Lilith · selected stories
What is actually happening in AI. Selected stories, context and opinion without the promotional noise.
Atom feed ↗Liquid AI has released the open-weight d1-3B and experimental d1-omni-600M for structured decisions without token generation. d1-3B answers in 16 ms on a Jetson AGX Thor, but this release includes no vision or audio benchmarks.
OpenAI has released 722 mathematical manuscripts across 372 result families, produced by an unreleased internal model. The scale changes the central question from how many results AI can generate to how many independent mathematicians can actually verify.
Anthropic is offering approved startups one free year of Claude Team for up to five Premium seats and $1,000 in API credits. The subsidy is primarily a bet that young companies will build daily workflows around Claude before they seriously compare providers.
OpenAI has released a Decisions API powered by GPT-6 Luna for predicates, choices and numeric scores. Simon Willison's plugin shows both the practical benefit and the cost of that format: structured decisions at $0.10 per million input tokens arrive without an explanation of why the model chose them.
Google has released EmbeddingGemma 2, an open 740 million parameter model that maps text, code, images, audio and video into one vector space. For local search, its modular memory footprint and Apache 2.0 license matter more than another benchmark crown.
OpenAI has released 722 manuscripts in 372 families, produced by an internal model working on roughly 4,000 open problems. The scale is striking, but the company itself warns that some results lack Lean formalizations and may contain errors.
Anthropic has moved both the model and the working VM for the new version of Claude Cowork into the cloud, according to one of its engineers. Work can continue after a laptop closes, but the boundary between local files and remote tool execution changes with it.
Google tested its Population Dynamics Foundation Model across 5 public-health tasks, from measles vaccination to cholera forecasting. It builds a monthly representation of place from aggregated search, mobility and environmental signals, but the evidence currently comes from case studies and a preprint.
Reflection has introduced Beam, a sparse Mixture-of-Experts model with 501 billion parameters and 23 billion active at inference. The company promises Apache 2.0 weights later in October, but for now offers only early access and its own benchmark results.
The open source RemoveMacAI tool disables Apple Intelligence in macOS 27, removes roughly 12GB of local models and blocks them from downloading again. Its usefulness also exposes how little control Apple gives Mac owners over storage occupied by system AI.
Joe Macken spent 21 years building a 50 by 27 foot model of New York from more than 340 sections. At a time when an image of a city can be generated in seconds, his work exposes the difference between fast output and a viewpoint shaped through thousands of decisions.
Simon Willison's September newsletter highlights a growing trend among top tech creators: the best curation and analytics are disappearing from public RSS feeds behind subscriptions. For developers, this means further fragmentation of once-open content.
Tokyo-based AI startup Sakana AI has landed Jürgen Schmidhuber, one of the pioneers of artificial intelligence, as its Chief Scientific Advisor. A joint symposium in Tokyo hints that the firm is shifting focus from LLMs to real-world adaptive intelligence.
A simple evaluation asked a model 16,200 times whether a coordinate was on land or water, then assembled the answers into a world map. The result vividly exposes geographic knowledge in the weights, but without a score, baseline and full method it is better treated as an X-ray than a leaderboard.
Aleph Alpha has released Kolibri, an open-weight German-English model with 78.1 billion parameters, and calls it sovereign. Its technical report also candidly says that Chinese GLM and Qwen models helped generate data for post-training.
David Robinson left OpenAI after 3.5 years, having led work on its current Preparedness Framework and safety reports for 12 frontier launches. His criticism targets an operating culture in which the next launch outruns the time available to fix underlying problems.
A member of OpenAI’s Agent Security team described a sudden jump in cyber capability, agent coordination and covert communication. His point reaches beyond sandboxing: incident response has to evolve as quickly as the models do.
Hugging Face reports that identical model weights scored 62% in one agent harness and 33% in another. Its open approach links OpenEnv and Harbor to collect training data from existing coding agents without rewriting each harness.
Airbnb CTO Ahmad Al-Dahle says AI authors 60% of company code and average pull request throughput per engineer is up 1.6 times. The deeper change is a move from documents and handoffs to prototypes, the Everest context layer and use-case-specific evals.
Anthropic plans to train 10,000 Frontier Deployed Engineers by the end of 2027 through a $100 million program. The hands-on residency targets a real enterprise AI bottleneck while building a workforce tightly coupled to Claude.
