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OpenAI bought Ona to power persistent, secure agents in its Codex platform, while Anthropic lifted its hidden safeguards after researchers flagged degraded outputs. The issue also covers Xiaomi’s MiMo Code AI assistant beating Claude on long tasks and dives into tokenizers, vintage LLM builds, compute markets, data debugging, and PyTorch optimizations.
OpenAI trained a new LLM, GPT-Rosalind, on 50 common biological workflows and major public databases to help researchers navigate massive genomic and protein datasets. The model links genotype to phenotype, suggests biological pathways, and prioritizes potential drug targets by leveraging mechanistic understanding.
The article analyzes the unit economics of large language models (LLMs), focusing on the compute costs associated with training and inference. It discusses how companies like OpenAI and Anthropic manage their financial projections and cash flow, emphasizing the need for revenue growth or reduced training costs to achieve profitability.