05 Sci-Tech
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As major artificial intelligence breakthroughs arrive on what seems to be a near-weekly basis, the race between the US and China continues to intensify. In this post and the next, we will examine the good and bad news for the prospects of American triumph in the battle for AI superiority, a skirmish that could well determine the future of global innovation.
Let’s start with the bad news.
Last week, I attended a hearing of the House Select Committee on the Chinese Communist Party entitled “China’s Campaign to Steal America’s AI Edge.” Chairman John Moolenaar (R-MI) opened the proceedings by asserting that “China’s smuggling of advanced AI chips is a pervasive threat facing law enforcement” and observing that “just last month, the Department of Justice announced a $2.5 billion chip smuggling case, which would be the largest export control violation in US history.”
Moolenaar then asked, “Why is China so desperate to acquire US-designed chips? The reason is obvious. AI is a truly transformative technology. It’s already changing how we fight wars, run our government, and operate companies.” Critically, the chairman contended, “it is essential for the United States to maintain a decisive lead in the AI race. We cannot afford a future where Beijing dominates this technology.”
At the hearing, Dmitri Alperovitch, the founder and chairman of the Silverado Policy Accelerator, echoed Moolenaar, arguing that “we are in a race, and the stakes could not be higher. Artificial intelligence will transform every industry, every battlefield, and every government.” Critically, Alperovitch asserted, “whoever fields the best models running on the best infrastructure will likely win not just the AI race itself but the 21st century. The single most important input to winning is compute—the processing power used to train and run AI models.”
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Federal officials are scrambling after a powerful new artificial intelligence (AI) model demonstrated the ability to hack virtually every major operating system and web browser, triggering urgent warnings from top government and financial leaders.
AI giant Anthropic’s new system, known as “Mythos,” is being kept under tight restrictions.
However, insiders say the threat is already serious enough that the U.S. government is racing to understand it before it’s too late.
Treasury Rushes to Access High-Risk AI
According to reports, the U.S. Treasury Department is urgently seeking access to Anthropic’s restricted model
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One of the biggest takeaways of the war with Iran is that it has proven itself to be a surprisingly capable adversary against the United States. In addition to its willingness to go on the offensive, Iran has forced the U.S. and its regional allies to confront the rise of cheap drones on the battlefield.
Iranian drones, made with commercial-grade technology, cost roughly $35,000 to produce. That is a fraction of the cost of the high-tech military interceptors sometimes used to shoot them down.
Note: Estimated price of munitions per unit. In practice, multiple interceptors are fired when targeting a drone. For instance, with the $80 bullet fired by the Centurion Counter-Rocket, Artillery, and Mortar (C-RAM), 75 rounds are fired in a second. Sources: Department of Defense, Lockheed Martin, Northrop Grumman, Open Source Munitions Portal, SRC Inc, U.S. Army and U.S. Navy.
Cheap drones changed the war in Ukraine, and they have enabled Iranians to exploit a gap in American defense investments, which have historically prioritized accurate but expensive solutions.
Countering drones has been a major priority for the Pentagon for years, according to Michael C. Horowitz, who was a Pentagon official in the Biden administration. “But there has not been the impetus to scale a solution,” he said.
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PHALABORWA, South Africa — Two enormous sandlike dunes at an old chemical processing plant in South Africa are at the center of an exploratory U.S.-backed project to extract highly sought-after rare earth elements from industrial mining waste.
The Phalaborwa Rare Earths Project has U.S. support through a $50 million equity investment by the government’s International Development Finance Corporation and is part of accelerated U.S. efforts to reduce reliance on economic rival China for the minerals crucial for making electronic devices, robotics, defense systems, electric vehicles and other high-tech products.
Countries have identified dozens of minerals, including copper, cobalt, lithium and nickel, as critical because they are essential for new technologies. The 17 rare earth elements are a subset of them.
President Donald Trump has made expanding U.S. access to critical minerals, including rare earth elements, a central policy to counter China. The Trump administration said this year it will deploy nearly $12 billion to create its own strategic reserve.
