Nvidia on Monday announced a new generation of artificial intelligence chips and software for running AI models.
Category: robotics/AI – Page 405
Google Research releases the Skin Condition Image Network (SCIN) dataset in collaboration with physicians at Stanford Med.
Designed to reflect the broad range of conditions searched for online, it’s freely available as a resource for researchers, educators, & devs → https://goo.gle/4amfMwW
#AI #medicine
Health datasets play a crucial role in research and medical education, but it can be challenging to create a dataset that represents the real world. For example, dermatology conditions are diverse in their appearance and severity and manifest differently across skin tones. Yet, existing dermatology image datasets often lack representation of everyday conditions (like rashes, allergies and infections) and skew towards lighter skin tones. Furthermore, race and ethnicity information is frequently missing, hindering our ability to assess disparities or create solutions.
NASA is developing autonomous space robots to build shelters, solar arrays, and more on the moon and Mars.
A new research paper has discovered the usefulness of DRAM cache for GPUs which can help enable higher performance at low power.
Researchers Propose The Use Of Dedicated DRAM Caches Onto Newly-Built SCMs For GPUs, Replacing Conventional HBM Configuration
The GPU industry, which involves consumer, workstation, and AI GPUs, is proceeding in a way that we are seeing advancements in memory capacities and bandwidth, but it isn’t sustainable, and ultimately, we could hit the limits if an innovative approach isn’t taken.
The advanced artificial intelligence model powering Copilot’s Pro tier wasn’t free to all until now.
A small research group from the University of Michigan has developed a three-legged skating/shuffling robot called SKOOTR that rolls as it walks, can move along in any direction and can even rise up to overcome obstacles.
The idea for the SKOOTR – or SKating, Omni-Oriented, Tripedal Robot – project came from assistant professor Talia Y. Moore at the University of Michigan’s Evolution and Motion of Biology and Robotics (EMBiR) Lab.
“I came up with this idea as I was rolling around on my office chair between groups of students,” said Moore. “I realized that the passively rolling office chair could easily spin in any direction, and I could use my legs to perform a variety of maneuvers while staying remarkably stable. I realized that this omnidirectional maneuverability is similar to how brittle stars change directions while swimming.”
MIT CSAIL researchers introduce FeatUp, a model-agnostic framework designed to significantly enhance the spatial resolution of deep learning features for improved performance in computer vision tasks such as semantic segmentation, depth prediction, and object detection.
According to Nvidia’s roadmap, it’ll unveil its next-gen Blackwell architecture soon. The company always launches a new architecture with data center products first and then reveals the cut-down GeForce versions many months later, so that’s what’s expected this time as well. On that note, the company’s semi-annual GTC technology conference starts in two weeks, so we expect a lot to be revealed at the show. As proof that Nvidia is close to pulling the wraps off its new data center GPUs, a Dell executive has already shared some juicy info about next-gen Nvidia hardware, saying in a recent earnings call the company has a 1,000W data center GPU in the pipeline.
The executive who has probably already received an angry call from Jensen is Jeff Clarke, a COO at Dell. On a Feb. 29 earnings call (PDF), the executive discussed Dell’s engineering superiority and how upcoming hardware from Nvidia will give the company a chance to show it off. “We’re excited about what happens at the B100 and the B200,” he said, which are the die names for Nvidia’s next-generation data center GPU and its apparent successor. For context, Nvidia currently has the H100 as its flagship data center GPU and is just now launching the second iteration with faster HBM3e memory, dubbed H200. We all know the B100 is the Blackwell successor to this chip, so it appears the B200 will be that GPU’s second iteration, though it does not currently appear on Nvidia’s roadmap (below).
He then left Google and started a new AI lab called Inflection AI, which he ran as CEO. He and Inflection’s chief scientist, Karén Simonyan, are now jumping ship to help lead Microsoft AI.
Suleyman will become both a Microsoft EVP and run the new Microsoft AI group as CEO. On why he was selected, Nadella said: “I’ve known Mustafa for several years and have greatly admired him as a founder of both DeepMind and Inflection, and as a visionary, product maker, and builder of pioneering teams that go after bold missions.”
Meanwhile, Suleyman noted in a LinkedIn post: “I’ll be leading all consumer AI products and research, including Copilot, Bing and Edge.” Several of his co-workers at Inflection have also decided to migrate to Microsoft, he wrote.
GTC— NVIDIA today announced Project GR00T, a general-purpose foundation model for humanoid robots, designed to further its work driving breakthroughs in robotics and embodied AI.
As part of the initiative, the company also unveiled a new computer, Jetson Thor, for humanoid robots based on the NVIDIA Thor system-on-a-chip (SoC), as well as significant upgrades to the NVIDIA Isaac™ robotics platform, including generative AI foundation models and tools for simulation and AI workflow infrastructure.
“Building foundation models for general humanoid robots is one of the most exciting problems to solve in AI today,” said Jensen Huang, founder and CEO of NVIDIA. “The enabling technologies are coming together for leading roboticists around the world to take giant leaps towards artificial general robotics.”