May 17, 2020

LGE and Qualcomm to develop autonomous vehicle technologies

LG Electronics
LGE
Qualcomm
5G
Jonathan Dyble
2 min
autonomous vehicles
South Korea’s LG Electronics (LGE) and US-based Qualcomm have announced a new partnership, whereby the two firms will team up to develop technologies...

South Korea’s LG Electronics (LGE) and US-based Qualcomm have announced a new partnership, whereby the two firms will team up to develop technologies that will be crucial to the success of autonomous vehicles.

With both firms having significant experience in the mobile innovation, including extensive knowledge surrounding the development of 5G mobile technology, the collaboration will develop a 5G for vehicle network – vital to the deployment of a fully connected autonomous car platform.

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The aim is for the network to be five times faster than the best available LTE technology, with 10 times lower latency, delivering data at the necessary speeds for real life driving situations.

“LG plans to lead the next-generation vehicle components market by combining our experience in automotive communication technologies with Qualcomm’s advanced connected solutions from LTE to 5G,” said Kim Jin-yong, Executive Vice President of LG’s Vehicle Components Smart Business Unit.

“We are optimistic that the combined research strength of Qualcomm and LG will yield benefits that would not be feasible working independently.”

Additionally, Qualcomm and LGE will develop C-V2X (cellular vehicle-to-everything), a technology that delivers double the operation time at a lower cost.

“Building on our long-standing relationship with LG, this effort to advance C-V2X technology further demonstrates our continued commitment to the development of advanced solutions for safe, connected and increasingly autonomous vehicles,” said Nakul Duggal, vice president of product management, Qualcomm Technologies, Inc.

“With the automotive industry on a clear path to 5G, we look forward to working together with LG to meet the demands of today’s drivers and advance the commercialization of C-V2X technology in next-gen vehicles.”

The partnership, effective immediately, will be based in LGE’s Science Park in Seoul, South Korea.

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Jun 11, 2021

Google AI Designs Next-Gen Chips In Under 6 Hours

Google
AI
Manufacturing
semiconductor
3 min
Google AI’s deep reinforcement learning algorithms can optimise chip floor plans exponentially faster than their human counterparts

In a Google-Nature paper published on Wednesday, the company announced that AI will be able to design chips in less than six hours. Humans currently take months to design and layout the intricate chip wiring. Although the tech giant has been working in silence on the technology for years, this is the first time that AI-optimised chips have hit the mainstream—and that the company will sell the result as a commercial product. 

 

“Our method has been used in production to design the next generation of Google TPU (tensor processing unit chips)”, the paper’s authors, Azalea Mirhoseini and Anna Goldie wrote. The TPU v4 chips are the fastest Google system ever launched. “If you’re trying to train a large AI/ML system, and you’re using Google’s TensorFlow, this will be a big deal”, said Jack Gold, President and Principal Analyst at J.Gold Associates

 

Training the Algorithm 

In a process called reinforcement learning, Google engineers used a set of 10,000 chip floor plans to train the AI. Each example chip was assigned a score of sorts based on its efficiency and power usage, which the algorithm then used to distinguish between “good” and “bad” layouts. The more layouts it examines, the better it can generate versions of its own. 

 

Designing floor plans, or the optimal layouts for a chip’s sub-systems, takes intense human effort. Yet floorplanning is similar to an elaborate game. It has rules, patterns, and logic. In fact, just like chess or Go, it’s the ideal task for machine learning. Machines, after all, don’t follow the same constraints or in-built conditions that humans do; they follow logic, not preconception of what a chip should look like. And this has allowed AI to optimise the latest chips in a way we never could. 

 

As a result, AI-generated layouts look quite different to what a human would design. Instead of being neat and ordered, they look slightly more haphazard. Blurred photos of the carefully guarded chip designs show a slightly more chaotic wiring layout—but no one is questioning its efficiency. In fact, Google is starting to evaluate how it could use AI in architecture exploration and other cognitively intense tasks. 

 

Major Implications for the Semiconductor Sector 

Part of what’s impressive about Google’s breakthrough is that it could throw Moore’s Law, the axion that the number of transistors on a chip doubles every five years, out the window. The physical difficulty of squeezing more CPUs, GPUs, and memory on tiny silicon die will still exist, but AI optimisation may help speed up chip performance.

 

Any chance that AI can help speed up current chip production is welcome news. Though the U.S. Senate recently passed a US$52bn bill to supercharge domestic semiconductor supply chains, its largest tech firms remain far behind. According to Holger Mueller, principal analyst at Constellation Research, “the faster and cheaper AI will win in business and government, including with the military”. 

 

All in all, AI chip optimisation could allow Google to pull ahead of its competitors such as AWS and Microsoft. And if we can speed up workflows, design better chips, and use humans to solve more complex, fluid, wicked problems, that’s a win—for the tech world and for society. 

 

 

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