Lifeboat Foundation

How Big Tech, startups, AI devices, and trade wars will transform the way chips are made and the technologies they power.

“Big machine learning models have to consume lots of power to crunch data and come out with the right parameters, whereas our model and training is so extremely simple that you could have systems learning on the fly,” said Robert Kent.

How can machine learning be improved to provide better efficiency in the future? This is what a recent study published in Nature Communications hopes to address as a team of researchers from The Ohio State University investigated the potential for controlling future machine learning products by creating digital twins (copies) that can be used to improve machine learning-based controllers that are currently being used in self-driving cars. However, these controllers require large amounts of computing power and are often challenging to use. This study holds the potential to help researchers better understand how future machine learning algorithms can exhibit better control and efficiency, thus improving their products.

“The problem with most machine learning-based controllers is that they use a lot of energy or power, and they take a long time to evaluate,” said Robert Kent, who is a graduate student in the Department of Physics at The Ohio State University and lead author of the study. “Developing traditional controllers for them has also been difficult because chaotic systems are extremely sensitive to small changes.”

Continue reading “Optimizing Machine Learning Controllers with Digital Twins” »

AI was the center of the show at Google’s annual IO developers conference.

The feature is part of the search giant’s vision for Gemini for Workspace.

We think of GoogleDeepMind as the engine room of Google in the #AI era.

We’re sharing updates across our Gemini family of models and a glimpse of Project Astra, our vision for the future of AI assistants.

Google is trying to turn AI chatbots to intelligent systems that can reason, plan, and remember. Project Astra is a window into this potential future.

Strong AI and consciousness.

Shared with Dropbox.

Qualcomm’s Snapdragon X Elite will eventually face competition in the ARM-based AI chipset space from MediaTek and NVIDIA, who have reportedly joined forces to co-develop a new SoC whose design is said to be finalized in the third quarter of this year. The upcoming silicon is said to support advanced technologies, including being mass produced on TSMC’s 3nm process, with the new entrant possibly competing with Apple’s M4 when comparing lithography.

The unnamed chipset from MediaTek and NVIDIA is rumored to fetch a price of $300 per unit, likely due to leveraging advanced nodes and packaging technologies

With the AI PC segment estimated to grow massively by 2027, MediaTek and NVIDIA want to pounce on this opportunity, giving this category a healthy dose of competition. The Taiwanese fabless semiconductor manufacturer has already received praise from Morgan Stanley analysts for its Dimensity 9,300, so there is no question that the company’s chip-making prowess has a gold-standard label. Add NVIDIA to the mix, and we could see an SoC that overtakes the competition in graphics performance, though Economic News Daily has not mentioned this.

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