Will AGI's guest appearances

Will AGI

Towards Data Science

The Sci-AI Podcast

Artificial General Intelligence (AGI) Show with Soroush Pour

Sarah Williams

Ben Goertzel

Jeremy Howard

Roland Memisevic

Max Welling

Ayanna Howard

Mike Tung

Margaret Mitchell

Melanie Mitchell

Gillian Hadfield

Anders Sandberg

Brian Christian

Joel Grus

Jeffrey Ding

Ben Lorica

OwlTail

Jack Kendall

In this episode, we speak with Rain.AI CTO Jack Kendall about his timelines for the arrival of AGI. He also speaks to how we might get there and some of the implications.Hosted by Soroush Pour.Show linksJack KendallBio: Jack invented a new method for connecting artificial silicon neurons using coaxial nanowires at the U. Florida before starting Rain as co-founder and CTO.LinkedIn: https://www.linkedin.com/in/jack-kendall-21072887/Website: https://rain.aiFurther resourcesTry out ChatGPT: https://openai.com/blog/chatgpt/Judea Pearl's book, "The Book of Why"[Paper] https://www.deepmind.com/publications/causal-reasoning-from-meta-reinforcement-learning[Paper] Backpropagation and the Brain: https://www.nature.com/articles/s41583-020-0277-3

In this episode, we speak with <a href="https://rain.ai" rel="nofollow" target="_blank">Rain.AI</a> CTO Jack Kendall about his timelines for the arrival of AGI. He also speaks to how we might get there and some of the implications. Hosted by Soroush Pour. Show links <ul><li>Jack Kendall<ul><li>Bio: Jack invented a new method for connecting artificial silicon neurons using coaxial nanowires at the U. Florida before starting Rain as co-founder and CTO.</li><li>LinkedIn: <a href="https://www.linkedin.com/in/jack-kendall-21072887/" rel="nofollow" target="_blank">https://www.linkedin.com/in/jack-kendall-21072887/</a></li><li>Website: <a href="https://www.rain.ai" rel="nofollow" target="_blank">https://rain.ai</a></li></ul></li><li>Further resources<ul><li>Try out ChatGPT: <a href="https://openai.com/blog/chatgpt/" rel="nofollow" target="_blank">https://openai.com/blog/chatgpt/</a></li><li>Judea Pearl's book, "The Book of Why"</li><li>[Paper] <a href="https://www.deepmind.com/publications/causal-reasoning-from-meta-reinforcement-learning" rel="nofollow" target="_blank">https://www.deepmind.com/publications/causal-reasoning-from-meta-reinforcement-learning</a></li><li>[Paper] Backpropagation and the Brain: <a href="https://www.nature.com/articles/s41583-020-0277-3" rel="nofollow" target="_blank">https://www.nature.com/articles/s41583-020-0277-3</a></li></ul></li></ul>

Ep 3 - When will AGI arrive? - Jack Kendall (CTO, Rain.AI, maker of neural net chips)

Alex Browne

In this episode, we speak with ML Engineer Alex Browne about his timelines for AGI. He also speaks to how we might get there and some of the implications.Hosted by Soroush Pour.Show linksFollow Alex Browne:GitHub: https://github.com/albrowBlog: https://medium.com/@albrowFurther resources:ChatGPT: https://openai.com/blog/chatgpt/Stable Diffusion: https://stability.ai/blog/stablediffusion2-1-release7-dec-2022

In this episode, we speak with ML Engineer Alex Browne about his timelines for AGI. He also speaks to how we might get there and some of the implications. Hosted by Soroush Pour. Show links<ul><li>Follow Alex Browne:<ul><li>GitHub: <a href="https://github.com/albrow" rel="nofollow" target="_blank">https://github.com/albrow</a></li><li>Blog: <a href="https://medium.com/@albrow" rel="nofollow" target="_blank">https://medium.com/@albrow</a></li></ul></li><li>Further resources:<ul><li>ChatGPT: <a href="https://openai.com/blog/chatgpt/" rel="nofollow" target="_blank">https://openai.com/blog/chatgpt/</a></li><li>Stable Diffusion: <a href="https://stability.ai/blog/stablediffusion2-1-release7-dec-2022" rel="nofollow" target="_blank">https://stability.ai/blog/stablediffusion2-1-release7-dec-2022</a></li></ul></li></ul>

Ep 2 - When will AGI arrive? - Alex Browne (Machine Learning Engineer)

The leap from today’s narrow AI to a more general kind of intelligence seems likely to happen at some point in the next century. But no one knows exactly how: at the moment, AGI remains a significant technical and theoretical challenge, and expert opinion about what it will take to achieve it varies widely. Some think that scaling up existing paradigms — like deep learning and reinforcement learning — will be enough, but others think these approaches are going to fall short. Geordie Rose is one of them, and his voice is one that’s worth listening to: he has deep experience with hard tech, from founding D-Wave (the world’s first quantum computing company), to building Kindred Systems, a company pioneering applications of reinforcement learning in industry that was recently acquired for $350 million dollars. Geordie is now focused entirely on AGI. Through his current company, Sanctuary AI, he’s working on an exciting and unusual thesis. At the core of this thesis is the idea is that one of the easiest paths to AGI will be to build embodied systems: AIs with physical structures that can move around in the real world and interact directly with objects. Geordie joined me for this episode of the podcast to discuss his AGI thesis, as well as broader questions about AI safety and AI alignment.

The leap from today’s narrow AI to a more general kind of intelligence seems likely to happen at some point in the next century. But no one knows exactly how: at the moment, AGI remains a significant technical and theoretical challenge, and expert opinion about what it will take to achieve it varies widely. Some think that scaling up existing paradigms — like deep learning and reinforcement learning — will be enough, but others think these approaches are going to fall short. Geordie Rose is one of them, and his voice is one that’s worth listening to: he has deep experience with hard tech, from founding D-Wave (the world’s first quantum computing company), to building Kindred Systems, a company pioneering applications of reinforcement learning in industry that was recently acquired for $350 million dollars. Geordie is now focused entirely on AGI. Through his current company, Sanctuary AI, he’s working on an exciting and unusual thesis. At the core of this thesis is the idea is that one of the easiest paths to AGI will be to build embodied systems: AIs with physical structures that can move around in the real world and interact directly with objects. Geordie joined me for this episode of the podcast to discuss his AGI thesis, as well as broader questions about AI safety and AI alignment.

63. Geordie Rose - Will AGI need to be embodied?