In the brain, timekeeping is done with neurons that relax at different rates after receiving a signal; now memristors—hardware analogs of neurons—can do that too.
Artificial neural networks may soon be able to process time-dependent information, such as audio and video data, more efficiently. The first memristor with a ‘relaxation time’ that can be tuned is reported today in Nature Electronics, in a study led by the University of Michigan.
Energy Efficiency and AI.
What if the singularity heralds not AI dominance, but a profound unity consciousness, connecting human and machine minds into a symbiotic, transcendent intelligence?
Scientists used machine learning to discover what they say could be a new way to speed up the process of breaking down plastic significantly, Vice reports.
As detailed in a new paper published in the journal Nature, a research team from the University of Texas at Austin modified an enzyme to break down the individual components of polyethylene terephthalate (PET), a commonly used plastic that makes up a staggering 12 percent of global waste.
Impressively, the modified enzyme also reduced the amount of time it takes for the plastic to degrade from months to a just single week.
Battery technologies that can reliably operate at very low temperatures could be highly valuable for a wide range of applications. These batteries could, for instance, power devices, vehicles, and robotic systems in outer space, deep under the sea, and in other extreme environments.
AMD on Monday announced its new artificial intelligence chips for everything from cutting-edge data centers to advanced laptops, ramping up its challenge to the runaway market leader Nvidia.
Demand has exploded in the past two years for the specialized processors that help develop, train and run AI applications such as ChatGPT.
AMD has emerged as one of Nvidia’s most serious contenders and CEO Lisa Su said the firm’s next-generation processors will rival the top offerings from competitors.
AMD is releasing a chip later this year with 288 GB of cache on it! My high-end PC only has 256 GB of memory in total with only 0.0188 GB of cache on my main chip.
NVIDIA today announced the general availability of NVIDIA ACE generative AI microservices to accelerate the next wave of digital humans, as well as new generative AI breakthroughs coming soon to the platform.
Nvidia Corp. has launched Rubin, its next-generation artificial intelligence (AI) chip platform, which will be available in 2026, according to CEO Jensen Huang. The announcement was made during a presentation at National Taiwan University in Taipei as part of the Computex trade fair.
Rubin platform to include advanced CPUs, GPUs, and networking chips.
The Rubin chip family will include new GPUs, CPUs, and networking processors. The new CPU, called Versa, will be geared to improve AI capabilities. The GPUs, which are critical for powering AI applications, will use next-generation high-bandwidth memory from industry giants including SK Hynix, Micron, and Samsung. Despite the enthusiasm surrounding the introduction, Huang revealed only limited information regarding the Rubin platform’s specific features and capabilities.
Learn the basics of Convolutional Neural Networks (CNNs) in this beginner-friendly guide. Discover how they work, their applications in image recognition, and how they’re changing the world of AI.
