Podcasts about numenta

After learning about the amazing work of my guest this week, I had an idea that I wanted to test out. Perhaps our current obsession with Large Language Models is revealing of our historic obsession with a narrow cognitivist view of how human learning happens (and, therefore, how schooling is structured)?!Memorise the largest possible bank of static data and then output plausible propositions, in response to prompts from a teacher or a standardised exam! Obviously that's a bit of an unfair caricature of the industrial schooling system, but also not a million miles from the truth! As you will have seen from my explorations over the last few years in episodes on ecological psychology, play, movement, active inference and 4E cognitive science, I believe that there is an emerging understanding of how radically embodied and embedded in place and in relationships human learning is actually is. So that's why I was so excited to learn about a vastly different approach to artificial intelligence that is based on a sensorimotor learning framework and Jeff Hawkin's Thousand Brains theory of the neocortex. Dr Viviane Clay is Executive Director of the Thousand Brains Project and a scientist with years of experience in neuroscience, AI and machine learning. She has a PhD in Cognitive Computing. The Thousand Brains Project grew out of decades of research at Numenta, a leading company in neuroscience-based AI technology, and is developing Monty, a new type of artificial intelligence based on the sensorimotor principles observed in the brain. Numenta's co-founder Jeff Hawkins is Research Advisor and Board Member of the Thousand Brains Project.You can find links to additional information about Monty and the Thousand Brains Project below:https://thousandbrains.org/ https://linktr.ee/1000brainsproj2 page overview: https://thousandbrains.org/wp-content/uploads/2024/12/TBP_Overview.pdfhttps://www.youtube.com/@thousandbrainsproject

Jim talks with Jeff Hawkins and Viviane Clay about the Thousand Brains Project and Jeff's book A Thousand Brains: A New Theory of Intelligence. They discuss Mountcastle's theory of the neocortex's universal algorithm, cortical columns & their structure, learning modules in AI sensory systems, reprogramming of the neocortex, the 6 layers of cortex, mini-columns & macro-columns, the visual cascade, reference frames as essential for knowledge representation, "voting" for perceptual consensus, how the project differs from deep learning & LLM approaches, William Gibson's concept of affordances, the "Jennifer Aniston neuron" idea, current state of the Monte project, solving fundamental problems vs making impressive demos, avoiding "old brain" traits in AI systems, and much more. Episode Transcript Perceptual Neuroscience: The Cerebral Cortex, Vernon B. Mountcastle On Intelligence, Jeff Hawkins and Sandra Blakeslee (2004) A Thousand Brains: A New Theory of Intelligence, Jeff Hawkins Monte Project – Open-Source Implementation Superintelligence: Paths, Dangers, Strategies, Nick Bostrom Jeff Hawkins is a scientist whose life-long interest in neuroscience led to the creation of Numenta and its focus on neocortical theory. His research focuses on how the cortex learns predictive models of the world through sensation and movement. In 2002, he founded the Redwood Neuroscience Institute, where he served as Director for three years. The institute is currently located at U.C. Berkeley. Previously, he co-founded two companies, Palm and Handspring, where he designed products such as the PalmPilot and Treo smartphone. Jeff has written two books, On Intelligence (2004 with Sandra Blakeslee) and A Thousand Brains: A New Theory of Intelligence (2021). Viviane Clay is the director of the Thousand Brains Project. She received her doctorate degree in Cognitive Computing and master's degree in Cognitive Science at University of Osnabrück in Germany, where she focused on sensorimotor learning as a key aspect in intelligence. She brings to Numenta fifteen years of coding experience, along with her background in neuroscience, psychology, and machine learning.

