Podcasts about chief scientist

Eric Roy, the Founder and Chief Scientist of Hydroviv, joins the show to share his journey from wanting to help out with the Flint Water Crisis to creating the water filter that customizes to your home's water. Hear how to study your customers, hire your first employee, make your company acquirable, apply the scientific method to entrepreneurship, and Eric's adventures in Antarctica. Connect with Eric at Hydroviv.com, LinkedIn, and Instagram @EricRoyPhD

Say goodbye to the boring grind and hello to a career that brings out the best in you! Gallup's research has revealed the one thing that has the biggest impact on whether or not your work is fulfilling. Can you guess what it is? (You probably can from the title of this episode…) It's whether or not your strengths fit the role you're in. That's right, the key to unlocking fulfillment in your work lies in fitting your strengths to your career. In this episode, Scott discusses these findings with Dr. Jim Harter, the Chief Scientist of Workplace and Wellbeing at Gallup! What you'll learn  How organizations can create a thriving culture of engaged employees  The research and data-backed knowledge that supports the link between strengths and finding fulfilling work How to have more meaningful conversations with your leader (or your team if you are a leader!)   Have you had the chance to read our new book? “Happen To Your Career: An Unconventional Approach To Career Change and Meaningful Work” is the best place to find all of the most valuable HTYC advice, and it's now available in print, ebook, and on audiobook (hello, podcast listeners!) Visit happentoyourcareer.com/book for more information Want to chat with someone on the team about your situation? Schedule a conversation   Free Resources What career fits you? Join our free 8 Day Mini Course to figure it out!  Career Change Guide - Learn how high-performers discover their ideal career and find meaningful, well-paid work without starting over.   Related Episodes Discover Your Strengths to Find Your Ideal Career (Spotify / Apple Podcasts) Should I Quit My Job? How to Know It's Time (Spotify / Apple Podcasts)    

With the advent of new Artificial Intelligence (AI) tools, where is risk management headed? How are they affected by the changes? Risk management is essential and becoming more so due to increased risk measures, and it's important to understand what's happening in the industry. To that end, today's guest, Tyler Foxworthy, will share his expertise on the subject. Tyler Foxworthy was the Chief Data Scientist at Resultant, then the Chief Scientist at Demand Jump. Before founding his own company, he applied statistics and machine learning to help the medical device industry make informed decisions about changes to their devices. The company that he founded, Vertex was acquired by Greenlight Guru, where Tyler is now the Chief Scientist.Listen to the episode to hear Tyler explain more about data quality, the future of risk assessment, and how Bayesian statistics and analysis come into play.Some of the highlights of this episode include:When can we reach a point where we know the data is accurateThe future of risk assessment for MedTechWhy use a model for predicting riskHow this model impacts a companyThe change in trajectory for the medical device industryMemorable quotes from Tyler Foxworthy:“There is no such thing as absolutely perfect data, there's only degrees of quality.”“I would like to see it as more rigor, in general, brought to the industry.”“This whole field of probabilistic risk assessment is firmly rooted in Bayesian analysis.”“This idea of using, bringing out tools and techniques and knowledge from other domains and fork lifting it into our industry, and making it valuable, to me there's just something really intellectually appealing about that.”Links:Tyler Foxworthy LinkedInEtienne Nichols LinkedInGreenlight Guru AcademyGreenlight Guru

Why is 5G coverage so limited? And can we expand 5G coverage globally? Doug Kirkpatrick, CEO of Eridan, joins Ryan Chacon on the IoT For All Podcast to discuss global 5G coverage with IoT. They cover the current state of 5G, the factors preventing 5G expansion, reducing the environmental impact of 5G, and whether or not 5G can solve certain IoT connectivity challenges. Dr. Doug Kirkpatrick is the CEO and co-founder of Eridan Communications. Dr. Kirkpatrick's professional career includes being DARPA's Chief Scientist (2002 - 2010) and the Vice President of Research and Development at Fusion Lighting (1997 - 2002). He also spent time in venture capital, most notably as a Partner for VantagePoint Venture Partners (2010 - 2013) and a General Partner for InnerProduct Partners (2013 - present). In addition, he founded natural gas packaging company BlackPack Inc. in 2013. Dr. Kirkpatrick graduated with a doctorate in Physics from MIT in 1988. Eridan is a rapidly-growing startup building 5G radios to enable abundant wireless connectivity everywhere in the world. Their MIRACLE transceiver is based on a patent-protected switching architecture that decreases the amount of power required to transmit a gigabit of data by 5-10x.  Discover more about 5G and IoT at https://www.iotforall.com More about Eridan: https://eridan.io Connect with Doug: https://www.linkedin.com/in/doug-kirkpatrick-579332a/ Our sponsor: https://www.avnet-silica.com  Key Questions and Topics from this Episode: (00:00) Welcome to the IoT For All Podcast (00:33) Sponsor (01:06) Introduction to Doug and Eridan (03:38) The current state of 5G (06:17) What is preventing the expansion of 5G coverage? (11:03) Global 5G coverage (15:54) Reducing 5G environmental impact (20:37) Can 5G solve IoT connectivity challenges? (25:50) Learn more and follow up  SUBSCRIBE TO THE CHANNEL: https://bit.ly/2NlcEwm​ Join Our Newsletter: https://www.iotforall.com/iot-newsletter Follow Us on Twitter: https://twitter.com/iotforall Check out the IoT For All Media Network: https://www.iotforall.com/podcast-overview

Discover when Peter Voss (Founder and CEO of AIGO.AI) decided to create a "Chatbot with a Brain", why he was able to lead a team of 400 people, and how he discovered his leadership blind spot (12 minute episode). CEO BLINDSPOTS® PODCAST GUEST: Peter Voss. He is the Founder, CEO, and Chief Scientist of AIGO.AI, an AGI-based Cognitive AI company with the world's first and only Chatbot with a Brain. Aigo AI is used by enterprise customers to deliver hyper-personalized experiences for their customers and employees. Aigo AI is at the forefront of the trend where 'Conversational AI is the new UI'. Peter started out in electronics engineering, but quickly moved into software. After developing a comprehensive ERP software package, Peter took his first software company from a zero to 400-person IPO in seven years. Fueled by the fragile nature of software, Peter embarked on a 20-year journey to study intelligence (how it develops in humans, how to measure it, and current AI efforts), and to replicate it in software. His research culminated in the creation of a natural language intelligence engine that can think, learn, and reason -- and adapt to, and grow with the user. He even coined the term ‘AGI'(Artificial General Intelligence) with fellow luminaries in the space. Peter is a Serial Entrepreneur, Engineer, Inventor and a Pioneer in Artificial Intelligence. For more information about Peter Voss and his company AIGO.ai; https://aigo.ai/how-it-works/ CEO Blindspots® Podcast Host: ⁠⁠Birgit Kamps⁠⁠. Having built an Inc. 500 Fastest Growing Private Company, Birgit has become the world's most trusted bridge builder for getting leadership teams to go further, faster. Since Birgit sold her previous staffing company, she started a leadership consulting company and serves as a Board Member with various companies. In addition, Birgit started and is the host of the CEO Blindspots® Podcast, where leaders learn from other leaders as they share their best practices and blind spots; ⁠⁠https://www.ceoblindspots.com/⁠⁠ To ask questions about this or one of the 200+ other CEO Blindspots® Podcast episodes, send an email to⁠⁠ ⁠birgit@ceoblindspots.com⁠

Power and energy security strategist Emma Stewart is always on the lookout for what's next in the U.S. electric grid, whether that be an influx of renewable energy or cyberattacks by malicious hackers. Her engineering background helps her understand how things work so she can break them to build them again, but stronger. Emma has announced she's joining Idaho National Laboratory as Chief Power Grid Scientist and Research Strategist in the lab's National and Homeland Security Directorate, putting her on the forefront of efforts to keep Americans' electricity networks resilient in the face of cyberthreats. Emma previously worked as Chief Scientist for the National Rural Electric Cooperative Association, which represents the nation's roughly 900 non-profit electric co-ops. Because rural infrastructure can lack the same level of funding or support compared to bigger electric companies, she often had to puzzle over how to fortify distributed resources from nation-state cyberthreats.----------Listen to this episode to hear more about: * How cyber mutual assistance programs can help level the playing field in the fight against adversaries * Emma's cancer survivorship * Takeaways from the S4 industrial cybersecurity conference in Miami Beach, where Emma was a speaker

The Root Cause Medicine Podcast is created by Rupa Health, the best way to order, track & manage results from 30+ lab companies in one place for free. The Root Cause Medicine Podcast is a weekly one-on-one conversation with renowned medical experts, specialists, and pioneers who are influencing the way we look at our health and wellbeing. This week we're joined by Dr. Barrie Tan, Founder and Chief Scientist of American River Nutrition. In this episode, Dr. Barrie Tan educates us on the benefits and misconceptions of vitamin E, specifically tocotrienols. Dr. Barrie Tan is an internationally renowned expert in the field of Vitamin E, with over twenty years of experience in identifying primary sources of plant-based tocotrienols such as rice, palm, and annatto. His extensive research has been focused on the annatto plant, considered the most potent source of tocotrienol. As the editor of two prestigious books on tocotrienol and the founder of the International Tocotrienol Conference, Dr. Tan has earned the title of "Tocotrienol King." He has also served as the Chief Scientific Officer and Scientific Board Member for several multinational organizations. Throughout his career, Dr. Tan has collaborated with esteemed institutions, including the US Armed Forces and a Prince of Thailand. His contribution to the field of Vitamin E has been invaluable, and his expertise has been sought after by many. Key Takeaways: A short history of vitamin E Vitamin E, specifically alpha-tocopherol, was discovered about 100 years ago, being known as a birth vitamin because it can bring a fetus to full term. However, the vitamin's reputation as an antioxidant caused it to be overhyped in the first years after its discovery. In the nineties, a big study was done at Harvard and the VA school, which found that synthetic alpha-tocopherol, the most common form of vitamin E, did not do anything at best, and may cause breast and prostate cancer at worst. Tocotrienols: a powerful form of vitamin E Dr. Barrie Tan stresses that synthetic alpha-tocopherol is a counterfeit version of vitamin E and that it's crucial to consider other natural forms of vitamin E, such as tocotrienols. Studies have shown that tocotrienols offer numerous health benefits and are even more effective than the more commonly known form of vitamin E, tocopherol, in treating chronic conditions and cancer. However, Dr. Tan points out that alpha-tocopherol can interfere with the functions of tocotrienol when present together. Therefore, he advises against taking alpha-tocopherol supplements, except in cases of prenatal care for expectant mothers. This highlights the importance of understanding the different forms of vitamin E and using them correctly to optimize their benefits. Tocotrienols benefits Dr. Tan sheds light on the numerous health benefits of tocotrienol, which is effective in mitigating chronic conditions, reducing inflammation, treating hypercholesterolemia, and improving lipid levels. Additionally, studies suggest that tocotrienol may possess anti-cancer properties. Notably, tocotrienols have demonstrated promising results in pre-diabetic patients by moderately reducing both sugar and lipid levels. Learn more about vitamin E by checking out the key takeaways of this episode or the transcript below. Order tests through Rupa Health - https://www.rupahealth.com/reference-guide

Dr. Jessica Kriegel is the Chief Scientist of Workplace Culture at Culture Partners and an expert in workplace strategy, culture and driving results. Author of Unfairly Labeled: How Your Workplace Can Benefit From Ditching Generational Stereotypes, Jessica recently sold her company The Culture Equation to Culture Partners, where she works with Fortune 100 and other companies using data-driven insights to transform cultures to drive results.

In this episode of Life Science Success, my guest is Gino Martini.  Gino is the CEO of the Precision Health Technologies Accelerator (PHTA Ltd).  Previously, he was the Chief Scientist of the Royal Pharmaceutical Society.    Key Topics Covered:    Description of an accelerator program for health tech companies The importance of social interaction for innovation in a hybrid work environment Excitement for precision medicine and personalized treatment plans Interest in bedside manufacturing and its potential for patient care Challenges in the life sciences industry, such as the lack of lab space and access to skills Opportunities in precision medicine, bedside manufacturing, and the microbiome  

Today's interview is with Ryan McDonald, Chief Scientist at ASAPP. Ryan joins me today to talk about his experience over the last 20 years in the language technology space (AI: NLP, ML, LLMs), recent developments in the generative AI space, the challenges that enterprises face in embracing and leveraging this technology and how ASAPP is advancing AI to augment human activity to address real-world problems for enterprises, particularly in the area of customer care. This interview follows on from my recent interview – Well-being and the changing nature of management and leadership – Interview with Ray Biggs, Head of Customer Care at John Lewis & Waitrose – and is number 464 in the series of interviews with authors and business leaders that are doing great things, providing valuable insights, helping businesses innovate and delivering great service and experience to both their customers and their employees.

