TLDR AI 2025-09-09
OpenAI discusses leaving SF π, Databricks hits $100B π°, Veo 3 upgrades π₯
Redis' fall releases for AI are here (Sponsor)
Our latest releases for Redis for AI are full of core enhancements, new integrations, and dev tools to help you build fast, reliable apps at scaleβespecially AI ones. Here's
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- Redis LangCache for fully managed semantic caching (Public preview)
- Hybrid search enhancements
- Vector compression
- Vertical scaling (GA)
- New agent framework integrations
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Deep Dives & Analysis
Cognition: The Devin is in the Details (22 minute read)
Shawn Wang, founder of Smol AI, is joining Cognition, the makers of the Devin AI software engineer. The vast majority of Wang's equity/investor capital at Smol AI will be rolling over their investment to Cognition as part of the deal. Wang will continue to work on AI Engineer and Latent Space independently of Cognition. This post explains in detail Wang's reasons for betting on Cognition.
RL-as-a-Service will outcompete AGI companies (and that's good) (6 minute read)
RLaaS (Reinforcement Learning-as-a-Service) has proven performance, lower costs, is more excludable, and is safer. AI companies pivoting away from pursuing AGI towards RLaaS is good news because it promises a switch to a safer mode of AI development. While RLaaS is not without risks, the transition to an RLaaS model would reduce AI risk. The concatenation of specialized models may create or assist general intelligences.
Why do we take LLMs seriously as a potential source of biorisk? (10 minute read)
Anthropic details why it implemented ASL-3 safety protections against biological weapons development, noting Claude now exceeds expert performance on virology evaluations, and controlled trials showed significant uplift with Opus 4 for acquiring bioweapons compared to using just the open internet. It's obviously a low-probability risk, but the impact is so high β just one infraction could mean thousands of deaths β that it still requires serious evaluation and restriction.
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Engineering & Research
Deploy GenAI and Agents Smarter (Sponsor)
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I made AI coding agents more efficient (16 minute read)
AI coding agents are great, but they're too wasteful, they don't hold the context of the database, they only have a surface-level understanding, and they're too susceptible to context rot. These problems could be solved if agents had a semantic understanding of all functions and context about how functions are connected to other parts of code. This article looks at practical ways to make coding agents more efficient.
Meta's Set Block Decoding (19 minute read)
Set Block Decoding enables parallel sampling of multiple future tokens by combining next-token and masked token prediction. This reduces decoding passes up to 5x without sacrificing accuracy.
Don't Build an RL Environment Startup (7 minute read)
Reinforcement Learning environments are sandboxes for AI models to learn from. They keep track of an internal state, prompt AIs to take actions to complete a task, and assign scores based on the outcome. More and more startups are offering increasingly challenging environments under the assumption that machine learning is solved and the only remaining work is to provide models with simulations to learn from. Frontier AI labs pay a lot of money for these environments, but the supply side is set to become increasingly crowded - it likely won't be a long-lived business.
Judge skewers $1.5B Anthropic settlement with authors in pirated books case over AI training (3 minute read)
A federal judge expressed serious concerns about Anthropic's proposed settlement over the use of 500,000 pirated books to train an internal version of Claude. He questioned how the settlement money would be distributed: βI have an uneasy feeling about hangers on with all this money on the table.β
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