Google is reportedly designing its own Arm-based system-on-chips for Chromebook laptops and tablets to be launched in 2023.
The internet search giant appears to be following the same path as Apple by developing its own line of processors for client devices, according to Nikkei Asia. Read More
Tag Archives: Nvidia
Nvidia’s new voice A.I. sounds just like a real person
The “uncanny valley” is often used to describe artificial intelligence (A.I.) mimicking human behavior. But Nvidia’s new voice A.I. is much more realistic than anything we’ve ever heard before. Using a combination of A.I. and a human reference recording, the fake voice sounds almost identical to a real one. Read More
The world’s largest chip is creating AI networks larger than the human brain
Cerebras Systems, maker of the world’s largest chip, has lifted the lid on new architecture capable of supporting AI models that outscale the human brain.
The current largest AI models (such as Switch Transformer from Google) are built on circa 1 trillion parameters, which Cerebras suggests can be compared loosely to synapses in the brain, of which there are 100 trillion.
By harnessing a combination of technologies (and with the assistance of Wafer-Scale Engine 2 (WSE-2), the world’s largest chip), Cerebras has now created a single system capable of supporting AI models with more than 120 trillion parameters. Read More
Ahead of ‘Dojo,’ Tesla Reveals Its Massive Precursor Supercomputer
In spring 2019, Tesla made cryptic reference to a project called Dojo, a “super-powerful training computer” for video data processing. Then, in summer 2020, Tesla CEO Elon Musk tweeted: “Tesla is developing a [neural network] training computer called Dojo to process truly vast amounts of video data. It’s a beast! … A truly useful exaflop at de facto FP32.” Welcome to summer 2021 – it’s time for your annual Dojo update.
Well, sort of: instead of revealing the ins and outs of Dojo, Tesla instead opted to reveal a precursor cluster that the company estimates may be the fifth most-powerful supercomputer in the world. Read More
AI system outperforms humans in designing floorplans for microchips
A machine-learning system has been trained to place memory blocks in microchip designs. The system beats human experts at the task, and offers the promise of better, more-rapidly produced chip designs than are currently possible.
Success or failure in designing microchips depends heavily on steps known as floorplanning and placement. These steps determine where memory and logic elements are located on a chip. The locations, in turn, strongly affect whether the completed chip design can satisfy operational requirements such as processing speed and power efficiency. So far, the floorplanning task, in particular, has defied all attempts at automation. It is therefore performed iteratively and painstakingly, over weeks or months, by expert human engineers. But in a paper in Nature, researchers from Google (Mirhoseini et al.1) report a machine-learning approach that achieves superior chip floorplanning in hours. Read More
How the US Postal Service Is Using AI at the Edge to Improve Mail
Edge computing systems automate package identification at nearly 200 USPS processing centers.
If you paid attention to the US presidential election in 2020, the US Postal Service scandal probably came across your screen. The agency’s resources were stretched so thin, it was feared, that it would become a bottleneck in an election where an unprecedented number of people would vote by mail.
If you were left with the impression that USPS’s budget was close to if not in the red, you may feel some cognitive dissonance when you read that as an enterprise, it is one of the few success stories about the use of AI by the federal government. Read More
Microsoft details the latest developments in machine learning at GTC 21
With the rapid pace of change taking place in AI and machine learning technology, it’s no surprise Microsoft had its usual strong presence at this year’s Nvidia GTC event.
Representatives of the company shared their latest machine learning innovations in multiple sessions, covering inferencing at scale, a new capability to train machine learning models across hybrid environments, and the debut of the new PyTorch Profiler that will help data scientists be more efficient when they’re analyzing and troubleshooting ML performance issues.
In all three cases, Microsoft has paired its own technologies, like Azure, with open source tools and NVIDIA’s GPU hardware and technologies to create these powerful new innovations. Read More
NVIDIA and Cloudflare offer AI to all developers
The partnership said its workers developer platform is faster and 75% less expensive than AWS Lambda.
NVIDIA and Cloudflare announced a partnership that will “put AI into the hands of developers everywhere.”
Working with NVIDIA, Cloudflare will offer artificial intelligence (AI) tools to developers on top of its workers developer platform, making it “easier and faster for developers to build the types of applications that will power the future all within a platform.” On the Cloudflare blog, it claimed that it is faster and 75% less expensive than AWS Lambda. Read More
China Revs Up Grand Chip Ambitions to Counter U.S. Blacklistings
In just two decades, China sent people into space, built its own aircraft carrier and developed a stealth fighter jet. Now the world’s youngest superpower is setting out to prove its capabilities once more — this time in semiconductors.
At stake is nothing less than the future of the world’s No. 2 economy. Beijing’s blueprint for chip supremacy is enshrined in a five-year economic vision to be unveiled during a summit of top leaders in the capital this week. It’s a multi-layered strategy both pragmatic and ambitious in scope, embracing aspirations to replace pivotal U.S. suppliers and fend off Washington, while molding homegrown champions in emergent technologies. Read More
Fetching AI Data: Researchers Get Leg Up on Teaching Dogs New Tricks with NVIDIA Jetson
AI is going to the dogs. Literally.
Colorado State University researchers Jason Stock and Tom Cavey have published a paper on an AI system to recognize and reward dogs for responding to commands.
The graduate students in computer science trained image classification networks to determine whether a dog is sitting, standing or lying. If a dog responds to a command by adopting the correct posture, the machine dispenses it a treat. Read More
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