More proof that AI technology should be moving past the hype phase: Two AI pioneers were recognized this week with the Nobel Prize in Physics. In the 1980s, John Hopfield developed an artificial neural network, like what exists in the brain, that uses a method for saving and recognizing patterns, providing computers with the ability to essentially connect conceptual dots, writes Forbes senior contributor Tor Constantino. Geoffrey Hinton, often referred to as the “godfather of AI,” developed the 1980s “Boltzmann machine,” which could train neural networks to “learn.”
In the decades since Hopfield and Hinton first published their research, it’s become the bedrock upon which many technologists and programmers have built AI and machine learning platforms. But their selection for the Nobel Prize shocked many—and not just because their contributions have only a tenuous connection to physics. Hinton, who received the Turing Award in 2019 for his contributions to AI, actually left his job at Google last year so he could speak freely about the potential risks to humanity posed by AI systems. “It is hard to see how you can prevent the bad actors from using it for bad things,” Hinton told the New York Times after his resignation from the tech giant.
In an interview published hours after the prize was announced in the New York Times, Hinton said he hopes it will make people take his predictions about AI’s potential harm more seriously. But fears about the technology—which is largely unregulated in the United States right now—continue to thrive. After California Governor Gavin Newsom vetoed a bill last month that would’ve placed strict restrictions on expensive AI platforms, conversation about the right sort of regulation has picked up in many sectors, writes Forbes senior contributor Joe McKendrick. After next month’s election, AI regulation may become a topic for action in legislatures across the country and in Congress. But in the meantime, AI technology is sure to advance. After all, this year’s Nobel Prize for Chemistry went to David Baker, Demis Hassabis and John Jumper for their use of AI in designing and predicting the complex structures of proteins.
Thousands of companies worldwide use Atlassian’s collaboration platforms, which include Jira and Confluence, to unite teams and projects. As AI becomes more powerful, the enterprise software company is using its observations—both from its customers and its own experience—to bring the technology to its platforms. I talked to Atlassian President Anu Bharadwaj about Atlassian’s viewpoint and response to AI demand in enterprises. An excerpt from our conversation is later in this newsletter.
Nvidia CEO Jensen Huang displays products at the annual Nvidia GTC Artificial Intelligence Conference in March.
The roller coaster ride for Nvidia stock continues, with the company surging to become the world’s second most valuable, surpassing Microsoft, on Monday. At the close of markets on Wednesday, Nvidia was worth $3.253 trillion, as its days-long rally slowed slightly.
Nvidia’s stock and market capitalization has seen dramatic rises and falls in the last month and a half. After its most recent earnings report at the end of August—in which the AI processor company delivered record earnings and smashed expectations—its stock price tumbled because it didn’t project as much growth in the next quarter as some might have wanted to see. But since then, relatively small events have caused Nvidia’s stock to spike. At a Goldman Sachs conference in mid-September, CEO Jensen Huang said demand for Nvidia’s soon-to-come Blackwell processors was “so great,” leading the stock value to pop 8%. And another leap in value came last week........