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On Monday, at 4:53 P.M. local time, a magnitude 7.7 earthquake struck off the northeastern shores of Japan’s largest island, Honshu, where the Pacific tectonic plate plunges beneath the North American plate at the deep-sea Japan Trench. Immediately, the Japan Meteorological Agency (JMA) sent out a tsunami warning alert. Although small tsunami waves did soon reach various sections of the coast, no reports of injuries, deaths, or significant damage to homes or infrastructure were reported.
The danger, however, has not necessarily passed. Following the temblor, a JMA spokesperson told the media and those along the affected shoreline that “the likelihood of a new, huge earthquake occurring is relatively higher than during normal times.” Specifically, there is an elevated risk of a “megaquake”—one of magnitude 8.0 or greater—in the coming days.
The odds of an imminent megaquake are very low—around one in 100. “This 1 percent probability is still low in absolute terms, but it’s 10 times higher than normal, which is significant from a risk management perspective,” says Amilcar Carrera-Cevallos, an independent earthquake scientist.
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Big data, artificial intelligence and advanced pricing algorithms make it easier than ever for companies to fine-tune prices for individual products to closely reflect their unique value and cost. The conventional wisdom is straightforward: better data, better algorithms and sharper segmentation should produce better profits. But new research suggests that the most profitable answer isn’t always more fine-grained pricing across a product line. In fact, it is fewer, better-chosen price points.
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Key Takeaways
- The National Association for Gun Rights advocates for nationwide Constitutional Carry, citing data from the safest states without permit requirements.
- Recent data shows that crime decreased in Florida and Ohio after adopting Constitutional Carry laws, contradicting opponents’ claims.
- The safest states include Maine, New Hampshire, and North Dakota, all of which permit lawful carry without a permit.
- Strict gun control states like California and New York report higher death rates compared to Constitutional Carry states.
- Twenty-nine states now support the principle of carrying firearms without government permission, aligning with Second Amendment rights.
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The capabilities of leading AI models continue to accelerate, and the largest AI companies, including OpenAI and Anthropic, are hurtling toward IPOs later this year. Yet resentment toward AI continues to simmer, and in some cases has boiled over, especially in the United States, where local governments are beginning to embrace restrictions or outright bans on new data center development.
It’s a lot to keep track of, but the 2026 edition of the AI Index from Stanford University’s Human-Centered Artificial Intelligence center pulls it off. The report, which comes in at over 400 pages, includes dozens of data points and graphs that approach the topic from multiple angles, from benchmark scores to investment and public perception.
As in prior years (see our coverage from 2021, 2022, 2023, 2024, and 2025), we’ve read the report and identified the trends that encapsulate the state of AI in 2026.
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Internet users have found humor in the idea behind the tool, joking about automating their coworkers before themselves. However, Colleague Skill’s virality has sparked a lot of debate about workers’ dignity and individuality in the age of AI.
After seeing Colleague Skill on social media, Amber Li, 27, a tech worker in Shanghai, used it to recreate a former coworker as a personal experiment. Within minutes, the tool created a file detailing how that person did their job. “It is surprisingly good,” Li says. “It even captures the person’s little quirks, like how they react and their punctuation habits.” With this skill, Li can use an AI agent as a new “coworker” that helps debug her code and replies instantly. It felt uncanny and uncomfortable, Li says.
Even so, replacing coworkers with agents could become a norm. Since OpenClaw became a national craze, bosses in China have been pushing tech workers to experiment with agents.
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If you have ever stared at thousands of lines of integration test logs wondering which of the sixteen log files actually contains your bug, you are not alone — and Google now has data to prove it.
A team of Google researchers introduced Auto-Diagnose, an LLM-powered tool that automatically reads the failure logs from a broken integration test, finds the root cause, and posts a concise diagnosis directly into the code review where the failure showed up. On a manual evaluation of 71 real-world failures spanning 39 distinct teams, the tool correctly identified the root cause 90.14% of the time. It has run on 52,635 distinct failing tests across 224,782 executions on 91,130 code changes authored by 22,962 distinct developers, with a ‘Not helpful’ rate of just 5.8% on the feedback received.
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On an AstroTurf lawn in Berkeley, California, one recent Friday, content creators used to making videos about romance novels, climate change and tech tips got advice on covering a more theoretical topic: How to spread the message that rogue artificial intelligence could wipe out humankind.