Bill Gates Reveals 3 Jobs Most Immune To The AI Takeover
While Microsoft co-founder Bill Gates remains optimistic about the social benefits of artificial intelligence, now even the billionaire mogul fears that AI could take his job.
The candid quip came during a recent podcast conversation with OpenAI CEO Sam Altman, whose company is responsible for chungchinghecacloai.com/ the AI-powered chatbot ChatGPT.
Over the years, Gates has maintained that the three best career paths for recent graduates are those in alternative energy, health biosciences, and advancing artificial intelligence itself — but notably 'billionaire philanthropist' is not on that list.
'I could even lose my job,' Gates said on his podcast, 'Unconfuse Me with Bill Gates.'
'When the machine says to me, "Bill, go play pickleball, I've got malaria eradication. You're just a slow thinker,"' he worried, 'then it is a philosophically confusing thing.'
Over the years, Microsoft co-founder Bill Gates has maintained that the three best career paths for recent graduates are those in alternative energy, health biosciences, and advancing artificial intelligence (AI) itself — but notably 'billionaire philanthropist' is not on that list
While Gates remains optimistic about the social benefits of AI, now even the billionaire mogul fears that it could take his job. 'When the machine says to me, 'Bill, go play pickleball, I've got malaria eradication. You're just a slow thinker [...] it is a philosophically confusing thing'
'I was very skeptical,' Gates said about AI, in this conversation with Altman on the January 11, 2024 edition of his podcast. 'I didn't expect ChatGPT to get so good.'
He expressed his own bewilderment with how 'large language model' AIs like ChatGPT can process and imitate intricate textual information, like the works of William Shakespeare, with Altman chiming in that his team shared that confusion.
'When OpenAI built GPT-1, they had no deep understanding of how it worked or why it worked,' Altman confessed.
According to Altman, the company is now pursuing 'interpretability research' in order to more fully unpack all the intricacies and complexities that machine-learning and AI-training has done alone, away from the eyes of its initial coders.