DeepSeek, a Chinese AI research company, has introduced DeepSeek-R1, a reasoning AI model designed to compete with Open AI's advanced models. It emphasizes self-fact-checking and handling complex queries but faces challenges with simpler logic problems and concerns over security and censorship due to China's regulatory environment. European markets are experiencing volatility and economic shifts due to the Ukraine-Russia conflict, with increased defense spending, energy security concerns, and substantial financial aid to Ukraine. Investors are navigating a complex landscape influenced by geopolitical risks and the recent U.S. presidential election. Xpeng aims to achieve profitability by the end of 2025 through rising demand for new models, international market expansion, strategic investments in AI and autonomous driving technology, and cost efficiency measures. The company is leveraging partnerships, such as with Volkswagen, and exploring local manufacturing in Europe to navigate trade barriers and enhance its competitive edge in the global EV market. Shiva Suri founded New Lantern to automate tedious radiology tasks, inspired by observing inefficiencies in his mother's work as a radiologist. The startup's AI-driven software aims to enhance radiologists' productivity by integrating image analysis and reporting functions, ultimately improving healthcare outcomes and efficiency. Converge Bio is developing advanced AI tools to enhance large language models (LLMs) for antibody research, securing $5.5 million in funding to further their innovative data enrichment processes and improve drug discovery and diagnostics. The company focuses on creating user-friendly, explainable AI models that integrate comprehensive data, addressing the complexities of biological data and regulatory requirements. Numenta, backed by the Bill and Melinda Gates Foundation, has introduced an open-source AI model inspired by neuroscience. The company leverages Hierarchical Temporal Memory (HTM) to create AI systems that learn continuously from minimal data, with potential applications across healthcare, finance, cybersecurity, and more. The U.S. Department of Justice has recommended that Google divest its Chrome browser and potentially its Android operating system to dismantle its alleged monopoly in the online search market. If implemented, these measures could significantly disrupt Google's integrated ecosystem, alter the digital advertising landscape, and reshape the competitive dynamics of the tech industry.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Response to Dileep George: AGI safety warrants planning ahead, published by Steve Byrnes on July 8, 2024 on The AI Alignment Forum. (Target audience: Dileep George himself, and anyone coming from a similar place.) Dileep George is a researcher working at the intersection of AI and neuroscience. He started his career by co-founding Numenta in 2005 with Jeff Hawkins (while a Stanford PhD student), then he left to co-found Vicarious in 2010 with D. Scott Phoenix, and moved to DeepMind in 2022 when DeepMind acquired Vicarious. Dileep was recently interviewed by Daniel Faggella on his "The Trajectory" podcast: YouTube, Apple podcasts, X/Twitter. It's a fun interview that touched on many topics, most of which I'll ignore, in favor of one very important action-relevant disagreement between Dileep and myself. …And this is the point where everyone these days seems to assume that there are only two possible reasons that anyone would ever bring up the topic of Artificial General Intelligence (AGI) safety in conversation: The person is advocating for government regulation of large ML training runs …or the person is advocating against government regulation of large ML training runs. But, no! That's not my disagreement! That's not why I'm writing this post!! Quite the contrary, I join Dileep in being basically unenthusiastic about governmental regulation of large ML training runs right now. Instead, this post is advocating for Differential Intellectual Progress within technical AI research of the type that Dileep is doing - and more specifically, I'm advocating in favor of figuring out a technical approach to sculpting AGI motivations in docile and/or prosocial directions (a.k.a. "solving the technical alignment problem") before figuring out the exact data structures and parameter-updating rules that would constitute an AGI's ability to build and query a powerful world-model. The first half of this post (§1-2) will try to explain what I'm talking about, what it would entail, and why I think it's critically important. The second half of this post (§3) is more specifically my pessimistic response to Dileep's suggestion that, as AGI is gradually developed in the future, people will be able to react and adapt to problems as they arise. I really think Dileep is a brilliant guy with the best of intentions (e.g. he's a signatory on the Asilomar AI Principles). I just think there are some issues that he hasn't spent much time thinking through. I hope that this post will help. Post outline: Section 1 lists some areas of agreement and disagreement between Dileep and me. In particular, we have a giant area of agreement in terms of how we expect future AGI algorithms to work. Our massive common ground here is really why I'm bothering to write this post at all - it makes me hopeful that Dileep & I can have a productive exchange, and not just talk past each other. Section 2 argues that, for the kind of AGI that Dileep is trying to build, there's an unsolved technical alignment problem: How do we set up this kind of AGI with the motivation to behave in a docile and/or prosocial way? Section 3 is my pessimistic push-back on Dileep's optimistic hope that, if AGI is developed gradually, then we can regulate or adapt to problems as they arise: Section 3.1 lists some big obvious societal problems that have been around for a long time, but nevertheless remain unsolved, along with generic discussions of some underlying challenges that have prevented them from being solved, and why those challenges may apply to AGI too. Section 3.2 dives more specifically into the question of whether we can "keep strong AI as a tool, not a successor", as Dileep hopes. I think it sounds nice but will be impossible to pull off. Section 3.3 comments that, even if we could react and adapt to AGI given enough time - an assum...

Pulse of AI Podcast Season 6 Episode 140 On this podcast, one of the last episodes of season 6, I am joined by Subutai Ahmad, CEO of Numenta. Numenta is in many ways a uniquely Silicon Valley company. It was founded by tech luminaries and has spent the last 17 years doing deep neuroscience research with the goal of better understanding the brain so that those principles could be applied to AI. This work underpins and acts as a platform for their products, the first of which was just recently released.  Follow me on x @thepulseofai and go to our website and sign up for our newsletter at www.thepulseofai.com  In this podcast, Subutai shares: Shares the story of his journey and discusses: What Numenta has been focusing on for the last 17 years. Why AI needs neuroscience. The challenges companies/Numenta customers are facing. Generative and non-generative AI, and when to use which. Why CPUs are ideally suited for accelerating inference. How Numenta and Intel are shaping the future of AI. Where AI is going. Subutai Ahmad - CEO, Numenta Bio Subutai is passionate about neuroscience, deep learning, and building intelligent systems. An accomplished technologist, he has been instrumental in driving Numenta's research, technology and business since 2005. He previously served as VP Engineering at YesVideo where he helped grow the company from a three-person start-up to a leader in automated digital media authoring. In 1997, Subutai co-founded ePlanet Interactive which developed the IntelPlay Me2Cam, the first computer vision product developed for consumers. Subutai holds a B.S. in Computer Science from Cornell University, and a Ph.D in Computer Science from the University of Illinois at Urbana-Champaign.  

