Sam Altman meant no disrespect, puts competition comments in context

He had said at the event it was “totally hopeless to compete with us (OpenAI) on training foundation models,” citing a hypothetical scenario in which three engineers with $10 million tried to emulate the feat.

Altman was replying Saturday to Tech Mahindra MD and CEO CP Gurnani, who had earlier tweeted: “Dear @sama, from one CEO to another… challenge accepted,” citing the OpenAI CEO’s comment. “OpenAI founder Sam Altman said it’s pretty hopeless for Indian companies to try and compete with them,” Gurnani’s tweet read.

To this Altman tweeted: “This is really taken out of context! The question was about competing with us with $10 million, which I really do think is not going to work. But I still said try! However, I think it’s the wrong question.”

He went on to say: “The right question is what a startup can do that’s never been done before, that will contribute a new thing to the world. I have no doubt Indian startups can and will do that! And no one but the builders can answer that question.”

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Peak XV Partners managing director Rajan Anandan had posed the question to Altman at the event in New Delhi on Wednesday organised by The Economic Times. “If you want to build foundational models, how should we think about that? Where is it that a team from India, three super smart engineers with not $100 million, but let’s say $10 million, could actually build something truly substantial?”

To this, Altman had replied, “The way this works is we’re going to tell you, it’s totally hopeless to compete with us on training foundation models, you shouldn’t try and it’s your job to try anyway. And I believe both of those things. I think it is pretty hopeless.”

On Twitter, in response to Altman’s remark, Anandan had said: “Thank you @sama for the clear answer. As you said, ‘it is hopeless, but you will try anyway’. 5000 years of Indian entrepreneurship has shown us that we should never underestimate the Indian entrepreneur. We do intend to try.”

Gurnani’s subsequent tweet triggered a debate on social media about the capability of Indian startups to build AI products.

Unacademy cofounder Gaurav Munjal tweeted that founders and investors in India lack a long-term view.

“We didn’t build a global social network or an operating system or a browser or cloud infra. Yet we are so offended by @sama’s statement,” he said. “I would love nothing more than global products and companies being built out of India. But we have to also accept the reality. Founders and Investors in India don’t build / invest in things with truly a long-term view… We shouldn’t just be dominating SaaS and IT Services. We should be doing much more.”

“We need to build a better ecosystem for the next OpenAI to come out of India. We shouldn’t just be dominating SaaS and IT Services. We should be doing much more,” Munjal wrote.

Former Swiggy chief technology officer Dale Vaz, who worked at Amazon India previously, also joined in: “This answer by @sama has obviously ruffled feathers across India biz and tech ecosystem. My take is that Sam’s answer was taken out of context. He was answering a very specific question about whether ‘a group of 3 smart engineers with a $10mn budget could build foundational AI models.’ To which, Sam replied No.”
OpenAI took $1 billion of investment, an Azure super computing platform and 375 employees to get to where it is today, Vaz said.

“Is it any surprise that Sam was so prompt and clear in his response to the specific question?” he wrote. “Maybe, if the question was ‘can a well-funded Indian team with a billion dollar investment, long-term investors and the mandate to risk everything build the next OpenAI?’ the answer may have been a resounding Yes!,”

Nikhil Kumar, cofounder of application programming interface (API) infrastructure startup Setu, also chimed in.

“I don’t even know why some people are just trying to do chest thumping and saying challenge accepted,” he tweeted. “The long version of the no would have been: Foundational models are incredibly hard to build. It requires billions of dollars of investments… amazing partnerships for training data, a long-time horizon (which itself is anti VC thesis) and a community of top researchers. Instead, entrepreneurs should think about building their own finetuned models on top of GPT-4 as an example and build strong moats.”