Nvidia, AMD and Intel invest in startup that gives a light to AI chips

chip light ayar

Startup Ayar Labs is attracting the attention of major players in the AI industry. The company designs optical interconnections for AI chips to transmit data via light beams.

Ayar Labs, a California-based startup, has already raised a total of $370 million in investments. Those investments push the startup’s value to above one billion dollars. Among the investors are big names in the AI industry, including Nvidia, AMD and Intel. Ayer is trying to address one of the main bottlenecks in AI training and inference.

Data must move between chips while processing AI workloads. The components are connected with copper wires. Data is converted into electrical signals. At high data rates, forward error correction occurs, which increases latency and reduces performance.

The light seen

Ayer believes it has found a solution to this. The company designed TeraPHY, an optical interconnect that converts data to light signals instead of electrical. The technology enables more efficient communication between chips.

The modules offer 1,000 times higher bandwidth density while requiring up to 10 times less power than electrical interconnects. As a result, each module can transfer up to 25.6 terabits of data per second between a server’s chips, the company claims. The light signals are generated by another device called SuperNova.

Push back

The capital injection will allow Ayar to scale up production of TeraPHY, the company said in the press release. While it is no guarantee that Nvidia, AMD and Intel will actually implement the technology in their chips, as investors, they will be able to monitor the development more closely.

Parties like Nvidia regularly pull out the purse strings to boost the development of potentially interesting technologies. Dutch startup Nebius recently received a million-dollar check from Nvidia. They do so not only out of mercy, but also to be the first to get in line when the technology becomes widely available.

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