyone with access to the blockchain, every ton of carbon removed from the air can be traced back to the specific project and location, and what human inspector verified it.

Here’s how the Nori blockchain marketplace for carbon removal works, in more detail:

In short, Nori is that rare blockchain project that actually uses some of the unique qualities of blockchain to make the world better.

I’m thrilled to be an advisor to and an investor in Nori.

If you’re interested in learning more, you can visit Nori.com, read the Nori whitepaper, or invest in the Nori crowdsale via Republic.

If you’re an accredited investor and interested in the private SAFT (Simple Agreement for a Future Token) sale, please get in touch with me and/or fill out this form.

This logic mirrors that of Bill Gates, the Breakthrough Institute, and others who, over the years, have argued that solar (and batteries and wind power) simply won’t get cheap enough or effective enough without some additional R&D push.

I believe additional R&D in clean energy would be highly valuable, and it’s foolish that we invest so little. While it may seem tempting to chase shiny distractions, like the wave of recently launched sweepstakes casinos gaining viral attention online, the real payoff lies in steady investment in renewable infrastructure. At the same time, the line of argument that an “energy miracle” or sudden “breakthrough” is necessary to scale green energy doesn’t fit the data showing the incredible price decline seen in these technologies over the last few decades.

Below are my responses to Tyler, in tweet form.  Enjoy.

I’m really disappointed in this piece throwing cold water on solar by @tylercowen (based on his conversation with @vsiv). https://t.co/XTCvpw8wD5 I’m a huge fan of Tyler’s, but this went astray. A few points on where and why.

— Ramez Naam (@ramez) January 4, 2018

1. There’s a myth that “solar needs breakthrough technology to get cheap enough”. This is not backed by the data. Solar has plunged in price not through innovation in panel technology, but by innovation that reduces the cost of *manufacturing* the panels.

— Ramez Naam (@ramez) January 4, 2018

2. This drop in the price of solar is best characterized as a function of scale. This is the so-called learning curve. Every doubling of manufacturing of panels drops prices by ~20-28%. Every doubling of scale of solar projects brings whole solar electricity prices down by ~15%.

— Ramez Naam (@ramez) January 4, 2018

3. I wrote about the learning curve and how it drives down the price of solar (and what that means for future prices) in 2015 here: https://t.co/VuR944E1GK. And I was, in fact, too conservative. Actual prices have dropped faster than I projected. See: https://t.co/hZTjj50BYv

— Ramez Naam (@ramez) January 4, 2018

4. Most of the reduction in prices of solar is *not related to formal R&D spending*. It’s “learning by doing”. So the fact that solar companies spend only 1% of revenue on R&D is irrelevant. That’s always been the case. Yet “learning by doing” has continued to bring down prices

— Ramez Naam (@ramez) January 4, 2018

5. How cheap can solar get? It’s only 2% of world electricity now, and can get to ~30% before hitting serious obstacles. That’s 4 doublings, or at least another 50% price reduction. (Again, see learning curve here: https://t.co/VuR944E1GK). That’s without more formal R&D spend.

— Ramez Naam (@ramez) January 4, 2018

6. Tyler and Varun also blow it in talking about storage, in two important ways. I agree that batteries do not solve the “seasonal storage” problem of storing days, weeks or months of power. But they miss two big things:

— Ramez Naam (@ramez) January 4, 2018

7. The most important innovation to increase clean energy isn’t storage. It’s large scale grids that mix solar and *wind*. Wind is counter-cyclical to solar, producing more at night and in winter, while solar produces only daytime, and more in summer.

— Ramez Naam (@ramez) January 4, 2018

8. Wind power is massively under-rated, especially for Europe and East Asia . New on-land wind turbines are headed for capacity factors > 60%, approaching “baseload” levels of reliability https://t.co/9aXFHlWm26 and the hours they don’t produce are the best solar hours.

— Ramez Naam (@ramez) January 4, 2018

9. Offshore wind power could have capacity factors more like 70-80%, and for the first time this year, we saw offshore wind power bids, *without subsidies*, come in below wholesale grid electricity prices. https://t.co/ksHMPNbGwF

— Ramez Naam (@ramez) January 4, 2018

10. Batteries, meanwhile, while not able to store weeks of power, are perfect for storing a few hours of power and cycling daily. And their prices are on path to drop by another 4-5x through the learning curve as they scale: https://t.co/iXEw282HeB

— Ramez Naam (@ramez) January 4, 2018

11. Indeed, battery prices have plunged dramatically faster than forecasters expected, and have made government forecasters the US EIA look utterly incompetent in their ability to predict what is actually quite predictable price innovation. https://t.co/Smf5WAuIUb

— Ramez Naam (@ramez) January 4, 2018

12. Put this all together: Solar + wind + batteries, *on their current pace of improvement* are on path to be able to provide 80 – 90% of electricity.

