
Or… what if we gave you $100 in Codex credits if you tell us what you love about GPT-5.6 Sol or why you switched? Tweet it, claim your gift, enjoy more usage. First 10k get the free tokens! switch-to-codex.openai.chatgpt.site
He Qu
35 posts

@chen_rena20812
Engineer @ Oracle I sell the red pills 💊 in AI 💻 x Bio 🧬 https://t.co/g2ZUDfa3kz

Or… what if we gave you $100 in Codex credits if you tell us what you love about GPT-5.6 Sol or why you switched? Tweet it, claim your gift, enjoy more usage. First 10k get the free tokens! switch-to-codex.openai.chatgpt.site

Goldman Sachs: LLM primer A week or so ago there was a lot of questions about the model layer economics when LLMs are without a doubt viewed more and more as a commodity+ reaching a level where being on the frontier of intelligence is no longer the swaying factor. Economics 101, in a market with many substitutes like restaurants, price undercutting becomes a crucial factor and just like EV's is where China wins. Now these talks have been pushed to the background as the Lag 7 has revived on the back of Zucks considerations of an AI cloud business+producing an AI chip (positive read through to SUMCO/ I sold to early 😞). Back to the initial topic, Goldman provides a few insights into the landscape: → China's top coding models (GLM5.2, Qwen3.7 Max) sit at ~$1 per 1M blended tokens while US SOTA runs $4-8 for the same rung of output → And they are selling it below cost. GS pegs the value for money agentic model at a -30% EBIT margin today and the coding model at -39%, cash rich balance sheets eating the loss until it flips to +14% and +22% by 2030 on their numbers → The reason they can serve that cheap is architecture, sub-8% of params activated per token across the board, DeepSeek V4 Pro firing 49B of 1.6T and GLM5.2 40B of 744B, fewer FLOPs and a structural floor under the price → The adoption already shows up on OpenRouter where China models are 5-16% of spend by task but 85% of agent tokens and 89% of code tokens, winning wherever duration and volume make cost per task the number that matters → And the blended token price rolled over with it, SDLLMTK peaked around 2.07 in early June and sits at 1.67 now This seems somewhat similar to the EV playbook to me, we the consumers should win/benefit from a price war but the return to equity shareholders is more ify.

We're extending Claude Fable 5 access on all paid plans, as well as keeping Claude Code’s weekly rate limits 50% higher, through July 19.


I’m incredibly excited to share this: MiniMax has just closed a new $2B funding round. 🚀 At the same time, our CEO, IO, shared three long-term commitments with the team: • No salary until we achieve AGI. • Over the next four years, he will dedicate shares equivalent to 4% of the company’s total equity from his personal holdings to reward employees who are building MiniMax for the long term. • Another 1% will be committed to supporting the open-source community. The funding is exciting. But what excites me even more is what it represents: a long-term commitment to AGI, to our people, and to the open-source ecosystem. We’re living through one of the most exciting moments in the history of AI, and we’re just getting started. If you’re passionate about frontier AI, open source, and building the future, we’d love to build with you. Intelligence with Everyone. 🚀




Today, we're excited to share that Biomni is published in @ScienceMagazine. Biomedical research is still fragmented, manual, and difficult to scale. In this work, we introduce Biomni - the first general-purpose biomedical AI agent with an integrated biology environment that can reason, plan, and execute end-to-end scientific workflows. We show that, with the right environment and harness, AI can automate large-scale omics analyses, orchestrate laboratory robotics, optimize molecular properties, and even train new AI models for biology. We also introduce a reinforcement learning recipe for continually improving biomedical AI agents, enabling open-source models to achieve frontier-level performance. It's surreal to look back. We started the Biomni project in early 2024, when agentic AI was still nascent. It is exciting to see tens of thousands of biologists collaborating with agents every day to accelerate science. Try Biomni: biomni.phylo.bio Read more: science.org/doi/10.1126/sc… This work is not possible without this truly inter-disciplinary team: @serena2z @hcwww_ @YuanhaoQ Minta Lu, Ryan Li, @yusufroohani Lin Qiu @shiyi_c98 Gavin Junze Di @rickwierenga @kavi_deniz Sherry @TianweiShe Shruti Jennefer Xin Zhou @MWheelerMD Jon Bernstein @MengdiWang10 @PengHeAtlas @zhou_jingtian @SnyderShot @lecong Aviv Regev @jure @StanfordAILab @genentech @phylo_bio @arcinstitute @UW @berkeley_ai @RetroBio_ @tamarindbio @Princeton @UCSF

someone explain this to me


Less preaching, more practice. This Thursday three founders show what their in-production agents can do. An overnight software factory, graph memory, a whole company in one terminal. Live Q&A after every demo.