Peter Voss is a Pioneer in AI who coined the term ‘Artificial General Intelligence' and the CEO and Chief Scientist at Aigo.ai. For the past 15 years, Voss and his team at Aigo have been perfecting an industry disruptive, highly intelligent and hyper-personalized Chatbot, with a brain, for large enterprise customers. In this episode of the Product Science Podcast, we cover career opportunities in AI development, the potential of AI to be personal and an assistant, and how embracing a future with AI means focusing on critical thinking skills. Read the show notes to learn more: URL: www.h2rproductscience.com/post/the-peter-voss-hypothesis-we-will-soon-need-to-embrace-ai-to-be-effective-in-the-world

In this repeat episode of InTechnology, Camille and Tom get into sustainable computing with Dr. Tamar Eilam, IBM Fellow and Chief Scientist for Sustainable Computing. They talk about the effects of hardware and software on energy efficiency, the current state of sustainable computing in the tech industry, and how AI is being used to create climate change solutions. The views and opinions expressed are those of the guests and author and do not necessarily reflect the official policy or position of Intel Corporation.

Drones have become a ubiquitous part of our society, used by everyday people for fun or as part of their business. The potential of these tools seems limitless but one area that is less discussed is how they can be used by first responders and emergency managers to help keep the public safe. In this episode Addam Jordan and Marina Rozenblat join John Stimpson. To discuss how jurisdiction can successfully implement drones into their public safety and emergency response plans. Guest Biographies Marina Chumakov Rozenblat is the Chief Scientist for CNA's Center for Data Management and Analytics. She is an expert in data management, cybersecurity, uncrewed aircraft systems, and aviation applications of AI and machine learning. Addam Jordan is the Chief Scientist for CNA's Center for Enterprise Systems Modernization. He specializes in new entrants, uncrewed aircraft systems (UAS), artificial intelligence (AI) and cybersecurity. Further Reading Sign up for Marina's workshop here. CNA Spotlight: The Glorious Future of Unmanned Aircraft Systems

“AI gets back to how do I make decisions easier? Giving the right data to the right people at the right time — not perfect by any means, but it's a powerful notion.” Franz Dill is a retired P&G Technologist and independent consultant in AI and analytics. We wanted to tap into Franz's experience and expertise in technology to talk about Artificial Intelligence (AI) - a topic that issuddenly, everything, everywhere, all at once. Franz worked at P&G for 30+ years, where where he served as a Chief Scientist for analytics and as an emergent technologist. He founded P&G groundbreaking contextual innovation centers, established the company's Web 2.0 capabilities, wrote one of the most read blogs in the organization and was also a member of the Cognitive Alliance Analysis Council. Since retiring in 2008, Franz has remained an active consultant in Business Intelligence and Marketing, Retail Innovation, AI, and Business Process Improvement. Franz has also consulted with groups like GE Aviation and as an adjunct professor at Columbia University. Franz has a degree in astrophysics from the University of Pennsylvania, and a Master's in Industrial Mathematics from the University of Florida. With the rapid advancements in AI changing every day, things discussed in this March 2023 conversation may already have moved - but there's a lot of fundamentals in this candid conversation that make sense.

This edition features stories on Airmen from the 2nd and 19th Space Operations Squadrons taking control of the Air Force's newest GPS satellite, the Air Force Research Laboratory partnering with Sony to develop a super computer, neurology residents on Woolford Hall Medical Center on Lackland Air Base scoring amongst the highest of all residency programs in the nation

We hear from HIQA's Chief Scientist, Dr Conor Teljeur.

Chat GPT, Machine Learning, Artificial Intelligence (AI) - all buzz words that are taking over conversations in the tech space and beyond. With hot topics, there tends to be polarizing views and lots of opinions! In this episode, we talk to an expert in AI to help break down the concepts of Chat GPT, Machine Learning and AI in general. Listen in as Zico Kolter, Chief Scientist in AI for Bosch Research and a Professor of Computer Science Dept Carnegie Melon University shares insights on the quickly growing AI space and where we're heading in the future.     

Today's guest, Steve Shell, an accomplished scientist and engineer who is the current Chief Scientist at Heliogen, a California-based clean energy company. With him, we discuss:   

Our special guests are back to share their expertise on how to optimize your sleep and master your biological clock.In this episode, we'll delve into the latest updates and developments of the fantastic app— Time Shifter, designed to help you manage jet lag, shift work, and maintain a stable circadian rhythm. Whether you're a frequent traveler, shift worker, or simply looking to improve the quality of your sleep, tune in! You'll learn practical tips and strategies to improve your sleep and enhance your overall well-being.We'll also share some valuable insights on maintaining a regular light/dark cycle, a crucial factor for a healthy sleep-wake cycle.Take advantage of this incredible opportunity to level up your sleep game. So, say goodbye to feeling groggy and exhausted, and hello to a refreshed and energized you!GUEST BIOMickey Beyer-Clausen is an entrepreneur with a track record of building venture-backed, category-defining companies. In the '90s, Mickey was one of the first to launch Internet businesses, and since 2008, he has pioneered the use of cutting edge science and technology to improve people's lives. Currently, Beyer-Clausen is the Co-founder and CEO of Timeshifter - the world's most advanced circadian technology platform. Timeshifter translates complex circadian science into breakthrough solutions to give people control of their circadian rhythms for the first time. In 2018, Timeshifter launched its first service — now the most-downloaded and highest-rated jet lag app in the world. Recently, Timeshifter launched a new app to help shift workers optimize their sleep, alertness, health, and quality of life. Before Timeshifter, Beyer-Clausen co-founded several other businesses, including Trunk Archive and Ascio Technologies. He is also the Founder and Chairman of Happiness Foundation.Steven W. Lockley, BSc., Ph.D.Dr. Steven Lockley is a Neuroscientist at Brigham and Women's Hospital, an Associate Professor of Medicine in the Division of Sleep Medicine at Harvard Medical School, and Timeshifter's Co-founder and Chief Scientist. Dr. Lockley is also an Adjunct Professor and VC Fellow at the Surrey Sleep Research Centre, University of Surrey in the UK. He received his B.Sc. (Hons) in Biology from the University of Manchester, UK in 1992 and a PhD in Biological Sciences from the University of Surrey, UK in 1997. With nearly 30 years of research experience, he is considered an international authority on circadian rhythms and sleep in humans. In addition to his research, Dr. Lockley works with clients such as NASA Astronauts and Mission Controllers, and Formula 1's elite on managing jet lag, shift work, and peak performance.SHOW NOTES: ⏰ Mickey Beyer-Clausen, co-founder and CEO of the Timeshifter app, discusses the latest app updates and developments.⏰ Dr. Steven Lockley, Associate Professor at Harvard Medical School: Circadian science, biological clock and sleep timing.⏰ What health problems can occur due to disruptions in the biological clock?⏰ The circadian system craves "stability."⏰ What is the major environmental cue that resets our clock each day?⏰ What is non-24 hour sleep-wake disorder?⏰ What external factors affect the biological clock and how do they impact sleep-wake cycles?⏰ In what ways can Time Shifter assist frequent travelers and workers with irregular schedules?⏰ Big brands are increasingly adopting circadian science, and United Airlines has partnered with Time Shifter to offer the app for free to its premium members and at a discount to other members.⏰ What we can learn from the sleep habits of Mickey Beyer-Clausen⏰ What is the biggest game changer for Dr. Steven LockleySPONSOR:Huge shoutout to our sponsor: Biooptimizers!They are my nightly source of magnesium supplementationgo to www.magbreakthrough.com/sleepisaskill for the kind I use every night!GUESTS LINKS: Website: www.timeshifter.comLinkedIn: https://www.linkedin.com/company/timeshifter/Instagram: @timeshifterTwitter: @timeshifterappDISCLAIMER:The information contained on this podcast, our website, newsletter, and the resources available for download are not intended as, and shall not be understood or construed as, medical or health advice. The information contained on these platforms is not a substitute for medical or health advice from a professional who is aware of the facts and circumstances of your individual situation.

International food scientists are urging caution over the safe production of cell-based food, so what does this mean for futuristic food producers here? Growing animal protein directly from cell cultures is developing as a sustainable alternative to conventional meat. However, a World Health Organisation report has identified a list of potential hazards related to lab-based food production, urging attention to the safety of ingredients, including potential allergens, and equipment used which is unique to cell-based food production. The Food Safety Aspects of Cell-based Food report identifies possible hazards in the cell sourcing, production, harvesting and processing stages. Also the dangers inherent in inconsistencies of terminology. Kathryn speaks with Professor of Food Science at the University of Otago, Phil Bremer, who is also Chief Scientist for the New Zealand Food Safety Science Research Centre, where the WHO report is being welcomed as a blueprint for the New Zealand arm of the industry to develop new opportunities in a way that protects Kiwi consumers and our export industry.

The Marketing Institute Ireland recently held the National Digital Conference MII DMX, from brand managers to agencies, from digital specialists to CMO's, the who's-who in marketing returned for the 11th year. For the first time in two years it was held in person and the focus was on the hot topic theme of digital transformation. One of the main speakers was Dr Michael Wu a high-profile speaker on AI technology. Ronan attended this years DMX and got to talk to Dr Michael Wu. Dr Wu talks about the brief evolution of business intelligence, the definition of AI, the misconception of AI, the growth of AI adoption, AI bias and more. More about Dr. Michael Wu: Dr. Michael Wu is one of the world's premier authorities on artificial intelligence (AI), machine learning (ML), data science, and behavioural economics. He's currently the Chief AI Strategist at PROS (NYSE: PRO), an AI-powered SaaS provider that helps companies monetise more efficiently in the digital economy. He's been appointed as a Senior Research Fellow at the Ecole des Ponts Business School for his work in Data Science, and he serves as an advisor and a lecturer for UC Berkeley Extension's AI programs. Prior to PROS, Dr Wu was the Chief Scientist at Lithium for a decade, where he focuses on developing predictive and prescriptive algorithms to extract insights from social media big data. His research spans many areas, including customer experience, CRM, online influence, gamification, digital transformation, AI, etc. His R&D won him the recognition as an Influential Leader by CRM Magazine along with Mark Zuckerberg, Marc Benioff and other industry giants. Dr Wu has served as a DOE fellow at the Los Alamos National Lab conducting research in face recognition and was awarded 4 years of full fellowship under the Computational Science Graduate Fellowship. Prior to industry, Dr Wu received his triple major undergraduate degree in Applied Math, Physics, and Molecular & Cell Biology; and his Ph.D. from UC Berkeley's Biophysics program, where he uses machine learning to model visual processing within the human brain. Dr Wu believes in knowledge dissemination, and speaks internationally at universities, conferences, and enterprises. His insights have inspired many global enterprises and are made accessible through “The Science of Social,” and “The Science of Social 2”—two easy-reading e-books.