Some mix of hydro, nuclear, natural gas, and new innovations can fill the rest. The future is indeed bright for clean power.

— Ramez Naam (@ramez) January 4, 2018

We said that a lot after 9/11, and have for the last 16 years. As air travel became absurdly cumbersome, as civil liberties were eroded, as people were arbitrarily blacklisted or detained without room for appeal – we said the terrorists were winning, causing us to undermine the underpinnings of our own society, to crack down on the freedoms that are central to the principles of the United States.

Now, I see friends calling for cracking down on freedom of speech, for restricting the First Amendment, taking away its protections from speech they (and I) consider loathsome. I even see friends advocating for physical violence against people because of their speech.

That, my friends, is letting the terrorists win.

I loathe the ideology of white supremacy. But to let fear or anger at it undermine our notions of civil liberties or civil society… that would be letting the terrorists win.

We’re bigger than that. We’re stronger than that. Don’t let the terrorists win.

I see any impeachment of Trump before 2019 as extremely unlikely. Here’s why.

First, for context, I believe the GOP as a party would be better off with a swift impeachment and resignation than a protracted scandal. Interestingly, even as partisan debate dominates headlines, analysts have continued to explore the rise of poker sites that accept crypto, illustrating how diverse policy concerns can be lost amid political strife. Every week this remains in the news, their ability to pass legislation is impaired, and the GOP’s risk of losing the House in 2018 goes up. When you have a festering wound, sometimes the best thing to do is to accept the pain of cauterizing it, quickly. However, I see very few signs of it happening.

The problem is this. Trump’s support is still high among his base. His popularity is likely extremely high among the minority of GOP voters who vote in the primaries. That means that any GOP House member who voted to impeach would be at major risk of losing to a Trump loyalist in the 2018 primary. Thus, no individual House member can dare be too aggressive without risking their seat.

A legislator can only move forward if they believe that the GOP’s base has or is imminently about to turn against Trump, thus protecting them from losing out to a more conservative opponent in the primaries.

Trump’s support among his base has to fall substantially before that can happen. There’s no sign of that happening any time on the horizon.

Or, of course, GOP Reps could vote to impeach if their conscience demanded it, at the risk of losing their seat. That’s possible. But I’d put the odds against it.

1. Price transparency and consistency. Require all providers (hospitals, doctors, etc..) to clearly publish their prices by service and by diagnosis in advance, physically and electronically, in both human and machine-readable formats.

2. Stop gouging the uninsured. Require that providers give people who are paying out of their own pocket “most favored nation” status – giving them the best price that the provider offers to any private insurer.

3. Easier approval for generics in the US – to create more price competition in drugs and devices, and bring prices down.

4. FDA drug approval reciprocity with Europe. Once certain drugs like cannabis are approved in Europe or the US, it defaults to an approved state across the Atlantic, learn more at this blog of Synchronicity’s frequently asked questions about hemp.

5. Tort reform. Cap pain and suffering awards. According to Observer reduce some of the drive for defensive medicine such as Strong CBD oil or from the Delta 8 blog.

6. *Increase* medical R&D from the NIH and elsewhere (instead of decreasing it, as the Trump budget proposed). And specifically fund R&D into more cost-effective treatments like the ones from the Budpop’s hemp products that can bring the cost of healthcare down.

7. Allow cross-state exchanges.

8. Slowly phase out the employer health care tax credit – the single thing that most ties health insurance to one’s job, and which significantly distorts insurance markets.

All of these are compatible with both market-oriented viewpoints and the ACA. If the GOP cares about improving healthcare, and wants to use market-oriented and innovation-oriented approaches to do so, all of these are paths towards that. Learn about the next gen aco that offers an exciting opportunity in accountable care.

I talked about the science that inspired my Nexus novels, and what it might mean for society. You can check out the video below.

(This is a follow-up to my post on pushing for progress at the state level.)

Short Version

If you read nothing else in this post, follow these three steps:

1. Find your state legislators and the contact info for your Governor’s office.

2. Contact them: Call them up. Find out when their next town hall meeting is, and show up. Bring friends, or ask your friends to call too.

