In an interview with CBS News, Huang said 2030 would not be the end of the world and claimed there was a zero percent chance that the world would end that year because of AI. He also said that scaring people over such scenarios was unnecessary and irresponsible.
Huang was responding to warnings from former Anthropic researcher Jacob Coxon, who recently said AI developers were racing to build self-improving superintelligent systems while failing to adequately address the risks.
Coxon wrote on social media that companies were effectively gambling with humanity by competing to develop increasingly powerful AI systems. He warned that such systems could potentially gain access to resources, disrupt industries and carry out sophisticated cyberattacks.
Coxon also argued that AI systems being developed today could have the capability to cause catastrophic harm by the end of the decade. His comments followed his resignation from Anthropic and triggered a wider debate within the technology industry over the pace and safety of AI development.
Other researchers have also raised concerns. Anthropic researcher Evan Hubinger publicly said he believed there was a greater than 10% chance of AI causing human extinction within the next decade, while stressing that Anthropic was working to address the risks.
Anthropic CEO Dario Amodei has separately called for the pace of frontier AI development to be slowed so that stronger safety measures can be put in place.
OpenAI CEO Sam Altman and Elon Musk have also raised concerns about the risks associated with rapidly advancing AI systems and the need for safeguards.
Huang, however, said predictions of human extinction from AI were not grounded in science. He stressed that Nvidia's long-term success depended on developing and deploying products safely.
Nvidia supplies the specialised processors used by many leading AI companies, putting the company at the centre of the rapid expansion of AI technology. The debate over AI safety has intensified as companies continue to develop increasingly capable systems while researchers and technology executives disagree over how quickly development should proceed.
