Today's guest is one of the pioneers in generative AI having spent nine years at Google Research building teams that developed breakthrough technologies that led to innovations like the transformer architecture behind ChatGPT.
Jad Tarifi co-founded Integral AI in 2021 after a distinguished career in AI roles as a researcher and leader. He received his PhD in Computer Science and AI from the University of Florida and did his undergrad at the University of Waterloo.
Thanks to great former guest and friend of the podcast Hina Dixit from Samsung NEXT for the intro to Jad.
Listen and learn:
1. Can machines learn common sense? Do humans have common sense? 2. Why Integral AI is providing a “base model for the world” 3. Can machines ever learn as quickly as humans? 4. How to improve the efficiency of LLMs with better algorithms 5. Why the current transformer architecture is poorly designed for next word prediction 6. How to use AI and robotics to create “magic wands” and “crystal balls” 7. How to use AI to do “science at scale” 8. What are the ethical implications of bots that can change the human life span 9. How AGI is related to objective morality 10. Jad’s four tenets of a new definition of “freedom”
References in this episode…
Integral.ai Blake Lemoine and the “sentience” debate Podcastle, generative AI for podcasts • (a technology nobody needs)
Today's guest is one of the pioneers in generative AI having spent nine years at Google Research building teams that developed breakthrough technologies that led to innovations like the transformer architecture behind ChatGPT.
Jad Tarifi co-founded Integral AI in 2021 after a distinguished career in AI roles as a researcher and leader. He received his PhD in Computer Science and AI from the University of Florida and did his undergrad at the University of Waterloo.
Thanks to great former guest and friend of the podcast Hina Dixit from Samsung NEXT for the intro to Jad.
Listen and learn:
1. Can machines learn common sense? Do humans have common sense? 2. Why Integral AI is providing a “base model for the world” 3. Can machines ever learn as quickly as humans? 4. How to improve the efficiency of LLMs with better algorithms 5. Why the current transformer architecture is poorly designed for next word prediction 6. How to use AI and robotics to create “magic wands” and “crystal balls” 7. How to use AI to do “science at scale” 8. What are the ethical implications of bots that can change the human life span 9. How AGI is related to objective morality 10. Jad’s four tenets of a new definition of “freedom”
References in this episode…
Integral.ai Blake Lemoine and the “sentience” debate Podcastle, generative AI for podcasts • (a technology nobody needs)
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