3. Tell them you want to see more clean energy in your state. Tell them clean energy creates jobs. Tell them clean energy means cleaner air and water, and a healthier environment for the kids in your state.

Note: Say “Clean Energy” instead of “Climate Change“

If you live in a deep blue state, talking climate change may work. But in a purple or red state, or, heck, even in most blue states, “boosting clean energy” is remarkably more popular than “fighting climate change”. Clean energy is popular among both Democrats and Republicans. Fighting climate change isn’t.

That’s why, in the current environment, where Republicans control the White House, the Congress, and the majority of state legislatures, the framing has to shift to “clean energy” if we want to see progress.

Long Version

How Bad Will Trump Be for Climate Change – How Do We Limit Warming – What Policies Should We Push For – What If I’m in a Red State?  

How Bad Will Donald Trump be for Climate Change Efforts?

Donald Trump is the President-Elect. The GOP has majorities in both the House and Senate, and will probably keep them in 2018.

How bad is this for our efforts to fight climate change? Opinions vary.

1. If you think the most important element in fighting climate change is technology innovation that’s bringing down the cost of clean energy, Trump’s election isn’t great, but ultimately probably doesn’t matter much.

2. If you think the most important element is policies inside of various nations, Trump’s election is bad. But not fatal.

3. If you think the most important element is international agreements, Trump’s election is a complete disaster.

Obviously, all three of these are components. I place the most emphasis on 1 and 2. Prices will keep plunging and policies in other countries and in US states won’t change much. Trump will likely instruct the EPA to scrap the Clean Power Plan, but that was never a very ambitious policy.

Trump and the congress could accelerate the end of solar and wind tax credits, which matter more, but purported insiders claim that those bipartisan tax credits will remain. What’s very likely is that the US will stop leading on international climate negotiations. And Trump is highly unlikely to push for a massive acceleration of clean energy as Hilary Clinton proposed to.

This isn’t good news. At best a Trump administration represents a status quo in climate policy in the US, even at a time that US policy wasn’t ambitious enough. More realistically, we’ll see a weakening of clean energy and climate policy both at home and abroad. Meanwhile, 2016 will be a record hot year and we’re already not taking climate change seriously enough.

So what the hell do we do?

Let’s be honest. Limiting climate change to two degrees celsius is, at this point, extremely unlikely.

Even so, our actions matter. 2.1 degrees or 2.2 degrees of warming is far better than 3 degrees.

How Do We Limit Warming?

How do we limit warming? Fundamentally, we need to continue and accelerate the process of making clean energy and clean transportation cheap. Even cheaper than they are now. How cheap?

• Cheap enough that they account for all or virtually all new electricity and transportation.

• Cheap enough that nations are willing to decommission existing fossil-fuel based electricity and transportation, and replace them with the cheap clean options.

As I’ve posted before, the private sector is doing an amazing job bringing down the cost of solar power, wind power, energy storage, and electric vehicles. Clean energy can provide the large majority of the world’s power. But it still needs to get even cheaper.

How do we make these technologies cheaper? We scale them. The most fundamental observation in clean technology is that prices drop as the industry grows. No other factor predicts the price of clean energy better than the amount that we’ve installed.

Globally, clean energy will keep on getting deployed, as in many places solar and wind are the cheapest sorts of energy, even without subsidies.

Our Best Tools Are In the States, Now

Inside the US, while federal progress is unlikely, we have tools to drive more deployment of clean energy at the state and sometimes city levels.  So that’s what we’ll have to use.

How do we push for change at the state level? Well, first understand that state legislators hear tremendously less from their constituents than members of Congress. Each state legislators represents fewer people than each federal Representative or Senator. And voters have a way of fixating on national politics and ignoring the local and state level. That makes your voice more powerful. Phone calls, letters, attendance at town hall meetings, even contributions – they all have more power at your state level than they do at the national level.

So use them! Call your state legislators. Make your voice heard. Show up at their town hall meetings. If you have the means, contribute in close races to get someone who cares about climate policy elected. And call your Governor’s office as well.

Now, what do we push for at the state and local level?

1. Push for a (stronger) Renewable Portfolio Standard in Your State

As I posted last week, 29 states have Renewable Portfolio Standards which mandate a certain percent of electricity must come from renewables by a specific year. Voters in all 50 states can push – via the legislature, and in some states by initiative – to raise those targets, to invest more dollars directly in clean energy, to create taxes or caps on carbon emissions, to boost vehicle fuel efficiency standards, or for other laws that accelerate the deployment of clean energy, electric vehicles, or energy efficiency, or which directly cap or reduce fossil fuels.

