AI
Artificial intelligence: LLMs, agents, diffusion, vision, NLP and the latest from top labs.
196 published articles
Acquisition
Mistral buys its way into physics, and a race against NVIDIA and Ansys
Mistral buys its way into physics simulation, acquiring emmi AI's neural surrogates for CFD and plasma turbulence. The deal puts Mistral in direct competition with NVIDIA and Ansys for the industrial engineering market.
2026-07-11
Open Source Infrastructure
Your AI search pipeline is broken. This open-source framework fixes the plumbing.
Teams building AI search infrastructure still spend too much time on plumbing. Search Toolkit unifies ingestion, retrieval, and evaluation into a single open-source framework, eliminating the weeks of integration work needed to stitch together separate tools. It's designed for enterprise use cases like RAG quality, domain-specific retrieval, and agentic search.
2026-07-11
AI Agents
OpenManus just killed the invite wall for AI agents. Here's how to run it in ten minutes.
OpenManus is an open-source AI agent framework anyone can install and run immediately: no invite code, no gimmicks, just a Python environment and an API key. Here is why you need it.
2026-07-11
Financial AI
The world's first AI-native credit card just rewired spending into compute
Moonshot AI issues an AI-native credit card with Agricultural Bank of China and American Express, linking membership tiers to card levels and offering token-based rewards. A look at how this embeds AI token economics into daily payments.
2026-07-11
AI Research
Why GPT-5.5 dominates a benchmark that tests how agents improve themselves
EvoPolicyGym isolates a critical but understudied capability: an agent's ability to refine an executable policy through repeated feedback-constrained edits. The benchmark reveals GPT-5.5 as the strongest performer across 16 environments, and provides trajectory-level diagnostics that expose how different agents allocate budget and convert feedback into tuned parameters.
2026-07-11
Internal research update
OpenAI's AGI roadmap leans hard on voice and vision. The safety part is harder.
OpenAI's updated research roadmap runs from GPT-5 through multimodal generation to alignment work. The ambitions are huge; the safety section still reads like an afterthought.
2026-07-11
AI Research
DiScoFormer found a way to kill the AI bottleneck that KDE and neural nets both missed
DiScoFormer estimates density and score in one forward pass, beating KDE by 37x in density error at 100 dimensions. The same transformer could serve diffusion models, Bayesian inference, and particle simulations without retraining.
2026-07-11
Multimodal AI
ViQ just gave multimodal AI the one thing it needed: discrete tokens that don't lose detail
ViQ tackles a core trade-off in multimodal AI: discrete visual representations either lose semantic meaning or sacrifice detail. Tencent-Hunyuan's two-stage approach delivers competitive performance with continuous encoders while slashing training time by up to 70 percent.
2026-07-11
Tooling
Your AI model is a commodity. The pipeline is where the real advantage lives.
A practical, step-by-step analysis of building an AI writing pipeline in 2025: model selection, prompt chaining, and quality control. No hype, just the technical architecture that matters.
2026-07-11
Artificial Intelligence
The missing 'ums' and 'uhs' that finally make AI speech sound human
MiniMax's Speech 2.8 brings native filler words, breathing, and hesitation to AI voice synthesis, solving the 'too perfect' problem that has long made synthetic speech feel robotic. The model also delivers 10-second voice cloning and cross-language accuracy improvements.
2026-07-11
AI Safety
The AI safety framework nobody asked for might be the one we need
A new AI safety framework targets high-stakes deployments, emphasizing continuous monitoring and adversarial testing. Whether developers adopt it before the next high-profile failure may determine its legacy.
2026-07-11
Neuroscience
The neuroscience AI that finally explains what brain parts actually do
Generative causal testing (GCT) distills LLM-based brain-prediction models into concise verbal explanations, then uses an LLM to write stories that causally test those claims in fMRI. In experiments, GCT confirmed known selectivity, teased apart neighboring place-processing regions, and discovered new prefrontal micro-regions tuned to concepts like dialogue and measurements.
2026-07-11