White House Chronicle

News Analysis With a Sense of Humor

Tech Giants Will Boost Nuclear but Won’t Help With Your Bill

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There is an abiding faith that if someone is good at one thing, they must be good at many things. At heart, it is a belief that outside the metaphorical box, there is much greater ability than inside it.

This is once again on display with widespread enthusiasm for the idea that the looming shortage of electricity can be solved by companies like Amazon, Google, Microsoft and Meta because they have been so wildly successful at what they do — and have mountains of cash to demonstrate it. Also, it is thought they will somehow do it better than the entrenched utilities.

The argument is that those who use vast new quantities of electricity for data centers will pay for its generation, and somehow the rest of the electricity supply system will be unaffected. It won’t.

The new dedicated generators will still buy steel, connectors (wires), transformers, switches, and the myriad bits that go to generating and transmitting electricity. They will still buy uranium, natural gas, strain the gas pipelines and the transmission system.

They will still buy available solar cells, wind turbines and dominate the competition to site these. They will be exerting four-square price pressure for all supplies, including utility-scale batteries.

The data center-dedicated generator will still compete in the labor marketplace for precious skilled workers, now in perilous short supply as the utility industry, without counting data center generators, spends well over $2 billion yearly on upgrading its systems.

I am not saying it isn’t a good thing to shake up the utility industry. I am saying not to expect magical new electricity developments that won’t affect everyone. The bills will still come, and they will be hefty.

Also, big tech will learn some sharp and costly lessons.

The thing about the internet and the world of computing is that they have been a zero-sum game. There are no rules, there is no legacy drag, and every invention, every step forward, enters the marketplace unencumbered.

There was nothing and no one to hold things back. There still isn’t, except for the availability of power for the data centers.

Not so in the electricity ecosphere. There are rules — local, state and federal. There is political oversight, and issues such as land use, water supply and air pollution must be factored in.

The new generation has to accommodate the rules of yesterday. It will be examined, debated, disputed and delayed.

For big tech and artificial intelligence, its latest frontier, everything is possible. But in their new role of making kilowatt hours, there are entrenched stakeholders and they are vociferous and opinionated, and NIMBY (Not In My Back Yard) is an ever-present reality.

Building a power plant isn’t like designing an algorithm. It isn’t done in secret and then released to the world, as ChatGPT did in November 2022. It must be collaborative and transparent at every step.

The tech giants are betting on nuclear power for their future power needs. Two of them, Microsoft and Google, are supporting restarting mothballed reactors, Three Mile Island in Pennsylvania and Duane Arnold in Iowa. All of them are interested in small modular reactors and have working arrangements with SMR developers.

In this way, the future of nuclear power may rest with the tech giants: They have the money to take the risk. Microsoft has even signed an agreement with Helion, a company planning to bring fusion power to market.

These developments favor a bright future for all electricity as the tech giants assume the challenges and risks of new nuclear technologies. But they won’t contain electric bills in the years ahead. These will continue to rise.

The utilities are doing what they can to contain these bills. The future demands significant expenditures, and, in some way, these will be reflected in consumer electricity costs.

The fact that the tech giants with money aplenty are going to shoulder greater risks doesn’t mean that their presence as ever more demanding electricity consumers won’t affect the commodity’s cost.

The war with Iran will affect global electricity demand. Countries will seek to substitute electricity for oil and gas where they can, thereby straining already-tight supply chains for generation and transmission components.

The essentiality of electricity is growing, as is the household outlay on it. Ouch!

The AI Tsunami Is Approaching Shore; Jobs at Big Risk

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The Big One is coming, and it isn’t an earthquake in California or a hurricane in the Atlantic. It is the imminent upending of so many of the world’s norms by artificial intelligence, for good and for ill.

Jobs are being swept away by AI not in the distant future, but right now. A recent Stanford University study found that entry-level jobs for workers between 22 and 25 years old have dropped by 13% since the widespread adoption of AI.

Another negative impact of AI: The data centers that support AI are replacing farmland at a rapid rate. The world is being overrun with huge concrete boxes, Brutalist in their size and visual impact.

Meta Platforms (of which Facebook is part) plans to spend hundreds of billions of dollars to build several massive AI data centers; the first called Prometheus and the second Hyperion.

CEO Mark Zuckerberg said in a post on his Threads social media platform: “We’re building multiple more titan clusters as well. Just one of these covers a significant part of the footprint of Manhattan.”

Data centers are voracious in their consumption of electricity and are blamed for sending power bills soaring across the country.

But AI has had a positive impact on the quality of medicine, improving accuracy, consistency and efficacy, according to the National Institutes of Health.

