Beyond Nvidia: the search for AI's next breakthrough

TORONTO, Canada — For a few days the AI chip juggernaut Nvidia sat on the throne as the world's biggest company, but behind its success are questions on whether new entrants to the artificial intelligence realm can stake a claim in the bonanza.

Nvidia, which makes the processors that are the only way to train generative AI's large language models, is now big technology's newest member, and its stock market takeoff has lifted the whole sector.

Even technology's second rung on Wall Street has ridden on Nvidia's coattails with Oracle, Broadcom, HP and a spate of others seeing their stock valuations surge, despite sometimes shaky earnings.

Amid the champagne popping, startups seeking the attention of Silicon Valley venture capitalists are being asked to innovate, but without a clear indication of where the next chapter of AI will be written.

When it comes to generative AI, doubts persist on what exactly will be left for companies that are not existing model makers, a field dominated by Microsoft-backed OpenAI, Google and Anthropic.

Most agree that competing with them head-on could be a fool's errand.

"I don't think that there's a great opportunity to start a foundational AI company at this point," said Mike Myer, founder and chief executive of the technology firm Quiq, at the Collision technology conference in Toronto.

Some have tried to build applications that use or mimic the powers of the existing big models, but this is being slapped down by Silicon Valley's biggest players.

Vinod Khosla, a venture capital veteran and one of OpenAI's earliest investors, said, "What I find disturbing is that people are not differentiating between those applications which are roadkill for the models as they progress in their capabilities and those that are really adding value and will be here 10 years from now."

The spelling and grammar checking app Grammarly and companies with similar offerings "won't keep up", Khosla predicted, saying such firms, which put only a "thin wrapper" around what the AI models can offer, are doomed.

One of the fields ripe for the taking is chip design, Khosla said, with AI demanding ever more specialized processors that provide highly specific powers.

Rebecca Parsons, chief technology officer for the technology consultancy Thoughtworks, told Agence France-Presse, "If you look across the chip history, we really have for the most part focused on more general chips."

Providing more specialized processing for the many demands of AI is an opportunity seized by Groq, a startup that has built chips for the deployment of AI as opposed to its training, or inference, the specialty of Nvidia's world-dominating GPUs.

Groq CEO Jonathan Ross told AFP that Nvidia won't be the best at everything, even if they specialize in generative AI training.

Agencies Via Xinhua