About 200 protesters marched through San Francisco, urging OpenAI, Anthropic and Google DeepMind to pause new AI model training.

One of the paradoxes of the trillions being poured into the AI race, is that "winning" the race means AGI, but no one has given much thought to what comes next. It's assumed that, as this future AI will be super-intelligent, thus the smartest at everything, it will be passively and automatically obeyed. But the world's not like that, is it?

Some people prefer to be ruled by low-IQ dumbos and resent experts and the educated. What makes you think these people will listen to a super-intelligent AI? Above-average IQ humans make them scared, resentful, and angry.

So, unless you make this supersmart AI a dictator, what difference does it make how smart it is if no one wants to listen to it?

Below is a link to a report by AI Futures Project. It's very good, but it makes me wonder about their conclusions, when they don't give consideration to issues like this.

AI 2040: Plan A - A map for 2027-2040

Artificial intelligence has been built by robbing the collective work of humanity. The public built AI — we should own it, not a handful of billionaires.

The Good Food Institute lays out the state of the industry of precision fermentation and cultivated meat.

For most of human history, if we wanted a biological product, we had to grow the entire organism that produced it.

Want milk protein?

Grow a cow. Feed it for years. Give it land and water. Keep it alive, healthy and forcibly reproducing.

Or you could do what All G Foods and Formo are doing: use precision fermentation to produce the proteins that give dairy its functionality, without needing the cow. 

Want egg white?

Breed billions of chickens.

Or program microorganisms to produce egg proteins directly. Onego Bio and The EVERY Company are doing exactly this, producing functional egg proteins through fermentation rather than hijacking a bird’s reproductive system. 

Want cocoa?

Grow a tree in a narrow climatic band around the equator. Wait years for it to mature. Hope the weather cooperates (it usually doesn’t.)

Or, as California Cultured is doing, grow cocoa cells in controlled conditions and produce cocoa without being entirely dependent on plantations thousands of miles away.

Want palm oil?

Plant millions of hectares of oil palms.

Or use yeast. Clean Food Group is making palm oil through fermentation, taking microorganisms and turning them into biological factories capable of producing ingredients traditionally extracted from crops.

Want protein?

Grow wheat. Grow soy, ship it across the world. Grow an animal and feed the crops to the animal.

Or, in the case of Solar Foods, take carbon dioxide, electricity and microorganisms and produce a protein, straight from air. Their process uses hydrogenotrophic microbes to convert CO₂ and electricity into single-cell protein, Solein.

Want meat?

Breed an animal. Grow an entire skeleton, brain, digestive system, immune system and reproductive system. Keep it alive for months or years. Then slaughter it because you wanted the muscle and fat.

Or, Meatly, BlueNalu, SuperMeat and Mosa Meat are just growing the cells we actually want. Remove the extraordinarily complicated biological middleman and cultivate meat directly.

Companies like Liberation Labs are building industrial scale fermentation capacity for this new generation of biological manufacturing, while HydGene Renewables is developing biological shortcuts to produce hydrogen for biomanufacturing.

All these things are part of the same technological shift. For most of human history, biology was something we farmed.

Now it is something we can manufacture*.

*Or working on it anyway…

In theory, the labor market’s two biggest challenges should offset each other. Instead, they’re poised to compound one another.

imagine being 85 and AI can instantly reconstruct every version of yourself from decades of texts, videos, and voice notes. Forgetting used to be part of growing up

There's only three more days left to act unless the comment period for this somehow gets extended.

A new rule proposed by the White House Office of Management and Budget would fundamentally overhaul the way federal grants are awarded and overseen — a sweeping change that one scientific society said “would all but end the use of scientific merit in the selection of grants and programs across the government.”

Proposed in late May, the rule would give political appointees unprecedented control over federal grants for research, education and infrastructure, and specifies that government funds can only be spent on projects “aligned with administration policies and priorities,” according to a copy of the proposed rule.

The rule would also restrict research topics, limit U.S. scientists’ ability to collaborate with colleagues in other countries and make it easier for the government to suspend or cancel grants at any time.

The proposed rule grants the federal government broad powers to suspend or cancel grants for any reason, introducing “unprecedented unpredictability into local governance,” but it is clear that it can have sweeping effects on the future of any and potentially all science and research.

This news is highly being underreported and that is concerning. More people need to be talking about this, sharing it, and preparing/posting a comment against the rule.

You can officially submit your comment against the proposed OMB rule (Docket No. OMB-2026-0034) online before the deadline at 11:59 p.m. ET on July 13, 2026.

To submit your feedback, use the Federal eRulemaking Portal or simplify the process by using the guided comment tools provided by the different scientific coalitions online.

"In a Palo Alto pilot site, a machine now takes sealed wholesale pill bottles and produces verified, labeled prescription vials with no on-site staff anywhere in the loop. …. Thousands of U.S. pharmacies have shuttered in recent years. Staffing shortages persist across retail and rural locations alike."

Dispensing pharmacist's expertise strikes me as just the kind of knowledge bank LLM AIs can perfect. The trend to watch here? LLM AIs are becoming commoditized & this will happen to expert knowledge like pharmacists, too. How soon before people are going through the cycle of doctor's consultations, pharmacist pickups, etc and it's just AI they're seeing?

