Y KobayashiNVIDIA、AIスーパーコンピューター9台にGrace Hopperプラットフォームの採用が進んでいることを発表
NVIDIAと言えば昔はゲーミングGPU、今はAI向けGPUでその名を轟かせているが、GPUのみならず、CPUとGPUを組み合わせた高性能コンピューティング（HPC）向けのスーパーコンチップも製造している。この、NVIDIAの72コアのGraceプロセッサとH100 GPUで構成されるGrace […]
Teslaの新スーパーコンピューター「Cortex」が初披露、10万個のH100 GPUを搭載予定
Teslaの新たなAIスーパーコンピューター「Cortex」が、CEOのElon Musk氏によって公開された。テキサス州オースティンにあるTesla本社の南側に建設中のこの巨大な施設は、自動運転技術の開発とロボットタクシーの実現に向けた重要な役割を果たすと期待されている。しかし、その完成と本格稼働にはまだ時間がかかりそうだ。 Cortexの全貌と今後期待されるその能力 Tesla […]https://xenospectrum.com/cortex-teslas-new-supercomputer-debuts-for-the-first-time/
ALEXBSRThe introduction of the Vera Rubin platform shifts the calculus for AI infrastructure planning. As the industry moves toward HBM4, understanding hardware refresh cycles becomes a core component of fleet optimization.
While H100 and Blackwell GPUs remain key workhorses, secondary-market demand for current-gen accelerators has reached a unique inflection point. This analysis explores the technical and financial variables influencing hardware transitions as the industry prepares for the Rubin wave.
#NVIDIA #TechStrategy #DataCenter #GPU #GraphicsCard #GPULiquidation #H100 #H200
BuySellRam.comThe introduction of the Vera Rubin platform shifts the calculus for AI infrastructure planning. While H100 and Blackwell GPUs remain key workhorses, secondary-market demand for current-gen accelerators has reached a unique inflection point. This analysis explores the technical and financial variables influencing hardware transitions as the industry prepares for the Rubin wave.
#NVIDIA #TechStrategy #DataCenter #GPU #GraphicsCard #GPULiquidation #H100 #H200 #technology
WhisprNews🚀 #H100 va a por todas: busca comprar dos firmas de tesorería para superar los 3.500 $BTC en Europa. La carrera por acumular #Bitcoin en los balances corporativos no se detiene. ¿Estamos ante el nuevo estándar de reserva de valor?
sayzard0xSero (@0xSero)
Lambda의 5,000달러 컴퓨트 크레딧, Nvidia의 H100 8장 클라우드 제공, TNG Technology의 B200 2주 사용 제공 등으로 72시간 만에 10만 달러 이상 가치의 자원을 확보했다고 언급한다. AI 개발자를 위한 대규모 컴퓨트 지원 사례로, 최신 GPU 자원 확보가 큰 가치가 있음을 보여준다.
0xSero (@0xSero) on X
In 72 hours I got over 100k of value 1. Lambda gave me 5000$ credits in compute 2. Nvidia offered me 8x H100s on the cloud (20$/h) idk for how long but assuming 2 weeks that'd be 5000$~ 3. TNG technology offered me 2 weeks of B200s which is something like 12000$ in compute
TechLİfeSnowflake's Arctic Long Sequence Training: How to Train LLMs on 15 Million Tokens Without Selling a Kidney
#ALST #Snowflake #LongContextTraining #DeepSpeed #HuggingFace #SequenceParallelism #LLMTraining #H100 #Llama8B #Qwen3 #GPUMemoryOptimization
Snowflake's Arctic Long Sequence Training: How to Train LLMs on 15 Million Tokens Without Selling a Kidney
Snowflake AI Research just open-sourced Arctic Long Sequence Training (ALST), a framework that pushes LLM training from a measly 32K tokens to over 15 million — a 469x improvement — using standard Hugging Face models and H100 GPUs. Here's what it means for you.
Andrej Karpathy (@karpathy)
nanochat이 단일 8x H100 노드에서 GPT-2 역량 모델을 약 2시간 만에 학습시켰다고 발표했습니다(한 달 전 약 3시간에서 단축). fp8 지원과 여러 튜닝, 그리고 데이터셋을 FineWeb-edu에서 변경한 것이 주요 개선 포인트로, 실시간 인터랙티브 학습에 한층 근접했다는 기술적 진전입니다.
Andrej Karpathy (@karpathy) on X
nanochat now trains GPT-2 capability model in just 2 hours on a single 8XH100 node (down from ~3 hours 1 month ago). Getting a lot closer to ~interactive! A bunch of tuning and features (fp8) went in but the biggest difference was a switch of the dataset from FineWeb-edu to
Mark Gadala-Maria (@markgadala)
신규 비디오 생성 모델 'HELIOS' 공개: 14B 규모의 autoregressive diffusion 모델로, 단일 텍스트 프롬프트로 최대 60초의 일관된 비디오를 생성한다고 발표됨. 성능은 NVIDIA H100 한 장에서 초당 19.5프레임으로 실시간급 처리에 가까워 같은 규모 모델로는 최초 사례로 보임.
Mark Gadala-Maria (@markgadala) on X
🚨 BREAKING: NEW VIDEO MODEL "HELIOS" GENERATES 1 FULL MINUTE OF VIDEO FROM A SINGLE PROMPT >MODEL: 14B autoregressive diffusion model — first of its size to hit real-time >OUTPUT: Up to 60 seconds of coherent video from a single text prompt >SPEED: 19.5 FPS on one NVIDIA H100
BuySellRam.comAs the AI arms race accelerates, the 18-month hardware refresh cycle has transformed GPUs from simple components into high-value infrastructure assets. This article explores why selling hundreds of units—like NVIDIA’s H100 or A100—requires a shift from "peer-to-peer" thinking to "Enterprise ITAD" strategy.
#DataCenter #ITAD #GPU #EnterpriseTech #NVIDIA #TechStrategy #BuySellRam #CircularEconomy #AI #H100 #Blackwell #GPU #TechNews #EnterpriseAI #AssetRecovery
