Gary Marcus, NYU, Robust.ai Thursday, April 21st, 4:30m PM Towards a Proper Foundation for Artificial General Intelligence Large pretrained language models like BERT and GPT-3 have generated enormous enthusiasm, and are capable of producing remarkably fluent language. But they have also been criticized on many grounds, and described as “stochastic parrots.” Are they adequate as a basis for general intelligence, and if not, what would a better foundation for general intelligence look like? Gary Marcus is a scientist, best-selling author, and entrepreneur. He is Founder and CEO of Robust.AI, and was Founder and CEO of Geometric Intelligence, a machine learning company acquired by Uber in 2016. He is the author of five books, including The Algebraic Mind, Kluge, The Birth of the Mind, and The New York Times best seller Guitar Zero, as well as editor of The Future of the Brain and The Norton Psychology Reader. He has published extensively in fields ranging from human and animal behavior to neuroscience, genetics, linguistics, evolutionary psychology and artificial intelligence, often in leading journals such as Science and Nature, and is perhaps the youngest Professor Emeritus at NYU. His newest book, co-authored with Ernest Davis, Rebooting AI: Building Machines We Can Trust aims to shake up the field of artificial intelligence.
Artificial General Intelligence has been pursued by the biggest tech companies in the world, but recently Google has announced their new revolutionary AI algorithm which promises to create the most performant and best Artificial Intelligence Models in the world. They call it Pathways AI, and it’s supposed to behave just like the human brain and enable smart Robots which are superior to humans and help us do chores in our own apartments. This move by Google is somewhat scary and terrifying, as it gives them a lot of power over the AI industry and could enable them to do evil things with their other secret projects they’re working on. One thing is for sure though, AGI and the Singularity isn’t as far of as even Ray Kurzweil thinks according to Jeff Dean from Google AI and Deepmind. Maybe Elon Musk’s warnings about AI have been justified. —– Every day is a day closer to the Technological Singularity. Experience Robots learning to walk & think, humans flying to Mars and us finally merging with technology itself. And as all of that happens, we at AI News cover the absolute cutting edge best technology inventions of Humanity. —– TIMESTAMPS: 00:00 Google’s Path to AI Domination 00:56 What is Pathways? 02:53 How to make AI more efficient? 05:07 Is this Artificial General Intelligence? 07:42 Will Google Rule the world and the AI Industry? 09:59 Last Words —– #google #ai #agi
The H+ Academy Roundtable presents “AGI: How it got started and key issues ahead” with Peter Voss and Ben Goertzel.
Ben Goertzel is the CEO of SingularityNET, a well-known artificial general intelligence technologist and expert and is part of the Maltese Government Task Force on Artificial Intelligence. He is interviewed at the Malta Blockchain Summit on November 3, 2018 by David Orban, Founder of Network Society, who has known Goertzel for more than ten years. During the interview Goertzel describes what SingularityNET is doing in the context of artificial general intelligence. He also describes the importance of SOPHIA, the AI Robot, in helping to communicate what artificial intelligence is and its possibilities to the general public. He also describes his role as a member of the Malta Government’s new AI Task Force. Malta is seeking to do what it did to promote blockchain and DLT technology and related business practices to become “Blockchain Island” with artificial intelligence technologies. Special thanks to Ben Goertzel: http://goertzel.org/ The Global AI Network, SingularityNET: https://singularitynet.io/ Malta Government’s AI Task Force, MaltaAI: https://malta.ai/ David Orban: https://davidorban.com Network Society: https://netsoc.org/ Network Society Lab: http://netsoclab.com/ Network Society Ventures: https://netsoc.vc/