This is a new series of Crazy Wisdom where I invited my dad Stewart Alsop II to bring people from his past as a tech journalist and uncover the best stories from the 1980s, 90s and early 2000s about the personal computing revolution and apply them to the AI revolution currently happening. Our first guest Donna Dubinsky talks about her career experiences at Apple, handheld innovator Handspring, her work as the CEO of Palm (of the Palm Pilot handheld mobile device), and current AI work at Numenta. She and Stewart Alsop II both go deep on how the personal computing industry led to the mobile revoltuions and now how we got to where we are today. Dubinsky encourages listeners to stay tuned to developments at NatCast, her current project associated with the CHIPS Act. If you subscribe to chatGPT4, check out this GPT we trained on the conversation Timestamps 00:00 Introduction to the Podcast and the AI Revolution 00:50 The AI Bubble and Lessons from Past Revolutions 01:28 Invitation to Engage with the Podcast 02:04 Introducing the Special Guest: Donna Dubinsky 02:31 Reminiscing about the Past: The Agenda Conference 03:30 The Evolution of Computing Devices 06:14 The Changing Landscape of the Computer Industry 06:58 The Ubiquity of Computing and the Future of the Chips Industry 08:11 The Evolution of Apple and Personal Device Preferences 14:28 The Journey of Numenta and the Future of AI 29:15 The Evolution of Mainframes and the Future of AI on Phones 37:31 The Early Days of the Tech Community 38:30 Transition from Mainframes to Personal Computing 39:04 The Launch of the Palm Pilot 41:30 The Evolution of the Microcomputer Business 42:59 The Role of Government in Advancing Technology 44:46 The Challenges of Manufacturing and Design in the Tech Industry 01:08:05 The Impact of Pricing on Perceived Value 01:09:17 The Highs and Lows of the Palm Pilot Journey 01:12:26 Current Work in AI and the CHIPS Act Key Insights Early Days of Computing and Mainframes: Initially, computing was not a common feature on everyone's desk. Mainframes, the early giants of the computing world, were massive and expensive, accessible only to large corporations and the government. These machines were housed in special rooms and were far from being personal or portable​​​​. Transition to Client-Server Models and Personalization: Computing started evolving with the development of client-server architecture. From the large, centralized mainframes, the industry moved to a model where computing was more distributed. Time-sharing systems allowed multiple users to access mainframe resources, leading to a gradual democratization of computing power. This shift laid the groundwork for the development of personal computers​​. The Era of Desktops and Handheld Devices: The next significant shift was the move to desktops and eventually to handheld devices. This evolution represented a dramatic change in how people interacted with computers, making them more personal and portable. The podcast mentions how devices like the Apple II brought computing into educational settings, revolutionizing how people could use these tools​​​​. The Impact of the Palm Pilot: The Palm Pilot is highlighted as a significant milestone in personal computing. Before the Palm, handheld devices were simply smaller versions of existing technology. The Palm Pilot, however, adopted a different approach. It did not try to replicate all functionalities of a PC. For instance, it did not support printing directly, positioning itself as a window or client to the PC, thus embracing a kind of client-server model. This decision not only made the device more practical and focused but also less expensive to support​​. Evolution of Form Factors: The podcast discusses the evolution of computing devices in terms of form factors. There were three main form factors: desktop (too big to carry), notebook (fit in a briefcase), and handheld (fit in a pocket or purse). Each form factor was defined by how users could physically carry and interact with these devices. It was believed that devices falling between these form factors would not be successful, although this was later proven not entirely accurate with the success of intermediate devices like tablets​​.

"You have to be in constant motion and that's a clear advantage of being at a startup." - Christy Maver Christy brings more than two decades of technology marketing and communications experience to Numenta while holding a BA in Economics from Princeton University. Previously, she launched analytics programs for the Retail and Healthcare industries as the Global Product Marketing Director of Analytics at Actian. Christy held a number of software marketing roles during her 13 years at IBM, where she managed user groups, produced live demos and developed big data video tutorials. She was also one of the founding members of IBM's thought leadership group: the IBM Institute for Business Value. In this interview, Christy and I discuss her experience and knowledge in technology marketing and how to adapt with industry trends. Website: https://numenta.com LinkedIn: https://www.linkedin.com/in/cmaver/ Instagram: https://www.instagram.com/cdmaver/ Facebook: https://www.facebook.com/christy.maver

"You have to be in constant motion and that's a clear advantage of being at a startup." - Christy Maver Christy brings more than two decades of technology marketing and communications experience to Numenta while holding a BA in Economics from Princeton University. Previously, she launched analytics programs for the Retail and Healthcare industries as the Global Product Marketing Director of Analytics at Actian. Christy held a number of software marketing roles during her 13 years at IBM, where she managed user groups, produced live demos and developed big data video tutorials. She was also one of the founding members of IBM's thought leadership group: the IBM Institute for Business Value. In this interview, Christy and I discuss her experience and knowledge in technology marketing and how to adapt with industry trends. Website: https://numenta.com LinkedIn: https://www.linkedin.com/in/cmaver/ Instagram: https://www.instagram.com/cdmaver/ Facebook: https://www.facebook.com/christy.maver

Show Notes for Crazy Wisdom Podcast Episode with Subutai Ahmad Introduction The episode features Subutai Ahmad, the CEO of Numenta and a pioneering figure in both neuroscience and artificial intelligence (AI). The discussion navigates the complex relationship between the human brain's architecture and contemporary AI models like deep learning systems. Topics range from the historical evolution of these disciplines to the cutting-edge research that could shape their future. Historical Perspective The initial inspiration for artificial neural networks came from our rudimentary understanding of how neurons and connections work, going back to the 1940s. Donald Hebb significantly influenced the back-propagation model developed in the 1980s. Hebb's work, combined with the discoveries of Hubel and Wiesel in the '50s, laid the groundwork for understanding how neurons learn features from the visual world, including edge detectors and higher-level shapes. State of Neural Networks Today Despite advancements, today's neural networks still rely on a simplified model of what a neuron is, and they differ fundamentally from biological systems. One glaring difference is in power consumption; a human brain uses only about 20 watts, while running a deep learning network can require power equivalent to an entire city. Learning Modes and Algorithms Deep learning systems usually operate in two modes: inference and training. In contrast, the human brain doesn't distinguish between these states, learning continuously from environmental stimuli. Algorithms, particularly back propagation, are still part of the problem. They try to minimize error, unlike the brain, which adapts and learns contextually. The Numenta Angle Founded by Jeff Hawkins and Donna Dubinsky, Numenta has been researching to understand the principles underlying brain function. Recently, they have focused on applying this understanding to AI. Their approach comprises three main pillars: Efficiency: Using 'sparsity' to mimic the brain's efficient use of connections. Neuron Model: Incorporating the complex nature of neurons for continuous learning. Cortical Columns: Employing a standardized neural circuitry model to replicate intelligence. The Road Ahead For the future, Subutai discusses the need for AI systems to be autonomous and embodied, suggesting that agency and embodiment are crucial aspects of intelligent systems. He also touches on the importance of including elements like neuromodulators and even explores the potential role of quantum physics in neural processing. Conclusion We are in a transformative era where AI is far from being fully realized. Organizations are still trying to grasp how to incorporate these technologies effectively. However, the future is promising, especially with interdisciplinary approaches like Numenta's that blend neuroscience with AI, focusing on understanding the brain's core principles to improve AI's capabilities.

With the costs of large language models and generative AI platforms coming down, companies are beginning to explore highly focused systems that can answer questions to specific, niche topics. We explore the pros and cons of this approach with Lawrence Spracklen, senior technical advisor at Numenta.

