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Anthropic raises $65B in Series H at a $965B post-money valuation, releases Opus 4.8 and Dynamic Workflows
claude-opus-4.8 claude-opus-4.7 gpt-5.5 anthropic altimeter dragoneer greenoaks sequoia andonlabs model-release reinforcement-learning agentic-ai model-evaluation long-context model-optimization fine-tuning multitasking parallel-processing dan_shipper scaling01 zephyr_z9 teortaxes_tex kimmonismus
Anthropic announced a massive $65B Series H financing at a $965B valuation, led by Altimeter, Dragoneer, Greenoaks, and Sequoia, with run-rate revenue surpassing $47B. They launched Claude Opus 4.8, an update to Opus 4.7 featuring "sharper judgment," "more honesty," and longer autonomous work at the same price. Anthropic also introduced Dynamic Workflows in Claude Code, enabling orchestration of hundreds of parallel subagents for large tasks, available in research preview across multiple platforms. Opinions on Opus 4.8 vary, with some praising it as a major leap and others viewing it as incremental or catch-up to OpenAI's GPT-5.5 family.
not much happened today
glm-4.7-flash grok deepseek-r1 qwq x-ai unsloth-ai google deepseek ollama transformer-architecture recommendation-systems local-inference kv-cache quantization tensor-parallelism reasoning model-optimization fine-tuning giffmana david_sholz yuchenj_uw nearcyan sam_paech teortaxes_tex danielhanchen alexocheema nopmobiel rohanpaul_ai
X Engineering open-sourced its new transformer-based recommender algorithm, sparking community debate on transparency and fairness. GLM-4.7-Flash (30B-A3B) gains momentum as a strong local inference model with efficient KV-cache management and quantization tuning strategies. Innovations include tensor parallelism on Mac Minis achieving ~100 tok/s throughput. Research highlights "Societies of Thought" as a reasoning mechanism improving model accuracy by 20%+.
not much happened today
gemma-3n glm-4.1v-thinking deepseek-r1t2 mini-max-m1 o3 claude-4-opus claude-sonnet moe-72b meta scale-ai unslothai zhipu-ai deepseek huawei minimax-ai allenai sakana-ai-labs openai model-performance vision conv2d float16 training-loss open-source model-benchmarks moe load-balancing scientific-literature-evaluation code-generation adaptive-tree-search synthesis-benchmarks alexandr_wang natfriedman steph_palazzolo thegregyang teortaxes_tex denny_zhou agihippo danielhanchen osanseviero reach_vb scaling01 ndea
Meta has hired Scale AI CEO Alexandr Wang as its new Chief AI Officer, acquiring a 49% non-voting stake in Scale AI for $14.3 billion, doubling its valuation to ~$28 billion. This move is part of a major talent shuffle involving Meta, OpenAI, and Scale AI. Discussions include the impact on Yann LeCun's influence at Meta and potential responses from OpenAI. In model news, Gemma 3N faces technical issues like vision NaNs and FP16 overflows, with fixes from UnslothAI. Chinese open-source models like GLM-4.1V-Thinking by Zhipu AI and DeepSeek R1T2 show strong performance and speed improvements. Huawei open-sourced a 72B MoE model with a novel load balancing solution. The MiniMax-M1 hybrid MoE model leads math benchmarks on the Text Arena leaderboard. AllenAI launched SciArena for scientific literature evaluation, where o3 outperforms others. Research from Sakana AI Labs introduces AB-MCTS for code generation, improving synthesis benchmarks.