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Whale 0x0c17 has been buying the $MEME dip. Over the past 10 days, the whale spent $1.04M to buy 20.31M $MEME($930K now) at an average price of $0.051, making him the largest $MEME holder.

*TRUMP AGREES TO NEW BIPARTISAN ETHICS PROVISION IN MASSIVE CRYPTO BILL, GOP AIDE SAYS: AP *TRUMP AGREED TO CRYPTO ETHICS PROVISIONS IN A SWEEPING BILL HEADED FOR A VOTE *THE UPDATED BILL REQUIRES DIVESTING OR PLACING CRYPTO INTERESTS INTO A BLIND TRUST

I must be among an extremely small group of people (n=1?) that have both 1) trained a frontier LLM and 2) designed and synthesized custom viruses in a lab with my own two hands. And I think that the takes on AI killing us all by creating dangerous viruses is total bogus.

Another deep green night for commodities. The input costs for just about all basic necessities are in a strong bull market that is gaining momentum. Record diesel prices, record beef prices, $100+ oil prices, and record copper prices. The most interesting part of it all is that the S&P 500 is ~2% away from a record high and up sharply on the year. This is what happens when an energy crisis, inflation, and the biggest technological revolution in history all intersect. As we have been warning for 2+ years: Own assets or be left behind.

No stock pairing No overvalued useless tech No bundle, team, or insiders No false promises Just a coin with a cult community formed around a narrative everyone can understand Return to the basics Return to what made memecoins fun again

No stock pairing No overvalued useless tech No bundle, team, or insiders No false promises Just a coin with a cult community formed around a narrative everyone can understand Return to the basics Return to what made memecoins fun again

Micron Taiwan’s union at its Taoyuan plant rejected a package including an NT$1 million “appreciation bonus” for all workers and threatened to strike, media report, saying it wants a 15% profit-sharing system for when the company is profitable and reasonable safeguards during down cycles. Union officials were reportedly unhappy that Micron issued a press release about its proposed package instead of reaching a deal via talks. $MU #semiconductors#

Law enforcers already have authority to charge companies and their CEOs for creating and releasing dangerous, unvetted, or defective products. We shouldn’t let discussions about new legal regimes distract from the fact that there’s no AI exemption from laws already on the books — a point @FTC emphasized repeatedly during my tenure. 1. There is an extensive set of laws that govern dangerous and defective products. For example, releasing unvetted AI models or agents can violate consumer protection laws. Shipping flawed AI tools without implementing adequate measures to detect and stop rogue or defective AI agents can be an “unfair or deceptive” act or practice under the FTC Act (and analogous state laws). And some state AGs are already exploring holding AI firms and their CEOs criminally liable when their models participate in criminal activity. 2. Existing laws also prohibit “unfair methods of competition.” This covers instances where AI firms appropriate the competitively sensitive information of their customers, including through tracking their use of various tools. It can also cover instances where firms pursue dangerous behavior, aware that doing so may compel rivals to do the same. As the Supreme Court has noted: “A method of competition which casts upon one's competitors the burden of the loss of business unless they will descend to a practice which they are under a powerful moral compulsion not to adopt, even though it is not criminal, was thought to involve the kind of unfairness at which the [unfair methods of competition] statute was aimed." 3. The highly concentrated and interconnected structure of these markets could be creating major risks and conflicts of interest. We had started investigating these partnerships and cross-investments across the stack (and released a preliminarily overview of some findings: Both federal and state enforcers should be scrutinizing these opaque relationships and inter-dependencies. We are already seeing how these relationships could undermine accountability. For example, OpenAI could face liability given the Hugging Face incident, but Hugging Face being bought up by Nvidia means that we’re unlikely to see it file a lawsuit over this — given Nvidia’s strong incentive to see OpenAI continue full speed ahead. 4. As AI tools dramatically change the landscape of cybersecurity risks and hacks, all businesses should be doubling down on having core security protections in place. Firms that fail to invest in adequate data security measures or fix known vulnerabilities can also be breaking the law. A recent analysis showed that around 1/3 of Fortune 100 companies do not even have a way to notify them about security issues. During my @FTC tenure, we sued firms for poor data security practices and held CEOs liable when they were personally responsible. 5. As policymakers consider new legal regimes, we should be looking to lessons from prior efforts to govern major sectors, such as banking and other networks, platforms, and utilities. Tools like structural separations, nondiscrimination, and supervision could be key, and there’s a rich history of what works and what doesn’t. But we can and must pursue any new efforts alongside enforcing existing laws.

BREAKING: Elon Musk has just announced Grok 4.8, a massive 2.5 trillion-parameter model trained using SpaceXAI’s new C++ software stack. The model will begin reinforcement learning after training is complete.

Great example from @jeffhollan showing how Foundry makes long-running agents enterprise-ready, starting with business outcomes and building security, safety guardrails, auditability, and FinOps into the system from the start, across the entire multi-agent, multi-model workflow.