Lex Fridman Podcast full episode: https://www.youtube.com/watch?v=aGBLRlLe7X8 Please support this podcast by checking out our sponsors: – Shopify: https://shopify.com/lex to get 14-day free trial – Weights & Biases: https://lexfridman.com/wnb – Magic Spoon: https://magicspoon.com/lex and use code LEX to get $5 off – Blinkist: https://blinkist.com/lex and use code LEX to get 25% off premium GUEST BIO: Oriol Vinyals is the Research Director and Deep Learning Lead at DeepMind. PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 SOCIAL: – Twitter: https://twitter.com/lexfridman – LinkedIn: https://www.linkedin.com/in/lexfridman – Facebook: https://www.facebook.com/lexfridman – Instagram: https://www.instagram.com/lexfridman – Medium: https://medium.com/@lexfridman – Reddit: https://reddit.com/r/lexfridman – Support on Patreon: https://www.patreon.com/lexfridman
Oriol Vinyals is the Research Director and Deep Learning Lead at DeepMind. Please support this podcast by checking out our sponsors: – Shopify: https://shopify.com/lex to get 14-day free trial – Weights & Biases: https://lexfridman.com/wnb – Magic Spoon: https://magicspoon.com/lex and use code LEX to get $5 off – Blinkist: https://blinkist.com/lex and use code LEX to get 25% off premium EPISODE LINKS: Oriol’s Twitter: https://twitter.com/oriolvinyalsml Oriol’s publications: https://scholar.google.com/citations?user=NkzyCvUAAAAJ DeepMind’s Twitter: https://twitter.com/DeepMind DeepMind’s Instagram: https://instagram.com/deepmind DeepMind’s Website: https://deepmind.com Papers: 1. Gato: https://deepmind.com/publications/a-generalist-agent 2. Flamingo: https://deepmind.com/blog/tackling-multiple-tasks-with-a-single-visual-language-model 3. Language Models are Few-Shot Learners: https://arxiv.org/abs/2005.14165 4. Emergent Abilities of Large Language Models: https://arxiv.org/abs/2206.07682 5. Attention Is All You Need: https://proceedings.neurips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 OUTLINE: 0:00 – Introduction 0:34 – AI 15:31 – Weights 21:50 – Gato 56:38 – Meta learning 1:10:37 – Neural networks 1:33:02 – Emergence 1:39:47 – AI sentience 2:03:43 – AGI SOCIAL: – Twitter: https://twitter.com/lexfridman – LinkedIn: https://www.linkedin.com/in/lexfridman – Facebook: https://www.facebook.com/lexfridman – Instagram: https://www.instagram.com/lexfridman – Medium: https://medium.com/@lexfridman – Reddit: https://reddit.com/r/lexfridman – Support on Patreon: https://www.patreon.com/lexfridman
Dr. Ben Goertzel discusses artificial general, non-human and cosmist intelligences with Ed Keller at The Overview Effect Lectures, which is a series positioned as a survey of some of the key operational themes critical to post planetary and universal design. Ed Keller’s Youtube Channel – https://www.youtube.com/user/machinicphylum SingularityNET is a decentralized marketplace for artificial intelligence. We aim to create the world’s global brain with a full-stack AI solution powered by a decentralized protocol. We gathered the leading minds in machine learning and blockchain to democratize access to AI technology. Now anyone can take advantage of a global network of AI algorithms, services, and agents. Website: https://singularitynet.io Forum: https://community.singularitynet.io Telegram: https://t.me/singularitynet Twitter: https://twitter.com/singularity_net Facebook: https://facebook.com/singularitynet.io Instagram: https://instagram.com/singularitynet.io Github: https://github.com/singnet Linkedin: https://www.linkedin.com/company/singularitynet
This is the first, introductory episode in a series of videos discussing the General Theory of General Intelligence as overviewed in the paper Goertzel, Ben. “The General Theory of General Intelligence: A Pragmatic Patternist Perspective.” https://arxiv.org/pdf/2103.15100 For general background on Dr. Goertzel’s approach to AGI, see also the 2014 book The AGI Revolution: An Inside View of the Rise of Artificial General Intelligence https://www.amazon.com/AGI-Revolution-Artificial-General-Intelligence/dp/0692756876 ——– SingularityNET is a decentralized marketplace for artificial intelligence. We aim to create the world’s global brain with a full-stack AI solution powered by a decentralized protocol. We gathered the leading minds in machine learning and blockchain to democratize access to AI technology. Now anyone can take advantage of a global network of AI algorithms, services, and agents. Website: https://singularitynet.io​ Forum: https://community.singularitynet.io​ Telegram: https://t.me/singularitynet​ Twitter: https://twitter.com/singularity_net​ Facebook: https://facebook.com/singularitynet.io​ Instagram: https://instagram.com/singularitynet.io​ Github: https://github.com/singnet