In this podcast episode, the host engages in a conversation with Dr. Bill Rivers, a highly respected advocate for language access and diversity. Dr. Rivers shares his extensive background and sheds light on the importance of acculturation over assimilation, the negative effects of shaming students for speaking their home language, and the challenges faced by language access providers due to insufficient funding. Additionally, he highlights the numerous benefits of being bilingual and emphasizes the need for healthcare providers to prioritize language services. This discussion serves as a powerful reminder of the significance of linguistic diversity in the United States and the ongoing efforts required to ensure language access for all. Tune in to this thought-provoking and informative episode.Dr. Rivers has more than 30 years' experience in language advocacy and capacity at the national level, with significant experience in culture and language for economic development and national security. He is the immediate past and founding Chair of ASTM Technical Committee F43, Language Services and Products. Dr. Rivers serves as a member of the America's Languages Working Group of the American Academy of Arts and Sciences, and is an honorary lifetime member of the Association of Language Companies.  Before establishing WP Rivers & Associates, he served for eight years as the Executive Director of the Joint National Committee for Languages – National Council for Languages and International Studies, leaving a legacy of significant legislative and policy accomplishments.  Prior to his service at JNCL-NCLIS, he served as Chief Scientist at Integrated Training Solutions, Inc., a defense contractor in Research Triangle Park, North Carolina, and Arlington, Virginia. While at ITS, he served in a contractor role as the founding Chief Linguist of the National Language Service Corps, a field activity of the OUSD(P/R), with oversight of all language issues in the NLSC. Prior to working at ITS, he was a founding member of the Center for Advanced Study of Language (CASL) at the University of Maryland, the Nation's first Federally-funded research center for language, cognition, and national security. While at CASL, Dr. Rivers led R&D work at DLIFLC. During his career, Dr. Rivers has also taught Russian (beginning through advanced), graduate courses in research methods, language policy, and second language acquisition at the and worked as a freelance interpreter and translator (EnglishRussian). He received his PhD in Russian from Bryn Mawr College and his MA (Russian Linguistics), BA (Russian) and BS (Aerospace Engineering) from the University of Maryland. He speaks Russian and French at the C1 level, and Irish, German, and Spanish at the B1 level. Only on the podcast that shares your stories about our profession. Brand the Interpreter! Thanks for tuning in, till next time!

Ai-RGUS' CEO and Chief Scientist, Dr. Daniel Reichman, joins Coruzant Technologies for the Digital Executive podcast. He shares the keys to his success by being curious and always asking how can he learn more about a subject or validate that it is true. Today, Daniel runs his AI company that improves the video surveillance for cameras across the country, using Artificial Intelligence.

Andy is joined by Physicist, Chief Scientist & Principal Investigator on Skinwalker Ranch, Erik Bard, they discuss;Erik working with Brandon FugalHis first experience on the RanchStandout moments of his time thereWhat COULD be the explanation(s)What experiment he would like to do on the Ranchand much, much moreThe Secret of Skinwalker Ranch Season 4 Premieres on History April 18th, 10/9cSpotify listeners can now access premium content here > https://open.spotify.com/show/7wnXUAQ3vwdsX1BoyaEvjZSign up to support the podcast via Patreon.com/ThatUFOPodcast or Apple Podcast subscriptions (2 week free trial available)Please support the show sponsors;BlendJet2; Go to blendjet.com and use code thatufo12 to save 12% off your order OR use my special link and the discount will be applied at checkout zen.ai/thatufo12Wongo Puzzles; Use my special link zen.ai/thatufo10 to save 10% at wongopuzzles.com. The discount will be applied at checkout!Try Cure today and feel the difference for yourself! Use my special link zen.ai/ufopod20 for 20% off your order, coupon activated at checkout!Laird: Are you ready to feel more energized, focused, and supported? Go to zen.ai/thatufopod15 and add nourishing, plant-based foods to fuel you from sunrise to sunset.You can also sign up to Zencastr with 40% off for 3 months with promo code: ufopodcast at https://zencastr.com/pricing?coupon=ufopodcast&fpr=7ooh0 . Start recording your own podcast or meetings today!Buy the official podcast map/guide to UK UFO sightings here; https://www.herblester.com/products/the-skies-aboveGet in touch with the show;Twitter: @UFOUAPAMFacebook, YouTube & Instagram: "That UFO Podcast"YouTube: YouTube.com/c/ThatUFOPodcastEmail: UFOUAPAM@gmail.comAll podcast links & associated links;Linktr.ee/ufouapamThatUFOPodcast.comLinktr.ee/TheZignalUAPMedia.UKhttps://twitter.com/AnomalousPodNetDon't forget to subscribe, like and leave a review of the showEnjoy folks,Andy

This week on Pharm5: Cost Plus Drug Co. adds Invokana products Gohibic (vilobelimab) EUA for COVID-19 Makena (hydroxyprogesterone caproate injection) withdrawn from market APL treatment oral tretinoin shortage Federal judge strikes down ACA's OCP and PrEP coverage     Connect with us! Listen to our podcast: Pharm5 Follow us on Twitter: @LizHearnPharmD   References: Mark Cuban CostPlus Drug Company - Medications. http://bit.ly/3KjKYS5. Accessed April 6, 2023. Invokana® (canagliflozin) affordability. Janssen CarePath for Healthcare Professionals. http://bit.ly/3nWANLm. Published October 18, 2022. Accessed April 6, 2023. Center for Drug Evaluation and Research. FDA authorizes Gohibic (vilobelimab) injection. U.S. Food and Drug Administration. http://bit.ly/3nWDsVm. Published April 4, 2023. Accessed April 6, 2023. Gohibic [highlights of emergency use authorization]. Jena, Germany: InflaRx GmbH. Published April 2023. Accessed April 6, 2023. FDA Commissioner and Chief Scientist announce decision to withdraw approval of Makena. U.S. Food and Drug Administration. http://bit.ly/3ZMOY35. Published April 6, 2023. Accessed April 6, 2023. Drug shortage detail: Tretinoin capsules. ASHP. https://bit.ly/3KhQ2pT. Published March 20, 2023. Accessed April 6, 2023. Treatment of acute promyelocytic leukemia (APL). American Cancer Society. http://bit.ly/3mb3Nif. Accessed April 6, 2023. Cingam SR, Koshy NV. Acute Promyelocytic Leukemia. National Center for Biotechnology Information. http://bit.ly/3nGw5RV. Accessed April 6, 2023. Phillips C. Help Desk for Oncologists Treating People with a Rare Leukemia Pays Big Dividends. National Cancer Institute. http://bit.ly/40EtxT3. Published February 2, 2023. Accessed April 6, 2023. Braidwood Management, Inc., et al. v. Xavier Becerra, et al. Civil Action No. 4:20-cv-00283-O. Supreme Court of Texas, 2022. Accessed April 6, 2023. Judge strikes down Obamacare provisions requiring insurers cover some preventive care services. NBCNews.com. https://bit.ly/3MncZKV. Published March 30, 2023. Accessed April 6, 2023. Burwell v. Hobby Lobby and birth control. Planned Parenthood Action Fund. http://bit.ly/419fPaq. Accessed April 6, 2023. Stolberg SG, Abelson R. Federal judge strikes down Obamacare requirement for free preventive care. The New York Times. http://bit.ly/3nSSAU1. Published March 30, 2023. Accessed April 6, 2023.

Jessica Kriegel is a Workplace Culture Expert, the creator of The Culture Equation, and Chief Scientist of Workplace Culture at Culture Partners. Jessica knows that culture drives results, and through her tried and tested tools and strategies, she empowers leaders to improve employee fulfillment and increase performance and profitability. As a culture change specialist, Jessica is a sought-after keynote speaker and the author of Unfairly Labeled: How Your Workplace Can Benefit from Ditching Generational Stereotypes and Proving the Value of Soft Skills: Measuring Impact and Calculating ROI.In this episode, you'll hear from Jessica on:(00:09:20) Love-based leadership. According to Jessica, fear is our worst enemy when it comes to creating a healthy workplace culture. Instead, she advises CEOs to lead from the heart and concentrate on building a sense of loyalty and trust that improves performance and productivity.(00:21:06) The Culture Equation. Jessica sets out the basis of her Culture Equation model, where purpose and strategy combine with organizational culture to deliver consistent results. Plus, she points out that a company's key outcomes must be meaningful, measurable, and memorable so everyone knows what they are and if they're on course to achieving them.(00:32:53) Scaling culture. She explains how to build a more successful company culture by focusing on results and creating intentional employee experiences through a combination of culture management tools, such as feedback, employee recognition, and storytelling.(00:34:17) Saudi Arabia Vision 2030. We talk about Jessica's recent visit to Saudi Arabia and the country's efforts to create greater economic diversity and achieve gender equality for women and girls.(00:41:07) Accountability. Jessica stresses the importance of identifying problems, acknowledging shortcomings, and engaging in ‘above the line' thinking that concentrates on solving the problem rather than allocating blame.  

Friend of the pod, enemy of the state, and special Deep Dive husband Paul Scheer joins to sub-in for Jessica St Clair. Paul addresses his show ally-ship and key issues plaguing their household. Then, Chief Scientist of Oceana Katie Matthews joins June to discuss how important and powerful the Ocean is to our ecosystem, why stopping offshore drilling is so important and how to be active participants of Planet Ocean. And Deep Divers remember, sometimes you're the June and other times you're the Jessica, but Jessica will always remain Jessica.Visit Oceana.org to be an ocean wave maker and get updates on policy updates.Follow @oceana on twitter and InstagramDeep Dive Merch https://kinshipgoods.com/collections/deep-diveJune's new Amazon Store https://www.amazon.com/shop/junedianeJessica's Amazon Store https://www.amazon.com/shop/StclairjessicaYou can follow The Deep Dive on Twitter @thedeepdivepodJune Diane Raphael @MsJuneDiane on Twitter @junediane on InstagramJessica St. Clair @Jessica_StClair on Twitter @stclairjessica on InstagramCheck out the Jane Club at www.janeclub.comSend us your questions to thedeepdive@earwolf.com

Today's episode is a bonus episode from our podcast 0xResearch, produced by the Blockworks Research team. This is one of my favorite episodes they've done, a deep dive into the future of rollups, scaling and zk-tech. The first 15 minutes is the "analyst bullpen" segment on Arbitrum's recent governance debacle, followed by an interview with Preston Evans from Sovereign Labs (use the Timestamps if you want to skip ahead). If you enjoy this episode, follow the link in the show notes below to subscribe! - - Join us on 0xResearch as we interview Preston Evans, the Chief Scientist of Sovereign Labs. Why should you care about Sovereign? Because they're building the Sovereign SDK. Like the Cosmos SDK that enables modular plug-and-play experimentation for L1s, the Sovereign SDK is a modular toolkit for building zk-rollups on any chain with seamless composability. In this episode, we discuss how Sovereign's design compares to the Cosmos SDK and IBC, smart contract vs Sovereign rollups, the role of data availability, decentralized sequencer design and more! This is my favorite 0xResearch episode yet. And as usual, we start the episode with our analyst bullpen to discuss the recent governance drama at Arbitrum! - - Timestamps: (00:00) Introduction (00:45) Arbitrum's Governance Blunder (15:04) Blockworks Research (16:03) Interview Start: What is Sovereign? (22:23) The Sovereign SDK vs Cosmos SDK (23:59) Settlement on Smart Contract vs Sovereign Rollups (28:14) The Role of Data Availability (32:24) Decentralized Sequencers (37:54) Optimistic Rollup Tradeoffs (41:24) Composability and IBC (52:22) What Is Sovereign's X Factor? (54:17) Building Rollups on Bitcoin (59:11) Sovereign's Business Model and Timeline - - Follow Preston: https://twitter.com/prestonevans__ Follow Westie: https://twitter.com/WestieCapital Follow Dan: https://twitter.com/smyyguy Follow Sam: https://twitter.com/swmartin19 Follow Purplepill: https://twitter.com/purplepill3m Follow Matt: https://twitter.com/MattFiebach Follow Blockworks Research: https://twitter.com/blockworksres Subscribe on YouTube: https://bit.ly/3foDS38 Subscribe on Apple: https://apple.co/3SNhUEt Subscribe on Spotify: https://spoti.fi/3NlP1hA Get top market insights and the latest in crypto news. Subscribe to Blockworks Daily Newsletter: https://blockworks.co/newsletter/ - - Resources: Delegate ARB to Blockworks Research https://twitter.com/blockworksres/status/1639279479368368132 Sovereign Labs https://www.sovereign.xyz/ https://twitter.com/sovereign_labs - - Check out Blockworks Research today! Research, data, governance, tokenomics, and models – now, all in one place Blockworks Research: https://www.blockworksresearch.com/ Free Daily Newsletter: https://blockworks.co/newsletter - - Disclaimer: Nothing said on 0xResearch is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only, and any views expressed by anyone on the show are solely our opinions, not financial advice. Dan, Sam, and our guests may hold positions in the companies, funds, or projects discussed.

