For a few days, artificial intelligence (AI) chip juggernaut Nvidia Corp sat on the throne as the world’s biggest company, but behind its staggering success are questions on whether new entrants can stake a claim to the AI bonanza.
Nvidia, which makes the processors that are the only option to train generative AI’s large language models, is now big tech’s newest member and its stock market takeoff has lifted the whole sector.
Even tech’s second rung on Wall Street has ridden on Nvidia’s coattails, with Oracle Corp, Broadcom Inc, HP Inc and a spate of others seeing their stock valuations surge, despite sometimes shaky earnings.
Photo: AFP
Amid the champagne popping, start-ups 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 would be written.
When it comes to generative AI, doubts persist on what exactly would be left for companies that are not existing model makers, a field dominated by Microsoft Corp-backed OpenAI, Google and Anthropic PBC.
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 in time,” Quiq founder and CEO Mike Myer said at the Collision technology conference in Toronto last week.
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.
“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,” venture capitalist Vinod Khosla said.
The tough-talking Khosla is one of OpenAI’s earliest investors.
Companies which only put a “thin wrapper” around what the AI models can offer are doomed, he said.
One of the fields ripe for the taking is chip design, with AI demanding more specialized processors that provide highly specific powers, Khosla said.
“If you look across chip history, we really have, for the most, part focused on more general chips,” tech consultancy Thoughtworks Inc chief technology officer Rebecca Parsons told AFP.
Providing more specialized processing for the many demands of AI is an opportunity that has been seized by Groq Inc, a start-up that has built chips for the deployment of AI, as opposed to its training or inference — the specialty of Nvidia’s world-dominating GPUs.
Nvidia would not be the best at everything, even if they are uncontested for generative AI training, Groq CEO Jonathan Ross told AFP.
“Nvidia and [its CEO] Jensen Huang (黃仁勳) are like Michael Jordan... the greatest of all time in basketball. But inference is baseball, and we try and forget the time where Michael Jordan tried to play baseball and wasn’t very good at it,” he said.
Another opportunity would come from highly specialized AI that would provide expertise and knowhow based on proprietary data, which would not be co-opted by voracious big tech.
“Open AI and Google aren’t going to build a structural engineer. They’re not going to build products like a primary care doctor or a mental health therapist,” Khosla said.
Profiting from highly specialized data is the basis of Cohere Inc, another of Silicon Valley’s hottest start-ups, which pitches specifically-made models to businesses that are skittish about AI veering out of their control.
“Enterprises are skeptical of technology, and they’re risk-averse, and so we need to win their trust and to prove to them that there’s a way to adopt this technology that’s reliable, trustworthy and secure,” Cohere CEO Aidan Gomez told AFP.
Cohere has received funding from Nvidia and Salesforce Ventures LLC, and is valued in the billions of dollars.
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