When Better Models Make Riskier Systems
Why stronger models can raise system level risk, explained through LLM agents in financial markets with an engineering lens.
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Stories of AI technology, research, products, and the people shaping them
Thoughtful coverage of technology and product design and validation, notable papers and AI trends, Patty’s new initiatives, and the culture behind the work.
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How AI can support newsrooms that refuse to close
OpenAI, AIRPPU and WAN-IFRA started an AI program for independent journalism in Ukraine. This piece explains what that direction means inside real newsrooms.
Reading research acceleration from inside OpenAI
Following Simon Willison's notes on OpenAI's internal research acceleration, a walk through the RSI wording, daily coding agent use, and the sharp bend in AI spend per researcher.
IFM Releases K2 Horizon, Six Apache 2.0 Models From 0.9B to 375B
IFM, the frontier lab launched by MBZUAI, released six models from 0.9B to 375B under Apache 2.0 with the pretraining corpus. Here is what the fleet structure means.
The uncomfortable diagnosis that DNS spreads scams
Following the measurement that more than 10 percent of new gTLDs look like scams, a walk through the abuse structure and what engineers should watch.
Working with an unfamiliar mind
As AI systems grow more capable, keeping them aligned with human intent gets harder. A walk through Jakub Pachocki's An Alien Mind and what it means for engineering.
HarnessDev: Can LLMs create and evolve their own agent harness?
Instead of hand built agent frameworks, a loop where a language model writes harness code and keeps the variants that perform. A close read of the idea, the mechanism, and the hard parts.
Reading Repo-To-Skill: what agents lack is not models but operational knowledge
Following the DisCo paper on distilling operational knowledge into skills, with a close look at the AREX-Skill library and what the matched-budget experiments actually show.