Connect with us

Technologies

Brain-Inspired Algorithms Could Dramatically Cut AI Energy Use

A new study dives into a major redesign for AI architecture.

One major issue facing artificial intelligence is the interaction between a computer’s memory and its processing capabilities. When an algorithm is in operation, data flows rapidly between these two components. However, AI models rely on a vast amount of data, which creates a bottleneck. 

A new study, published on Monday in the journal Frontiers in Science by Purdue University and the Georgia Institute of Technology, suggests a novel approach to building computer architecture for AI models using brain-inspired algorithms. The researchers say that creating algorithms in this manner could reduce the energy costs associated with AI models. 

«Language processing models have grown 5,000-fold in size over the last four years,» Kaushik Roy, a Purdue University computer engineering professor and the study’s lead author, said in a statement. «This alarmingly rapid expansion makes it crucial that AI is as efficient as possible. That means fundamentally rethinking how computers are designed.»


Don’t miss any of our unbiased tech content and lab-based reviews. Add CNET as a preferred Google source. Don’t miss any of our unbiased tech content and lab-based reviews. Add CNET as a preferred Google source.


Most computers today are modeled on an idea from 1945 called the von Neumann architecture, which separates processing and memory. This is where the slowdown occurs. As more people around the world utilize data-hungry AI models, the distinction between a computer’s processing and memory capacity could become a more significant issue.

Researchers at IBM called out this problem in a post earlier this year. The issue computer engineers are running up against is called the ‘memory wall.’

Breaking the memory wall

The memory wall refers to the disparity between memory and processing capabilities. Essentially, computer memory is struggling to keep up with processing speeds. This isn’t a new issue. A pair of researchers from the University of Virginia coined the term back in the 1990s. 

But now that AI is prevalent, the memory wall issue is sucking up time and energy in the underlying computers that make AI models work. The paper’s researchers argue that we could try a new computer architecture that integrates memory and processing. 

Inspired by how our brains function, the AI algorithms referred to in the paper are known as spiking neural networks. A common criticism of these algorithms in the past is that they can be slow and inaccurate. However, some computer scientists argue that these algorithms have shown significant improvement over the last few years. 

The researchers suggest that AI models should utilize a concept related to SNNs, known as compute-in-memory. This concept is still relatively new in the field of AI. 

«CIM offers a promising solution to the memory wall problem by integrating computing capabilities directly into the memory system,» the authors write in the paper’s abstract. 

Medical devices, transportation, and drones are a few areas where researchers believe improvements could be made if computer processing and memory were integrated into a single system. 

«AI is one of the most transformative technologies of the 21st century. However, to move it out of data centers and into the real world, we need to dramatically reduce its energy use,» Tanvi Sharma, co-author and researcher at Purdue University, said in a statement. 

«With less data transfer and more efficient processing, AI can fit into small, affordable devices with batteries that last longer,» Sharma said. 

Technologies

Google races to put Gemini at the center of Android before Apple’s AI reboot

Google is using its latest Android rollout to position Gemini as the AI layer across phones, Chrome, laptops and cars.

Google is using its latest Android rollout to make Gemini less of a chatbot and more of an operating layer across the phone, browser, car and laptop, just weeks before Apple is expected to show its own Gemini-powered Apple Intelligence reboot at WWDC.
Ahead of its Google I/O developer conference next week, the company previewed a number of Android updates, including AI-powered app automation, a smarter version of Chrome on Android, new tools for creators, a redesigned Android Auto experience, and a sweeping set of new security features.
Alphabet is counting on Gemini to help Google compete directly with OpenAI and Anthropic in the market for artificial intelligence models and services, while also serving as the AI backbone across its expansive portfolio of products, including Android. Meanwhile, Gemini is powering part of Apple’s new AI strategy, giving Google a role in the iPhone maker’s reset even as it races to prove its own version of personal AI on the phone is further along.
Sameer Samat, who oversees Google’s Android ecosystem, told CNBC that Google is rebuilding parts of Android around Gemini Intelligence to help users complete everyday tasks more easily.
“We’re transitioning from an operating system to an intelligence system,” he said.
As part of Tuesday’s announcements. Google said Gemini Intelligence will be able to move across apps, understand what’s on the screen and complete tasks that would normally require a user to jump between multiple services. That means Android is moving beyond the traditional assistant model, where users ask a question and get an answer, and acting more like an agent.
For instance, Google says Gemini can pull relevant information from Gmail, build shopping carts and book reservations. Samat gave the example of asking Gemini to look at the guest list for a barbecue, build a menu, add ingredients to an Instacart list and return for approval before checkout.
A big concern surrounding agentic AI involves software taking action on a user’s behalf without permissions. Samat said Gemini will come back to the user before completing a transaction, adding, “the human is always in the loop.”
Four months after announcing its Gemini deal with Google, Apple is under pressure to show a more capable version of Apple Intelligence, which has been a relative laggard on the market. Apple has long framed privacy, hardware integration and control of the user experience as its advantages.
Google’s Android push is designed to show it can bring AI deeper into the device experience while still giving users control over what Gemini can see, where it can act and when it needs confirmation.
The app automation features will roll out in waves, starting with the latest Samsung Galaxy and Google Pixel phones this summer, before expanding across more Android devices, including watches, cars, glasses and laptops later this year.
The company is also redesigning Android Auto around Gemini, turning the car into another major surface for its assistant. Android Auto is in more than 250 million cars, and Google says the new release includes its biggest maps update in a decade and Gemini-powered help with tasks like ordering dinner while driving.
Alphabet’s AI strategy has been embraced by Wall Street, which has pushed the company’s stock price up more than 140% in the past year, compared to Apple’s roughly 40% gain. Investors now want to see how Gemini can become more central to the products people use every day.
WATCH: Alphabet briefly tops Nvidia after report of $200 billion Anthropic cloud deal

