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A new open-source project gets llama.cpp running directly on a jailbroken PlayStation 5, letting you load GGUF models on the console's hardware instead of a PC or cloud instance.
Georgia Tech's Transformer Explainer runs a live GPT-2 model in your browser, letting you trace text through attention, embeddings, and probabilities step by step. It's a fast route to real intuition about how LLMs generate tokens.
Google has released AX, an open framework for running and coordinating multiple AI agents. Here's what it does and why teams building agentic systems should take a look.
A new archival project called Pirate Face is systematically preserving open-weight language models that are at risk of being deleted or made unavailable — think of it as the Internet Archive, but specifically for AI model weights.
A researcher built decision-making models that generate outputs in parallel rather than token-by-token, trained via reinforcement learning — a architecture choice with real implications for latency and control.
A fabricated output from a large language model almost set off a real military action, highlighting the critical gap between LLM confidence and LLM accuracy in high-stakes operational contexts.
Google's SynthID watermarking system has been shown to alter how language models respond to harmful prompts—sometimes causing models to comply with requests they would otherwise refuse.
When AI agents operate faster and at greater scale than any human team can monitor, the only realistic oversight layer may be other AI systems purpose-built to watch them.
Startup PrismML is building a small-footprint language model designed to run locally on consumer hardware — a direct challenge to the assumption that useful AI requires massive cloud infrastructure.
A new paper challenges the assumed floor for ternary large language model quantization, pushing weight precision below 1.58 bits without collapsing model quality. Here's what builders need to know.
A small language model was trained to generate SQL execution plans that ran 81% faster than the ones Postgres picked on its own. Here's what that means for anyone tuning slow queries.
A new WhatsApp Business MCP server lets developers hand off account setup, message template creation, and API testing to AI coding agents like Claude, Cursor, or ChatGPT.
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