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The new chip can wire together supercomputers for artificial intelligence networks.

American semiconductor manufacturing company Broadcom Inc. has released a new chip Jericho3-AI, which is being touted by the company as the highest-performance fabric for artificial intelligence (AI) networks. The new chip will wire together supercomputers.


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Jericho3-AI is packed with features like improved load balancing — which ensures maximum network utilization under the highest network loads, congestion-free operation which implies no flow collisions and no jitter, high radix which allows Jericho3-AI to connect to 32,000 GPUs collectively, and Zero-Impact Failover — ensuring sub-10ns automatic path convergence. All of this would lead to cutting down on the job completion times for AI workload.

Despite the impressive recent progress in AI capabilities, there are reasons why AI may be incapable of possessing a full “general intelligence”. And although AI will continue to transform the workplace, some important jobs will remain outside the reach of AI. In other words, the Economic Singularity may not happen, and AGI may be impossible.

These are views defended by our guest in this episode, Kenneth Cukier, the Deputy Executive Editor of The Economist newspaper.

For the past decade, Kenn was the host of its weekly tech podcast Babbage. He is co-author of the 2013 book “Big Data”, a New York Times best-seller that has been translated into over 20 languages. He is a regular commentator in the media, and a popular keynote speaker, from TED to the World Economic Forum.

A wave of consumer enthusiasm following the launch of OpenAI’s viral ChatGPT has prompted some major tech companies to pour resources into AI development and launch new AI-powered products.

But not everyone is feeling optimistic about the highly intelligent technology.

Last month, several high-profile tech figures, including Elon Musk and Steve Wozniak, threw their weight behind an open letter calling for a pause on developing advanced AI. The letter cited various concerns about the consequences of developing tech more powerful than OpenAI’s GPT-4, including risks to democracy.

The New York Times has a big piece detailing Google’s “shock” and “panic” when Samsung recently floated the idea of switching its smartphones from Google Search to Bing. After being the butt of jokes for years, Bing has been seen as a rising threat to Google thanks to Microsoft’s deal with OpenAI and the integration of the red-hot ChatGPT generative AI. Now, according to the report, one of Android’s biggest manufacturers is threatening to switch its new phones away from Google Search.

Of course, preinstalled search deals are more about cash than quality. Google pays billions every year to be the default search engine on popular products with deals framed as either “revenue sharing” or “traffic acquisition fees.” Google reportedly pays as much as $3.5 billion per year to be the default search on Samsung phones, while it pays Apple $20 billion per year to be the default search on iOS and macOS. The report notes that the Samsung/Google search contract “is under negotiation, and Samsung could stick with Google.”

A new bio-inspired sensor can recognize moving objects in a single frame from a video and successfully predict where they will move to. This smart sensor, described in a Nature Communications paper, will be a valuable tool in a range of fields, including dynamic vision sensing, automatic inspection, industrial process control, robotic guidance, and autonomous driving technology.

Current motion detection systems need many components and complex algorithms doing frame-by-frame analyses, which makes them inefficient and energy-intensive. Inspired by the human visual system, researchers at Aalto University have developed a new neuromorphic vision technology that integrates sensing, memory, and processing in a single device that can detect motion and predict trajectories.

At the core of their technology is an array of photomemristors, that produce in response to light. The current doesn’t immediately stop when the light is switched off. Instead, it decays gradually, which means that photomemristors can effectively “remember” whether they’ve been exposed to light recently. As a result, a sensor made from an array of photomemristors doesn’t just record instantaneous information about a scene, like a camera does, but also includes a dynamic memory of the preceding instants.