Continue Reading

Technologies

Waymo recalls 3,800 robotaxis after glitch allowed some vehicles to ‘drive into standing water’

Waymo issued a voluntary recall of about 3,800 of its robotaxis to fix software issues that could allow them to drive into flooded roadways.

Waymo is recalling about 3,800 robotaxis in the U.S. to fix software issues that could allow them to “drive onto a flooded roadway,” according to a letter on the National Highway Traffic Safety Administration’s website.
The voluntary recall is for Waymo vehicles that use the company’s fifth and sixth generation automated driving systems (or ADS), the U.S. auto safety regulator said in the letter posted Tuesday.
Waymo autonomous vehicles in Austin, Texas, were seen on camera driving onto a flooded street and stalling, requiring other drivers to navigate around them. It’s the latest example of a safety-related issue for the Alphabet-owned AV unit that’s rapidly bolstering its fleet of vehicles and entering new U.S. markets.
Waymo has drawn criticism for its vehicles failing to yield to school buses in Austin, and for the performance of its vehicles during widespread power outages in San Francisco in December, when robotaxis halted in traffic, causing gridlock.
The company said in a statement on Tuesday that it’s “identified an area of improvement regarding untraversable flooded lanes specific to higher-speed roadways,” and opted to file a “voluntary software recall” with the NHTSA.
“Waymo provides over half a million trips every week in some of the most challenging driving environments across the U.S., and safety is our primary priority,” the company said.
Waymo added that it’s working on “additional software safeguards” and has put “mitigations” in place, limiting where its robotaxis operate during extreme weather, so that they avoid “areas where flash flooding might occur” in periods of intense rain.
WATCH: Waymo launches new autonomous system in Chinese-made vehicle

Continue Reading

Technologies

Qualcomm tumbles 13% as semiconductor stocks retreat from historic AI-fueled surge

Semiconductor equities reversed sharply after a broad AI-driven advance, with Qualcomm suffering its worst day since 2020 amid inflation concerns and rising oil prices.

Semiconductor stocks fell sharply on Tuesday, reversing course after an extensive rally that had expanded the artificial intelligence investment theme well past Nvidia and driven the industry to unprecedented levels.

Qualcomm plunged 13% and was on track for its steepest single-day decline since 2020. Intel shed 8%, while On Semiconductor and Skyworks Solutions each lost more than 6%. The iShares Semiconductor ETF, which benchmarks the overall sector, fell 5%.

The sell-off came after a key gauge of consumer prices came in above forecasts, and as conflict in Iran pushed crude oil higher—prompting investors to shift away from riskier assets.

The preceding advance had widened the AI opportunity set beyond longtime industry leader Nvidia, which for much of the past several years had largely carried the market to new peaks on its own.

Explosive appetite for central processing units, along with the graphics processing units that power large language models, has sent chipmakers to all-time highs.

Market participants are wagering that the shift from AI model training to autonomous agents will lift demand for additional AI hardware. Among the beneficiaries are memory chip producers, which are raising prices as supply remains tight.

Micron Technology slid 6%, and Sandisk cratered 8%. Sandisk’s stock has surged more than six times over since January.

Continue Reading

Trending

Copyright © Verum World Media