We’ve built an AI agent that acts as a secondary expert for a given domain, making deep specialist knowledge readily available and preserved for anyone in an organization to access, share, and build upon.
This is not a typical domain-specific agent. Its novelty comes from integrating two layers:
— A structured, auditable knowledge architecture separates what the agent knows from how it reasons.
— A self-improvement loop then compiles expert feedback into verified, regression-tested updates without model retraining.
Together, these two layers turn one-off expert corrections into permanent, compounding institutional memory, and the pattern is designed to generalize to other domains governed by retrievable text rather than model weights. — Read More
Daily Archives: September 3, 2026
LLMs: Intelligence vs. cost
ArtificialAnalysis is a website that benchmarks the intelligence of various LLM models. They publish a headline Intelligence Index, which is calculated as the mean output of the curated selection of benchmarks they run on each model. It’s a decent finger-in-the-air measure of how smart a model is overall.
AA also records useful information — namely, how much it cost them to run the benchmarks. Since the benchmarks are the same across all models, this offers a good indicator of how much it will cost a user to run each model, in relative terms.
One of their main plots is the Intelligence vs. cost plot, which shows the Pareto frontier, i.e. the cheapest model that can achieve each intelligence score. This frontier is important, because using a super-intelligent and super-expensive model to accomplish menial tasks that could be done by a much dumber and cheaper one is just a waste of money.
Over time, I’ve become progressively more irritated by this plot, for a few reasons. — Read More
The race to engineer new knobs for the human brain
I almost dropped my phone when I saw the news that chemogenetics was in human clinical trials. Chemogenetics is a powerful technique that modifies specific neurons so they can be controlled remotely by normally inert drugs. Bryan Roth, one of the technique’s inventors, told the BRAIN Initiative conference audience on August 13th1 that he had found seven ongoing clinical trials of chemogenetics in China. The disclosure set off a flurry of coverage in the trade media: We’re translating our sci-fi basic neuroscience tools to humans! We’re engineering new knobs for biology! We might have new ways of treating epilepsy, Parkinson’s disease, and pain! — Read More
How we make AI coding more cost efficient without sacrificing task quality
Output quality is important when working with AI coding agents, but true efficiency comes from getting work done quickly, efficiently, and with the right context.
That’s why token count of individual interactions alone isn’t a meaningful measure of efficiency. The goal shouldn’t be to use fewer tokens, but to tap into the right amount of context to move a task forward. — Read More
Atlas: A World Model for Spatial Intelligence
World models generate, reconstruct, and simulate any possible world. They understand how worlds appear, behave, and evolve so that we can render imagined worlds for creative users, simulate the real world in high fidelity, and help robots plan actions. At World Labs, we build these general purpose world models in pursuit of spatial intelligence.
Today we are introducing Atlas, our next-generation world model. Atlas is an omni model that we pretrained from scratch to natively operate on text, images, video, and 3D. It is a multimodal autoregressive diffusion transformer: all inputs are combined into a shared spatial context. Atlas uses that context to generate what comes next, staying consistent in 3D with everything it has seen and imagining what lies beyond it. — Read More
Rick's Cafe AI 