SANTA CLARA, California - Sept 24 (Reuters) - The

computing chips that power artificial intelligence consume a lot

of electricity. On Wednesday, the world's biggest manufacturer

of those chips showed off a new strategy to make them more

energy efficient: Using AI-powered software to design them.

At a conference in Silicon Valley, Taiwan Semiconductor

Manufacturing Co ( TSM ), the contract manufacturer that

fabricates chips for Nvidia ( NVDA ), showed off a range of ways

that it is hoping to boost the energy efficiency of AI computing

chips by about 10 times.

Nvidia's ( NVDA ) current flagship AI servers, for example, can

consume as much as 1,200 watts during demanding tasks, which

would be the equivalent of the power used by 1,000 U.S. homes if

run continuously.

The gains TSMC is hoping to achieve come from a new

generation of chip designs in which multiple "chiplets" -

smaller pieces of full computing chips - using different

technologies are packaged together to make one computing

package.

But to make use of those technologies, the firms that design

chips are increasingly relying on AI-powered software from

providers such as Cadence Design Systems ( CDNS ) and Synopsys ( SNPS )

, both of which rolled out new products on Wednesday

that had been developed in close coordination with TSMC.

For some of the complex tasks in designing chips, the tools

from TSMC's software partners found better solutions than TSMC's

own human engineers - and did so much faster.

"That helps to max out TSMC technology's capability, and we

find this is very useful," Jim Chang, deputy director at TSMC

for its 3DIC Methodology Group, said during a presentation

describing the findings. "This thing runs five minutes while our

designer needs to work for two days."

The current way of manufacturing chips is hitting limits, such

as the ability to move data on and off chips using electrical

connections. New technologies, such as moving information

between chips with optical connections, need to be made reliable

enough to use in massive data centers, said Kaushik

Veeraraghavan, an engineer in Meta Platforms' infrastructure

group who gave a keynote address.

"Really, this is not an engineering problem," Veeraraghavan

said. "It's a fundamental physical problem."