Predictive medicine is on a roll: Alzheimer’s Disease and some cancers, for example, can be predicted accurately. That raises the question: Do you want to know when you will lose your mind or get cancer?

Where AI is without downside is medical “exaptation.” That happens when a drug or therapy developed for one disease is found to be effective with another, opening up a field of possibilities.

AI also offers the chance of shortening clinical trials for new drugs from years to a few months. Side effects and downsides can be mapped instantly.

Life expectancy is predicted to increase substantially because of AI. Omar Hatamleh, an AI expert and author, told me, “A child born today can expect to live to 120.”

Likewise, predictive maintenance with AI is already useful in forecasting the failure of industrial plants, power station components and bridges.

Oh, and productivity will increase across the board where AI and AI agents — the AI tools developed for special purposes — are at work.

The trouble is AI will be doing the work that heretofore people have done.

Pick a field and speculate on the job losses there. This may be fun to do as a parlor game, but it is deeply distressing when you realize that it could happen in the very near future — like in the next year.

Most are low-skilled white-collar jobs, such as those in call centers, or in medical offices checking insurance claims, or in an accounting firm doing bookkeeping. In short, if you are a paper pusher, you will be pushed out.

Look a little further — maybe 10 years — and Uber, which has invested heavily in autonomous vehicles, will have decided that they are ready for general deployment. Bye-bye Uber driver, hello driverless car.

Taxis and truck drivers might well be the next to get to their career-end destinations quicker than they expected.

By the way, autonomous vehicles ought to have fewer accidents than cars with drivers do, so the insurance industry will take a hit and lots of workers there will get the heave-ho. And collision repairs may be nearly outdated.

These aren’t speculation; they are real possibilities in the near future. Yet the political world has been arguing about other things.

As far as I am aware, when the leadership of the U.S. military gathered at the Marine Corp Base Quantico in Virginia recently to get a pep talk on shaving, losing weight and gender superiority, they didn’t hear about how AI is transforming war and what measures should be taken. Or whether there will be work for those who leave the military.

The Big One is coming, and the politicians are worrying about yesterday’s issues. That is like worrying about your next guest list when an uninvited guest, a tsunami of historic proportions, is coming ashore.

The Backdoor Challenge of AI Machine-Learning

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The great race is on. It isn’t the one on television, but it is one that has put the world’s wealthiest companies in fierce competition to secure market share in artificial intelligence.

The handful of big-tech companies and their satellites may have spent as much as $1 trillion on machine-learning and data center infrastructure to stuff their AI systems with billions of bits of information hoovered up from public and private sources on the internet.

These companies — Amazon, Google, Meta, Microsoft and OpenAI among them — are rich and have made their creators rich beyond compare because of information technology. Their challenge is to hold onto what they have now and to secure their futures in the next great opportunity: AI.

An unfortunate result of the wild dash to secure the franchise is that the big-tech companies — and I have confirmed this with some senior employees — have rushed new products to market before they are ready.

The racers figure that the embarrassment of so-called hallucinations (errors) is better than letting a competitor get out in front.

The challenge is that if one of the companies — and Google is often mentioned — isn’t on the leaderboard, it could fail. It could happen: Remember “MySpace”?

The downside of this speedy race is that safety systems aren’t in place or effective — a danger that could spell operational catastrophe, particularly regarding so-called backdoors.

According to two savants in the AI world, Derek Reveron and John Savage, there is a clear-and-present danger presented by this urgency for market speed over dangerous consequences.

Savage is the An Wang professor emeritus of computer science at Brown, and Reveron is chair of the National Security Affairs Department at the Naval War College in Newport, Rhode Island.

Reveron and Savage have been sounding the alarm on backdoors, first in their book, “Security in the Cyber Age: An Introduction to Policy and Technology,” published by Cambridge University Press early this year, and later in an article in Binding Hook, a British website with a focus on cybersecurity and AI.

“AI systems are trained neural networks, not computer programs. A neural net has many artificial neurons with parameters on neuron inputs that are adjusted (trained) to achieve a close match between the actual and the desired outputs. The inputs (stimuli) and desired output responses constitute a training set, and the process of training a neural net is called machine-learning,” the co-authors write.

Backdoors were initially developed by telephone companies to assist the government in criminal or national security cases. That was before AI.

Savage told me that backdoors pose a grave threat because, through them, bad actors can insert malign information — commands or instructions — into computers in general and backdoors in machine-learning-based AI systems in particular. Some backdoors can be undetectable and capable of inflicting great damage.

Savage said he is especially worried about the military using AI prematurely and making the nation more vulnerable rather than safer.

