Tesla just switched on a massive supercomputer packed with 10,000 Nvidia H100 GPUs to accelerate its full self-driving development. The cluster delivers 340 FP64 PFLOPS of compute, beating Leonardo, the world's fourth most powerful supercomputer. Alongside its custom Dojo hardware, Tesla is building an unprecedented computing moat in the auto industry.
SemiAnalysis just dropped a deep dive revealing Google is accelerating Gemini training to beat GPT-4's pre-training compute by 5x by year-end, and up to 20x next year. The report divides the AI field into GPU-rich giants and struggling GPU-poor startups, noting Google's TPUv5 buildout may be the only force capable of breaking Nvidia's market dominance.
Nvidia just reported a massive $6.188B in quarterly net profit, up 843% year over year on $13.5B in revenue. The surge was driven by its data center business, which reached a record $10.32B as demand for generative AI chips exploded. Basically, Nvidia is dominating the hardware race while projecting an even bigger $16B next quarter.
Stability AI just partnered with NVIDIA to optimize SDXL using TensorRT, releasing open ONNX weights globally. The integration doubles performance on NVIDIA H100 GPUs, spitting out HD images in 1.47 seconds with a 41% latency drop and 70% throughput jump. Why it matters: high-end open-source image generation just got significantly faster and cheaper to scale.
NVIDIA just introduced DLSS 3.5 at Gamescom, featuring a new technology called Ray Reconstruction. Instead of relying on hand-tuned denoisers, it uses an AI network trained on an NVIDIA supercomputer with 5x more data than DLSS 3 to enhance reflections and global illumination across all RTX GPUs. The upgrade will debut this fall in titles like Cyberpunk 2077: Phantom Liberty.
NVIDIA just introduced FlexiCubes, a new approach designed to extract high-quality 3D meshes in generative AI and reconstruction pipelines. Acting as a drop-in replacement for traditional marching cubes, it introduces flexible parameters during optimization to capture finer details and produce meshes ready for physics simulations out of the box.
Shutterstock is tapping NVIDIA Picasso to let creators generate and light 3D scene backgrounds using text or image prompts. The models, trained on fully licensed data, spit out 8K 360-degree environment maps on demand. Why it matters: It offloads the tedious chore of background mapping and scene lighting, letting 3D artists focus their energy on core hero assets.
NVIDIA just unveiled AI Workbench, a unified developer toolkit that lets teams test and customize pretrained generative AI models locally on RTX PCs and workstations before scaling to the cloud. Alongside the tool, NVIDIA introduced AI Enterprise 4.0 with integrated NeMo support to bridge the gap between desktop experimentation and production-grade deployments.
NVIDIA just launched a suite of cloud APIs and developer services for OpenUSD, aiming to make building 3D virtual worlds as universal as the 2D web. The release includes ChatUSD, an LLM copilot that generates USD Python scripts, and DeepSearch for natural language asset hunting. Jensen Huang is placing a massive bet that OpenUSD will anchor the next generation of industrial digital twins.
NVIDIA just partnered with Hugging Face to bring its DGX Cloud supercomputing straight into the world's largest open-source AI community. Developers will soon get one-click access to clusters running eight H100 or A100 GPUs per node through a new Training Cluster as a Service. The integration aims to remove enterprise compute bottlenecks and launches in the coming months.
Microsoft just launched its Azure ND H100 v5 virtual machines, packing eight NVIDIA H100 GPUs and Quantum-2 InfiniBand networking for massive AI workloads. The cloud giant also expanded Azure OpenAI Service to five new regions, broadening access to models like GPT-4 as enterprise adoption surges. Why it matters: Microsoft is rapidly scaling up hardware muscle to meet insatiable cloud AI demand.
A Cointelegraph analysis warns that the generative AI hype is showing classic bubble symptoms after raising over $25B in the first half of 2023. Startups are burning funding just to stockpile scarce Nvidia GPUs rather than building product moats. With ChatGPT traffic slipping and API wrappers laying off staff, the market may face a reality check.
NVIDIA CEO Jensen Huang is returning to SIGGRAPH to deliver a live keynote on Aug. 8. He will showcase NVIDIA's latest generative AI breakthroughs and dive into OpenUSD developments following a new alliance with Apple, Pixar, and others. Watch out for what comes next in 3D graphics and visual computing.
Nvidia researchers just unveiled Perfusion, a lightweight personalization method for text-to-image models that takes up only 100KB. Developed with Tel-Aviv University, it trains in four minutes and uses "Key-Locking" to keep an object's visual identity while avoiding overfitting. Why it matters: It delivers results comparable to multi-gigabyte models like DreamBooth while taking up virtually no disk space.
Intel CEO Pat Gelsinger just told investors the company plans to build AI into every platform and product it makes. The rollout begins later this year with Meteor Lake, its first consumer chip sporting an onboard neural processor. Why it matters: As Nvidia dominates the AI cloud, Intel is betting that latency, bandwidth, and cost limits will force AI inferencing straight onto client devices and the edge.
Inflection AI just raised a staggering $1.3 billion in a new funding round led by Microsoft, Bill Gates, and Nvidia, pushing its valuation to $4 billion. The startup is partnering with CoreWeave and Nvidia to build an unprecedented 22,000 H100 GPU cluster to train models for its personal assistant, Pi.
Nvidia just swept all eight tests in the latest MLPerf training benchmarks, setting records across the board with its H100 GPUs. In one standout test, a cluster of 3,584 H100s run by CoreWeave completed a massive GPT-3 workload in under 11 minutes. Why it matters: The near-linear scaling proves Nvidia’s full-stack hardware and networking dominance remains virtually untouchable for training frontier AI.
Insilico Medicine just advanced an idiopathic pulmonary fibrosis drug candidate discovered using generative AI into Phase 2 clinical trials. Powered by its Pharma.AI platform and NVIDIA GPUs, the company reached Phase 1 in two and a half years at one-tenth the cost and one-third the time of traditional methods. Why it matters: It is real-world clinical proof that generative AI can design novel small molecules from scratch for human trials.
NVIDIA CEO Jensen Huang told Cannes Lions attendees that generative AI will augment, not replace, human creativity across text, 3D, and video. Through a partnership with ad giant WPP, NVIDIA is building an AI content engine to produce personalized marketing assets at scale. Why it matters: The $700B digital ad market is moving from retrieving a few static ads to generating billions of tailored variations on the fly.
AMD just laid out its next-gen data center roadmap at its premiere event, officially making AI its top strategic priority. The spotlight was firmly on the multi-die Instinct MI300 accelerators, designed directly to challenge Nvidia's dominant Hopper architecture.