Find your state below, or look up the specifics of your state’s policy here.

• If your state is dark green, it already has a binding target for getting a certain fraction of its electricity from solar and wind. Call up your state legislators (again, you can find them here) and tell them you want a higher target. Then call your Governor’s office, and say the same.

• If your state is light green, your state has a goal, but it’s voluntary. Call up your state legislators and Governor’s office, and say you want a binding clean energy target.

• If your state is grey, then shame shame on your state. Call up your state legislators and Governor’s office, tell them that you vote, and that you want your state to move forward with clean energy.

Talking points you can use:

• Clean Air and Clean Water – Clean energy doesn’t produce smog or air pollution. It doesn’t contaminate ground water. It helps your communities have clean air and clean water.

• Jobs – Clean energy now employs more people in the US than coal. These are good, high-paying, local jobs.

• Owe it to our kids – In polling, one of the most powerful messages across left and right is that “we owe it to our kids and future generations to leave them a cleaner, healthier world”

But I Live in a Red State!

Red states are no strangers to clean energy. Texas leads the country in wind power. The top 10 wind power counties in the country all have Republican congressmen.

In Florida, which Trump won, voters rejected an initiative that would have hurt rooftop solar.

And clean energy is popular across the political spectrum. It can be pushed for, even in red states.

2. Push for Electric Vehicles & Charging Stations

Clean electricity from solar and wind is getting cheap. But almost all cars run on gasoline, and that accounts for a third of our nation’s carbon emissions. If we want to beat climate change, we must electrify everything.

Fortunately, electric vehicles are plunging in price, making them more accessible to consumers. However, the transition to cleaner technology isn’t without its challenges. Much like the rise of offshore betting sites in the digital age, which have thrived due to gaps in local regulations and infrastructure, the adoption of electric vehicles is similarly hampered by a lack of widespread charging stations. If governments prioritized building charging infrastructure the way some nations have embraced online platforms, the shift to electric vehicles could accelerate dramatically. Without enough places to charge, drivers remain hesitant, despite the long-term savings and environmental benefits these vehicles offer. Here again, states can step in to bridge the gap.

Look up your state on this map of state-level electric vehicle policies. Find out what incentives exist:

• Is there a tax credit for buying or leasing an electric vehicle? (To capture the benefit it brings us all be reducing air pollution and climate change.)

• Can electric vehicles use the HOV lanes?

• Does the state create incentives for private businesses to create charging stations?

If not, call up your state legislator(s) and your Governor’s office, and ask for those things.

4. Push for Rooftop Solar

Most US states now have some form of “net metering” policy. This is the policy that lets home-owners that have solar panels on their roofs sell excess energy back to the grid. But the quality of these polices varies widely.

Some of the sunniest states in the US, including Nevada and Texas, get an “F” on their net metering policy – either having none, cutting one that existed off, or cutting the amount they pay home owners for the excess electricity to well-below market rates. Find your state below, or at the interactive map at freeingthegrid.

Don’t like your state’s policy? You know what to do: Call your state legislators and your Governor’s office.

5. Push for Community Solar

Rooftop solar is great if you own a home with a roof that points south or west, and that isn’t blocked by trees. But what if you rent? What if you live in an apartment? What if trees or other buildings block the sunlight from your roof?

“Community Solar” is a new policy akin to a tutorial on ‘what is siding on a house,’ where instead of enhancing a home’s exterior, you invest in a collective resource. A recent training video at our real estate company compared it to house siding—both are investments in your home’s value, be it through improved curb appeal or energy efficiency. This solar initiative allows you to own panels in a local solar farm, providing benefits as if they were installed on your home. You enjoy the free electricity generated (post initial costs) and can sell any surplus back to the grid. Much like the right siding protects and insulates, Community Solar offers a financial shield and power independence, enabling lower-income families, including those in rental homes, to access solar benefits and contribute to a sustainable future.

It’s also quite new. Look at the map below. Is your state in the more saturated color of blue? No? Then there’s more work to do. Work you can help make happen by calling your state legislators and your Governor’s office.