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efJf Hawkins' 2021 book A Thousand Brains: A New Theory of Intelligence, focuses on the neocortex and how it helps us to understand the world around us, before examining the future of artificial intelligence, based on what we already know about the brain.In this final episode of Tales from the Synapse, a 12-part podcast series about neuroscience, Hawkins describes how his book finishes on a philosophical note, by covering the future of humanity in an age of intelligent machines.Hawkins is chief scientist at Numenta, a research company he started 17 years ago in Redwood City, California. He career started in the semiconductor industry but his interest in the theories underpinning brain science was triggered by a 1979 article in Scientific American, written by Francis Crick.“I realized that I don't think there's anything more interesting or important to work on, because every human endeavour is based on the brain. Everything we have ever done in the arts and the sciences, and literature and humanities and politics. It's all brains,” he says.Hawkins' search for an academic career in theoretical brain science proved fruitless, prompting a return to industry and the founding of both Palm Computing and Handspring. In 2002 he established the Redwood Neuroscience Institute, now based at the University of California Berkeley.Tales from the Synapse is produced in partnership with Nature Neuroscience and introduced by Jean Mary Zarate, a senior editor at the journal. The series features brain scientists from all over the world who talk about their career journeys, collaborations and the societal impact of their research. Hosted on Acast. See acast.com/privacy for more information.

Today in Daily Web 3 News: Phillip Shoemaker, Executive Director, Identity.com - Phillip Shoemaker brings over 20 years of experience in the mobile space to Identity.com. He helped build the Apple App Store including building the review operations team to over 300 people, writing the guidelines with Steve Jobs, and testifying with global government authorities. Most recently, Phillip has served as an advisor and investor for multiple blockchain startups. Prior to Apple, Phillip was the head of Developer Relations at Numenta, a company focused on understanding the brain and developing deep learning AI technology to solve real-world problems. At Numenta, he worked with AI technology in automotive, and government entities to aid in bot detection, self-driving features, and cybersecurity solutions, in addition to standard machine vision problems.Identity.com is a 501(c)(4) non-profit organization providing decentralized identity verification. it aims to promote social welfare to create a world where individuals and organizations freely access decentralized identity verification services. Identity.com's flagship technology, the Gateway Protocol, provides permissionless authentication and verification. Together with Identity.com, companies and developers may create convenient, on-demand identity verification solutions that offer consumers ownership and control over their digital identities.©Copyright 2023 Matthew Aaron Podcasts LLC Hosted on Acast. See acast.com/privacy for more information.

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Cortex, Ergo Sum: 'On Intelligence,' by Jeff Hawkins

Today we're joined by Subutai Ahmad, VP of research at Numenta. While we've had numerous conversations about the biological inspirations of deep learning models with folks working at the intersection of deep learning and neuroscience, we dig into uncharted territory with Subutai. We set the stage by digging into some of fundamental ideas behind Numenta's research and the present landscape of neuroscience, before exploring our first big topic of the podcast: the cortical column. Cortical columns are a group of neurons in the cortex of the brain which have nearly identical receptive fields; we discuss the behavior of these columns, why they're a structure worth mimicing computationally, how far along we are in understanding the cortical column, and how these columns relate to neurons.   We also discuss what it means for a model to have inherent 3d understanding and for computational models to be inherently sensory motor, and where we are with these lines of research. Finally, we dig into our other big idea, sparsity. We explore the fundamental ideals of sparsity and the differences between sparse and dense networks, and applying sparsity and optimization to drive greater efficiency in current deep learning networks, including transformers and other large language models.  The complete show notes for this episode can be found at twimlai.com/go/562

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Jeff Hawkins on neuromorphic AGI within 20 years, published by Steven Byrnes on the LessWrong. I just listened to AI podcast: Jeff Hawkins on the Thousand Brain Theory of Intelligence, and read some of the related papers. Jeff Hawkins is a theoretical neuroscientist; you may have heard of his 2004 book On Intelligence. Earlier, he had an illustrious career in EECS, including inventing the Palm Pilot. He now runs the company Numenta, which is dedicated to understanding how the human brain works (especially the neocortex), and using that knowledge to develop bio-inspired AI algorithms. In no particular order, here are some highlights and commentary from the podcast and associated papers. Every part of the neocortex is running the same algorithm The neocortex is the outermost and most evolutionarily-recent layer of the mammalian brain. In humans, it is about the size and shape of a dinner napkin (maybe 1500cm²×3mm), and constitutes 75% of the entire brain. Jeff wants us to think of it like 150,000 side-by-side "cortical columns", each of which is a little 1mm²×3mm tube, although I don't think we're supposed to the "column" thing too literally (there's no sharp demarcation between neighboring columns). When you look at a diagram of the brain, the neocortex has loads of different parts that do different things—motor, sensory, visual, language, cognition, planning, and more. But Jeff says that all 150,000 of these cortical columns are virtually identical! Not only do they each have the same types of neurons, but they're laid out into the same configuration and wiring and larger-scale structures. In other words, there seems to be "general-purpose neocortical tissue", and if you dump visual information into it, it does visual processing, and if you connect it to motor control pathways, it does motor control, etc. He said that this theory originated with Vernon Mountcastle in the 1970s, and is now widely (but not universally) accepted in neuroscience. The theory is supported both by examining different parts of the brain under the microscope, and also by experiments, e.g. the fact that congenitally blind people can use their visual cortex for non-visual things, and conversely he mentioned in passing some old experiment where a scientist attached the optic nerve of a lemur to a different part of the cortex and it was able to see (or something like that). Anyway, if you accept that premise, then there is one type of computation that the neocortex does, and if we can figure it out, we'll understand everything from how the brain does visual processing to how Einstein's brain invented General Relativity. To me, cortical uniformity seems slightly at odds with the wide variety of instincts we have, like intuitive physics, intuitive biology, language, and so on. Are those not implemented in the neocortex? Are they implemented as connections between (rather than within) cortical columns? Or what? This didn't come up in the podcast. (ETA: I tried to answer this question in my later post, Human instincts, Symbol grounding, and the blank-slate neocortex.) (See also previous LW discussion at: The brain as a universal learning machine, 2015) Grid cells and displacement cells Background: Grid cells for maps in the hippocampus Grid cells, discovered in 2005, help animals build mental maps of physical spaces. (Grid cells are just one piece of a complicated machinery, along with "place cells" and other things, more on which shortly.) Grid cells are not traditionally associated with the neocortex, but rather the entorhinal cortex and hippocampus. But Jeff says that there's some experimental evidence that they're also in the neocortex, and proposes that this is very important. What are grid cells? Numenta has an educational video here. Here's my oversimplified 1D toy example (the modules can als...

