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Tech News
Former FTC Chair Lina Khan argues that regulators do not need new legislation to hold AI company executives accountable, pointing to established legal precedent such as a 1934 Supreme Court ruling that barred a competitive 'race to the bottom' among companies. Her comments push back on the idea that AI's novelty exempts its leaders from existing corporate and antitrust law.
New federal rules, including a proposed $100,000 fee on H-1B visa applications introduced in September 2025, are adding to a string of immigration restrictions on skilled foreign workers. IEEE Spectrum found that U.S. tech companies are responding by expanding hiring and opening offices abroad rather than sponsoring visas domestically, though none of the 25 firms contacted would discuss the shift publicly.
A group of drug companies trained an open-source AlphaFold 3 replica called OpenFold3 on more than 20,000 proprietary protein structures pooled from their private vaults. The resulting model outperformed versions trained only on public data or on any single firm's siloed dataset, according to an unpublished, non-peer-reviewed blog post.
Employees are increasingly suspicious of coworkers who use AI tools, largely because organizations haven't established clear guidelines on when and how AI use is appropriate. This ambiguity is creating friction and eroding trust among team members who lack a shared understanding of acceptable practices.
A group of mathematicians argues that while large language models have rapidly gained the ability to solve major outstanding problems, AI companies' drive to treat these solutions as benchmarks conflicts with how mathematics actually operates as a discipline. They describe this as a broader misalignment between AI industry goals and the values of the mathematical community, which relies on slow, collective processes of verification, teaching, and simplification rather than one-off problem-solving feats.
A group of 25 Fields Medal-winning mathematicians has issued a joint declaration warning that AI companies' rush to use famous unsolved math problems as benchmarks for large language models is harming the discipline. They argue that while LLMs have rapidly gained the ability to crack major open problems, this benchmark-driven approach conflicts with how mathematical knowledge has traditionally been built and validated over generations.
Apple continues to frame its artificial intelligence efforts around everyday usefulness rather than grand claims of achieving superhuman or godlike machine intelligence. This contrasts with rivals who often emphasize dramatic warnings or promises about AI's transformative, even existential, power.
U.S. security agencies have publicly accused six Chinese artificial intelligence companies of systematically using American AI models to train their own systems through a technique known as distillation. The practice allows a smaller model to learn from the outputs of a larger, more advanced one, effectively transferring capabilities without the original research investment.
Fast Company has released its 2026 Best Workplaces for Innovators list, recognizing nine companies with 50 or fewer employees for category honors. Judges evaluated these small firms specifically on how well they cultivate cultures that encourage innovation among staff.
Fast Company has released its Best Workplaces for Innovators 2026 list, recognizing six companies with 51 to 200 employees as category winners in the midsize business segment. These firms were selected by Fast Company judges for standout innovation practices within their organizations.
Fast Company's judging panel selected six companies with more than 1,000 employees as category winners in its Best Workplaces for Innovators 2026 rankings. The recognition highlights organizations judged to have strong cultures of innovation despite their large size.
Enterprise software firms including Salesforce and Workday reported resilient financial performance even as investors sold off their shares over fears that AI would erode their business models. The disconnect suggests markets are pricing in disruption faster than it is actually materializing in company earnings.