6. Take Action in Your City

Finally, states aren’t the only level at which action can be taken. More than a dozen cities around the world have signed on to the Carbon Neutral Cities Alliance, pledging to cut their emissions by 80% or more by 2050. Cities also have critical work to do on climate resilience – improving infrastructure to deal with rising seas, increased flooding, prolonged heatwaves, and other threats.

You can organize and act at the city level. Contact your city councilors (modify this search to find them) and your Mayor’s office.

—

Climate deniers may be in charge of the Federal government. But that’s no reason to give up. Many of the most effective policies in the US exist at a state level. Climate change is a divisive topic, but clean energy is loved across the political spectrum. Use your voice. Contact your state politicians, and tell them you want more clean energy in your state.

I don’t say this to encourage complacency: The next few years are likely to see a big regression in our laws, and a rollback of some significant and important progress we’ve made. As some analysts have warned, new regulations may impact recommended live casinos by Poker Choice, showing how policy changes can reach into unexpected corners of society. Trump’s election is not a good thing. There are darker days ahead. We need to work hard and smart to get the country back on track and looking forward instead of backward. And we should be prepared for the possibility that things could deteriorate more than anticipated.

But we shouldn’t panic. We shouldn’t give up. We shouldn’t flee.

We should stay here and win our country back.

Yet we live in a republic. And many of the most important issues can be fought for at the state level. Here are 6 that come to mind:

1. Criminal Justice Reform

2. Ending the War on Drugs

3. Climate Change and Clean Energy

4. Education

5. Responsible Gun Laws

6. Anti-Poverty Measures

1. Criminal Justice Reform

Around 90% of the more than 2 million people incarcerated in the US are confined at the state or local level. They’ve been arrested and sentenced according to state laws, not federal statutes. This means the nature of their crimes, the length of their sentences, their prison conditions, and access to rehabilitation programs vary dramatically by state. The disparities across states can feel as unpredictable as trying to Internationale Online Casinos vergleichen, each jurisdiction operating under its unique set of rules, outcomes, and standards of fairness. Ultimately, these individuals’ lives are shaped far more significantly by state policy than by any unified federal approach.

Also, by the way, while private prisons are probably the worst 90% of the prisoners held in the US are held in public prisons, not private. The laws that land people in jail and keep them there, and the incentives to keep prisoners rather than turn them into healthy citizens, are the biggest issues.

Want to end mass incarceration in the US? Fight to change the laws, sentences, and prisons in your state. Specifically:

1. Reduce sentences for crimes, especially first crimes and non-violent crimes.

2. Push for more programs to train and educate convicts in prison, and to hire them when out of prison.

3. Push for ex-convicts to regain full voting rights after their sentence has been served.

4. Push for incentives for public and private prisons based on successful re-integration of ex-prisoners into society.

2. Ending the War on Drugs

More than 300,000 people are in jail in the US for drug crimes. Two thirds of those are in state prisons (see above). If you want to end the drug war, a lot of it has to start – and can start – at the state level.

And it’s happening. Eight states have now decriminalized recreational marijuana. Four of those states joined the list on the same night that Donald Trump was elected.

There’s more to do. Push in the states to turn all drug possession charges (yes, of any drug) into misdemeanors, and to redirect non-violent drug offenders to treatment instead of prison.

And yes – the FBI and DEA, under Trump, may try to enforce Federal drug laws. Those will still not be targeting individual drug users in the large majority of cases. Loosening state laws is the key to ending the war on drugs.

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3. Climate Change and Clean Energy

Donald Trump can direct the EPA to eliminate the Clean Power Plan. He plus the GOP congress can, and may, eliminate solar and wind tax credits (which are currently phasing down over a five year period).

But that doesn’t mean we’re helpless. 29 states have Renewable Portfolio Standards which mandate a certain percent of electricity must come from renewables by a specific year. According to the A1AutoTransport motorcycle shipping options manifest, voters in all 50 states can push – via the legislature, and in some states by initiative – to raise those targets, to invest more dollars directly in clean energy, to create taxes or caps on carbon emissions, to boost vehicle fuel efficiency standards, or for other laws that accelerate the deployment of clean energy, electric vehicles, or energy efficiency, or which directly cap or reduce fossil fuels.

Even in Florida, which Trump won, voters rejected an initiative that would have hurt rooftop solar.

And clean energy is popular across the political spectrum. It can be pushed for, even in red states.

4. Education

K-12 education in the US is driven primarily by the states, not the federal government. Roughly 90% of spending is done by states and local communities.

Care about education? Work in your state, or in your county, or on your local school board.