He said an example would be a weapon fired from a drone fighter jet flying under AI guidance alongside a piloted fighter jet where the weapon fired by a drone could be directed to do a U-turn and come right back and destroy the piloted plane. Extrapolate that to the battlefield or to an aerial bombardment.

Savage says that researchers have recently shown that undetectable backdoors can be inserted into AI systems during the training process, which is a new, extremely serious, and largely unappreciated cybersecurity hazard.

The risk is exacerbated because feeding billions of words into big-tech companies’ machine-learning systems is now done in low-wage countries. This was highlighted in a recent “60 Minutes” episode about workers in Kenya earning  $2 an hour, feeding data to machine-learning systems for American tech companies.

The bad actors can attack American AI by inserting dangerous misinformation in Kenya or in any other low-wage country. Of course, they can launch backdoor attacks here, too, where AI is used to write code, and then control for that code is lost.

In their Binding Hook article, Reveron and Savage make a critical point about AI. It isn’t just another more advanced computer system. It is fundamentally different and less manageable by its human masters. It lacks an underlying theory to explain its anomalous behavior, which is why the AI specialists who train machine-learning systems cannot explain this behavior.

Deploying technology with serious deficits is always risky until a way to compensate for them has been discovered. Trouble in is trouble out.

Tech Giants Want In on Electricity, Google Has a Foothold

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During the desperate days of the energy crisis in the 1970s, it looked as though the shortage was permanent and we would have to change the way we lived, worked and played to accommodate it.

In the end, it was technology that solved the crisis.

For fossil fuels, 3D seismic, horizontal drilling and fracking were used. For electricity, it was wind and solar, and better technology for making electricity with gas — a swing from burning it under boilers to burning it in aero-derivative turbines, essentially airplane engines on the ground.

A new energy shortage — this time confined to electricity — is in the making. There are a lot of people who think that, magically, the big tech companies, headed by Alphabet’s Google, will jump in and use their tech muscle to solve the crisis.

The fact is that the tech giants, including Google, Amazon, Microsoft, Apple and Meta, are highly interested in electricity because they depend on supplies for their voracious data centers. According to many experts, the electricity demand will increase exponentially as AI takes hold.

The tech giants are aware of this and have been busy as collaborators and innovators in the electric space. They want to ensure an adequate electricity supply and insist it is green and carbon-free.

Google has been a player in the energy field with its Nest Renew service. This year, it stepped up its participation by merging with OhmConnect to form Renew Home. It is what its CEO, Ben Brown, and others call a virtual power plant (VPP). These are favored by environmentalists and utilities.

A VPP collects or saves energy from the system without requiring additional generation. It can be hooking up solar panels and domestic batteries or plugging in and reversing the flow from an electric vehicle at night.

For Renew Home, the emphasis is definitely the home, Brown said in an interview.

For cash or other incentives (like rebates), participants cut their home consumption, managed by a smart meter so that air conditioning can be put up a few notches, washing machines are turned off, and an EV can be reversed to feed the grid.

Brown said that at present, Renew Home controls about 3 gigawatts of residential energy use —  a gigawatt is sometimes described as enough electricity to power San Francisco — and plans to expand that to 50 GW by 2030. All of it is already in the system and doesn’t require new lines, power plants or infrastructure.

“We are hooking up millions of customers,” he said, adding that Renew Home is cooperating with 100 utilities.

Fortunately, peak demand and the ability to save on home consumption coincide between 5 p.m. and 9 p.m.

There is no question that more electricity will be needed as the nation electrifies its transportation and its manufacturing — and especially as AI takes hold across the board.

Todd Snitchler, president of the Electric Power Supply Association, told the annual meeting of the U.S. Energy Association that a web search using ChatGPT uses nine times as much power as a routine Google search.

Google and the other four tech giants are in the electric supply space, but not in the way people expect. Renew Home is an example; although Google’s name isn’t directly connected, it is the driving force behind Renew Home.

Sidewalk Infrastructure Partners (SIP) has invested $100 million in Renew Home. Brown is a former Google executive, and Jonathan Winer is a co-CEO and cofounder of SIP.

As Jim Robb, the president of the North American Electric Reliability Corp., the congressionally mandated, not-for-profit supply watchdog, said recently on the TV show “White House Chronicle,” the expectation that Google will go out and build power plants is silly as they would face the same hurdles that electric utilities already face.

But Google is keenly interested in power supply, as are the other tech behemoths. The Economist reports they are talking to utilities and plant operators about partnering on new capacity.

Also, they are showing an interest in small modular reactors and are working with entrepreneurial power providers on building capacity, with the tech company taking the risk. Microsoft has signed a power-purchase agreement with Helion Energy, a fusion power developer.

Big tech is on the move in the electric space. It may even pull nuclear across the finish line.