Glassdoor found that 77% of job seekers consider a company's culture before applying for a job, and 56% of employees say that company culture is more important than salary when it comes to job satisfaction. Needless to say, having a workplace culture that is positive, creative, and safe is of the utmost importance. Jessica Kriegel, Chief Scientist of Workplace Culture for Culture Partners shares the do's and don'ts of getting company culture right. Plus, what radical honestly really looks like in a job Interview and a winning formula for delivering constructive feedback to your team.   RESOURCES: To connect with Jessica Kriegel click here To follow Culture Partners click here To connect with Jaclyn Johnson click here To follow along with Create & Cultivate click here To submit your questions call the WorkParty Hotline: 1-(833)-57-PARTY (577-2789)   SPONSORS: Culture Partners This episode may contain paid endorsements and advertisements for products and services. Individuals on the show may have a direct, or indirect financial interest in products, or services referred to in this episode. Visit culture.io/resources to sign up for my newsletter and receive regular culture insights   Produced by Dear Media

Jonathan Frankle, Chief Scientist at MosaicML and Assistant Professor of Computer Science at Harvard University, joins us on this episode. With comprehensive infrastructure and software tools, MosaicML aims to help businesses train complex machine-learning models using their own proprietary data.We discuss:- Details of Jonathan's Ph.D. dissertation which explores his “Lottery Ticket Hypothesis.”- The role of neural network pruning and how it impacts the performance of ML models.- Why transformers will be the go-to way to train NLP models for the foreseeable future.- Why the process of speeding up neural net learning is both scientific and artisanal. - What MosiacML does, and how it approaches working with clients.- The challenges for developing AGI.- Details around ML training policy and ethics.- Why data brings the magic to customized ML models.- The many use cases for companies looking to build customized AI models.Jonathan Frankle - https://www.linkedin.com/in/jfrankle/Resources:- https://mosaicml.com/- The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural NetworksThanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation.#OCR #DeepLearning #AI #Modeling #ML