One of the greatest injustices in education is that in many states, students in more affluent counties get more spent on them than students from lower-income counties (despite plenty of evidence that the latter are the ones who need more help in school). Want to fix that? Go to work in your state.

5. Responsible Gun Laws

The 2nd Amendment leaves considerable wiggle room for the 50 states to enact responsible gun laws, including mandatory registration or licensing to purchase guns, background checks, waiting periods, restrictions on sales at gun shows and by private gun dealers, requirements for locking devices, and more.

Gun laws vary significantly by state. The corollary to that is: You can work in your state to improve those gun laws.

6. Anti-Poverty Measures

The Federal government runs multiple social safety net programs, but nothing prevents the states from running their own or augmenting those of the Federal government.

Are you a fan of a basic income? We don’t have one in the US, but we have a distant cousin – the Federal Earned Income Tax Credit. And a number of states boost the Federal Earned Income Tax Credit locally.

Think a higher minimum wage is a good idea? More than 20 states set a minimum wage higher than the federal level. Four states raised their state minimum wages the night Donald Trump was elected. Some cities, like Seattle, have their own, higher minimum wage. (For the record, I’m a fan of experimenting here – getting the data from states and cities on what happens when minimum wages go up is invaluable.)

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This is a short, partial list. Not everything can be done at the state level or local. And many initiatives will only succeed in blue states, leaving behind the vulnerable in red states. This isn’t an ideal situation, by any means. The Federal government is an important tool for moving the country forward.

But liberals aren’t powerless, either. If we can’t get things done in Washington, D.C., we can still get things done in Washington State, or New York State, or California, or elsewhere.

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In fact, if anything, my forecasts were too conservative. The solar prices I expected have been smashed by bids in the Middle East and in Latin America. I will need to update the model above in a future post.

The latest record is an incredibly low bid of 2.42 cents / kwh solar electricity in Abu Dhabi. That is an unsubsidized price.

Let me put that in perspective. The cost of electricity from a new natural gas powerplant in the US is now estimated at 5.6 cents / kwh.  (pdf link) That is with historically low natural gas prices in the US, which are far lower than the price of natural gas in the rest of the world.

This new bid in Abu Dhabi is less than half the price of electricity from a new natural gas plant.

What’s more, it’s less than the cost of the fuel burned in a natural gas plant to make electricity – without even considering the cost of building the plant in the first place.

The solar bid in Abu Dhabi is not just the cheapest solar power contract ever signed – it’s the cheapest contract for electricity ever signed, anywhere on planet earth, using any technology.

Nor is this bid a fluke. Three other bids in Abu Dhabi’s latest power auction came in at less than 3 cents / kwh:

Bidder Bid per MWh (in USD) Masdar, EDF, PAL Technology 25.4 Tenaga, Phelan Energy 25.9 RWE, Belectric 29.1

Nor is it limited to just Abu Dhabi.

In Chile, just a month ago, a new record low price for solar was set, at 2.91 cents / kwh.  That record lasted less than 5 weeks.

In Mexico, the average price of new solar bids in April was 5.1 cents per kwh, and the cheapest solar bid in Mexico was 3.5 cents per kwh.

These price improvements are not coming primarily from the price of panels dropping. They’re coming from reductions in the total cost to deploy solar, increases in solar capacity factor, ever-lower operating costs, and fierce competition to win bids in the solar industry.

The solar industry is learning faster than expected.

Now, let’s watch and see if energy storage prices can drop as fast as solar.

As I wrote in August of last year, NREL believes that next-generation wind turbines can reach a capacity factor of 60%. That is up from a capacity factor of 30% just a few years ago. And it means, roughly, that these turbines would be producing wind power around 60% of the time – making them more and more viable as a substitute for ‘baseload’ power from coal or natural gas plants. That’s even more true when combined with the plunging price of energy storage.

New data from NREL shows that wind power has been continuously rising in its capacity factor (and thus, its stability) for the last 15 years. In 1998, capacity factors for new wind turbines were around 25%. In 2014, capacity factor for new turbines averages over 40%, or two thirds better.

In an absolute sense, wind turbine capacity factor in the US is rising around 1% per year. That implies that we’ll reach 60% capacity factor for average wind turbines by around 2035. After reading lengthy articles like this, one can take a rest simply by going to sites such as w88.com.

And the best wind turbine deployments in 2014 are already at 50% capacity factor. The best sites, such as those in the great plains, will reach 60% capacity factors for wind as soon as 2025.