🔥 https://youtu.be/VFuElWbRuHM Quantum AI is the use of quantum computing for computation of machine learning algorithms. Thanks to computational advantages of quantum computing, quantum AI can help achieve results that are not possible to achieve with classical computers. Quantum data: Quantum data can be considered as data packets contained in qubits for computerization. However, observing and storing quantum data is challenging because of the features that make it valuable which are superposition and entanglement. In addition, quantum data is noisy, it is necessary to apply a machine learning in the stage of analyzing and interpreting these data correctly. Quantum algorithms: An algorithm is a sequence of steps that leads to the solution of a problem. In order to execute these steps on a device, one must use specific instruction sets that the device is designed to do so. Quantum computing introduces different instruction sets that are based on a completely different idea of execution when compared with classical computing. The aim of quantum algorithms is to use quantum effects like superposition and entanglement to get the solution faster. Why is it important? Although AI has made rapid progress over the past decade, it has not yet overcome technological limitations. With the unique features of quantum computing, obstacles to achieve AGI (Artificial General Intelligence) can be eliminated. Time Stamps🎯 0:00 – Story 2:10 – Ai Pattern Prediction and Applications 3:35 – GPT3 8:20 – The Truth About Ai 11:30 – Ai Social impacts 12:32 – AGI 17:10 – Conscious Ai 21:00 [More]
Provided to YouTube by DistroKid Artificial General Intelligence · Bzk Singularity ℗ Bzk Records Released on: 2019-01-02 Auto-generated by YouTube.
Lunch & Learn presentation and Q&A at Toronto’s Centre for Social Innovation. Prepared and delivered by Wyatt Tessari L’Allié. Slide deck available at https://drive.google.com/open?id=1-8JC3D5q6Wa2OeNdJL40PN5miOQxjpQa
Why to build AGI if it is an existential threat for all of us? There will be 5 reasons why we need to build Artificial General Intelligence as soon as possible and regardless of the threat. Contents of this video: 0:00 | Introduction 0:27 | Reason 1 – Technological singularity 2:37 | Reason 2 – Great filter 5:13 Reason 3 – Keep intelligence through generations 6:50 Reason 4 – We stick to one planet 7:11 Reason 5 – There is no way research in the AI field can be forbidden 7:46 Bonus reason 9:05 Question of the week 9:24 Next episode – Can we build True AI? LINKS: Artificial general intelligence: https://en.wikipedia.org/wiki/Artificial_general_intelligence Reason 1 – Technological singularity: Technological singularity: https://en.wikipedia.org/wiki/Technological_singularity Cat and the lunch box: https://www.youtube.com/watch?v=JhlfT-x6Ys0 Reason 2 – Great filter: Great filter: https://en.wikipedia.org/wiki/Great_Filter Doomsday argument: https://en.wikipedia.org/wiki/Doomsday_argument Drake equation: https://en.wikipedia.org/wiki/Drake_equation Fermi paradox: https://en.wikipedia.org/wiki/Fermi_paradox Anthropic principle: https://en.wikipedia.org/wiki/Anthropic_principle Gray goo: https://en.wikipedia.org/wiki/Gray_goo Warp drive: https://en.wikipedia.org/wiki/Warp_drive Gros Michel banana: https://en.wikipedia.org/wiki/Gros_Michel_banana Reason 3 – Keep intelligence through generations: Hayflick limit: https://en.wikipedia.org/wiki/Hayflick_limit Telomere: https://en.wikipedia.org/wiki/Telomere DNA: https://en.wikipedia.org/wiki/DNA Chromosome: