Models & Labs · United States

BOJ raises economic assessment for Tohoku and Shikoku as tech demand remains strong

Credited to The Japan Times · japantimes.co.jp · 8h ago

Photograph · The Japan Times

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The Bank of Japan revised up its economic assessment for two of the country’s nine regions in a quarterly report released Thursday while leaving it unchanged for the rest.

The central bank compiled the report at the day’s meeting of managers of its regional branches, which was held at its headquarters in Tokyo. Demand related to artificial intelligence remained strong, including for semiconductor manufacturing equipment and electronic components. When it comes to production, the BOJ raised its economic assessment for seven of the nine regions, excluding Hokkaido and the Tokai region.

In the report, the BOJ said the economy in all nine regions has been “picking up moderately,” “recovering moderately,” or “on a moderate recovery trend” while noting that “some weakness has been seen in part.”

The central bank revised upward its economic assessment for the Tohoku region from the assessment that the economy “has been picking up” to the view that the economy “has been recovering moderately.” It also raised its economic view for Shikoku from an assessment that the economy “has been picking up moderately” to the view that the economy “has been picking up.”

In interviews with companies, an electrical equipment maker in Osaka said that AI-related demand has been increasing faster than expected and that robust demand is likely to continue for about the next three years.

Many branch chiefs reported that private consumption has generally remained resilient, supported by improvements in real income. A department store operator in Shizuoka Prefecture said that sales of high-priced goods, such as luxury watches and jewelry, remained strong. Against the backdrop of rising stock prices, there were also reports that sales to wealthy consumers showed no signs of weakening.

Meanwhile, a retailer in Nagoya said that bad weather, including typhoons and heavy rain, weighed on consumption.

Kenji Fujita, manager of the central bank’s branch in Osaka, said at a news conference that small and midsize companies have made relatively smooth progress in passing on higher costs in business-to-business transactions, but that the process is still only halfway along and uneven among businesses closer to consumers.

Regarding the impact of the BOJ’s interest rate hikes to date, an official at the central bank’s Research and Statistics Department said only some companies had indicated that they would put off capital investment, while many said they would make necessary investments, including in labor-saving measures.

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Marvell's custom AI chip upgrade points to a broader fight over peripherals

Credited to DigiTimes$ · digitimes.com17h ago

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Marvell's higher long-term target for custom AI chip revenue suggests the market for artificial intelligence hardware is widening beyond accelerators, into management chips, storage, memory, and networking. The shift could benefit Taiwanese design firms, but it also raises the…

View the article · $DigiTimes

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Models & Labs · United States

US government, tech giants and Biohub commit $1.8B to AI biology initiative

Credited to SiliconANGLE · siliconangle.com · 22h ago

Photograph · SiliconANGLE

More than a half-dozen public and private sector organizations are teaming up to develop biology datasets for artificial intelligence models.

The consortium, which announced the collaboration today, is committing $1.8 billion to the project.

Studying how a cell responds to a new therapy usually requires scientists to set up a physical test environment. That can take years of work and millions of dollars. A faster, more cost-efficient approach would be to test therapies using simulated cells. A simulation doesn’t require expensive lab equipment and can theoretically be spun up in a few hours.

Ultra-detailed, highly reliable simulations that can substitute lab equipment aren’t yet available. The reason is that creating such virtual cells would require a new generation of biology-optimized AI models. Training such models would only be possible with bigger biology datasets than those presently available to scientists.

The research initiative announced today aims to produce the necessary datasets. The biggest contributor to the project is the U.S. Department of Energy, which will commit more than $500 million over five years.

Some of the funds are earmarked for microscopy equipment. The hardware will be used to collect cell measurements for AI training datasets.

The Energy Department will prioritize three imaging methods: neutron scattering, X-ray and cryo-electron microscopy. The first two methods identify the materials that make up a biological sample. Neutron scattering equipment spots light elements and their isotopes, while X-ray machines detect heavier elements. Cryo-electron microscopy, the third imaging method on the list, maps out the internal structure of cells.

The second biggest contributor to the project is Biohub, a research nonprofit backed by Mark Zuckerberg. It’s committing $400 million to the initiative. Three quarters of the funds will go toward in-house research endeavors, while the rest will support external projects.

Like the Energy Department, Biohub will use cryo-electron microscopy to collect cell data. The nonprofit plans to use a specific variant of the technology called cryo-ET. It works by freezing a biological sample and exposing it to an electron beam. When the electrons come into contact with the sample, they change their course and thereby provide insight into its internal structure.

Biohub’s work will also extend to other areas. It plans to collect data about not only the inner workings of cells but also how different cells interact with one another. According to the group, the plan is to create images that contain millions to billions of cells.

The U.S. National Institutes of Health, or NIH, is also participating. It will provide access to biology datasets developed “through more than $500 million in prior federal investment aligned to this initiative.” Biohub and NIH will team up to organize the data into a form that can be more easily processed by AI models.

Google DeepMind, fellow Alphabet Inc. subsidiary Isomorphic Labs and Meta Platforms Inc. are together contributing $300 million. Nvidia Corp., meanwhile, plans to support aspects of the project that will use accelerators and specialized software to run research workloads. The tech giants will be joined by a half-dozen nonprofit research groups including the Allen Institute.

“An accurate predictive model of biology could dramatically accelerate scientific discovery by enabling scientists to perform experiments digitally,” said Biohub head of science Alex Rives. “The insights that come from this could unlock a far greater understanding of disease and open up completely new paths for cures.”

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