I went over to the OpenAI offices in San Fransisco to ask the Chief Scientist and cofounder of OpenAI, Ilya Sutskever, about:* time to AGI* leaks and spies* what's after generative models* post AGI futures* working with Microsoft and competing with Google* difficulty of aligning superhuman AIWatch on YouTube. Listen on Apple Podcasts, Spotify, or any other podcast platform. Read the full transcript here. Follow me on Twitter for updates on future episodes.As always, the most helpful thing you can do is just to share the podcast - send it to friends, group chats, Twitter, Reddit, forums, and wherever else men and women of fine taste congregate.If you have the means and have enjoyed my podcast, I would appreciate your support via a paid subscriptions on Substack.Timestamps(00:00) - Time to AGI(05:57) - What's after generative models?(10:57) - Data, models, and research(15:27) - Alignment(20:53) - Post AGI Future(26:56) - New ideas are overrated(36:22) - Is progress inevitable?(41:27) - Future BreakthroughsTranscriptTime to AGIDwarkesh Patel  Today I have the pleasure of interviewing Ilya Sutskever, who is the Co-founder and Chief Scientist of OpenAI. Ilya, welcome to The Lunar Society.Ilya Sutskever  Thank you, happy to be here.Dwarkesh Patel  First question and no humility allowed. There are not that many scientists who will make a big breakthrough in their field, there are far fewer scientists who will make multiple independent breakthroughs that define their field throughout their career, what is the difference? What distinguishes you from other researchers? Why have you been able to make multiple breakthroughs in your field?Ilya Sutskever  Thank you for the kind words. It's hard to answer that question. I try really hard, I give it everything I've got and that has worked so far. I think that's all there is to it. Dwarkesh Patel  Got it. What's the explanation for why there aren't more illicit uses of GPT? Why aren't more foreign governments using it to spread propaganda or scam grandmothers?Ilya Sutskever  Maybe they haven't really gotten to do it a lot. But it also wouldn't surprise me if some of it was going on right now. I can certainly imagine they would be taking some of the open source models and trying to use them for that purpose. For sure I would expect this to be something they'd be interested in the future.Dwarkesh Patel  It's technically possible they just haven't thought about it enough?Ilya Sutskever  Or haven't done it at scale using their technology. Or maybe it is happening, which is annoying. Dwarkesh Patel  Would you be able to track it if it was happening? Ilya Sutskever I think large-scale tracking is possible, yes. It requires special operations but it's possible.Dwarkesh Patel  Now there's some window in which AI is very economically valuable, let's say on the scale of airplanes, but we haven't reached AGI yet. How big is that window?Ilya Sutskever  It's hard to give a precise answer and it's definitely going to be a good multi-year window. It's also a question of definition. Because AI, before it becomes AGI, is going to be increasingly more valuable year after year in an exponential way. In hindsight, it may feel like there was only one year or two years because those two years were larger than the previous years. But I would say that already, last year, there has been a fair amount of economic value produced by AI. Next year is going to be larger and larger after that. So I think it's going to be a good multi-year chunk of time where that's going to be true, from now till AGI pretty much. Dwarkesh Patel  Okay. Because I'm curious if there's a startup that's using your model, at some point if you have AGI there's only one business in the world, it's OpenAI. How much window does any business have where they're actually producing something that AGI can't produce?Ilya Sutskever  It's the same question as asking how long until AGI. It's a hard question to answer. I hesitate to give you a number. Also because there is this effect where optimistic people who are working on the technology tend to underestimate the time it takes to get there. But the way I ground myself is by thinking about the self-driving car. In particular, there is an analogy where if you look at the size of a Tesla, and if you look at its self-driving behavior, it looks like it does everything. But it's also clear that there is still a long way to go in terms of reliability. And we might be in a similar place with respect to our models where it also looks like we can do everything, and at the same time, we will need to do some more work until we really iron out all the issues and make it really good and really reliable and robust and well behaved.Dwarkesh Patel  By 2030, what percent of GDP is AI? Ilya Sutskever  Oh gosh, very hard to answer that question.Dwarkesh Patel Give me an over-under. Ilya Sutskever The problem is that my error bars are in log scale. I could imagine a huge percentage, I could imagine a really disappointing small percentage at the same time. Dwarkesh Patel  Okay, so let's take the counterfactual where it is a small percentage. Let's say it's 2030 and not that much economic value has been created by these LLMs. As unlikely as you think this might be, what would be your best explanation right now of why something like this might happen?Ilya Sutskever  I really don't think that's a likely possibility, that's the preface to the comment. But if I were to take the premise of your question, why were things disappointing in terms of real-world impact? My answer would be reliability. If it somehow ends up being the case that you really want them to be reliable and they ended up not being reliable, or if reliability turned out to be harder than we expect. I really don't think that will be the case. But if I had to pick one and you were telling me — hey, why didn't things work out? It would be reliability. That you still have to look over the answers and double-check everything. That just really puts a damper on the economic value that can be produced by those systems.Dwarkesh Patel  Got it. They will be technologically mature, it's just the question of whether they'll be reliable enough.Ilya Sutskever  Well, in some sense, not reliable means not technologically mature.What's after generative models?Dwarkesh Patel  Yeah, fair enough. What's after generative models? Before, you were working on reinforcement learning. Is this basically it? Is this the paradigm that gets us to AGI? Or is there something after this?Ilya Sutskever  I think this paradigm is gonna go really, really far and I would not underestimate it. It's quite likely that this exact paradigm is not quite going to be the AGI form factor. I hesitate to say precisely what the next paradigm will be but it will probably involve integration of all the different ideas that came in the past.Dwarkesh Patel  Is there some specific one you're referring to?Ilya Sutskever  It's hard to be specific.Dwarkesh Patel  So you could argue that next-token prediction can only help us match human performance and maybe not surpass it? What would it take to surpass human performance?Ilya Sutskever  I challenge the claim that next-token prediction cannot surpass human performance. On the surface, it looks like it cannot. It looks like if you just learn to imitate, to predict what people do, it means that you can only copy people. But here is a counter argument for why it might not be quite so. If your base neural net is smart enough, you just ask it — What would a person with great insight, wisdom, and capability do? Maybe such a person doesn't exist, but there's a pretty good chance that the neural net will be able to extrapolate how such a person would behave. Do you see what I mean?Dwarkesh Patel  Yes, although where would it get that sort of insight about what that person would do? If not from…Ilya Sutskever  From the data of regular people. Because if you think about it, what does it mean to predict the next token well enough? It's actually a much deeper question than it seems. Predicting the next token well means that you understand the underlying reality that led to the creation of that token. It's not statistics. Like it is statistics but what is statistics? In order to understand those statistics to compress them, you need to understand what is it about the world that creates this set of statistics? And so then you say — Well, I have all those people. What is it about people that creates their behaviors? Well they have thoughts and their feelings, and they have ideas, and they do things in certain ways. All of those could be deduced from next-token prediction. And I'd argue that this should make it possible, not indefinitely but to a pretty decent degree to say — Well, can you guess what you'd do if you took a person with this characteristic and that characteristic? Like such a person doesn't exist but because you're so good at predicting the next token, you should still be able to guess what that person who would do. This hypothetical, imaginary person with far greater mental ability than the rest of us.Dwarkesh Patel  When we're doing reinforcement learning on these models, how long before most of the data for the reinforcement learning is coming from AI and not humans?Ilya Sutskever  Already most of the default enforcement learning is coming from AIs. The humans are being used to train the reward function. But then the reward function and its interaction with the model is automatic and all the data that's generated during the process of reinforcement learning is created by AI. If you look at the current technique/paradigm, which is getting some significant attention because of chatGPT, Reinforcement Learning from Human Feedback (RLHF). The human feedback has been used to train the reward function and then the reward function is being used to create the data which trains the model.Dwarkesh Patel  Got it. And is there any hope of just removing a human from the loop and have it improve itself in some sort of AlphaGo way?Ilya Sutskever  Yeah, definitely. The thing you really want is for the human teachers that teach the AI to collaborate with an AI. You might want to think of it as being in a world where the human teachers do 1% of the work and the AI does 99% of the work. You don't want it to be 100% AI. But you do want it to be a human-machine collaboration, which teaches the next machine.Dwarkesh Patel  I've had a chance to play around these models and they seem bad at multi-step reasoning. While they have been getting better, what does it take to really surpass that barrier?Ilya Sutskever  I think dedicated training will get us there. More and more improvements to the base models will get us there. But fundamentally I also don't feel like they're that bad at multi-step reasoning. I actually think that they are bad at mental multistep reasoning when they are not allowed to think out loud. But when they are allowed to think out loud, they're quite good. And I expect this to improve significantly, both with better models and with special training.Data, models, and researchDwarkesh Patel  Are you running out of reasoning tokens on the internet? Are there enough of them?Ilya Sutskever  So for context on this question, there are claims that at some point we will run out of tokens, in general, to train those models. And yeah, I think this will happen one day and by the time that happens, we need to have other ways of training models, other ways of productively improving their capabilities and sharpening their behavior, making sure they're doing exactly, precisely what you want, without more data.Dwarkesh Patel You haven't run out of data yet? There's more? Ilya Sutskever Yeah, I would say the data situation is still quite good. There's still lots to go. But at some point the data will run out.Dwarkesh Patel  What is the most valuable source of data? Is it Reddit, Twitter, books? Where would you train many other tokens of other varieties for?Ilya Sutskever  Generally speaking, you'd like tokens which are speaking about smarter things, tokens which are more interesting. All the sources which you mentioned are valuable.Dwarkesh Patel  So maybe not Twitter. But do we need to go multimodal to get more tokens? Or do we still have enough text tokens left?Ilya Sutskever  I think that you can still go very far in text only but going multimodal seems like a very fruitful direction.Dwarkesh Patel  If you're comfortable talking about this, where is the place where we haven't scraped the tokens yet?Ilya Sutskever  Obviously I can't answer that question for us but I'm sure that for everyone there is a different answer to that question.Dwarkesh Patel  How many orders of magnitude improvement can we get, not from scale or not from data, but just from algorithmic improvements? Ilya Sutskever  Hard to answer but I'm sure there is some.Dwarkesh Patel  Is some a lot or some a little?Ilya Sutskever  There's only one way to find out.Dwarkesh Patel  Okay. Let me get your quickfire opinions about these different research directions. Retrieval transformers. So it's just somehow storing the data outside of the model itself and retrieving it somehow.Ilya Sutskever  Seems promising. Dwarkesh Patel But do you see that as a path forward?Ilya Sutskever  It seems promising.Dwarkesh Patel  Robotics. Was it the right step for Open AI to leave that behind?Ilya Sutskever  Yeah, it was. Back then it really wasn't possible to continue working in robotics because there was so little data. Back then if you wanted to work on robotics, you needed to become a robotics company. You needed to have a really giant group of people working on building robots and maintaining them. And even then, if you're gonna have 100 robots, it's a giant operation already, but you're not going to get that much data. So in a world where most of the progress comes from the combination of compute and data, there was no path to data on robotics. So back in the day, when we made a decision to stop working in robotics, there was no path forward. Dwarkesh Patel Is there one now? Ilya Sutskever  I'd say that now it is possible to create a path forward. But one needs to really commit to the task of robotics. You really need to say — I'm going to build many thousands, tens of thousands, hundreds of thousands of robots, and somehow collect data from them and find a gradual path where the robots are doing something slightly more useful. And then the data that is obtained and used to train the models, and they do something that's slightly more useful. You could imagine it's this gradual path of improvement, where you build more robots, they do more things, you collect more data, and so on. But you really need to be committed to this path. If you say, I want to make robotics happen, that's what you need to do. I believe that there are companies who are doing exactly that. But you need to really love robots and need to be really willing to solve all the physical and logistical problems of dealing with them. It's not the same as software at all. I think one could make progress in robotics today, with enough motivation.Dwarkesh Patel  What ideas are you excited to try but you can't because they don't work well on current hardware?Ilya Sutskever  I don't think current hardware is a limitation. It's just not the case.Dwarkesh Patel  Got it. But anything you want to try you can just spin it up? Ilya Sutskever  Of course. You might wish that current hardware was cheaper or maybe it would be better if it had higher memory processing bandwidth let's say. But by and large hardware is just not an issue.AlignmentDwarkesh Patel  Let's talk about alignment. Do you think we'll ever have a mathematical definition of alignment?Ilya Sutskever  A mathematical definition is unlikely. Rather than achieving one mathematical definition, I think we will achieve multiple definitions that look at alignment from different aspects. And that this is how we will get the assurance that we want. By which I mean you can look at the behavior in various tests, congruence, in various adversarial stress situations, you can look at how the neural net operates from the inside. You have to look at several of these factors at the same time.Dwarkesh Patel  And how sure do you have to be before you release a model in the wild? 100%? 95%?Ilya Sutskever  Depends on how capable the model is. The more capable the model, the more confident we need to be. Dwarkesh Patel Alright, so let's say it's something that's almost AGI. Where is AGI?Ilya Sutskever Depends on what your AGI can do. Keep in mind that AGI is an ambiguous term. Your average college undergrad is an AGI, right? There's significant ambiguity in terms of what is meant by AGI. Depending on where you put this mark you need to be more or less confident.Dwarkesh Patel  You mentioned a few of the paths toward alignment earlier, what is the one you think is most promising at this point?Ilya Sutskever  I think that it will be a combination. I really think that you will not want to have just one approach. People want to have a combination of approaches. Where you spend a lot of compute adversarially to find any mismatch between the behavior you want it to teach and the behavior that it exhibits.We look into the neural net using another neural net to understand how it operates on the inside. All of them will be necessary. Every approach like this reduces the probability of misalignment. And you also want to be in a world where your degree of alignment keeps increasing faster than the capability of the models.Dwarkesh Patel  Do you think that the approaches we've taken to understand the model today will be applicable to the actual super-powerful models? Or how applicable will they be? Is it the same kind of thing that will work on them as well or? Ilya Sutskever  It's not guaranteed. I would say that right now, our understanding of our models is still quite rudimentary. We've made some progress but much more progress is possible. And so I would expect that ultimately, the thing that will really succeed is when we will have a small neural net that is well understood that's been given the task to study the behavior of a large neural net that is not understood, to verify. Dwarkesh Patel  By what point is most of the AI research being done by AI?Ilya Sutskever  Today when you use Copilot, how do you divide it up? So I expect at some point you ask your descendant of ChatGPT, you say — Hey, I'm thinking about this and this. Can you suggest fruitful ideas I should try? And you would actually get fruitful ideas. I don't think that's gonna make it possible for you to solve problems you couldn't solve before.Dwarkesh Patel  Got it. But it's somehow just telling the humans giving them ideas faster or something. It's not itself interacting with the research?Ilya Sutskever  That was one example. You could slice it in a variety of ways. But the bottleneck there is good ideas, good insights and that's something that the neural nets could help us with.Dwarkesh Patel  If you're designing a billion-dollar prize for some sort of alignment research result or product, what is the concrete criterion you would set for that billion-dollar prize? Is there something that makes sense for such a prize?Ilya Sutskever  It's funny that you asked, I was actually thinking about this exact question. I haven't come up with the exact criterion yet. Maybe a prize where we could say that two years later, or three years or five years later, we look back and say like that was the main result. So rather than say that there is a prize committee that decides right away, you wait for five years and then award it retroactively.Dwarkesh Patel  But there's no concrete thing we can identify as you solve this particular problem and you've made a lot of progress?Ilya Sutskever  A lot of progress, yes. I wouldn't say that this would be the full thing.Dwarkesh Patel  Do you think end-to-end training is the right architecture for bigger and bigger models? Or do we need better ways of just connecting things together?Ilya Sutskever  End-to-end training is very promising. Connecting things together is very promising. Dwarkesh Patel  Everything is promising.Dwarkesh Patel  So Open AI is projecting revenues of a billion dollars in 2024. That might very well be correct but I'm just curious, when you're talking about a new general-purpose technology, how do you estimate how big a windfall it'll be? Why that particular number? Ilya Sutskever  We've had a product for quite a while now, back from the GPT-3 days, from two years ago through the API and we've seen how it grew. We've seen how the response to DALL-E has grown as well and you see how the response to ChatGPT is, and all of this gives us information that allows us to make relatively sensible extrapolations of anything. Maybe that would be one answer. You need to have data, you can't come up with those things out of thin air because otherwise, your error bars are going to be like 100x in each direction.Dwarkesh Patel  But most exponentials don't stay exponential especially when they get into bigger and bigger quantities, right? So how do you determine in this case?Ilya Sutskever  Would you bet against AI?Post AGI futureDwarkesh Patel  Not after talking with you. Let's talk about what a post-AGI future looks like. I'm guessing you're working 80-hour weeks towards this grand goal that you're really obsessed with. Are you going to be satisfied in a world where you're basically living in an AI retirement home? What are you personally doing after AGI comes?Ilya Sutskever  The question of what I'll be doing or what people will be doing after AGI comes is a very tricky question. Where will people find meaning? But I think that that's something that AI could help us with. One thing I imagine is that we will be able to become more enlightened because we interact with an AGI which will help us see the world more correctly, and become better on the inside as a result of interacting. Imagine talking to the best meditation teacher in history, that will be a helpful thing. But I also think that because the world will change a lot, it will be very hard for people to understand what is happening precisely and how to really contribute. One thing that I think some people will choose to do is to become part AI. In order to really expand their minds and understanding and to really be able to solve the hardest problems that society will face then.Dwarkesh Patel  Are you going to become part AI?Ilya Sutskever  It is very tempting. Dwarkesh Patel  Do you think there'll be physically embodied humans in the year 3000? Ilya Sutskever  3000? How do I know what's gonna happen in 3000?Dwarkesh Patel  Like what does it look like? Are there still humans walking around on Earth? Or have you guys thought concretely about what you actually want this world to look like? Ilya Sutskever  Let me describe to you what I think is not quite right about the question. It implies we get to decide how we want the world to look like. I don't think that picture is correct. Change is the only constant. And so of course, even after AGI is built, it doesn't mean that the world will be static. The world will continue to change, the world will continue to evolve. And it will go through all kinds of transformations. I don't think anyone has any idea of how the world will look like in 3000. But I do hope that there will be a lot of descendants of human beings who will live happy, fulfilled lives where they're free to do as they see fit. Or they are the ones who are solving their own problems. One world which I would find very unexciting is one where we build this powerful tool, and then the government said — Okay, so the AGI said that society should be run in such a way and now we should run society in such a way. I'd much rather have a world where people are still free to make their own mistakes and suffer their consequences and gradually evolve morally and progress forward on their own, with the AGI providing more like a base safety net.Dwarkesh Patel  How much time do you spend thinking about these kinds of things versus just doing the research?Ilya Sutskever  I do think about those things a fair bit. They are very interesting questions.Dwarkesh Patel  The capabilities we have today, in what ways have they surpassed where we expected them to be in 2015? And in what ways are they still not where you'd expected them to be by this point?Ilya Sutskever  In fairness, it's sort of what I expected in 2015. In 2015, my thinking was a lot more — I just don't want to bet against deep learning. I want to make the biggest possible bet on deep learning. I don't know how, but it will figure it out.Dwarkesh Patel  But is there any specific way in which it's been more than you expected or less than you expected? Like some concrete prediction out of 2015 that's been bounced?Ilya Sutskever  Unfortunately, I don't remember concrete predictions I made in 2015. But I definitely think that overall, in 2015, I just wanted to move to make the biggest bet possible on deep learning, but I didn't know exactly. I didn't have a specific idea of how far things will go in seven years. Well, no in 2015, I did have all these best with people in 2016, maybe 2017, that things will go really far. But specifics. So it's like, it's both, it's both the case that it surprised me and I was making these aggressive predictions. But maybe I believed them only 50% on the inside. Dwarkesh Patel  What do you believe now that even most people at OpenAI would find far fetched?Ilya Sutskever  Because we communicate a lot at OpenAI people have a pretty good sense of what I think and we've really reached the point at OpenAI where we see eye to eye on all these questions.Dwarkesh Patel  Google has its custom TPU hardware, it has all this data from all its users, Gmail, and so on. Does it give them an advantage in terms of training bigger models and better models than you?Ilya Sutskever  At first, when the TPU came out I was really impressed and I thought — wow, this is amazing. But that's because I didn't quite understand hardware back then. What really turned out to be the case is that TPUs and GPUs are almost the same thing. They are very, very similar. The GPU chip is a little bit bigger, the TPU chip is a little bit smaller, maybe a little bit cheaper. But then they make more GPUs and TPUs so the GPUs might be cheaper after all.But fundamentally, you have a big processor, and you have a lot of memory and there is a bottleneck between those two. And the problem that both the TPU and the GPU are trying to solve is that the amount of time it takes you to move one floating point from the memory to the processor, you can do several hundred floating point operations on the processor, which means that you have to do some kind of batch processing. And in this sense, both of these architectures are the same. So I really feel like in some sense, the only thing that matters about hardware is cost per flop and overall systems cost.Dwarkesh Patel  There isn't that much difference?Ilya Sutskever  Actually, I don't know. I don't know what the TPU costs are but I would suspect that if anything, TPUs are probably more expensive because there are less of them.New ideas are overratedDwarkesh Patel  When you are doing your work, how much of the time is spent configuring the right initializations? Making sure the training run goes well and getting the right hyperparameters, and how much is it just coming up with whole new ideas?Ilya Sutskever  I would say it's a combination. Coming up with whole new ideas is a modest part of the work. Certainly coming up with new ideas is important but even more important is to understand the results, to understand the existing ideas, to understand what's going on. A neural net is a very complicated system, right? And you ran it, and you get some behavior, which is hard to understand. What's going on? Understanding the results, figuring out what next experiment to run, a lot of the time is spent on that. Understanding what could be wrong, what could have caused the neural net to produce a result which was not expected. I'd say a lot of time is spent coming up with new ideas as well. I don't like this framing as much. It's not that it's false but the main activity is actually understanding.Dwarkesh Patel  What do you see as the difference between the two?Ilya Sutskever  At least in my mind, when you say come up with new ideas, I'm like — Oh, what happens if it did such and such? Whereas understanding it's more like — What is this whole thing? What are the real underlying phenomena that are going on? What are the underlying effects? Why are we doing things this way and not another way? And of course, this is very adjacent to what can be described as coming up with ideas. But the understanding part is where the real action takes place.Dwarkesh Patel  Does that describe your entire career? If you think back on something like ImageNet, was that more new idea or was that more understanding?Ilya Sutskever  Well, that was definitely understanding. It was a new understanding of very old things.Dwarkesh Patel  What has the experience of training on Azure been like?Ilya Sutskever  Fantastic. Microsoft has been a very, very good partner for us. They've really helped take Azure and bring it to a point where it's really good for ML and we're super happy with it.Dwarkesh Patel  How vulnerable is the whole AI ecosystem to something that might happen in Taiwan? So let's say there's a tsunami in Taiwan or something, what happens to AI in general?Ilya Sutskever  It's definitely going to be a significant setback. No one will be able to get more compute for a few years. But I expect compute will spring up. For example, I believe that Intel has fabs just like a few generations ago. So that means that if Intel wanted to they could produce something GPU-like from four years ago. But yeah, it's not the best, I'm actually not sure if my statement about Intel is correct, but I do know that there are fabs outside of Taiwan, they're just not as good. But you can still use them and still go very far with them. It's just cost, it's just a setback.Cost of modelsDwarkesh Patel  Would inference get cost prohibitive as these models get bigger and bigger?Ilya Sutskever  I have a different way of looking at this question. It's not that inference will become cost prohibitive. Inference of better models will indeed become more expensive. But is it prohibitive? That depends on how useful it is. If it is more useful than it is expensive then it is not prohibitive. To give you an analogy, suppose you want to talk to a lawyer. You have some case or need some advice or something, you're perfectly happy to spend $400 an hour. Right? So if your neural net could give you really reliable legal advice, you'd say — I'm happy to spend $400 for that advice. And suddenly inference becomes very much non-prohibitive. The question is, can a neural net produce an answer good enough at this cost? Dwarkesh Patel  Yes. And you will just have price discrimination in different models?Ilya Sutskever  It's already the case today. On our product, the API serves multiple neural nets of different sizes and different customers use different neural nets of different sizes depending on their use case. If someone can take a small model and fine-tune it and get something that's satisfactory for them, they'll use that. But if someone wants to do something more complicated and more interesting, they'll use the biggest model. Dwarkesh Patel  How do you prevent these models from just becoming commodities where these different companies just bid each other's prices down until it's basically the cost of the GPU run? Ilya Sutskever  Yeah, there's without question a force that's trying to create that. And the answer is you got to keep on making progress. You got to keep improving the models, you gotta keep on coming up with new ideas and making our models better and more reliable, more trustworthy, so you can trust their answers. All those things.Dwarkesh Patel  Yeah. But let's say it's 2025 and somebody is offering the model from 2024 at cost. And it's still pretty good. Why would people use a new one from 2025 if the one from just a year older is even better?Ilya Sutskever  There are several answers there. For some use cases that may be true. There will be a new model for 2025, which will be driving the more interesting use cases. There is also going to be a question of inference cost. If you can do research to serve the same model at less cost. The same model will cost different amounts to serve for different companies. I can also imagine some degree of specialization where some companies may try to specialize in some area and be stronger compared to other companies. And to me that may be a response to commoditization to some degree.Dwarkesh Patel  Over time do the research directions of these different companies converge or diverge? Are they doing similar and similar things over time? Or are they branching off into different areas? Ilya Sutskever  I'd say in the near term, it looks like there is convergence. I expect there's going to be a convergence-divergence-convergence behavior, where there is a lot of convergence on the near term work, there's going to be some divergence on the longer term work. But then once the longer term work starts to fruit, there will be convergence again,Dwarkesh Patel  Got it. When one of them finds the most promising area, everybody just…Ilya Sutskever  That's right. There is obviously less publishing now so it will take longer before this promising direction gets rediscovered. But that's how I would imagine the thing is going to be. Convergence, divergence, convergence.Dwarkesh Patel  Yeah. We talked about this a little bit at the beginning. But as foreign governments learn about how capable these models are, are you worried about spies or some sort of attack to get your weights or somehow abuse these models and learn about them?Ilya Sutskever  Yeah, you absolutely can't discount that. Something that we try to guard against to the best of our ability, but it's going to be a problem for everyone who's building this. Dwarkesh Patel  How do you prevent your weights from leaking? Ilya Sutskever  You have really good security people.Dwarkesh Patel  How many people have the ability to SSH into the machine with the weights?Ilya Sutskever  The security people have done a really good job so I'm really not worried about the weights being leaked.Dwarkesh Patel  What kinds of emergent properties are you expecting from these models at this scale? Is there something that just comes about de novo?Ilya Sutskever  I'm sure really new surprising properties will come up, I would not be surprised. The thing which I'm really excited about, the things which I'd like to see is — reliability and controllability. I think that this will be a very, very important class of emergent properties. If you have reliability and controllability that helps you solve a lot of problems. Reliability means you can trust the model's output, controllability means you can control it. And we'll see but it will be very cool if those emergent properties did exist.Dwarkesh Patel  Is there some way you can predict that in advance? What will happen in this parameter count, what will happen in that parameter count?Ilya Sutskever  I think it's possible to make some predictions about specific capabilities though it's definitely not simple and you can't do it in a super fine-grained way, at least today. But getting better at that is really important. And anyone who is interested and who has research ideas on how to do that, that can be a valuable contribution.Dwarkesh Patel  How seriously do you take these scaling laws? There's a paper that says — You need this many orders of magnitude more to get all the reasoning out? Do you take that seriously or do you think it breaks down at some point?Ilya Sutskever  The thing is that the scaling law tells you what happens to your log of your next word prediction accuracy, right? There is a whole separate challenge of linking next-word prediction accuracy to reasoning capability. I do believe that there is a link but this link is complicated. And we may find that there are other things that can give us more reasoning per unit effort. You mentioned reasoning tokens, I think they can be helpful. There can probably be some things that help.Dwarkesh Patel  Are you considering just hiring humans to generate tokens for you? Or is it all going to come from stuff that already exists out there?Ilya Sutskever  I think that relying on people to teach our models to do things, especially to make sure that they are well-behaved and they don't produce false things is an extremely sensible thing to do. Is progress inevitable?Dwarkesh Patel  Isn't it odd that we have the data we needed exactly at the same time as we have the transformer at the exact same time that we have these GPUs? Like is it odd to you that all these things happened at the same time or do you not see it that way?Ilya Sutskever  It is definitely an interesting situation that is the case. I will say that it is odd and it is less odd on some level. Here's why it's less odd — what is the driving force behind the fact that the data exists, that the GPUs exist, and that the transformers exist? The data exists because computers became better and cheaper, we've got smaller and smaller transistors. And suddenly, at some point, it became economical for every person to have a personal computer. Once everyone has a personal computer, you really want to connect them to the network, you get the internet. Once you have the internet, you suddenly have data appearing in great quantities. The GPUs were improving concurrently because you have smaller and smaller transistors and you're looking for things to do with them. Gaming turned out to be a thing that you could do. And then at some point, Nvidia said — the gaming GPU, I might turn it into a general purpose GPU computer, maybe someone will find it useful. It turns out it's good for neural nets. It could have been the case that maybe the GPU would have arrived five years later, ten years later. Let's suppose gaming wasn't the thing. It's kind of hard to imagine, what does it mean if gaming isn't a thing? But maybe there was a counterfactual world where GPUs arrived five years after the data or five years before the data, in which case maybe things wouldn't have been as ready to go as they are now. But that's the picture which I imagine. All this progress in all these dimensions is very intertwined. It's not a coincidence. You don't get to pick and choose in which dimensions things improve.Dwarkesh Patel  How inevitable is this kind of progress? Let's say you and Geoffrey Hinton and a few other pioneers were never born. Does the deep learning revolution happen around the same time? How much is it delayed?Ilya Sutskever  Maybe there would have been some delay. Maybe like a year delayed? Dwarkesh Patel Really? That's it? Ilya Sutskever It's really hard to tell. I hesitate to give a longer answer because — GPUs will keep on improving. I cannot see how someone would not have discovered it. Because here's the other thing. Let's suppose no one has done it, computers keep getting faster and better. It becomes easier and easier to train these neural nets because you have bigger GPUs, so it takes less engineering effort to train one. You don't need to optimize your code as much. When the ImageNet data set came out, it was huge and it was very, very difficult to use. Now imagine you wait for a few years, and it becomes very easy to download and people can just tinker. A modest number of years maximum would be my guess. I hesitate to give a lot longer answer though. You can't re-run the world you don't know. Dwarkesh Patel  Let's go back to alignment for a second. As somebody who deeply understands these models, what is your intuition of how hard alignment will be?Ilya Sutskever  At the current level of capabilities, we have a pretty good set of ideas for how to align them. But I would not underestimate the difficulty of alignment of models that are actually smarter than us, of models that are capable of misrepresenting their intentions. It's something to think about a lot and do research. Oftentimes academic researchers ask me what's the best place where they can contribute. And alignment research is one place where academic researchers can make very meaningful contributions. Dwarkesh Patel  Other than that, do you think academia will come up with important insights about actual capabilities or is that going to be just the companies at this point?Ilya Sutskever  The companies will realize the capabilities. It's very possible for academic research to come up with those insights. It doesn't seem to happen that much for some reason but I don't think there's anything fundamental about academia. It's not like academia can't. Maybe they're just not thinking about the right problems or something because maybe it's just easier to see what needs to be done inside these companies.Dwarkesh Patel  I see. But there's a possibility that somebody could just realize…Ilya Sutskever  I totally think so. Why would I possibly rule this out? Dwarkesh Patel  What are the concrete steps by which these language models start actually impacting the world of atoms and not just the world of bits?Ilya Sutskever  I don't think that there is a clean distinction between the world of bits and the world of atoms. Suppose the neural net tells you — hey here's something that you should do, and it's going to improve your life. But you need to rearrange your apartment in a certain way. And then you go and rearrange your apartment as a result. The neural net impacted the world of atoms.Future breakthroughsDwarkesh Patel  Fair enough. Do you think it'll take a couple of additional breakthroughs as important as the Transformer to get to superhuman AI? Or do you think we basically got the insights in the books somewhere, and we just need to implement them and connect them? Ilya Sutskever  I don't really see such a big distinction between those two cases and let me explain why. One of the ways in which progress is taking place in the past is that we've understood that something had a desirable property all along but we didn't realize. Is that a breakthrough? You can say yes, it is. Is that an implementation of something in the books? Also, yes. My feeling is that a few of those are quite likely to happen. But in hindsight, it will not feel like a breakthrough. Everybody's gonna say — Oh, well, of course. It's totally obvious that such and such a thing can work. The reason the Transformer has been brought up as a specific advance is because it's the kind of thing that was not obvious for almost anyone. So people can say it's not something which they knew about. Let's consider the most fundamental advance of deep learning, that a big neural network trained in backpropagation can do a lot of things. Where's the novelty? Not in the neural network. It's not in the backpropagation. But it was most definitely a giant conceptual breakthrough because for the longest time, people just didn't see that. But then now that everyone sees, everyone's gonna say — Well, of course, it's totally obvious. Big neural network. Everyone knows that they can do it.Dwarkesh Patel  What is your opinion of your former advisor's new forward forward algorithm?Ilya Sutskever  I think that it's an attempt to train a neural network without backpropagation. And that this is especially interesting if you are motivated to try to understand how the brain might be learning its connections. The reason for that is that, as far as I know, neuroscientists are really convinced that the brain cannot implement backpropagation because the signals in the synapses only move in one direction. And so if you have a neuroscience motivation, and you want to say — okay, how can I come up with something that tries to approximate the good properties of backpropagation without doing backpropagation? That's what the forward forward algorithm is trying to do. But if you are trying to just engineer a good system there is no reason to not use backpropagation. It's the only algorithm.Dwarkesh Patel  I guess I've heard you in different contexts talk about using humans as the existing example case that AGI exists. At what point do you take the metaphor less seriously and don't feel the need to pursue it in terms of the research? Because it is important to you as a sort of existence case.Ilya Sutskever  At what point do I stop caring about humans as an existence case of intelligence?Dwarkesh Patel  Or as an example you want to follow in terms of pursuing intelligence in models.Ilya Sutskever  I think it's good to be inspired by humans, it's good to be inspired by the brain. There is an art into being inspired by humans in the brain correctly, because it's very easy to latch on to a non-essential quality of humans or of the brain. And many people whose research is trying to be inspired by humans and by the brain often get a little bit specific. People get a little bit too — Okay, what cognitive science model should be followed? At the same time, consider the idea of the neural network itself, the idea of the artificial neuron. This too is inspired by the brain but it turned out to be extremely fruitful. So how do they do this? What behaviors of human beings are essential that you say this is something that proves to us that it's possible? What is an essential? No this is actually some emergent phenomenon of something more basic, and we just need to focus on getting our own basics right. One can and should be inspired by human intelligence with care.Dwarkesh Patel  Final question. Why is there, in your case, such a strong correlation between being first to the deep learning revolution and still being one of the top researchers? You would think that these two things wouldn't be that correlated. But why is there that correlation?Ilya Sutskever  I don't think those things are super correlated. Honestly, it's hard to answer the question. I just kept trying really hard and it turned out to have sufficed thus far. Dwarkesh Patel So it's perseverance. Ilya Sutskever It's a necessary but not a sufficient condition. Many things need to come together in order to really figure something out. You need to really go for it and also need to have the right way of looking at things. It's hard to give a really meaningful answer to this question.Dwarkesh Patel  Ilya, it has been a true pleasure. Thank you so much for coming to The Lunar Society. I appreciate you bringing us to the offices. Thank you. Ilya Sutskever  Yeah, I really enjoyed it. Thank you very much. Get full access to The Lunar Society at www.dwarkeshpatel.com/subscribe