Jeffrey Hawkins speaks exclusively to Indian Genes, he is the American founder of Palm Computing and Handspring where he invented the PalmPilot and Treo, respectively. He has since turned to work on neuroscience full-time, founding the Redwood Center for Theoretical Neuroscience (formerly the Redwood Neuroscience Institute) in 2002 and Numenta in 2005. Hawkins is currently Chief Scientist at Numenta, where he leads a team in efforts to reverse-engineer the neocortex and enable machine intelligence technology based on brain theory. Hawkins is the author of On Intelligence which explains his memory-prediction framework theory of the brain. In March 2021, he released his second book, A Thousand Brains: A New Theory of Intelligence, which details the discoveries he and the Numenta team made that led to the Thousand Brains Theory of Intelligence.

In this episode of the podcast Danese Cooper, Founder & Chair of InnerSource Commons, and long time open source veteran discusses Debunking Common Fears about Open Source (a great segway into our Open Source Strategy Forums upcoming in London and New York in October and November - that deal with open source in the regulated industry of financial services). How can a regulated-industry business get ready for Open Source? That's really a multi-layered question because of special requirements created by those regulations. The process of developing Open Source readiness through an internal InnerSource practice has been a focus in FinTech for most of the past decade, thanks to success stories from the likes of Lloyd's Bank. How does the fact that FinTech companies are subject to strict regulation play into undertaking such a transformation? FINOS's James McLeod was tweeting with Danese Cooper about a podcast they'd recorded when a follower asked that seemingly simple question, and out of the resulting conversation comes this webinar! We'll be looking at issues such as PCI-compliance, GDPR-compliance, distributed-ledger systems such as Blockchain, and new regulations surrounding Transfer Pricing and exploring strategies to mitigate risk and what lessons can be learned from innovative new companies. Slides PDF Link Danese's Bio: Ms. Danese Cooper has been the Head of Open Source Software at PayPal, Inc. since February 2014. She has served as inaugural Chairperson of the Node.js Foundation from June 2015-2017. Ms. Cooper previously served as the CTO of Wikimedia Foundation, Inc., as Chief Open Source Evangelist for Sun and as Sr. Director of Open Source Strategies for Intel. She concentrates on creating healthy open source communities and has served on the Boards of the Drupal Association, the Open Source Initiative, the Open Hardware Association and has advised Mozilla and the Apache Software Foundation. She also runs a successful open source consultancy which counts Bill & Melinda Gates Foundation, SETI Foundation, Harris Corporation and Numenta as clients. She has been known to knit through meetings. Danese's Twitter | Danese's LinkedIn | InnerSource Commons OSSF London Agenda | OSSF London Registration | More information about OSSF ►► Visit FINOS www.finos.org ►► Get In Touch: info@finos.org

Jeff Hawkins is the founder of Redwood Center for Theoretical Neuroscience in 2002 and Numenta in 2005. In his 2004 book titled On Intelligence, and in his research before and after, he and his team have worked to reverse-engineer the neocortex and propose artificial intelligence architectures, approaches, and ideas that are inspired by the human brain. His previous book, On Intelligence, was an impressive scientific journey into intelligence as a memory-prediction system for experiences and therefore vastly different than a computer. He compared a human brain’s neuron to two machine neurons: a traditional neural network neuron and his version of a more sophisticated one in the form of hierarchical temporal memory (HTM) cells. Almost 20 years later, he takes this earlier HTM concept to a higher plane and has truly established himself as both a formidable teacher and an ardent student of intelligence. His latest book, A Thousand Brains: A New Theory of Intelligence, is framed in the construct of how the neocortex represents object compositionally, object behaviors, and higher level concepts. The main premise is that every part of the neocortex learns complete models of objects and concepts, and that there are many such models of each object distributed throughout the neocortex that have long range connections (hence the title of the book). https://numenta.com https://twitter.com/numenta https://www.youtube.com/watch?v=-EVqrDlAqYo https://www.ted.com/speakers/jeff_hawkins https://ai-med.io/analysis/a-thousand-brains-jeff-hawkins/ HELP ME CROWDFUND MY GAMESTOP BOOK. Go to https://wen-moon.com or join the crowdfunding campaign and pre-order my next book If you haven’t already and you enjoyed this episode, please subscribe to this podcast and our mailing list, and don’t forget, my book, Brexit: The Establishment Civil War, is now out, you’ll find the links in the description below. Express VPN 12 Months 35% off!! - https://www.xvinlink.com/?a_fid=chatter​ NameCheap - https://namecheap.pxf.io/WD4Xrn Spreaker - https://spreaker.pxf.io/0JmQoL Watch Us On Odysee.com - https://odysee.com/$/invite/@TheJist:4 Sign up and watch videos to earn crypto-currency! Buy Brexit: The Establishment Civil War - https://amzn.to/39XXVjq Mailing List - https://www.getrevue.co/profile/thejist Twitter - https://twitter.com/Give_Me_TheJist Website -

Jeff Hawkins is a neuroscientist and cofounder of Numenta, a neuroscience research company. Please support this podcast by checking out our sponsors: – Codecademy: https://codecademy.com and use code LEX to get 15% off – BiOptimizers: http://www.magbreakthrough.com/lex to get 10% off – ExpressVPN: https://expressvpn.com/lexpod and use code LexPod to get 3 months free – Eight Sleep: https://www.eightsleep.com/lex and use code LEX to get special savings – Blinkist: https://blinkist.com/lex and use code LEX to get 25% off premium EPISODE LINKS: A Thousand Brain (book): https://amzn.to/3AmxJt7 Numenta's Twitter: https://twitter.com/Numenta Numenta's Website: https://numenta.com/ PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS:

