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Amid lawsuits, executive departures, and preparations for an IPO, Greg Brockman has emerged as an increasingly powerful figure at OpenAI. The article analyzes how the co-founder and current president has consolidated influence over the company’s engineering and strategic direction.
Apple Machine Learning studies how to mix scarce target-domain data with abundant generic data during language-model pretraining. Across more than 2,000 training runs, the research examines the trade-off between insufficient target exposure, repeated examples, diminishing returns, and overfitting.
OpenAI is seeking to compete more directly with Anthropic by introducing stronger privacy protections for enterprise customers. The two companies are increasingly competing over how securely customer data is handled.
Flock is testing an AI tool that tracks and identifies people based on their driving habits. The system goes beyond conventional license-plate monitoring, raising significant surveillance and privacy concerns.
The article reports that Anthropic and Amazon have reportedly purchased large volumes of physical books, scanned them, and destroyed the originals to reduce copyright risk in AI training. It argues that this strategy is tied to differences in US and Chinese copyright law, while also raising concerns about the irreversible loss of cultural artifacts.
WIRED reconstructed the code behind Flock’s next-generation AI surveillance system. The system is already being used by some police departments and appears capable of tracking more than license plates.
Z.ai argues that model scaling should account for data, compute allocation, inference cost, sparsity, effective depth, and post-training—not parameters alone. The post presents GLM-5.3 as a controlled experiment using the same total and activated parameters as GLM-5.2 while scaling long-horizon environments and reinforcement learning for one month.
OpenAI rolled out support for controlling Apple’s iMessage service through ChatGPT. The integration could create new privacy concerns for Apple and users handling message data through an AI assistant.
Incogni researchers evaluated 13 AI platforms to assess the privacy risks associated with each service. The analysis suggests that larger platforms generally present greater privacy risks, with one notable exception.
Australia’s parliament passed the News Bargaining Incentive, requiring major platforms to face the law even if they choose not to carry news. Meta, Google, TikTok, and LinkedIn are among the affected companies.