NVIDIA

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DeepSeekV4 1.6T Day 0 to Day 43 Performance Over Time - Huawei, GB300 NVL72, MI355X, B200

 🧠LLMs  Content type: News

Release TorchCodec 0.14: HDR Video Decoding for CPU & CUDA, and Fast Wav Decoder · meta-pytorch/torchcodec

 🎵Vibe Coding  Content type: Code
github.com··Hacker News

Expanding Private Cloud Compute - Apple Security Research

 ☁️Cloud Computing  Content type: Blog

Train Models Faster with JAX and MaxText Using NVFP4 on NVIDIA Blackwell

 🏠Local LLMs  Content type: News  Content type: Blog
developer.nvidia.com·

NVIDIA, KRAFTON, NC and Reigning ‘League of Legends’ Champions T1 Celebrate RTX Spark at Korea’s PC Bangs

 🧠Transformers  Content type: Blog
blogs.nvidia.com·

Apple rebuilt its on-device AI stack at WWDC 2026

 🛠️Developer Tools  Content type: Blog
ziraph.com··Hacker News

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

 💻Code Generation  Content type: Academic
arxiv.org··Hacker News

KaiFelixBennett/gemma4-turboquant-rdna4: Run Gemma-4-31B at full 256K context on a $1,400 AMD RDNA4 GPU (gfx1201): TurboQuant KV cache + HIP-graph-safe Flash-Attention for llama.cpp, fully measured on real hardware.

 🤗Open Source AI  Content type: Code
github.com··Hacker News

Microsoft continues its big Linux push at Build 2026

 ☁️Cloud Computing
zdnet.com··Hacker News

Why Compiler Engineers Rarely Use Strassen's Algorithm for Fast Matrix Multiplications

 🏗️Software Architecture  Content type: News  Content type: Blog

On-device AI is a margin decision

 🏠Local LLMs  Content type: Blog
ziraph.com··Hacker News

Fine-tune FLUX.2 [Klein] with a LoRA under 60 minutes

 🤗Open Source AI  Content type: Blog

Huawei-led team claims it post-trained DeepSeek's 1.6-trillion-parameter model — 1,000 Ascend 910C chips used in training

 🤗Open Source AI  Content type: News

NVIDIA and LG Group Build an AI Factory to Advance Physical AI, Mobility and AI Infrastructure

 🏗️Software Architecture  Content type: Blog

Ideogram-4-FP8 Brings High-Quality Text-to-Image Generation to More Hardware

 ✍️Prompt Engineering
hackernoon.com·

The Download: how the World Cup ball will fly and OpenAI’s “super app”

 💻Tech Industry  Content type: News

Apple Silicon's on-device AI bet hasn't moved – only the chip range that runs it

 💻Tech Industry

Unpacking AI: The Hardware Behind AI

 🕵️Agentic AI  Content type: News

Scarcity is driving AI innovation outside Silicon Valley

 📈AI Industry

bigattichouse/packed-twin-inference: PTI achieves ~2× throughput using a single quantized model (Q5_K_M or better) by running 4 generation streams in one batched decode call. The GPU loads model weights once per step and produces 4 predictions simultaneously. KV cache overhead is ~0.8 GiB total for all 4 streams. No draft model. No quality loss

 🏠Local LLMs  Content type: Code
github.com··r/LocalLLaMA

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