In this episode of the podcast, Sam Harris speaks with Jeff Hawkins about the nature of intelligence. They discuss how the neocortex creates models of the world, the role of prediction in sensory-motor experience, cortical columns, reference frames, thought as movement in conceptual space, the future of artificial intelligence, AI risk, the “alignment problem,” the distinction between reason and emotion, the “illusory truth effect,” bad outcomes vs existential risk, and other topics. Jeff Hawkins is a scientist whose life-long interest in neuroscience led to the co-founding and creation of Numenta, a team of scientists and engineers applying neuroscience principles to machine intelligence research. His research focuses on how the cortex learns predictive models of the world through sensation and movement. In 2002, he founded the Redwood Neuroscience Institute, where he served as Director for three years. The institute is currently located at U.C. Berkeley. Previously, he co-founded two companies, Palm and Handspring, where he designed products such as the PalmPilot and Treo smartphone. Jeff has written two books, On Intelligence (2004 with Sandra Blakeslee) and A Thousand Brains: A New Theory of Intelligence (2021). Jeff earned his B.S. in Electrical Engineering from Cornell University in 1979. He was elected to the National Academy of Engineering in 2003. Website: numenta.com Twitter: @Numenta Learning how to train your mind is the single greatest investment you can make in life. That’s why Sam Harris created the Waking Up app. From rational mindfulness practice to lessons on some of life’s most important topics, join Sam as he demystifies the practice of meditation and explores the theory behind it.

In this episode I have a really interesting conversation with Karan Grewal, member of the research staff at Numenta where he investigates how biological principles of intelligence can be translated into silicon. We speak about the thousand brains theory and why neural networks forget.     References Main paper on the Thousand Brains Theory: https://www.frontiersin.org/articles/10.3389/fncir.2018.00121/full Blog post on Thousand Brains Theory: https://numenta.com/blog/2019/01/16/the-thousand-brains-theory-of-intelligence/ GLOM paper by Geoff Hinton: https://arxiv.org/pdf/2102.12627.pdf Why neural networks forget? https://numenta.com/blog/2021/02/04/why-neural-networks-forget-and-lessons-from-the-brain  

Join Guy Kawasaki on this week's Remarkable People podcast with guest Jeff Hawkins. Jeff a Silicon Valley veteran often credited with starting the entire handheld computing industry. He is a serial entrepreneur, scientist, engineer, and inventor. He also founded two mobile computing companies, Palm and Handspring, and is the architect of many computing products such as the PalmPilot and Treo smartphone. Jeff is the cofounder of Numenta, a research company focused on brain theory and AI. Previously, he founded the Redwood Neuroscience Institute, a scientific institute focused on understanding the neocortex. The Redwood Institute is located at U.C. Berkeley. Jeff recently published his second book, A Thousand Brains: A New Theory of Intelligence.

Jeff Hawkins has spent nearly twenty years on a quest to discover how the brain's cortex generates intelligence. In this episode he talks about his new book A Thousand Brains: A New Theory of Intelligence, which describes some of his most recent research in a way that is accessible to readers of all backgrounds. Links and References: A Thousand Brains: A New Theory of Intelligence by Jeff Hawkins Detailed References on Numenta website Please visit http://brainsciencepodcast.com for additonal references and episode transcripts.   Please Visit Our Sponsors TextExpander at textexpander.com/podcast Announcements: Brain Science comes out on 4th Friday each month. Support Brain Science by buying Are You Sure? The Unconscious Origins of Certainty by Virginia "Ginger" Campbell, MD. (Autographed copies are available) Learn more ways to support Brain Science at http://brainsciencepodcast.com/donations Sign up for the free Brain Science Newsletter to get show notes automatically every month. You can also text brainscience to 55444 to sign up. Check out the free Brain Science Mobile app for iOS, Android, and Windows. (It's a great way to get both new episodes and premium content.) Email Dr. Campbell if you want to help design the new website for Brain Science. Your feedback is greatly appreciated. Connect on Social Media: Twitter: @docartemis Facebook page: http://www.facebook.com/brainsciencepodcast Contact Dr. Campbell: Email: brainsciencepodcast@gmail.com

Michael Shermer speaks with Jeff Hawkins, cofounder of Numenta: a neuroscience research company, about his new book A Thousand Brains: A New Theory of Intelligence in which Hawkins explains how simple cells in the brain create intelligence by using maplike structures to build hundreds of thousands of models of everything we know. Listen to this in-depth dialogue about the discoveries that allow Hawkins to answer important questions about how we perceive the world, why we have a sense of self, and the origin of high-level thought.

Donna is a serial entrepreneur best known for her work as CEO of Palm Computing and then Handspring, pioneers of the first successful handheld computers and smartphones. Previously, Donna spent 10 years in a multitude of sales, sales support, and logistics functions—both at Apple and at Claris, an Apple software subsidiary. In 2005, she founded machine intelligence neuroscience company Numenta with her long-time business partner, Jeff Hawkins. She is still the acting CEO of Numenta today. Donna earned a B.A. from Yale University, and an M.B.A. from Harvard Business School. In addition to chairing Numenta's board, she currently serves on the boards of Stanford Health Care (Palo Alto, CA), and public company Twilio (which is valued at over $60B). Donna also served on the board of Yale from 2006-2018.This episode was originally a live fireside chat.

