Ilya Sutskever is one of the most influential figures in artificial intelligence, celebrated for his foundational contributions to deep learning, computer vision, and natural language processing. As Co-founder and Chief Scientist at OpenAI, he has guided the creation of some of the world’s most impactful AI systems, including ChatGPT, GPT-4, and DALL·E 2. His leadership has helped establish OpenAI as a global force for advancing and safely deploying artificial general intelligence.
Before co-founding OpenAI, Ilya made defining contributions to the field through his work at Google Brain and DeepMind, where he co-invented technologies that changed the trajectory of AI, including sequence-to-sequence learning, key components behind modern machine translation, and the research foundations influencing AlphaGo. Earlier in his career, his work with Geoffrey Hinton produced AlexNet, the breakthrough neural network that transformed computer vision and ignited the deep learning revolution.
A Fellow of the Royal Society and a Time 100 Innovators honoree, Ilya is a sought-after keynote speaker whose insights illuminate the future of human-machine collaboration and the societal impact of advanced AI.
Ilya Sutskever is a world-renowned thought leader in artificial intelligence, respected for his pioneering contributions to computer vision, machine translation, and robotics. As Co-founder and Chief Scientist at OpenAI, he has been instrumental in the development of transformative technologies including ChatGPT, GPT-4, and DALL·E 2. Ilya’s early breakthroughs — notably co-inventing DeepMind’s AlphaGo and Google Brain’s TensorFlow — have firmly established him as one of the most influential figures in AI. His expertise in neural networks, deep learning, and natural language processing makes him a sought-after speaker at leading technology and cybersecurity events worldwide.
Raised in Jerusalem, Ilya Sutskever pursued his studies in Computer Science at The Open University of Israel before transferring to the University of Toronto, where he earned a bachelor’s degree in Mathematics and a PhD in Computer Science. Under the mentorship of AI pioneer Geoffrey Hinton, he co-invented the AlexNet, a convolutional neural network that revolutionized computer vision. Following a prestigious postdoctoral fellowship with Andrew Ng at Stanford University, Ilya went on to co-found DNN Research, later acquired by Google, where he advanced his expertise as a Research Scientist on the Google Brain project.
Ilya Sutskever’s career has been defined by his drive to push the boundaries of AI innovation. In 2016, he became Research Director at OpenAI and has served as its Chief Scientist since 2018, guiding some of the organization’s most significant advancements. Notably, he is the inventor of sequence-to-sequence learning, a technique fundamental to the evolution of machine translation. His work is motivated by a mission to develop artificial general intelligence (AGI) that benefits all of humanity, positioning him at the forefront of the future of AI and cybersecurity.
Recognized with honors such as inclusion in MIT Technology Review’s 35 Innovators Under 35 and the Time 100 Most Influential People in AI, as well as being elected a Fellow of the Royal Society, Ilya Sutskever’s achievements speak volumes. His speaking engagements offer rare insight into the future of technology, cybersecurity, and human-machine collaboration. Hire Ilya Sutskever via The Cyber Security Speakers Agency to bring unparalleled expertise and vision to your event.
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Just weeks before the management shakeup at OpenAI rocked Silicon Valley and made international news, the company's cofounder and chief scientist Ilya Sutskever explored the transformative potential of artificial general intelligence (AGI), highlighting how it could surpass human intelligence and profoundly transform every aspect of life. Hear his take on the promises and perils of AGI — and his optimistic case for how unprecedented collaboration will ensure its safe and beneficial development. (Recorded October 17, 2023)
You’ve all experienced the progress of artificial intelligence. Many of you may have spoken with a computer, and a computer understood you and spoke back to you. With the rate of progress being what it is, it’s not difficult to imagine that at some point in the future, our intelligent computers will become as smart or smarter than people. And it’s also not difficult to imagine that when that happens, the impact of such artificial intelligence is going to be truly, truly vast.
And you may wonder: Is it going to be OK when technology is so impactful?
And here my goal is to point out the existence of a force that many of you may have not noticed — a force that gives me hope that indeed, we will be happy with the result.
Artificial intelligence is nothing but digital brains inside large computers.
Every single interesting AI that you’ve seen is built on this idea.
Over decades, scientists and engineers have been figuring out how such digital brains should work and how to build and engineer them.
It is fitting that the seat of intelligence in humans is our biological brain, and the seat of intelligence in artificial intelligence is an artificial brain.
As AI advances, people — companies, governments, researchers — will increasingly:
Recognize the stakes
Collaborate to ensure safety
Act out of enlightened self-interest
Prioritize humanity’s future over competitive pressure
He believes this global shift in behavior will help us navigate AGI wisely.
In this 47 minute conversation, OpenAI Chief Scientist Ilya Sutskever explains why next-token prediction may exceed human intelligence, how AI progress unfolds, and what breakthroughs still matter.
In this wide-ranging interview on The Lunar Society, Ilya Sutskever reflects on the drivers of his research success, the dynamics of AI capabilities, and the path from today’s large language models to systems that surpass human performance. He attributes his scientific breakthroughs not to innate advantage but to giving his work everything he has, emphasizing perseverance and deep understanding over flashes of new ideas.
He discusses why illicit use of AI has not yet exploded, suggesting it may already be occurring quietly or that foreign actors have not fully operationalized current models. He notes that large-scale tracking of misuse is technically possible with specialized operations.
On AI’s economic window before AGI, he expects a multi-year period of rapidly increasing value, though hindsight may compress it into only a few standout years. When asked why AI adoption might disappoint, he identifies reliability as the sole plausible culprit; unreliable systems dampen real-world value regardless of capability.
Sutskever challenges the assumption that next-token prediction limits models to human-level performance. Accurate prediction requires understanding the underlying reality that produces text, and a sufficiently capable model can extrapolate beyond any individual person by inferring how a hypothetical, more advanced mind would behave.
On training, he explains that most reinforcement learning data already comes from models themselves, with humans training only the reward function. He expects human-AI collaboration, not full automation, to dominate future training improvements.
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