The Future of AI According to Jensen Huang: Challenges, Computational Power, and Innovations | Free generative ai tools for images | Free generative ai api | What is generative ai google | Turtles AI

Jensen Huang, CEO of Nvidia, spoke about the challenges of AI, especially the problem of hallucinations, and the growing demand for computational power. He also discussed Nvidia’s innovations, his contributions, and how he seduced his wife with a promise of a career.

Key Points:

• The problem of hallucinations in AI is still years away from being solved.
• Computational power for AI has increased exponentially in the past 10 years.
• Nvidia has dramatically reduced the cost of computation, driving AI adoption.
• Huang revealed his promise to become CEO by age 30 to win over his wife.

Nvidia CEO Jensen Huang recently shared some insights in an interview at the Hong Kong University of Science and Technology, touching on important topics for the evolution of AI and Nvidia’s role in shaping the future of technology. In particular, Huang highlighted one of the most difficult challenges for AI: the problem of hallucinations, or the tendency of AIs to generate incorrect or invented information to fill in gaps in their data. According to Huang, overcoming this problem is not expected in the short term, stating that the solution is still a few years away. This is because, despite the progress in various areas of AI, such as pre-training, post-training and test scalability, there is still insufficient confidence in the results provided by AI. It is not just about getting better answers, but ensuring that the answers are actually reliable and not the result of “hallucinations.” Huang added that improving this aspect will require a continuous increase in computational resources.

During the interview, the CEO also explained how the AI ​​industry has seen unprecedented growth in computational power requirements over the past decade. According to Huang, the demand for power has increased fourfold each year, with an overall increase of about a million times in a decade. This surge has had a direct impact on the value of Nvidia, whose stock has increased 300 times. However, Huang did not want to make precise predictions about the future, although he stressed that the increase in power demand will continue. One of Nvidia’s key innovations has been the ability to drastically reduce the marginal cost of computation, reducing the cost of using resources for AI researchers. Huang stated that, if it were not for Nvidia, AI computation would cost millions of times more today, placing the company as a central player in the global adoption of machine learning technologies.

On a personal level, Huang told a curious anecdote about his career and his private life. During the interview, a promise he made to his future wife, Lori, came up: to become a CEO by the time he was 30. Huang joked that, at the time, that was just a “courtship line,” but over time it became a real motivation to push his career. In fact, at just 17, when he met Lori, Huang made a promise that later proved to be crucial in his life. His courtship strategy, which included weekly homework meetings, culminated in a promise to become a CEO by the time he was 30, a goal he said he didn’t even have clear in his mind at the time, but which actually came to fruition.

The interview also offered an interesting insight into Huang’s vision for the evolution of AI and technology. Despite the great progress made, he reiterated that there is still a long way to go to make AI completely reliable. Solutions to these problems, Huang says, will require further developments across all areas of computation, with the adoption of new learning and simulation techniques.

Huang’s reflections provide important insight into the future direction of AI and the fundamental contribution that Nvidia is making to address the increasingly complex challenges of advanced computing.