In this episode, we talk with Jeff Hawkins—an entrepreneur and scientist, known for inventing some of the earliest handheld computers, the Palm and the Treo, who then turned his career to neuroscience and founded the Redwood Center for Theoretical Neuroscience in 2002 and Numenta in 2005—about a new theory about how the cells in our brain work to create intelligence. What exactly is happening in the neocortex as our brains process and interpret information and sensory input—like sight, smell, touch, or language, or math—to create a perception of and to navigate through the world around us?  a16z General Partner Vijay Pande and I talk to Jeff about the basic principles in this new idea of the brain’s learning methodology for creating not just human intelligence, but animal intelligence, artificial intelligence, even alien intelligence, which he lays out in his newly just released book, A Thousand Brains: A New Theory of Intelligence. The conversation covers how the neocortex builds models of the world around us, and what this could mean for how we design the next generation of truly intelligent machines. This episode goes all the way from tiny neurons and how they speak to each other to what’s happening in optical illusions to the future of humanity and beyond.

In this final episode in the series, Jeff Hawkins, author of A Thousand Brains, talks with Christy Maver, VP of Marketing at Numenta, about the last section of his new book, Part Three: Human Intelligence.  Jeff briefly discusses each chapter in this section, from why people create false beliefs to estate planning for humanity.  They conclude with Jeff’s final thoughts about the book. #athousandbrainsOrder A Thousand Brains here: https://www.amazon.com/Thousand-Brains-New-Theory-Intelligence/dp/1541675819/

Today we’re joined by Dileep George, Founder and the CTO of Vicarious. Dileep, who was also a co-founder of Numenta, works at the intersection of AI research and neuroscience, and famously pioneered the hierarchical temporal memory. In our conversation, we explore the importance of mimicking the brain when looking to achieve artificial general intelligence, the nuance of “language understanding” and how all the tasks that fall underneath it are all interconnected, with or without language. We also discuss his work with Recursive Cortical Networks, Schema Networks, and what’s next on the path towards AGI!

В гостях Григорий Сапунов - кандидат технических наук, CTO компании Intento, а в прошлом - руководитель команды разработки Яндекс-новостей. Обсудили с Григорием возможные направления, из которых может (или не может) возникнуть искусственный интеллект общего назначения. Поговорили про эволюционный подход, про развитие капсульных сетей, авто-ML, проблемы софта и железа в современном машинном обучении. Получилось насыщенно и интересно! Ссылки выпуска: Компания intento, в которой Григорий является со-основателем и техническим директором (https://inten.to/) Сайт компании Numenta, занимающейся машинным интеллектом (https://numenta.com/) Небольшая статья на Хабре про капсульные нейронные сети Хинтона (https://habr.com/ru/post/417223/) Статья "The Hardware Lottery", рекомендованная Григорием к прочтению (https://arxiv.org/pdf/2009.06489.pdf) Группа CyberBiology, посвященная эволюционным вычислениям (https://vk.com/cyberbiology) Канал Григория в телеграме "gonzo-обзоры ML статей" (https://t.me/gonzo_ML) Буду благодарен за обратную связь! Оставляйте ваши комментарии там, где можно. Например, в Apple Podcasts. Они помогут сделать подкаст лучше! Напишите что вам было понятно, что не очень, какие темы раскрыть, каких гостей пригласить, ну, и вообще в какую сторону катить этот подкаст :) Подписывайтесь на телеграм-канал "Стать специалистом по машинному обучению" (https://t.me/toBeAnMLspecialist) Телеграм автора подкаста (https://t.me/kmsint) Со мной также можно связаться по электронной почте: kms101@yandex.ru Music by Audionautix.com

Dileep George is a researcher at the intersection of neuroscience and artificial intelligence, co-founder of Vicarious, formerly co-founder of Numenta. From the early work on Hierarchical temporal memory to Recursive Cortical Networks to today, Dileep’s always sought to engineer intelligence that is closely inspired by the human brain. Support this channel by supporting our sponsors. Click links, get discount: – Babbel: https://babbel.com and use code LEX – MasterClass: https://masterclass.com/lex – Raycon: https://buyraycon.com/lex If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can

Matt Taylor interviews Florian Fiebig, PhD, a Visiting Scientist at Numenta.

We're back! After a summer hiatus, we are back with a new episode. Host Matt Taylor talks to Numenta VP of Research Subutai Ahmad about the effort he has been leading in applying Numenta research and HTM principles to deep learning systems. This episode is also available as a video.

Donna Dubinsky, ex-Apple executive and CEO of Numenta, joins Paul Martino and Randy Komisar again to discuss how Bill ran the board of Columbia University, why he escaped from an Apple cruise on a helicopter, and the time he agreed to stop swearing. Donna offers her take on who taught Bill.

Jeff Hawkins is the founder of Redwood Center for Theoretical Neuroscience in 2002 and Numenta in 2005. In his 2004 book titled On Intelligence, and in his research before and after, he and his team have worked to reverse-engineer the neocortex and propose artificial intelligence architectures, approaches, and ideas that are inspired by the human brain. These ideas include Hierarchical Temporal Memory (HTM) from 2004 and The Thousand Brains Theory of Intelligence from 2017. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where

In this episode, host Matt Taylor asks Numenta co-founder Jeff Hawkins to define intelligence. Jeff outlines 3 components of intelligence, and revisits them through the lens of the Thousand Brains theory of Intelligence. According to Jeff, "The bottom line is that Intelligence is only as good as the model that you build."

Dr. Konrad Kording is a professor at University of Pennsylvania, known for his contributions to the fields of motor control, neural data methods, and computational neuroscience. He runs the Kording Lab, or K-Lab, which focused on computational neuroscience early on and now focuses on causality in data science applications. His lab has made an impact across many fields over time, including Bayesian brains, causal effects in human behavior, and uncertainty in the brain. In this episode, Matt Taylor interviews Dr. Kording over Skype about motor representations in the brain, intentionality, time-warping in neurons, and causality. A video of this episode is available on the HTM School YouTube channel.

