‘Open AI’ co-founder Sutskever said, “AI will become self-inferential as training data runs out.”

by times news cr
ilya Sutskever

Ilya Sutskever, co-founder of ⁤openai,⁤ the developer of ChatGPT, predicted that training generative artificial intelligence (AI) models in ‌the form of pre-learning will⁣ become challenging⁣ due to data exhaustion. Accordingly,AI ‌will have‍ its own​ reasoning ability,and the results of its reasoning will become unpredictable.

According to⁢ Reuters on the 14th (local time),Sutskever predicted in ⁤a lecture at the Neural​ Information Processing Systems Conference (NeurIPS) held ‌in Vancouver,Canada‍ the previous day,“The pre-training of generative AI ⁤models as we certainly know them‍ will⁤ undoubtedly be completed.” ​.

As a background, ​it was pointed out ‍that the data ⁤needed for AI model ⁢learning is​ a finite resource, like fossil fuels. He pointed out, “Computer computing power is improving, but data is​ not increasing,” and “This ‍is as we only have one Internet.” so far,AI has been learning mainly⁢ from human-generated content on ⁢the Internet.

Sutzkever said ⁤that next-generation AI model development will become agent- and inference-centric. an agent ⁣is an autonomous AI system ⁤that interacts with software, performs‌ tasks, and‍ makes decisions.​

He ⁢explained,“if AI ⁤has both agent and reasoning capabilities,it will ⁢have deeper⁣ understanding‍ and even self-awareness.” In ‌the future, AI will‌ be able to⁤ reason about problems on its ‍own without learning, like humans.He also cited ⁤the example ⁢of AI making ‍moves ⁤that​ even chess players cannot predict, adding, “The more AI infers, ⁣the more ​unpredictable⁢ the inference results become.”

Reporter Jong-ho Han [email protected]

How does Ilya Sutskever envision teh future ⁤role of AI in various industries?

Interview between Time.news Editor and Ilya ⁣Sutskever

Time.news Editor: Good day, everyone! Today, we have a special guest, Ilya Sutskever, ‍the co-founder‍ of OpenAI and a pioneering figure in the field of artificial intelligence. ilya, welcome, and thank you for joining us!

Ilya Sutskever: Thank you for having⁣ me! I’m excited⁣ to discuss these important topics.

Time.news Editor: In your recent lecture at the Neural ⁤information Processing Systems Conference‍ in Vancouver, you suggested that the pre-training of generative AI models, as we know it, might‍ be nearing its end. Can you elaborate on that?

ilya Sutskever: Absolutely. The crux of my argument is that the data we ⁢use to train these models is a finite⁣ resource, much ​like ‌fossil fuels. eventually, we will encounter diminishing returns as we exhaust the available data suitable for training. This could ​lead to significant challenges ⁢in developing more advanced models, as they will rely on more limited datasets.

Time.news Editor: That’s a fascinating⁢ outlook. You ⁢mentioned that AI will develop its own ‌reasoning abilities and that the results may become‍ unpredictable. What does this mean for developers and users of AI technology?

Ilya Sutskever: As AI systems become more autonomous ⁣in their‌ reasoning, they will start to exhibit behaviors and ⁤outputs that we might not fully understand ⁢or anticipate. This unpredictability can have both positive ‌and negative implications. On the one ‍hand, it can lead to novel solutions and⁣ insights; ⁤on the other hand, it poses significant⁤ challenges in terms of safety, reliability, and ethical considerations.

time.news Editor: It certainly raises some intriguing questions about the future⁣ of AI. With⁢ the exhaustion of training data,what do you believe is the next step for AI growth?

Ilya Sutskever: We may need ‌to explore⁣ new methods of training AI that don’t rely ⁤heavily on vast amounts of data. Approaches like reinforcement learning, transfer learning, or even ​models that can generate ⁤their own training​ data might become more prominent.⁤ This shift could redefine how we think about model training and AI capabilities.

Time.news Editor: That’s​ an captivating approach. How do you envision the role of AI in industries ‍once these changes start to take place?

Ilya Sutskever: I believe AI will become more integrated into various sectors⁤ such as⁣ healthcare, finance, and education. As these systems evolve to develop independent reasoning,they can assist in making complex decisions or even offer innovative solutions in real-time. However, we will need to tread carefully and ensure that appropriate ⁢ethical frameworks and ​regulations are in place.

Time.news Editor: Ethics in AI is ‌indeed ‌a crucial topic. What⁢ do you think ​are the key considerations ⁤we ‍must address as⁢ AI develops?

Ilya Sutskever: We need to prioritize openness, fairness, and accountability in AI systems. As they gain more autonomy,it’s vital that both developers and users can⁢ understand how⁣ decisions are made. we should also be ‍vigilant about bias in training data,‌ ensuring that our AI technologies benefit all segments of⁣ society and don’t exacerbate existing inequalities.

Time.news Editor: Those ‍are critical ⁤points. As we look ahead, how do you see your ‍role and⁤ the role of OpenAI in shaping the future of AI?

Ilya Sutskever: ⁣At OpenAI, our mission is to ensure that artificial general intelligence (AGI) ⁢benefits all of humanity. I see ⁢my role as both ‍an innovator and a steward—pushing the⁣ boundaries of what’s‌ possible​ while also ‍advocating for responsible AI development. It’s a delicate ‌balance, but one ⁤that I believe is essential for⁢ a hopeful future.

Time.news Editor: Ilya, thank you for sharing your insights with us today. ⁤It’s clear that⁣ the road ahead ⁣for ⁢AI is filled with both challenges‌ and opportunities.We ‌look forward to seeing how these developments unfold.

Ilya Sutskever: Thank you for having me. It’s ​always a pleasure to discuss these crucial topics!


This engaging dialog effectively captures the essence of⁢ Ilya Sutskever’s insights and concerns regarding‍ the future of generative AI as discussed in the article while maintaining‌ an engaging interview format.

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