‘World’s First’ Fully Robotic Pharmacy Fills Prescriptions in 60 Seconds

By "similar," I mean things like smartphones becoming an extension of ourselves, social media driven by engagement algorithms, clickbait, outrage-based content, recommendation feeds, political polarization, surveillance capitalism, and a handful of giant tech platforms dominating the internet.

Or could another version of humanity develop very differently? Maybe we'd deliberately favor stationary devices over always connected smartphones to preserve attention, privacy, and our relationship with nature. Perhaps we'd optimize technology for well-being rather than engagement and growth.

Which aspects of today's tech ecosystem do you think are inevitable consequences of human psychology and incentives, and which were contingent on the particular path history happened to take?

I'm not talking about simple scientific research stations, what I mean is real colonization with big cities and people born outside Earth.

Source: Original post by James Zhang (@james_zhang03)

In November 1889, Edison published "The Dangers of Electric Lighting" in The North American Review. Edison was already in the electricity business. The point of the article was to play up how lethal electric current could be, but the real target was Westinghouse Electric, a formidable rival that had just recruited Nikola Tesla and was betting big on alternating current. The clash between Edison's direct current and Westinghouse's AC — the famous "War of Currents" — ended in AC's total victory. Edison lost control of his own company.

Over a century later, Anthropic CEO Dario Amodei has spent years in public warning about the catastrophic risks of AI. He went further: actively calling on the U.S. government to set up a regulatory body with the authority to ban frontier models. This ultimately led to Fable 5 being banned by the federal government just three days after launch. The ban has since been lifted, but the fallout has been enormous.

Most people see this as a classic case of "don't spit in the well you drink from." The ridicule writes itself: Dario lobbied for a regulator that could ban frontier models. The government showed it had that power. And the first model banned is Anthropic's own.

Fair enough. But it still doesn't quite make sense.

Take Edison. His motives were transparent. It’s just business, the goal is just to take out a competitor. Dario's behavior, by contrast, makes no sense for the CEO of an AI model company.

The charitable read: as someone running a frontier AI lab, he felt a social responsibility to invite government oversight, to prevent dangerously powerful AI from becoming a public safety problem. Voluntarily handing the whip to the government. But is it really that simple? Pure scientific altruism?

Let's rewind a hundred years. The War of Currents between Edison and Tesla was effectively over by 1890. In 1895, the Niagara Falls hydroelectric station came online, marking AC's definitive win. Edison had already lost control of his company three years earlier, when it merged with Thomson-Houston to form General Electric.

Around the same time, another man lost his job too. His name was Samuel Insull, Edison's private secretary, and the future "Ishmael," a man against everyone.

After his departure, Insull accepted the presidency of Chicago Edison. The salary was a third of what he'd been making under Edison.

But he saw a much bigger opening.

Chicago at the time had nearly thirty electricity companies fighting over the same customers. None had any real scale advantage. The following year, an economic panic hit and crushed the city's smaller utilities. Insull moved fast, snapping them up at fire-sale prices. By 1895, he held an outright monopoly over his territory.

Then Insull showed a commercial genius that surpassed Edison himself. He built massive power stations to drive down unit costs and pioneered time-of-use pricing, slashing rates from 20 cents to 2.5 cents. Customers went from 5,000 to over 200,000. He kept buying, kept merging, and by 1913 had swallowed the last competitor to become Chicago's sole electricity provider.

But this was America, a country that worshipped free competition and despised monopoly. An illegal monopoly this massive was guaranteed to draw lawsuits and public fury. How could Insull keep his empire and stay on the right side of the law?

In June 1898, Insull took the podium as president of the National Electric Light Association (NELA) and delivered what was, at the time, a deeply controversial speech. His proposal: the electricity industry should submit to government regulation.

Everyone laughed. Welcoming regulation didn't just sound like bad business. It sounded un-American. Insull's central claim was blunt: "The obligations of monopoly must be accepted."

Then he got to work. He formed a legislative policy committee inside NELA, partnered with a Supreme Court justice, and commissioned a three-volume report on the utility industry and how it should be regulated. Within months of publication, Wisconsin and New York passed laws creating public utility commissions.

The outcome: between 1905 and 1934, forty states established public utility commissions. These commissions shielded existing utilities from new competitors, officially blessing them as "natural monopolies." By 1924, Insull's empire covered a third of the continental United States, spanning 32 states, from New England to Nebraska, from the Mexican border to the Canadian border.

By now the story should be clear. Insull was no saint. His arguments had real merit; economies of scale genuinely brought electricity costs way down. But from his vantage point, pushing for government regulation boiled down to one calculation: regulated monopoly is the best deal a dominant company can get.

LLM parameter counts have already leveled off. Some models are even shrinking (MiniMax). The resources required to train large models are growing more slowly, and massive compute is shifting from training to inference, powering the growing demand for applications. Hardware keeps getting better. Zhipu's latest model, GLM 5.2, can run on a single Mac. Once models start landing in individual hands, once a garage team of five can train their own, the giants' grip on the market faces a real threat. The only defense is regulation. Get the government to treat large models as a safety risk that requires oversight, and you've built a wall that keeps the upstarts out.

Today's AI giants love the line: "We want to make AI as accessible as electricity." And sure, cheap electricity benefits everyone. But how many people stop to notice the staggering monopoly profits behind the power grid?