Dr. Konrad Kording is a professor at University of Pennsylvania, known for his contributions to the fields of motor control, neural data methods, and computational neuroscience. He runs the Kording Lab, or K-Lab, which focused on computational neuroscience early on and now focuses on causality in data science applications. His lab has made an impact across many fields over time, including Bayesian brains, causal effects in human behavior, and uncertainty in the brain. In this episode, Matt Taylor interviews Dr. Kording over Skype to discuss illusions of perception, how uncertainty might be represented in the brain, and more. A video of their conversation is available on the HTM School YouTube channel.

After a couple episodes of deep neuroscience, co-host Christy Maver takes us back to the business side of things in an interview with Numenta CEO Donna Dubinsky. They discuss the challenge of navigating a dual mission, why she believes it’s important even for non-neuroscientists to understand how the brain works, and where she believes the company is going.

Blake Richards is Assistant Professor and Associate Fellow of the Canadian Institute for Advanced Research (CIFAR). Author of the papers, “Toward deep learning with segregated dendrites” and “The Persistence and Transience of Memory,” Blake answers questions about how deep learning models can incorporate segregated dendrites, whether loss functions pertain to the neocortex and what it means to identify as a theoretical neuroscientist.

Podcast host Christy Maver interviews Francisco Webber, CEO and Co-founder of Cortical.io. Cortical.io is a strategic partner of Numenta that specializes in natural language understanding. In this episode, Francisco talks about the spark that started it all for him while watching a YouTube video of our Co-founder, Jeff Hawkins, the advantages of their patented semantic folding methodology over other machine learning, statistical-based approaches, and the many natural language use cases the company addresses.

New to Numenta? Bit of a beginner in brains? Then this episode is for you. In their 20 minute conversation, Numenta On Intelligence Podcast hosts Christy Maver and Matt Taylor break down the top 5 things you need to know about Numenta, including key resources to learn more and how you can get involved.

In this episode, Numenta's Matthew Taylor and Christy Maver introduce the Numenta On Intelligence podcast. Whether you're a scientist, engineer, hobbyist, programmer, or somebody interested in discovering new things about your brain, this podcast is for you! Tune in to the Numenta On Intelligence podcast.

Welcome Tech News Facebook in news again! Google paying to true up employees Sports News March Madness update Tiger is back and so are golf fans Placing Bets Dell Match Play winner Big Topic AI bias This week/day in tech history 3/21/2006 @jack sends the 1st tweet. When did you join? (Gina 7/2007) 3/25/1995 1st wiki created wiki wiki web 3/22/1993 Intel begins shipping the Pentium chip March is Women’s history month! Donna Dubinsky was the co-founder and CEO of Palm (and Handspring and Numenta). Final Word

Jeff Hawkins founded Numenta in 2005, shortly after publishing his best seller "On Intelligence." Numenta's goal is to create a computer model of how the human cortex functions and more importantly advance our theoretical understanding of why it has the structure that it does. In BS 139 Hawkins describes some of his team's latest research and some exciting new ideas. Complete show notes and transcripts are available at http://brainsciencepodcast.com.   Send feed back to brainsciencepodcast@gmail.com or via Speakpipe.

This week, we’ll be featuring a series of shows recorded from Strange Loop, a great developer-focused conference that takes place every year right in my backyard! The conference is a multi-disciplinary melting pot of developers and thinkers across a variety of fields, and we’re happy to be able to bring a bit of it to those of you who couldn’t make it in person! In this episode, I speak with Matthew Taylor, Open Source Manager at Numenta. You might remember hearing a bit about Numenta from an interview I did with Francisco Weber of Cortical.io, for TWiML Talk #10, a show which remains the most popular show on the podcast. Numenta is basically trying to reverse-engineer the neocortex, and use what they learn to develop a neocortical theory for biological and machine intelligence called Hierarchical Temporal Memory. Matt joined me at the conference to discuss his talk “The Biological Path Towards Strong AI”. In our conversation, we discuss the basics of HTM, it’s biological inspiration, and how it differs from traditional neural network models including deep learning. This is a Nerd Alert show, and after you listen I would encourage you to check out the conversation with Francisco which we’ll link to in the show notes. The notes for this show can be found at twimlai.com/talk/71 For series information, visit twimlai.com/stloop

This week I interviewed Celeste Baranski. She's VP of Engineering at Numenta, a company that develops machine intelligence technology.

Donna Dubinsky and Jeff Hawkins — the co-founders of Palm, Handspring and Numenta — talk with Recode's Kara Swisher about their efforts to decode the human brain. They say everything that makes us human, from language to art to engineering, derives from the same learning algorithm, and Numenta hopes to ultimately teach that algorithm to a machine. Dubinsky and Hawkins explain why we shouldn't be afraid that machines will take over the world and why they believe artificial intelligence will drive advancements in technology for the rest of the century. Learn more about your ad choices. Visit megaphone.fm/adchoices

Adam, Derek, Dieter, and Keith discuss the week's news and the Verizon Palm Pre 2. We want you to introduce the PalmCast. Email us an audio introduction to podcast@precentral.net! Thanks to everybody for writing in! News HP Releases webOS 3 Enyo Beta HP webOS developer portal revamped, webOS 3.0 SDK details webOS 3 Enyo tidbits: cross device, cross-platform, PDK, and more webOS 3.0 hacked to boot on Chinese desktop [video] Joe Hayashi leaves HP for Numenta, drinks with old friends Review: Verizon Palm Pre 2 Thanks again to everybody for writing in as well as everybody that participated live in person and in the chat! Credits Thanks to the PreCentral Store for sponsoring the Palmcast. You can email the PalmCast at podcast@treocentral.com or leave us a voicemail at 800-557-6819 x222. Music comes from ccMixter.org, a great Creative Commons music site. Our specific music is the following: "The New Music" by Alex Beroza

Numenta's Jeff Hawkins, a frequent company founder, inventor, and product designer for Palm and Handspring, highlights lessons learned during his tenure in technology. He also confesses that these accomplishments were mere way stations in his 30-year passionate pursuit of neuroscience.

Jeff Hawkins, founder of Palm Computing and director of the Redwood Neuroscience Institute, speaks at Stanford University's Entrepreneurial Thought Leader lecture series.