https://en.wikipedia.org/wiki/Chromosome Reason 4 – We stick to one planet: Kardashev scale: https://en.wikipedia.org/wiki/Kardashev_scale Reason 5 – There is no way research in the AI field can be forbidden: Zugzwang: https://en.wikipedia.org/wiki/Zugzwang Bonus: Existential crisis: https://en.wikipedia.org/wiki/Existential_crisis Images used: https://commons.wikimedia.org/wiki/File:Dr._Frank_Drake.jpg Raphael Perrino, CC BY 2.0 [https://creativecommons.org/licenses/by/2.0], via Wikimedia Commons https://commons.wikimedia.org/wiki/File:Enrico_Fermi_1943-49.jpg Department of Energy. Office of Public Affairs, Public domain, via Wikimedia Commons https://commons.wikimedia.org/wiki/File:DNA_orbit_animated.gif Zephyris, CC BY-SA 3.0 [http://creativecommons.org/licenses/by-sa/3.0/], via Wikimedia Commons
Artificial General Intelligence or AGI is a hot topic among researchers and computer scientists in the field of A.I The dawn of a Superintelligence or the process of the creation of artificial general intelligence has often been described as a digital metamorphosis. By seeking better and cheaper technology, we are inevitably fueling the process that will eventually give rise to a superintelligence or AGI. Computer scientists have pointed out that there are only two possibilities why AGI wont emerge. Either we destroy ourselves, or we agree not to pursue better technology. Since the last alternative is quite improbable, one day, if we do not destroy civilization, we will witness the rise of artificial general intelligence. Superintelligent machines pose a unique threat to humanity if our values are not aligned. One solution to the apparent Fermi paradox could be the misaligned values between artificial life and biological life. The development of AI, in particular Strong AI or General AI most often referred as AGI could also be the architect of a Utopian world. However we can not afford for a best case scenario by sitting on our hands. We have to tread carefully in these unfamiliar digital waters and put the right systems and regulations into place. There is also hope for humanity in the sense of us merging with intelligent machines into a symbiotic relationship. The dawn of artificial general intelligence and aligning our values with such an AGI which is also known as the AI control problem, might be [More]
This is a talk by Ilya Sutskever for course 6.S099: Artificial General Intelligence. He is the Co-Founder of OpenAI. This class is free and open to everyone. Our goal is to take an engineering approach to exploring possible paths toward building human-level intelligence for a better world. OUTLINE: 0:00 – Introduction 0:55 – Talk 43:04 – Q&A INFO: Course website: https://agi.mit.edu AI podcast: https://lexfridman.com/ai CONNECT: – AI Podcast: https://lexfridman.com/ai/ – Subscribe to this YouTube channel – LinkedIn: https://www.linkedin.com/in/lexfridman – Twitter: https://twitter.com/lexfridman – Facebook: https://www.facebook.com/lexfridman – Instagram: https://www.instagram.com/lexfridman
This is a talk by Stephen Wolfram for MIT course 6.S099: Artificial General Intelligence. This class is free and open to everyone. Our goal is to take an engineering approach to exploring possible paths toward building human-level intelligence for a better world. INFO: Course website: https://agi.mit.edu AI podcast: https://lexfridman.com/ai CONNECT: – If you enjoyed this video, please subscribe to this channel. – AI Podcast: https://lexfridman.com/ai/ – Show your support: https://www.patreon.com/lexfridman – LinkedIn: https://www.linkedin.com/in/lexfridman – Twitter: https://twitter.com/lexfridman – Facebook: https://www.facebook.com/lexfridman – Instagram: https://www.instagram.com/lexfridman
“Whoever gets to Artificial General Intelligence Wins” Ben Shapiro & Glen Beck ‘EPIC DISCUSSION’ on AI. Thanks for watching, please Like, Comment, Share & Subscribe to Liberty Bell https://www.youtube.com/channel/UC0SxUDuR0GEI6aY0wiN0lEg
Gary Marcus is a researcher whose work focuses on language, biology, and the mind. Marcus is a Professor in the Department of Psychology at New York University. December 9th, 2017