Bob Rogers, AI pioneer, entrpreneur, and author, started Oii in 2019 to automate supply chain design. The company uses advanced modeling and AI to optimize supply chain planning and automate the configuration of complex networks. Bob started his career as a Harvard physicist using neural networks to measure activity near black holes in deep space. During his 35 year career Bob has been a trailblazer in using AI to solve complex problems. He's also an Expert in Residence for AI at UCSF Smarter Health and was Chief Data Scientist in the Data Center Group at Intel as well as co-founder and Chief Scientist at Apixio, a Healthcare AI company. Additionally, he co-authored the books Artificial Neural Networks: Forecasting Time Series and “De-mystifying Big Data and Machine Learning for Healthcare“. Bob received his BA in physics at UC Berkeley and his PhD in physics at Harvard. Listen and learn...How neural nets work... from a pioneerWhat it was like to co-author a book with ChatGPTWhat surprised Bob most when he tested the boundaries of ChatGPTWhy ChatGPT spews credible nonsenseThe ethics of using generative AI to sell content derived from copyrighted materialsWhy ChatGPT became an instant global phenomenonHow OpenAI trained ChatGPT "to be nice"Is there another "AI winter" ahead?References in this episode:The book Bob co-authored with ChatGPTCan AI be an author of a publication in a scientific journal?Bob's previous book: Demystifying AI for the enterpriseStanford's Dr. Fei-Fei Li in conversation with OpenAI CTO Mira MuratiFuturists Peter Scott and David Wood on AI and the Future of WorkBob's company: Oii.ai

