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Computational papers ship code that readers must clone, install, configure and debug. That cost keeps useful methods locked inside PDFs. A Stanford team led by Jiacheng Miao and James Zou proposes a fix. Paper2Agent was published in Nature on 16 September 2026. It converts a paper and its codebase into a Model Context Protocol (MCP) […]
In this tutorial, we work through the cuDNN Frontend‘s graph API from below the framework: we describe a computation as a graph of operations, let cuDNN pick an engine to run it, and then take control of that choice ourselves. Every kernel we build here is expressed the same way: we declare tensors by their
Inside NVIDIA’s cuDNN Graph API: Fusion, Autotuning, and Plan Reuse with cuDNN Frontend Read More »
Google has introduced Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, its most advanced live dialogue models to date. Both are native speech to speech models built for real time voice agents. They extend the Gemini Audio family that Google expanded last month with Gemini 3.5 Transcribe. The release targets a specific gap: voice
Backpropagation is a global algorithm: a forward pass, then a backward pass, then a weight update, each locked behind the previous one. Brains have no known mechanism for that kind of network-wide phase locking, which is why local-learning alternatives such as predictive coding (PC) keep drawing research interest. Sakana AI researchers propose Augmented Lagrangian Predictive
In most decoder-only LLMs, nothing computed at the last layer of token t feeds the first layer of token t+1; positions communicate only through attention over cached keys and values. A Princeton researcher’s (Yifan Zhang) technical report, Recurrent Looped Transformer (RLT), proposes closing that loop. The decoder’s final hidden state and its layerwise sliding-window attention
An agent, in its simplest form, is an LLM calling tools in a loop. That loop works for short jobs. Give it a task that runs for an hour and 200 tool calls, and it breaks in 2 predictable ways. The AWS Samples design guide for autonomous cloud coding agents names them directly: shallow agents
Cognition, the company behind the Devin coding agent, has released SWE-2, its most capable coding model to date. SWE-2 is post-trained with reinforcement learning from Kimi K3, Moonshot AI’s 2.8T-parameter open model. Cognition reports a score of 50.0% on FrontierCode 1.1 Main, within 1 point of Fable 5.1 at 64% lower cost. It is also
The Fly Language Model (FLM) is a public chatbot that couples the complete retained MaleCNS v1.0 fruit fly connectome to a frozen LiquidAI LFM2.5-1.2B-Instruct backbone. The developer who created the FLM calls it the world’s first Fly Language Model, built on an architecture called GPF (Generative Pre-trained Fly). It does not use the GPF label,
Cohere has released North Small Translate, an open-weight machine translation model from Cohere and Cohere Labs. It is a sparse Mixture-of-Experts (MoE) model with 218B total and 25B active parameters. It covers 50 languages, from Albanian to Vietnamese. On Cohere’s WMT26 evaluation, it scores 83.6 averaged across all languages. Cohere says that beats DeepL and
Sakana AI has released Fugu Max and Fugu Ultra v2, 2 new models in its Sakana Fugu family. Fugu is not a single foundation model. It is a learned orchestrator that routes work across a pool of other models behind 1 API. The new release tunes that architecture for 2 missions. Fugu Max targets the
