LLMs absolutely do not have access to the same tools unless they're explicitly given access to them. Running on a computer means nothing.
It sounds like you don't like LLMs! In that case, you may be more interested in our REST Api. All the same functions, but designed for edge computing, where dependency bloat is a real issue https://tinyfn.io/edge
They're building a moat with data. They're building their own datasets of trusted sources, using their own teams of physicians and researchers. They've got hundreds of thousands of physicians asking millions of questions everyday. None of the labs have this sort of data coming in or this sort of focus on such a valuable niche
saying they aren't pioneering is very different than saying they aren't a major player in the space. There're only like 5-7 players with a foundational model that they can serve at scale. xAI is one of them
This is an interesting read, and while I support being nice to every_thing_ in principle. Most of the research into this actually shows that being mean yeilds better results
This looks pretty cool. I keep seeing people (an am myself) using claude code for more an more _non-dev_ work. Managing different aspects of life, work, etc. Anthropic has built the best harness right now. Building out the UI makes sense to get genpop adoption
Standard benchmarks (like BEIR/MS MARCO) are great, but they are likely already in distribution for foundation models training sets, and crucially, they lack the complex, structured metadata needed to test real-world filtering scenarios (e.g., "Find docs from region X, between dates Y and Z, with tag A").
datasetFactory is an orchestrated LLM pipeline that turns a single natural language prompt into a (potentially) massive, structured evaluation dataset.