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Artificial Intelligence
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Google introduces Gemini Notebook
Google combines NotebookLM’s source-grounded research workflow with Gemini’s broader workspace tools.
Read the article at Google ↗LM Studio introduces Bionic
The desktop AI tool adds a coding workspace designed to run local models alongside a project’s files.
Read the article at LM Studio ↗Inside an AI-assisted code migration
Anthropic explains where agents helped with a large migration, where they failed, and which review practices kept the work on track.
Read the article at Claude ↗How OpenAI’s Sol learned better design judgment
Design Arena examines the training and evaluation work behind a coding model that can make more coherent interface decisions.
Read the article at Design Arena ↗Thinking Machines introduces Inkling
A new open-source library focuses on reinforcement-learning experiments that researchers can inspect and adapt.
Read the article at Thinking Machines ↗A primer on self-improving agents
This technical overview separates realistic feedback loops from the stronger claims often made about recursive improvement.
Read the article at TechTalks ↗Why AI implementation may be the next large market
Anthropic and Blackstone argue that adapting models to real organisations could matter more than another benchmark win.
Read the article at TechCrunch ↗The AI gold rush shifts to tokens and loops
A16z examines the business models forming around repeated model calls, agents, and the infrastructure that supports them.
Read the article at A16z ↗The real price of frontier models
A hands-on comparison shows how token prices, retries, latency, and tool calls change the cost of production AI work.
Read the article at PlayCode ↗Anthropic’s newest advertisement unsettles viewers
The campaign’s reaction is a useful case study in how quickly AI branding can cross from memorable into uncomfortable.
Read the article at TechCrunch ↗The most human technology ever made
A16z considers why conversational software feels unusually personal and what product teams should do with that responsibility.
Read the article at A16z ↗How MAPFRE modernised fraud detection with EMR Serverless
The case study connects Iceberg, Airflow, graph features, model scoring, and production claims workflows.
Read the article at AWS Architecture ↗