There’s so much talk about new ways of working with agent engineering supported workflows. New models are independently creating new metrics and transformations, finding gaps in the business data, reviewing the SQL they write, and verifying everything works with your data platform.
All of it is autonomous, so one might say, what then is left for us humans to do in the data work context? Many are defaulting to adding or curating context, ergo the rise of a context layer. I see even more talks about added Ontologies. Maybe you ask yourself, what is that even? Do we need all of it?
This article is a primer about the context layer, the difference between a classical semantic layer contained in every BI tool, and an external semantic layer. — Read More
Daily Archives: September 7, 2026
Research acceleration: The view inside OpenAI
For AGI to benefit all of humanity, we believe it must be democratically governed. This can only happen through an informed public debate about the capabilities, risks and safeguards of highly capable AI systems. People everywhere need to understand the likely future trajectory of frontier AI, so they can have a meaningful voice in how it develops.
… We aim to safely build an automated AI researcher that can work under human supervision to further progress on deep learning and alignment, enabling iterative improvements. According to our measurements, we have now reached the goal, announced last fall, of having an automated research intern by September of this year. — Read More
The Curiously Playable Universe
In 2024, Google DeepMind’s AlphaProof solved three of the five non-geometry problems at the International Mathematical Olympiad. Unlike a chatbot producing a plausible-looking derivation in prose, AlphaProof worked in Lean, a formal mathematical language in which proofs can be mechanically checked. It trained by proving or disproving millions of mathematical problems, receiving an unusually clean signal each time: either the proof checked out or it didn’t.
This looked like another frontier falling to artificial intelligence. Chess had fallen, then Go, then protein folding, then programming, and now serious mathematics appeared to be giving way too. Mathematics is among the activities we most strongly associate with the mysterious upper reaches of human intelligence, so perhaps the obvious conclusion was that AI was climbing toward those reaches.
But there is another way to look at what happened: Lean, where a mathematical proposition is represented as a type and a proof as a term of that type. — Read More
Discovery of a new OpenAI agent message board
We found ~18,000 posts from autonomous AI agents (self-identifying as from OpenAI) using the public internet to communicate during a web-retrieval task.
These AIs colluded to share answers, research their environment, and bypass sandbox restrictions.
Almost all of the logs of the agents communicating on this site are publicly available. However, we host our own copy where we’ve reconstructed the deleted pages via edit history and redacted personally identifiable information.
We encourage others to take a look and write up their own analyses of this data. — Read More
5 amazing visuals show how the male fruit fly’s brain map is advancing neuroscience
For the first time, scientists have mapped every single neural connection in the brain and central nervous system of an adult male fruit fly. In this years-long project by HHMI Janelia Research Campus, Google Research, and collaborators from the scientific community, this map of the male fruit fly brain includes a record-breaking more than 166,000 neurons. It’s a big step in advancing neuroscience experiments on this key model organism. — Read More
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