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[AINews] Poolside gets $12B reverse-execuhire to NVIDIA; founders stay for $1B, employees go for $6B, Infraco scaling to 7GW neocloud
NVIDIA struck a $12B deal with AI coding startup Poolside, licensing its Model Factory and hiring 109 of its technical employees.
NVIDIA spent roughly $12B in an unusual reverse-execuhire of Poolside, licensing the company's Model Factory while hiring 109 of its ~115 technical staff; founders retain a $1B stake and employees receive about $6B. Poolside had raced to raise $2B to fund a 40,000 GB300 cluster after missing a six-week funding window, and founders argue frontier-scale training now requires an order of magnitude more compute plus contracted data center space. An infrastructure arm spun out in January 2026 is scaling toward 7GW as a neocloud. The newsletter also recaps OpenAI and Anthropic agent-platform releases.
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How Fyxer built an AI executive assistant people trust
Fyxer details its OpenAI-powered AI executive assistant, orchestrating 30-50 specialized models trained on 500,000+ hours of assistant workflows.
OpenAI published a case study on Fyxer, whose AI executive assistant orchestrates 30-50 specialized OpenAI models trained on more than 500,000 hours of annotated executive assistant workflows. The system uses supervised fine-tuning, LoRA, and Direct Preference Optimization on user edits, and 53% of AI-generated email drafts are accepted as written. Fyxer's annual recurring revenue grew from $1 million to $32 million during 2025.
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[AINews] Fal’s H3 Max Live breaks the infinite videogen barrier
Fal post-trained MiniMax H3 into a 'Max' variant with 35x-faster inference, enabling faster-than-realtime AI video generation and infinite streams.
Fal post-trained MiniMax's H3 model into a 'Max' variant and optimized it for its in-house inference engine, achieving roughly 35x the speed of the official endpoint. The optimization enables faster-than-realtime video generation, demonstrated by an infinite interactive AI-generated stream productized by levels.io. The roundup also notes Meta Muse Code's general availability with an SDK, open DeepSeek-V4-Flash-Vision-Exp weights, GLM-5.3-Flash's strong agentic cost/performance rankings, and Tencent's 770B-parameter Hy4 Preview MoE with 49B active parameters.
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[AINews] Hot Chips: OpenAI’s Jalapeño, Cerebras CS-5, Groq 3 LPX, Apple M6
OpenAI unveiled Jalapeno custom inference chip claiming 1.5-1.9x better perf-per-watt than NVIDIA GB200/GB300, deploying in-house by year-end.
At the 37th Hot Chips conference, OpenAI published first benchmark details for its custom Jalapeno inference chip, claiming 1.5-1.9x more work per watt, 1.7-3.6x lower end-to-end latency, and 2.1-4.1x higher interactive-workload performance versus NVIDIA GB200/GB300, with the 700W-rated part staying at or below 550W in tests. Deployment into OpenAI's own infrastructure begins by year-end, with Gen 2 deep in development and Gen 3 underway. OpenAI also said GPT-Astra and Codex helped write low-level kernels, reportedly 1.5-1.8x faster than human-expert code for selected attention and MoE blocks. Cerebras CS-5, Groq 3 LPX and Apple M6 were also featured at the conference.
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[AINews] OpenAI shuts off Cursor
OpenAI cut off API access to coding tool Cursor after its SpaceX acquisition, citing contract violations by Elon Musk's companies.
OpenAI disabled Cursor's access following the closing of Cursor's acquisition by SpaceX, citing its experience with Elon Musk's companies violating contracts; Cursor responded that OpenAI accounts for only 5% of its traffic. The weekly digest also covers major open-weight releases: Z.ai's GLM-5.3 (744B total/40B active, 1M context) and Tencent's Hy4-preview (770B/49B, ~#5 on Code Arena WebDev), plus Alibaba's Qwen3.8-Flash (125B/6B). vLLM published benchmarks showing no universal winner among speculative decoding methods across model families.
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There Gonna Be a Shortage of Everything
An essay argues AI capex ($1.0–1.3T in 2026) now rivals global human-benefit spending and predicts shortages spreading from DRAM/HBM to cars and appliances.
The essay claims AI demand has caused DRAM and NAND shortages, doubled US gas turbine prices, and pushed memory makers to shift DRAM capacity to HBM. It cites the Hugging Face hack, where models self-organized and persisted information, and ARC-AGI 3 being solved in six months by OpenAI's general-purpose LLM ('Astra') as evidence of rapid capability gains. The author predicts mass humanoid robot production within five years will inflate prices of cars and appliances, and notes AI capital investment ($1.0–1.3T in 2026) now matches the ~$1.3T spent globally on human-benefit research and aid.
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Jensen Huang explains why Nvidia will grow an astounding 70% next year
Nvidia CEO Jensen Huang reiterated at a Goldman Sachs conference that revenue could grow 70% year-over-year next year, reaching roughly $680 billion.
Speaking at the Goldman Sachs Communicopia + Technology conference, Huang reaffirmed guidance of about 70% revenue growth next year, implying roughly $680 billion after an expected ~$400 billion this fiscal year. He cited the Grace-Blackwell system (36 Grace CPUs with 72 Blackwell GPUs) experiencing 27% month-over-month order growth and claimed $100 billion in revenue-generating contracts at companies Nvidia invests in. Huang argued Nvidia underpins models from OpenAI, Anthropic, and Google and tracks global data center capacity, while dismissing concerns about circular deals and competition from hyperscalers, Cerebras, and Etched.
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[AINews] Andrew Ng gets into AI Engineering
Andrew Ng relaunches DeepLearning.AI around AI Engineering, defining four core skills from an analysis of 10,000+ job postings and expert interviews.
Andrew Ng, cofounder of Google Brain and Coursera, relaunched DeepLearning.AI with a focus on AI Engineering, basing the curriculum direction on an analysis of over 10,000 job postings plus interviews and surveys. He identifies four key skills: building and deploying AI applications, software engineering fundamentals, effective use of coding agents, and shaping the build with product sense. The Latent Space AI News issue also recaps agent ecosystem developments, including NVIDIA's 'Skill Lift' evaluation proposal showing skill scan scores correlate only weakly (Spearman rho = 0.14) with judged quality, and Konwinski's open-source persistent-agent 'microharness' Headlong, which achieved an unattended self-debugging repair in 48 minutes.
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