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NVIDIA hardware, software, and developer news.
On speakerphone at All-In, Huang told Trump “you’re right” — they won’t let an AI slowdown happen — as the president branded the scare a hoax.
Onstage at the All-In Summit, Jensen Huang put President Trump on speakerphone — and Trump called AI slowdown fears a “hoax” while promising robots won’t take over.
NVIDIA says Transformer Engine plus JAX lifted DeepSeek-V3 MoE training from 103 to 1,068 TFLOPS/GPU on GB200 — a 10.4× jump — while keeping dropless routing.
Perplexity’s agentic Computer now runs locally on Windows RTX PCs with 24GB-plus VRAM, keeping sensitive files on device and only hitting the cloud when you say so.
NVIDIA open-sources OSMO, a Kubernetes-native orchestrator that runs robot training, Isaac Sim, and Jetson hardware tests from one YAML across heterogeneous clusters.
A hands-on RAPIDS cuML tutorial shows how to accelerate scikit-learn-style workflows on GPU—benchmarks, UMAP/HDBSCAN, FIL inference, SHAP, and HPO—without abandoning familiar APIs.
At Goldman Sachs, Jensen Huang doubles down on 70% revenue growth next year—not from one chip story, but from sitting inside every lab, cloud, and gigawatt of the AI build-out.
NVIDIA’s NIM 2.0.12 stack more than doubles concurrent users on Nemotron 3 Ultra at a fixed interactivity target — and the win is packaging, not a single magic switch.
Skild’s S1 foundation model learns long-horizon robot tasks from one video demo — no weight update — and NVIDIA’s physical-AI stack is underneath the training loop.
NVIDIA’s three-computer robotaxi stack — train, simulate, drive — is becoming the shared backplane for almost every commercial-scale autonomous fleet program it names.
UMG is pairing its catalog with ElevenLabs so fans can remix licensed tracks — another rights-first bet after years of lawsuits against unlicensed AI music.
NVIDIA’s BioNeMo Inference Runtime is turning proteome-scale folding from a hero run into a throughput problem — with measured gains on Boltz-2 and a path into Ray-scaled GPU replicas.