In this Partnering Leadership conversation, Mahan Tavakoli speaks with Louis Rosenberg. Louis Rosenberg is a pioneer in virtual and augmented reality with over 300 patents; he has started multiple businesses, including Founder Immersion Corp, Founder Outland Research, and Unanimous A.I., for which he currently serves as CEO and Chief Scientist.     Louis Rosenberg has focused his work on the boundary between technology and human perception, aiming to enhance human performance with technology. In the conversation, Louis Rosenberg shared why he is wary of the potential for technology to dehumanize people and works to push the boundaries to augment rather than replace human intelligence.   Louis Rosenberg shared why he believes A.R. will be the primary way people access digital lives, replacing mobile phones with eyewear that spatially registers content to the real world. In addition, augmented reality and mixed reality will become more prevalent as society progresses. Finally, Louis Rosenberg shared his perspectives on the power of human swarm intelligence through Swarm technology as an example of the potential positives for the future of humanity in the collaborative use of artificial intelligence.  Some Highlights:- Louis Rosenberg on the Potential of Virtual, Augmented, and Mixed Reality Technologies- The inevitability of Augmented and Mixed Reality in the digital age- Use of Augmented Reality in the medical space - The impact of Augmented Reality on different professions - Louis Rosenberg on Augmented Reality's potential in education and training - Why there is a need for policy solutions in Augmented Reality - The positive potential of the Metaverse- Dangers of unregulated AI-driven persuasion in the Metaverse- Louis Rosenberg on using Swarm Intelligence for smarter decision making - The use of Swarm Technology to forecast the future - How to use A.I. to harness the power of the human brain and the knowledge and information it containsMentioned:Partnering Leadership conversation with Tom Taulli on A.I. Bootcamp for LeadersPartnering Leadership conversation with Dan Turchin on A.I. & The Future of WorkConnect with Louis Rosenberg:Unanimous A.I. Website Louis Rosenberg's articles on BIG THINK Louis Rosenberg's articles on Venture BeatLouis Rosenberg on LinkedIn Louis Rosenberg's TEDx Talk New hope for humans in an A.I. worldConnect with Mahan Tavakoli: Mahan Tavakoli Website Mahan Tavakoli on LinkedIn Partnering Leadership Website

Try Acres for free: https://www.acres.co/Tule Technologies: https://tule.ag/CropX: Today's episode features Tom Shapland of Tule Technologies and John Gates of CropX. We have a great episode for you talking about Tule's technology, Tom's entrepreneurial journey, The decision on both sides for Cropx to acquire Tule, M&A in agtech and integration lesson, and the future of artificial intelligence in agtech. Tom is the co-founder and CEO of Tule Technologies, which is now part of CropX. As a graduate student at UC Davis, Tom developed the underlying technology that Tule commercialized which is a way to measure water use of crop plants over a broad area. Specifically they measure actual crop evapotranspiration or ET and he'll talk a lot more about that. He founded Tule in 2013 after finishing his PhD work in this area. He went out and started talking to customers and getting sales early, which you'll find is an important part of his entrepreneurial journey. Him and his co-founder Jeff LaBarge went the Y Combinator program, which is our second episode this month with a YC alum. Joining us from CropX is senior vice president and global head of product John Gates. John also has a background in academia. He was a professor of Hydrology at University of Nebraska. He evenutally joined CropMetrics as their Chief Scientist and stayed on with CropX after they acquired CropMetrics a few years ago. You'll hear from Tom first about Tule's technology and trajectory, and then we'll invite John in to talk about the acquisition and much much more.

This hour, we listen to a panel discussion that Khalilah hosted for The Nature Conservancy in Connecticut's annual Nature Talks series. The discussion was called “Oceans: Our Global Watchdog.” It was recorded in front of a live audience at Grace Farms in New Canaan, CT. The panelists talked about topics like how some communities are disproportionately affected by climate change and why we need to act now to protect the planet. The guests were Dr. Sylvia Earle, Explorer-in-Residence at the National Geographic Society, first woman Chief Scientist at NOAA and Time Magazine's first “Hero for the Planet;” Dr. Camille Gaynus, Board Chair of Black in Marine Science and Assistant Teaching Professor of Biology at Penn State Brandywine; Dr. Lizzie McLeod, Global Reef Systems Lead at The Nature Conservancy and Dr. Tiara Moore, Founder and CEO of Black in Marine Science and the Black in Marine Science Program Lead at the Nature Conservancy. To learn more about the impact of climate change on our state, watch Cutline: Climate Change Along Connecticut's Coast. GUESTS: Dr. Sylvia Earle: Explorer-in-Residence at the National Geographic Society, first woman Chief Scientist at NOAA, Founder of Mission Blue / The Sylvia Earle Alliance, Founder of Deep Ocean Exploration and Research and Time Magazine's first “Hero for the Planet” Dr. Camille Gaynus: Board Chair of Black in Marine Science, Assistant Teaching Professor of Biology at Penn State Brandywine and Co-founder of A WOC Space Dr. Lizzie McLeod: Global Reef Systems Lead at The Nature Conservancy Dr. Tiara Moore: Founder and CEO of Black in Marine Science, the Black in Marine Science Program Lead at The Nature Conservancy and Founder of A WOC Space See omnystudio.com/listener for privacy information.

What if you got the chance to dive to the bottom of the ocean? Would you go? And what would you find there? That's today's big question and my returning guest, one of my all-time favorites, is Dr. Dawn Wright, better known the world over as Deep Sea Dawn. Dawn recently became the 27th person ever in history and the first Black person ever to dive into the Challenger Deep, the deepest part of Earth's ocean.Dawn is an elected member of both the National Academy of Sciences and the National Academy of Engineering and the Chief Scientist at Esri, where she works with other scientists to map the ocean floor in 3D. As our oceans heat up and rise, as we try to reduce overfishing, and as our governments and companies race to mine minerals for our all-electric future, there has never been a more monumental and historic, and vitally important project than trying to understand our oceans.A lot has happened, since Dawn and I last spoke. It shouldn't be surprising then, that this conversation not only talked about the wonder of the deep seas and the Earth's crust but also went to some wonderful and unexpectedly emotional places. I'm so thankful to have shared another conversation with Deep Sea Dawn.-----------Have feedback or questions? Tweet us, or send a message to questions@importantnotimportant.comNew here? Get started with our fan favorite episodes at importantnotimportant.com/podcast.-----------INI Book Club:Surrender by BonoFind all of our guest recommendations at the INI Book Club: https://bookshop.org/lists/important-not-important-book-clubLinks:5 Ways Scientists, NGOs, and Governments Can Support Indigenous-led Conservation The “story maps” that Esri made for Victor Vescovo and Caladan Oceanic after Kathy Sullivan's dive to Challenger The “story map” of Dawn's dive The MPA Guide – great resource for all things designating and managing Marine Protected Areas Dawn's mom's story Follow Deep Sea Dawn on Twitter, Instagram, and LinkedInFollow us:Subscribe to our newsletter at

We are honored to speak with Richard Haines, PhD. former NASA research scientist & Chief Scientist of NARCAP(National Aviation Reporting Center on Anomalous Phenomena. We discuss UFOs, NARCAP, Aviation Safety, & Close Encounters of the Fifth Kind(CE-5) See Here: https://youtu.be/1jH0Pjt2XvM In this episode of Engaging The Phenomenon we are honored to speak with Richard Haines, PhD. former NASA research scientist and Chief Scientist of NARCAP(National Aviation Reporting Center on Anomalous Phenomena. We discuss UFOs, NARCAP, Aviation Safety, & Close Encounters of the Fifth Kind(CE-5) Words from Ted Roe - My mentor and cofounder of NARCAP. He is really the godfather of UAP/aviation safety studies. He introduced the term UAP with his definition in 1999... hope you brought that up. Nobody would be using the acronym were it not for him. His legacy continues w the UAP/aviation safety program I helped design and implement at the American Institute of Aeronautics and Astronautics, AIAA, aiaauap.org - Follow us on Twitter: https://twitter.com/EngagingThe?t=iEVw2QagEoCgZey4H_zT9Q&s=09 Engaging The Phenomenon Podcast: https://anchor.fm/engagingthephenomenon Support us on Patreon: https://www.patreon.com/Engagingthephenomenon Support us w/ Paypal: https://paypal.me/engagingthephenomeno?country.x=US&locale.x=en_US Read Our Articles on Medium: https://medium.com/@EngagingThePhenomenon Greatly appreciate all the support!! Another way to support the channel is to share the work on social media networks! Thanks for joining us! Support The Podcast: https://anchor.fm/engagingthephenomenon/support Engaging The Phenomenon LinkTree(https://linktr.ee/EngagingThePhenomenon) We've created a Twitter account for our initiative! Follow us here to stay tuned! Inquire Anomalous Follow Here: https://twitter.com/InquireAnomalus?t=PWi80yvgFpRVdflA_S242g&s=09 --- Support this podcast: https://podcasters.spotify.com/pod/show/engagingthephenomenon/support

Dr. Travis Taylor, from Skinwalker Ranch and Chief Scientist for the Unidentified Aerial Phenomena Task Force, analyzes the metal we dug up near the 2008 UFO crash in Needles, CA. Watch on YouTube to see the metal! https://youtu.be/lUuFwQhINJ0 FOLLOW EMMETT & JOEwww.twitter.com/realufobroswww.instagram.com/realufobroswww.facebook.com/realufobroswww.realufobros.comTikTok: @realufobrosSUBSCRIBE to audio version on all podcasting platformsUFO BROS Joe and Emmett have been described as the next generation of UFO researchers and explorers who have taken the UFO world by storm. The brothers have investigated the Roswell crash site of 1947, Stormed Area 51, and retrieved a piece of metal in the Needles desert, CA UFO crash of 2008. Their most recent adventures include taking one of the world's biggest pop stars, Demi Lovato, on a night UFO investigation. With their UFO Bros: Probecast and television appearances, the UFO Bros continue to bring a unique brand of fun and humor to UFO research while still taking the topic seriously.