A.G.I. Artificial General Intelligence – How to achieve it. Part 1 PART 2: https://youtu.be/jyLqiU9uD-Y PART 3: https://youtu.be/gLE5aEMIcH0
Maluuba Research has developed a suite of tasks that teach artificial agents how to seek information actively, by asking questions. We’ve also designed a deep neural agent that learns to accomplish these tasks through efficient information-seeking behaviour. Such behaviour is a vital research step towards Artificial General Intelligence. Read the paper: https://arxiv.org/abs/1612.02605 Learn more about Maluuba Research: https://www.maluuba.com
In 2020, several powerful AI programs were developed which have the potential to alter many aspects of our everyday life. What are these programs, and who is behind them? Discord link: https://discord.gg/bQrBVb6 Song source: Savfk – Music: Ultra by Savfk (copyright and royalty free sci-fi electronic cinematic epic soundtrack music) – https://www.youtube.com/watch?v=8A4Jak73Lao Image, song, video, thumbnail and information sources: https://drive.google.com/file/d/1XstdBbyQBZh8NsSCW0su5yqiOnONUp1x/view?usp=sharing Shoutout to Max P for the audio editing and to saviors for the AI advice!
The presentation by Eric Steinberger introduces the audience to what AI can’t do yet and why it is important to research into these capabilities. Furthermore, it explores ways to move forward with AI from a research point of view. The global dev community meets at WeAreDevelopers, an event dubbed by many as the “Woodstock of Developers”. The WeAreDevelopers World Congress 2018 brought together 8,000 techies from 70 countries for 72-hours of pure dev-fun. Visit the largest developer playground in Europe! https://www.wearedevelopers.com/ Facebook: https://www.facebook.com/wearedevelopers Twitter: https://twitter.com/WeAreDevs Instagram: https://www.instagram.com/_wearedevelopers/ #WeAreDevs ©2018, WeAreDevelopers
Cyber & Defence: Digital transformation and UK defence: A discussion with Major General Tom Copinger-Symes Recently, we’ve seen £16 billion injected into British defence — the biggest investment since the end of the Cold War. What does this mean for the UK’s standing against new superpowers? In this session, we look at how the sector is being transformed and the critical role that emerging technologies will play. Featuring: Major General Tom Copinger-Symes – Director Strategy and Military Digitsation – Ministry of Defence Grace Cassy – Co-Founder – CyLon #CogX2021 #JoinTheConversation
The field of Artificial Intelligence was founded in the mid 1950s with the aim of constructing “thinking machines” – that is to say, computer systems with human-like general intelligence. Think of humanoid robots that not only look but act and think with intelligence equal to and ultimately greater than that of human beings. But in the intervening years, the field has drifted far from its ambitious old-fashioned roots. Dr. Ben Goertzel is an artificial intelligence researcher, CEO and founder of SingularityNET. A project combining artificial intelligence and blockchain to democratize access to artificial intelligence. Ben seeks to fulfil the original ambitions of the field. Ben graduated with a PhD in Mathematics from Temple University in 1990. Ben’s approach to AGI over many decades now has been inspired by many disciplines, but in particular from human cognitive psychology and computer science perspective. To date Ben’s work has been mostly theoretically-driven. Ben thinks that most of the deep learning approaches to AGI today try to model the brain. They may have a loose analogy to human neuroscience but they have not tried to derive the details of an AGI architecture from an overall conception of what a mind is. Ben thinks that what matters for creating human-level (or greater) intelligence is having the right information processing architecture, not the underlying mechanics via which the architecture is implemented. Ben thinks that there is a certain set of key cognitive processes and interactions that AGI systems must implement explicitly such as; working and long-term [More]