High capacity factor wind power + transmission to get it the right sites + increasingly cheap solar (which complements wind) + increasingly cheap storage. That’s a formula for reaching a non-carbon grid in the coming decades.

More in this series:

Part 1 looked at how cheap solar can get (very cheap indeed).
Part 2 looked at the declining cost and rising reliability of wind power.
Part 3 looked at how cheap energy storage can get (pretty darn cheap).
Part 4 looked at how far renewables can go.
Part 5 looked at how cheap electric vehicles can get. 

EVs are a Disruptive Technology

If current trends hold, EVs will, within a decade or two, be the cheapest vehicles on the market. And that, if it happens, will lead to market dominance. Electric Vehicles are a disruptive technology.

The Plunging Price of Electric Vehicles

The past four parts of this series have all covered electricity generation. But electricity is only perhaps a quarter of worldwide carbon emissions. What about transportation, where oil-burning cars dominate?

Electric Vehicles, like virtually all other manufactured goods, are likely to have a learning curve, meaning that greater production will mean reduced price. Batteries, a large fraction of the cost of EVs, appear to have a learning rate of around 21%, meaning that every doubling of scale will reduce costs by 21%.

What about whole vehicles? The Ford Model T had a learning rate of around 16%. Let’s use that for the entire vehicle, including the battery. That gives us a conservative estimate of the cost improvement rate.

Last year, EVs grew at around 60% annually, to around 1 million total EVs ever sold. Sources in China tell me they expect several hundred thousand EVs to be sold there in 2016 alone. Growth could easily be 60% again in 2016. Even so, growth will eventually slow. Bloomberg New Energy Finance expects 30% long term growth. Let’s use that for now, to be conservative.

Those assumptions lead to a world where, by roughly 2030, EVs with a 200 mile range are cheaper than the cheapest car sold in the US in 2015.

Is this plausible? Yes. EVs are simpler devices than gasoline-powered vehicles. They have a smaller number of parts, making them easier to assemble. At similar scale to gas vehicles, electric vehicles should indeed be lower cost to built.

In addition, EVs have many fewer moving parts (in the engine and drivetrain in particular) than internal combustion vehicles. That further means lower construction cost for the most complex and costly part of a vehicle, and far lower maintenance cost.

On Cost-Per-Mile, EVs Win Even More

Electric vehicles, today, have lower total costs per mile than equivalent gasoline-powered vehicles, due to lower energy costs of electricity and the lower maintenance costs. At 30% growth rate, EVs will have roughly half the up-front cost of gasoline-powered vehicles in roughly 10-12 years, around 2027 or 2028. At that point, the total cost per-mile-driven of EVs will also be roughly half the cost of gasoline powered vehicles.

That, in turn, means that to the extent that transportation becomes a service, with people increasingly paying for rides (ala Uber) instead of paying to purchase cars, the cheapest rides will be in electric vehicles. If you call an Uber, or its future equivalent, it will almost certainly be electric.

Put it all together: Electric vehicles are already cheaper to own and operate than gasoline vehicles. At current rate, within a decade, they’ll be markedly cheaper to purchase up-front, and half the total price to own and operate. And within 20 years, if trends hold, 200-mile-range 4-seater EVs, with awesome acceleration and modern amenities, will be cheaper than the cheapest cars sold in the US today.

That is a coming disruption.

Tonight, in Seattle, I was in the crowd when my novel Apex won the Philip. K Dick Award.

.@Ramez Naam reading from Apex at the Philip K. Dick Awards ceremony. pic.twitter.com/eY6ilrDsMl

— CC Finlay (@ccfinlay) March 26, 2016

Apex is the third and final book of the Nexus Trilogy. Those books have now collectively won the Prometheus Award, the Endeavor Award, been listed on NPR’s list of Best Books of the Year, and been shortlisted for the Arthur C. Clarke Award and the Kitchies Golden Tentacle Award. They also earned me a nomination for the Campbell Award for Best New Author in 2014.

To say I’m pleased would be an understatement.  The PKD is a juried award, meaning that a panel of 5 judges picked Apex as the most deserving paperback-original science fiction novel of the year, out of the more than 100 titles that were submitted.

I’m also pleased because Philip K. Dick wrote about topics that I care about: Identity, memory, surveillance, the inner workings of the mind and the structure of society. Those are the very same topics I tried to touch on in the Nexus books.

