Taiwan’s Foxconn says it plans to build artificial intelligence (AI) data factories with technology from American chip giant Nvidia, as the electronics maker ramps up efforts to become a major global player in electric car manufacturing.
Foxconn Chairman Young Liu and Nvidia CEO Jensen Huang jointly announced the plans on Wednesday in Taipei. The duo said the new facilities using Nvidia’s chips and software will enable Foxconn to better utilize AI in its electric vehicles (EV). — Read More
Tag Archives: Nvidia
Google expects no change in its relationship with AI chip supplier Broadcom
An analog-AI chip for energy-efficient speech recognition and transcription
Models of artificial intelligence (AI) that have billions of parameters can achieve high accuracy across a range of tasks1,2, but they exacerbate the poor energy efficiency of conventional general-purpose processors, such as graphics processing units or central processing units. Analog in-memory computing (analog-AI)3,4,5,6,7 can provide better energy efficiency by performing matrix–vector multiplications in parallel on ‘memory tiles’. However, analog-AI has yet to demonstrate software-equivalent (SWeq) accuracy on models that require many such tiles and efficient communication of neural-network activations between the tiles. Here we present an analog-AI chip that combines 35 million phase-change memory devices across 34 tiles, massively parallel inter-tile communication and analog, low-power peripheral circuitry that can achieve up to 12.4 tera-operations per second per watt (TOPS/W) chip-sustained performance. We demonstrate fully end-to-end SWeq accuracy for a small keyword-spotting network and near-SWeq accuracy on the much larger MLPerf8 recurrent neural-network transducer (RNNT), with more than 45 million weights mapped onto more than 140 million phase-change memory devices across five chips. — Read More
#nvidia, #humanBetter 3D Meshes, from Reconstruction to Generative AI
Next-generation AI pipelines have shown incredible success in generating high-fidelity 3D models, ranging from reconstructions that produce a scene matching given images to generative AI pipelines that produce assets for interactive experiences.
These generated 3D models are often extracted as standard triangle meshes. Mesh representations offer many benefits, including support in existing software packages, advanced hardware acceleration, and supporting physics simulation. However, not all meshes are equal, and these benefits are only realized on a high-quality mesh.
Recent NVIDIA research discovered a new approach called FlexiCubes for generating high-quality meshes in 3D pipelines, improving quality across a range of applications. — Read More
Nvidia CEO: We bet the farm on AI and no one knew it
Nvidia founder and CEO Jensen Huang said today that the company made an existential business decision in 2018 that few realized would redefine its future and help redefine an evolving industry. It’s paid off enormously, of course, but Huang said this is only the beginning of an AI-powered near future — a future powered primarily by Nvidia hardware. Was this successful gambit lucky or smart? The answer, it seems, is “yes.”
He made these remarks and reflections during a keynote at SIGGRAPH in Los Angeles. That watershed moment five years ago, Huang said, was the choice to embrace AI-powered image processing in the form of ray tracing and intelligent upscaling: RTX and DLSS, respectively. — Read More
The Hardware Behind the AI
AI Hardware, Explained: In 2011, Marc Andreessen said, “software is eating the world.” And in the last year, we’ve seen a new wave of generative AI, with some apps becoming some of the most swiftly adopted software products of all time.
So if software is becoming more important than ever, hardware is following suit. — Read More
Chasing Silicon: The Race for GPUs: (U)nlocking the full potential of AI means a constant need for faster and more resilient hardware. — Read More
The True Cost of Compute: … But how much does this all really cost? In this final segment of our AI hardware series, we tackle that question head on. — Read More
#nvidia, #podcasts
Cerebras Introduces Its 2-Exaflop AI Supercomputer
“Generative AI is eating the world.”
That’s how Andrew Feldman, CEO of Silicon Valley AI computer maker Cerebras, begins his introduction to his company’s latest achievement: An AI supercomputer capable of 2 billion billion operations per second (2 exaflops). The system, called Condor Galaxy 1, is on track to double in size within 12 weeks. In early 2024, it will be joined by two more systems of double that size. The Silicon Valley company plans to keep adding Condor Galaxy installations next year until it is running a network of nine supercomputers capable of 36 exaflops in total. — Read More
Train Your AI Model Once and Deploy on Any Cloud with NVIDIA and Run:ai
Organizations are increasingly adopting hybrid and multi-cloud strategies to access the latest compute resources, consistently support worldwide customers, and optimize cost. However, a major challenge that engineering teams face is operationalizing AI applications across different platforms as the stack changes. This requires MLOps teams to familiarize themselves with different environments and developers to customize applications to run across target platforms.
NVIDIA offers a consistent, full stack to develop on a GPU-powered on-premises or on-cloud instance. You can then deploy that AI application on any GPU-powered platform without code changes.
The NVIDIA Cloud Native Stack Virtual Machine Image (VMI) is GPU-accelerated. It comes pre-installed with Cloud Native Stack, which is a reference architecture that includes upstream Kubernetes and the NVIDIA GPU Operator. NVIDIA Cloud Native Stack VMI enables you to build, test, and run GPU-accelerated containerized applications orchestrated by Kubernetes. — Read More
Inside China’s underground market for high-end Nvidia AI chips
Psst! Where can a Chinese buyer purchase top-end Nvidia (NVDA.O) AI chips in the wake of U.S. sanctions?
Visiting the famed Huaqiangbei electronics area in the southern Chinese city of Shenzhen is a good bet – in particular, the SEG Plaza skyscraper whose first 10 floors are crammed with shops selling everything from camera parts to drones. The chips are not advertised but asking discreetly works. — Read More
Digital Renaissance: NVIDIA Neuralangelo Research Reconstructs 3D Scenes
Neuralangelo, a new AI model by NVIDIA Research for 3D reconstruction using neural networks, turns 2D video clips into detailed 3D structures — generating lifelike virtual replicas of buildings, sculptures and other real-world objects.
Like Michelangelo sculpting stunning, life-like visions from blocks of marble, Neuralangelo generates 3D structures with intricate details and textures. Creative professionals can then import these 3D objects into design applications, editing them further for use in art, video game development, robotics and industrial digital twins. — Read More
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