GoKawiil
Tech News
A new essay argues that writers should draft their own work entirely by hand, then feed it to a large language model purely to spot flaws, never to supply finished phrasing. The author lays out two guiding rules: never use a specific wording an LLM suggests, and treat the model strictly as a copyeditor rather than a co-writer, to avoid producing text that reads as generic machine output.
Leading AI developers are now using their most advanced models to help design and accelerate the next generation of AI systems, according to researchers tracking the industry's progress. This shift is prompting fresh warnings that the pace of development could compound on itself, moving faster than safety and alignment work can keep up with.
Broadcom CEO Hock Tan told CNBC that his company's AI semiconductor revenue forecasts remain unchanged despite market jitters over Anthropic CEO Dario Amodei's call to slow frontier AI development. Broadcom shares fell 4.8% and chip stocks broadly dropped after Amodei's comments, which drew backing from Sam Altman and Elon Musk. Tan said demand for AI compute infrastructure remains strong and durable, and reaffirmed that Anthropic is set to become Broadcom's largest custom chip customer by 2027.
Caltech is organizing a 40-hour event called Mathathon, running October 30 to November 1, where about 100 teams will use frontier AI models with over $2 million in compute credits to tackle open mathematical conjectures. Teams will present their findings to leading mathematicians, who will judge their understanding and rigor, with prizes awarded initially and again later once results are independently verified by the math community.
A new study from Google Research and Technion shows that when models like GPT-5 and Gemini-3 hallucinate, the underlying fact is usually already stored in their parameters rather than missing entirely. The researchers found these models encode 95-98% of tested facts, but often fail to surface them during generation due to retrieval, not storage, limits. They propose 'fact-level profiling' to separate whether a fact is encoded versus reliably retrievable across different phrasings.
Perplexity has launched a hybrid compute feature for its Computer agentic platform that splits AI tasks between cloud-based frontier models and smaller open-weight models running locally on Apple silicon Macs. Sensitive data is automatically routed to the on-device model via a locally-run 'Privacy Gate' classifier that detects personal information before anything reaches the cloud, without interrupting the task or losing context. The feature launches today for opted-in enterprise customers plus Pro and Max subscribers on Macs running macOS 15 or later.