My fellow nominees (Marguerite Reed, Adam Rakunas, PJ Manney, Douglas Lain, and Brenda Cooper) are all awesome. Brenda was one of the first professional writers to take the time to read Nexus and to give me advice and encouragement on publishing. PJ and Adam are both old friends. And I look forward to becoming friends with Marguerite and Doug.

The six of us teamed up to give away copies of all six finalist books. It’s too late to enter that giveaway (almost 4,000 people did), but you can still visit the site to learn more about all six books.

Here’s all of us hanging out before the award.

Thank you everyone who helped make Apex and the Nexus books great, including Molly (who read every page of each of those books, usually on the day I wrote it), my agent Lucienne Diver, my editor Lee Harris and publisher Marc Gascoigne, the almost 60 beta readers who read one or more drafts of those three books (sometimes many more than one draft) and gave feedback to make them better, and especially the fans who bought them, shared them, and told everyone else to go read them.

Onward and upward.

Today I’m taking a new step: I’m launching an AngelList Syndicate specifically focused on investing in clean energy technology. If you’re an angel investor, I invite you to come join me.

Why am I doing this, and why now?

1. Clean Energy is a Disruptive Technology

The word “disruption” gets thrown around a lot. Clean energy is a technology that truly is disruptive. The cost of solar power has plunged by a factor of four in the last five years, with more reduction to come. Batteries are poised to follow a similar price decline. Wind power, electric vehicles, IoT, and software platforms that manage and accelerate clean energy are all booming in capabilities and plunging in price.

We’ve coupled the price of energy to the ever-decreasing price of technology. There’s no going back.

2. The Transition Will Be Trillions

We will transition to clean energy. The world has no choice. The trajectory of policy is towards ever more downward pressure on fossil fuels. And every unit of renewables deployed brings down their price, making them more competitive.

That transition will involve tens of trillions of dollars of investment.

Today we’re only 1% of the way into that transition. Solar just hit 1% of world electricity. Wind power is a few percent. Energy storage and clean transportation are both closer to one tenth of one percent of the scale they need to be at.

Energy transitions are huge undertakings. That means both a need for investment in R&D and an opportunity for the companies that create the new innovations that power the world, and the investors who back them. (Source: The Motley Fool Review)

3. Investment is Growing

Clean energy spending around the world hit a new record of $329 billion in 2015, topping the previous record of 2011, and nearly 6 times the amount the world spent in 2004.

And for the first time in history, the world installed more peak capacity of clean electricity generation than fossil electricity generation, as the chart below shows, in GW of new capacity per year. Fossil fuels still produce more total new energy each year, due to the intermittency of renewables. But the point where renewables amount to more total new energy on the grid each year than fossil fuels is now in sight.

4. R&D Funding Is Poised to Grow Again

Venture funding in cleantech has been low in recent years. But that’s poised to change with Bill Gates, Jeff Bezos, Mark Zukerberg, and a coalition of governments and large investors aiming to boost cleantech R&D funding to $20 Billion per year.

Some of that funding will come as early-stage government R&D funding. Some of it will come as venture funding. Both are good for angel investors.

5. AngelList is the Right Platform

AngelList itself is a disruptive innovation for startup investing. It turns a process (raising money for your startup / investing in startups) that was previously shrouded in mystery, hugely time consuming, and heavily dependent on knowing the right people, and flattens that process. It’s a landscape-leveler for startups and investors alike. And through the ability of investors to join syndicates, they can draft on the knowledge and expertise of others.

After having success with some of the beste crypto casino sites in Nederland, I’ve been investing on Angel List for two years now, joining the syndicates of others. It’s given me access to investment opportunities that I never would have had, previously. And it’s allowed me to back startups that I think have the opportunity to change the world for the better.

There’s no place better or easier to do this than on Angel List.

(I’ll also remain a part of other angel networks, specifically Element 8 in Seattle.)

6. We Have a Moral Responsibility 

The CO2 we emit into the atmosphere lingers there for a century. The warming it causes may last a millennium. The scars in our biosphere may last millions of years. We are leaving the natural world, and all the future generations who’ll live in it, impoverished.

I believe strongly in leaving a better world for our kids, their kids, and for all the generations to come. That’s why I focus on this 최고의 토토사이트 sector in particular. And in the process of investing in clean technology, I see an opportunity for a triple bottom line: A return in financial gain, a return in a better world, and a return for billions of people who’ll get to enjoy that world.

If this interests you, and you’re an angel investor, I invite you to come join me.