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NVIDIA AI Just Released cuda-oxide: An Experimental Rust-to-CUDA Compiler Backend that Compiles SIMT GPU Kernels Directly to PTX

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NVIDIA AI researchers recently released cuda-oxide, an experimental compiler that allows developers to write CUDA SIMT (Single Instruction, Multiple Threads) GPU kernels in standard Rust code. The project compiles Rust directly to PTX (Parallel Thread Execution) — the assembly-like intermediate representation that CUDA uses to target NVIDIA GPUs — without requiring domain-specific languages, foreign function […]

NVIDIA AI Just Released cuda-oxide: An Experimental Rust-to-CUDA Compiler Backend that Compiles SIMT GPU Kernels Directly to PTX Read More »

NVIDIA AI Releases Star Elastic: One Checkpoint that Contains 30B, 23B, and 12B Reasoning Models with Zero-Shot Slicing

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Training a family of large language models (LLMs) has always come with a painful multiplier: every model variant in the family—whether 8B, 30B, or 70B—typically requires its own full training run, its own storage, and its own deployment stack. For a dev team running inference at scale, this means multiplying compute costs by the number

NVIDIA AI Releases Star Elastic: One Checkpoint that Contains 30B, 23B, and 12B Reasoning Models with Zero-Shot Slicing Read More »

OpenAI Adds Chrome Extension to Codex, Letting Its AI Agent Access LinkedIn, Salesforce, Gmail, and Internal Tools via Signed-In Sessions

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OpenAI has launched a Codex Chrome extension for Mac and PC to streamline browser-based workflows that were previously difficult to handle via APIs or plugins. This release follows a trend where most users preferred working in a browser after the launch of “Computer Use,” allowing Codex to operate more effectively across various web-based tasks. What

OpenAI Adds Chrome Extension to Codex, Letting Its AI Agent Access LinkedIn, Salesforce, Gmail, and Internal Tools via Signed-In Sessions Read More »

Anthropic Introduces Natural Language Autoencoders That Convert Claude’s Internal Activations Directly into Human-Readable Text Explanations

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When you type a message to Claude, something invisible happens in the middle. The words you send get converted into long lists of numbers called activations that the model uses to process context and generate a response. These activations are, in effect, where the model’s “thinking” lives. The problem is nobody can easily read them.

Anthropic Introduces Natural Language Autoencoders That Convert Claude’s Internal Activations Directly into Human-Readable Text Explanations Read More »

OpenAI Releases Three Realtime Audio Models: GPT-Realtime-2, GPT-Realtime-Translate, and GPT-Realtime-Whisper in the Realtime API

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OpenAI released three new audio models through its Realtime API, each targeting a distinct capability in live voice applications: GPT-Realtime-2 for voice agents with reasoning, GPT-Realtime-Translate for live speech translation, and GPT-Realtime-Whisper for streaming transcription. Alongside the model releases, the Realtime API officially exits beta and is now generally available — a meaningful signal for

OpenAI Releases Three Realtime Audio Models: GPT-Realtime-2, GPT-Realtime-Translate, and GPT-Realtime-Whisper in the Realtime API Read More »

Meta AI Releases NeuralBench: A Unified Open-Source Framework to Benchmark NeuroAI Models Across 36 EEG Tasks and 94 Datasets

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Evaluating AI models trained on brain signals has long been a messy, inconsistent topic. Different research groups use different preprocessing pipelines, train models on different datasets, and report results on a narrow set of tasks — making it nearly impossible to know which model actually works best, or for what. A new framework from Meta

Meta AI Releases NeuralBench: A Unified Open-Source Framework to Benchmark NeuroAI Models Across 36 EEG Tasks and 94 Datasets Read More »

OpenAI Introduces MRC (Multipath Reliable Connection): A New Open Networking Protocol for Large-Scale AI Supercomputer Training Clusters

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Training frontier AI models is not just a compute problem — it is increasingly a networking problem. And OpenAI just introduced its solution. OpenAI announced the release of MRC (Multipath Reliable Connection), a novel networking protocol developed over the past two years in partnership with AMD, Broadcom, Intel, Microsoft, and NVIDIA. The specification was published

OpenAI Introduces MRC (Multipath Reliable Connection): A New Open Networking Protocol for Large-Scale AI Supercomputer Training Clusters Read More »

Zyphra Releases ZAYA1-8B: A Reasoning MoE Trained on AMD Hardware That Punches Far Above Its Weight Class

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Zyphra AI has released ZAYA1-8B, a small Mixture of Experts (MoE) language model with 760 million active parameters and 8.4 billion total parameters. Trained end-to-end on AMD hardware, the model outperforms open-weight models many times its size on math and coding benchmarks, and is now available under an Apache 2.0 license on Hugging Face and

Zyphra Releases ZAYA1-8B: A Reasoning MoE Trained on AMD Hardware That Punches Far Above Its Weight Class Read More »

A Groq-Powered Agentic Research Assistant with LangGraph, Tool Calling, Sub-Agents, and Agentic Memory: Lets Built It

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In this tutorial, we build a Groq-powered agentic research workflow that runs directly using Groq’s free OpenAI-compatible inference endpoint. We configure LangChain’s ChatOpenAI interface to work with Groq by setting the Groq API key and base URL, allowing us to use fast hosted models such as llama-3.3-70b-versatile for tool-based reasoning. We then connect the model

A Groq-Powered Agentic Research Assistant with LangGraph, Tool Calling, Sub-Agents, and Agentic Memory: Lets Built It Read More »

Google AI Releases Multi-Token Prediction (MTP) Drafters for Gemma 4: Delivering Up to 3x Faster Inference Without Quality Loss

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Large language models are getting incredibly powerful, but let’s be honest—their inference speed is still a massive headache for anyone trying to use them in production. Google just launched Multi-Token Prediction (MTP) drafters for the Gemma 4 model family. This specialized speculative decoding architecture can actually triple (3x) your speed at inference time, all without

Google AI Releases Multi-Token Prediction (MTP) Drafters for Gemma 4: Delivering Up to 3x Faster Inference Without Quality Loss Read More »