OpenAI limits GPT-5.6 rollout and Polymarket hits $1B

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OpenAI is limiting the release of its newest AI models to a “small group of trusted partners” at the behest of the U.S. government, the company said Friday.

The next generation GPT-5.6 lineup includes Sol, its flagship model; Terra, a more balanced model for everyday use; and Luna, a faster, lower-cost option. Although Sol is the company’s most powerful model, the Trump administration has restricted the release of all three. OpenAI said the preview is limited to partners “whose participation has been shared with the government.”

The administration’s request comes as the U.S. government puts new pressure on AI companies to restrict their most advanced systems. After Anthropic released its most powerful public model Fable 5, the administration ordered the company to remove access for any foreign national, prompting Anthropic to take the model down entirely.

Polymarket has crossed a monumental financial milestone, reporting an annualized revenue run rate exceeding $1 billion.

The platform's explosive growth is backed by transaction data showing a massive surge in user engagement over the late spring.

Dune Analytics reports that daily trading volume on Polymarket's U.S. platform jumped from $50 million in mid-May to over $200 million in June.

This rapid scaling highlights the massive demand for decentralized prediction markets and real-time sentiment tracking.

The platform's success is cementing prediction markets as a primary source of alternative data for finance, tech, and politics.

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Paul Meade, the Apple vice president in charge of the Vision Pro headset, is leaving the company to join OpenAI’s hardware team, according to Bloomberg’s Mark Gurman .

Meade also reportedly led the development of the AI-powered smart glasses that Apple plans to launch next year . The costly Vision Pro was not a hit, but Apple is hoping that more affordable smart glasses will help it compete with wearable devices from Meta .

Gurman frames this departure as a byproduct of John Ternus’ imminent elevation to Apple CEO , and of Ternus’ decision to shake up the hardware engineering team, which left some of the company’s vice presidents feeling like they’d been demoted.

Building financial technology is notoriously difficult due to the zero-tolerance policy for data loss, race conditions, and ledger discrepancies.

The newly released Fintech Engineering Handbook addresses these challenges head-on by providing a clear, structured roadmap for developers.

The handbook covers fundamental concepts such as double-entry accounting, transaction isolation levels, and idempotent API design.

It also dives deep into the realities of integrating with legacy banking networks, processing credit cards, and handling multi-currency reconciliations.

The guide has quickly become a highly recommended resource on Hacker News for engineers looking to build robust, audit-ready financial backends.

Radio frequency chip design has historically been one of the most stubborn bottlenecks in hardware engineering, relying heavily on highly experienced specialists.

Unlike digital chip design, which is highly automated, RFIC design involves complex electromagnetic interactions that behave more like an art than a science.

New AI models are now mastering these analog complexities, learning to optimize layouts, minimize noise, and maximize signal integrity.

This breakthrough promises to drastically compress the development cycles for next-generation 5G, 6G, and satellite communication hardware.

By automating the tedious trial-and-error phases of RF design, engineers can focus on higher-level system architectures and novel chip topologies.