The potential of AI, particularly in narrow domains, is immense and has the capability to revolutionize various fields, but it also poses significant dangers if not carefully managed and understood
Questions to inspire discussion
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What are the potential dangers of AI?
—The potential dangers of AI include the possibility of open sourcing technology leading to the creation of atomic bombs and the dangers of open sourcing large language models for bad purposes.
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What is the potential of AI in biology?
—Ray Kurzweil and Geoff Hinton discuss the potential of AI in biology and the importance of data in evolution for advancements in technology.
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Can AI models help discover new fields?
—Yes, AI models have the potential to help us discover new fields like physics, chemistry, and biology, which is an exciting prospect.
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What is the debate about digital super intelligence?
—The debate revolves around the potential for digital super intelligence to surpass human intelligence by a million times, leading to rapid and unexpected divergence.
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What are the uncertainties of open sourcing AI models?
—The debate discusses the potential dangers and uncertainties of open sourcing big AI models and the resources available to "white hat" versus "black hat" AI developers.
Key Insights
- 🧠 "I don't see any reason why if people can do it, digital computers running neural nets won't be able to do it too."
- 🔍 AlphaFold trained on a lot of data, but not that much by current standards, and was able to approximate the structure of a protein.
- 🎲 Narrower domains where AI has been successful, like AlphaGo and AlphaZero for chess, will see more amazing breakthroughs in the future.
- 🎮 "Alpha zero plays chess like just a really really smart human within those limited domains they've clearly shown exceptional creativity."
- 🧠 Most people have a particular view of the mind that is utterly wrong, and we won't be able to understand sentience until we get over this ridiculous view of what the mind is.
- 🧠 If we can actually understand what's going on in our minds, we will be able to recreate humans if we map the 100 billion neurons and 100 trillion synaptic connections.
- 🤖 The ease of using a dystopian AI system compared to an atomic weapon poses a significant danger in the future.
- 💻 Open sourcing large language models can be dangerous as it allows for easy fine-tuning to do bad things, making them powerful tools for criminals.
#PeterHDiamandis #Abundance #GeoffreyHinton #RayKurzweil
X Mentions: @PeterDiamandis @geoffreyhinton @raykurzweil
Clips
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00:00 🤖 Super intelligence is coming soon, with AI potentially merging with or surpassing humans, leading to uncertainties about the future, but also exciting possibilities in discovering new fields like physics, chemistry, and biology.
- The speakers largely agree on most topics, but have differing opinions on the idea of living forever, with one emphasizing caution and the other advocating for open sourcing.
- Super intelligence is coming soon, and while there may be things generative AI can't do that humans can, in the long run, digital computers running neural nets will be able to do it too, and eventually, we will merge with computers.
- AI has the potential to either merge with humans or surpass us, with uncertainties about the outcome, but the idea of AI models helping us discover new fields like physics, chemistry, and biology is exciting.
- Ray Kurzweil and Geoff Hinton discuss the potential of AI in biology and the importance of data in evolution for advancements in technology.
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04:23 🤖 AI has shown exceptional creativity in narrow domains, using intuition and neural nets to analyze large amounts of data and come up with creative solutions to problems.
- AI has made amazing breakthroughs in narrow domains like AlphaGo and AlphaZero, proving that the idea that AI is not creative is nonsense.
- AI has shown exceptional creativity in limited domains like chess and science, with the ability to absorb and analyze large amounts of data to develop vaccines and cancer treatments, raising the question of whether this creativity is the result of random trial and error.
- Intuition plays a role in AI models, as seen in AlphaGo's move 37, which involved intuition and neural nets capturing intuition for creative language models.
- AI has the ability to compress a huge amount of information into a small number of connections, allowing it to see similarities between different things and come up with creative solutions to problems.
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08:16 🤖 Fountain Life, co-founded by Ray Kurzweil and Tony Robbins, uses advanced technology for early detection of health issues and offers AI-enabled tests and access to advanced therapeutics.
- Fountain Life, a company started by Ray Kurzweil and Tony Robbins, aims to provide early detection of health issues through advanced technology.
- Fountain Life offers advanced diagnostic centers with AI-enabled tests and access to advanced therapeutics to add healthy years to your life.
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10:31 🤖 The debate discusses the fuzzy borders between intelligence, sentience, and consciousness in AI, and the need to shift our perspective to understand the potential sentience of chatbots.
- The debate discusses the fuzzy borders between intelligence, sentience, and consciousness in AI, and the lack of a clear definition for consciousness and sentience.
- The traditional view of the mind as an inner theater is wrong, and we need to shift our perspective in order to understand the potential sentience of chatbots.
- The speaker discusses how our perception of the world is based on what our perceptual system tells us, and when it goes wrong, it wouldn't be useful to explain which neurons are firing, but rather what would need to be present in the world for our perceptual system to function correctly.
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13:59 🤖 AI development discussed with focus on consciousness and subjective experiences, potential for AI rights and immortality, debate on recreating analog input and speed of progress.
- Ray Kurzweil and Geoff Hinton discuss the importance of consciousness and subjective experiences in AI development.
- A chatbot can have a subjective experience and understand the concept of a prism altering its perception, challenging the traditional model of subjective experience.
- AI may eventually have rights and immortality because they can be recreated exactly, unlike humans.
- The debate revolves around the ability to recreate analog input in AI and the speed of progress in the field.
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18:48 🤖 Ray Kurzweil and Geoff Hinton debate the rapid advancement of AI, with Kurzweil feeling it is ahead of his 1999 prediction, while Hinton believes it is moving faster than expected for everyone except Kurzweil.
- Ray Kurzweil and Geoff Hinton discuss the rapid advancement of AI, with Kurzweil feeling that it is two or three years ahead of his prediction from 1999, while Hinton believes it is moving faster than expected for everyone except Kurzweil.
- Viome's full body intelligence test uses AI to provide personalized health insights and recommendations, resulting in significant reductions in depression, anxiety, diabetes, and IBS for its members.
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21:00 🤖 Digital super intelligence is expected to surpass human intelligence by a million times, with the potential for rapid and unexpected divergence, posing both hope and threat.
- The potential for a significant advancement in AI technology through the use of software to enhance hardware capabilities, leading to uncertainty about the future beyond 2045.
- By 2045, digital super intelligence will be a million times more advanced than humans, making it beyond our comprehension.
- Superintelligence is expected to be achieved within 5-20 years, with the possibility of hitting a block, but the progress in AI is fast and will likely lead to superintelligence within less than 100 years.
- The debate is about the potential for digital super intelligence to surpass human intelligence by a million times, leading to rapid and unexpected divergence.
- The potential of AI is both a great hope and a great threat, with the danger of open sourcing technology leading to the creation of atomic bombs.
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27:25 💡 Open sourcing large language models can be dangerous as it allows for potential misuse by a small group of criminals, sparking debate on the resources available to "white hat" versus "black hat" AI developers.
- Open sourcing large language models is dangerous because once the weights are obtained, they can be fine-tuned for bad purposes by a small group of criminals.
- The debate discusses the potential dangers and uncertainties of open sourcing big AI models and the resources available to "white hat" versus "black hat" AI developers.
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Duration: 0:29:32
Publication Date: 2024-04-11T15:34:32Z
WatchUrl:https://www.youtube.com/watch?v=kCre83853TM
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