Section
Research
Papers, techniques and results from labs and universities, translated into what they mean in practice.
12 stories
Analysis
What changes when an AI agent gets laboratory feedback
A robot's successful movement, a promising computational score and a measured binder answer different questions. New Google research shows why the feedback loop needs all three.
Explainer
Can an AI response prove which model produced it?
FlashProve makes model identity a checkable computation. A request-by-request guide to what the proof establishes, what it costs and where trust remains.
Analysis
Can one small model inherit several specialists' skills?
A new distillation study combines teacher feedback with parameter priors. The result sharpens the question of how to consolidate expertise without losing weaker domains.
Explainer
Why Google wants language models to sleep between tasks
Periodic consolidation offers a different answer to stale knowledge. The important questions are what persists, what changes and whether older capabilities survive.
Analysis
Developer tools drew half of all stated AI deal money from 9% of deals
We analysed 189 AI deals since January 2025. Developer tools took $76.3B of the $153.6B in stated prices, one deal is 39% of it, and only 16 prices came from the companies.
Analysis
AI-native companies post 24% more for AI engineers, and two labs carry most of it
We analysed 832 US AI job postings with published pay ranges. AI-native firms post a $295.5K median midpoint against $238K elsewhere; without Anthropic and OpenAI the gap is 9%.
Analysis
Tracked AI lawsuits tripled since 2023, and 58 of 66 are still unresolved
We analysed 66 AI lawsuits: filings rose from 8 in 2023 to 24 in 2026 so far, 88% are unresolved, and copyright's share of new suits fell from 73% to 46%.
Analysis
Salesforce, Meta and Microsoft cut 16,800 jobs and kept buying AI companies
We cross-referenced 65 AI-linked layoffs with 190 AI acquisitions and 832 AI job postings. Three companies cut and bought; five cut and are still hiring for AI roles.
Explainer
What is an agent harness? The loop, tools and context around the model
An agent harness is everything around the model: the loop, tools, context, memory, permissions and sandbox. Why it moves benchmark scores as much as the model.
Explainer
What reasoning models actually do: a training recipe and a token budget
Reasoning models are ordinary LLMs post-trained with RL on checkable problems, then given a thinking budget at inference. The lineage, the training loop, the costs, and where the gains actually land.
Analysis
Test-time compute changed the scaling roadmap. Here is what it costs, and who pays
Labs can now buy accuracy per query instead of per training run. The evidence from Snell, Brown, o3, DeepSeek-R1 and the 2026 effort dials, and what the second axis does to your bill.
Explainer
Prompt injection attacks: real examples, why they work and the defences that hold
Prompt injection examples from documented incidents, why no model has solved it, and the layered defences that cap the damage when an AI agent is fooled.