In episode 64 of The Gradient Podcast, Daniel Bashir speaks to Richard Socher.Richard is founder and CEO of you.com, a new search engine that lets you personalize your search workflow and eschews tracking and invasive ads. Richard was previously Chief Scientist at Salesforce where he led work on fundamental and applied research, product incubation, CRM search, customer service automation and a cross-product AI platform. He was an adjunct professor at Stanford's CS department as well as founder and CEO/CTO of MetaMind, which was acquired by Salesforce in 2016. He received his PhD from Stanford's CS Department in 2014.Have suggestions for future podcast guests (or other feedback)? Let us know here!Subscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterOutline:* (00:00) Intro* (02:20) Richard Socher origin story + time at Metamind, Salesforce (AI Economist, CTRL, ProGen)* (22:00) Why Richard advocated for deep learning in NLP* (27:00) Richard's perspective on language* (32:20) Is physical grounding and language necessary for intelligence?* (40:10) Frankfurtian b******t and language model utterances as truth* (47:00) Lessons from Salesforce Research* (53:00) Balancing fundamental research with product focus* (57:30) The AI Economist + how should policymakers account for limitations?* (1:04:50) you.com, the chatbot wars, and taking on search giants* (1:13:50) Re-imagining the vision for and components of a search engine* (1:18:00) The future of generative models in search and the internet* (1:28:30) Richard's advice for early-career technologists* (1:37:00) OutroLinks:* Richard's Twitter * YouChat by you.com* Careers at you.com* Papers mentioned* Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions* Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank* Grounded Compositional Semantics for Finding and Describing Images with Sentences* The AI Economist* ProGen* CTRL Get full access to The Gradient at thegradientpub.substack.com/subscribe

Dr. Jessica Kriegel is the Chief Scientist of Workplace Culture for Culture Partners, leading research and strategy in best practices for driving results through culture. How do you define culture? Why is corporate culture important? How does it drive results? What is the biggest mistake that leaders make? You do research work on corporate culture, what is your process? Dr. Jessica Kriegel Dr. Jessica Kriegel is the Chief Scientist of Workplace Culture for Culture Partners, leading research and strategy in best practices for driving results through culture. She is a Fortune 100 Thought Leader and keynote speaker as well as author of Unfairly Labeled: How Your Workplace Can Benefit From Ditching Generational Stereotypes. Her upcoming book, The Culture Equation will be published in 2023 and is based on her 15+ years of guiding global and national organizations on the path to creating intentional workplace cultures that accelerate performance and put people first. Excellent Executive Coaching Podcast If you have enjoyed this episode, subscribe to our podcast on iTunes. We would love for you to leave a review. The EEC podcasts are sponsored by MKB Excellent Executive Coaching that helps you get from where you are to where you want to be with customized leadership and coaching development programs. MKB Excellent Executive Coaching offers leadership development programs to generate action, learning, and change that is aligned with your authentic self and values. Transform your dreams into reality and invest in yourself by scheduling a discovery session with Dr. Katrina Burrus, MCC to reach your goals. Your host is Dr. Katrina Burrus, MCC, founder and general manager of www.mkbconseil.ch a company specialized in leadership development and executive coaching.

What if I told you there was less oxygen in the ocean than there used to be? That's today's big question, and my guest is Dr. Dawn Wright, or as many in the ocean community know her "Deep Sea Dawn." Dawn Wright is an elected member of both the National Academy of Sciences and the National Academy of Engineering. She's the Chief Scientist at ESRI, where she works with other scientists to map the ocean floor in 3D. In 2018, when I was just a baby podcaster, when Brian was my co-host, I saw a headline about the ocean that made me question a lot. I knew the oceans were heating up. I was beginning to understand, I think we were all beginning to understand, just how much global heating the oceans had absorbed over the years.But I didn't know what that meant for the billions of creatures that call the ocean home. I didn't know what it meant for us. So I called Dawn. In celebration of Dawn's return to the show next week, I wanted to replay this incredible conversation we had with her to better understand how far we've come.-----------Have feedback or questions? Tweet us, or send a message to questions@importantnotimportant.comNew here? Get started with our fan favorite episodes at importantnotimportant.com/podcast.-----------Follow us:Subscribe to our newsletter at importantnotimportant.comFollow us on Twitter: twitter.com/ImportantNotImpSubscribe to our YouTube channelFollow Quinn: twitter.com/quinnemmettEdited by Anthony LucianiProduced by Willow BeckIntro/outro by Tim Blane: timblane.comFind our more about our guests here: https://www.importantnotimportant.com/guest-statsAdvertise with us: https://www.importantnotimportant.com/sponsors

Have you ever experienced psychic phenomena? How about an experience that could only be regarded as “magic”? It's more than likely you have, considering a survey conducted where over 90% of participants, all being scientific academics, reported to have had at least one of these experiences in their life. Today's podcast is with Dean Radin, Chief Scientist at the Institute of Noetic Sciences. Dean has an impressively prestigious background- with a Masters degree in electrical engineering and a PhD in psychology, he has spent decades engaged in research on the frontiers of consciousness, with over 100 peer-reviewed studies and author of numerous books. In our discussion, we discuss the gamut of magical experiences, including; telepathy, clairvoyance, levitation, manifestation, sigils, and more. We dive into the scientific studies that validate these kinds of experiences, discuss the history of suppression, and posit the potential of our future if we begin to harness these abilities. Get Dean Radin's book: Real Magic Connect with Dean Radin: Website | www.deanradin.com/ Linkedin | www.linkedin.com/in/dean-radin-9417877/ Twitter | https://twitter.com/deanradin Facebook | www.facebook.com/DeanRadinsPage/ This episode is sponsored by: ONNIT Get 10% off all Onnit Products: https://bit.ly/3LMVArK HELIX SLEEP is offering up to 20% off all mattress orders AND two free pillows: HelixSleep.com/AMP MUD/WTR Visit mudwtr.com/amp and get 15% off your order by using the discount code AUBREY at checkout To partner with the Aubrey Marcus Podcast | Connect with Aubrey | Website | http://bit.ly/2GesYqi Instagram | http://bit.ly/2BlfCEO Facebook | http://bit.ly/2F4nBZk Twitter | http://bit.ly/2BlGBAdAd Check out "Own your Day, Own Your Life" by Aubrey Marcus | http://bit.ly/2vRz4so Subscribe to the Aubrey Marcus newsletter: https://www.aubreymarcus.com/pages/email Subscribe to the Aubrey Marcus podcast: iTunes | https://apple.co/2lMZRCn Spotify | https://spoti.fi/2EaELZO Stitcher | http://bit.ly/2G8ccJt IHeartRadio | https://ihr.fm/3CiV4x3 Google Podcasts | https://bit.ly/3nzCJEh Android | https://bit.ly/2OQeBQg

On Sunday, the Republican-led House Oversight Committee released new emails that prove that Anthony Fauci was instrumental in prompting the drafting of the fraudulent Proximal Origin paper. That paper was first published by a group of Fauci-funded scientists on Feb. 16, 2020. The paper immediately became the media's go-to evidence to propagate the fake natural origin theory. In fact, it became one of the most cited papers in history. And it was all a fraud. While bits and pieces of the fraud were already known, the stunning new emails released by House Oversight now place Fauci and his British side-kick, pharmaceutical trust CEO Jeremy Farrar at the center of the fraud. It's an incredible story of lies and deceit. ⭕️ Watch in-depth videos based on Truth & Tradition at Epoch TV

Last week, journalists from the WSJ reported that the US Department of Energy [DOE] had joined the FBI in concluding that the COVID-19 pandemic most likely arose from a lab leak in Wuhan. While the DOE assessment is supported by a growing body of circumstantial evidence in the public domain, the cloak and dagger manner in which it was leaked to the Press raises more questions than it answers. Today Sam Husseini and I discuss the DOE assessment—what we know and what we don't know, the “limited hangout” post 9/11 that manipulated US public opinion to believe Iraq had WMDs, the WHO role in the ongoing investigation of the origin of SARS-CoV-2 and their appointment of Jeremy Farrar as Chief Scientist, and the rapidly evolving “official narrative” on the origin of COVID-19. Sam Husseini is an independent reporter covering WMDs and biowarfare since 9/11.

Minter Dialogue with Dr Alan Cowen Dr Alan Cowen is the CEO and Chief Scientist at Hume AI, a science-backed expression API platform for researchers and developers, whose mission is to align science and technology with human well-being. In this conversation, we discuss his background, including 5 years working at Google, doing scientific research on AI, the Hume AI project and business model, the state of play in understanding our emotions and creating artificial empathy. A perfect topic for any interested in how AI will play an important part in tending to our well being. If you've got comments or questions you'd like to see answered, send your email or audio file to nminterdial@gmail.com; or you can find the show notes and comment on minterdial.com. If you liked the podcast, please take a moment to rate/review the show on RateThisPodcast. Otherwise, you can find me @mdial on Twitter.

Not long ago, it was said that “hydrogen is the fuel of the future - and always will be.” Now, with the Bipartisan Infrastructure Law tagging $9.5 billion for developing a domestic hydrogen economy, this simplest of all elements is increasingly being discussed as a viable pathway for long-distance trucking, shipping, and hard-to-decarbonize industries like cement and steel. But how clean is clean hydrogen, really? And what will it take to make green hydrogen a cost-competitive option in applications like manufacturing, transportation, and grid-scale energy storage? Guests: Julio Friedmann, Chief Scientist, Carbon Direct Sunita Satyapal, Director, Hydrogen and Fuel Cell Technologies Office, DOE  Alan Krupnick, Senior Fellow, Resources for the Future  For show notes and related links, visit https://www.climateone.org/watch-and-listen/podcasts Learn more about your ad choices. Visit megaphone.fm/adchoices

Dr. Katharine Hayhoe is a world-renowned climate scientist, professor, and Chief Scientist for The Nature Conservancy, where she leads and coordinates the organization's scientific efforts. She is also the author of "Saving Us: A Climate Scientist's Case for Hope and Healing in a Divided World," an excellent book you've likely heard me reference on the podcast. Whether you are interested in learning more about the facts, data, or projections regarding climate change, or if you are seeking guidance on how best to approach challenging conversations about climate, I highly recommend "Saving Us." It's an optimistic, solutions-oriented guidebook for finding common ground and having productive conversations. - Katharine was born and raised in Canada and has been obsessed with science, the natural world, and the universe for as long as she can remember. Her undergraduate studies focused on physics and astronomy, but as she was finishing up her degree, she happened to take a climate science course, which captured her imagination and changed the focus of her education and career. Today, Katharine is a distinguished professor at Texas Tech, a highly respected researcher, and a sought-after speaker with a TED Talk that's been viewed more than 4 million times. And to top it all off, in 2021, she joined The Nature Conservancy as its Chief Scientist. - Katharine and I met up in Steamboat Springs, Colorado, where she was the keynote speaker at a community event focused on climate and climate change in the Yampa Valley and beyond. Katharine and I chatted for an hour before her event, and we managed to cover a lot of ground. We discussed her book "Saving Us," her TED talk, and a concept known as "The Six Americas of Global Warming." We discuss how and why her Christian faith plays such an important role in her work to solve climate change, and she offers some common-sense, optimistic approaches to having challenging conversations with smart people who do not think that climate change is a threat. She also talks about her role at The Nature Conservancy, specific climate opportunities and challenges facing the American West, and she offers a ton of excellent book recommendations. - Thank you to Dr. Hayhoe for taking the time out of her busy schedule to chat with me, and thank you for listening. Hope you enjoy. --- Dr. Katharine Hayhoe "Saving Us: A Climate Scientist's Case for Hope and Healing in a Divided World" Full episode notes and links: https://mountainandprairie.com/katharine-hayhoe/ --- This episode is brought to you in partnership with the Colorado chapter of The Nature Conservancy. Guided by science and grounded by decades of collaborative partnerships, The Nature Conservancy has a long-standing legacy of achieving lasting results to create a world where nature and people thrive. On the fourth Tuesday of every month throughout 2023, Mountain & Prairie will be delving into conversations with a wide range of The Nature Conservancy's leaders, partners, collaborators, and stakeholders, highlighting the myriad of conservation challenges, opportunities, and solutions here in the American West. To learn more about The Nature Conservancy's impactful work in Colorado and around the world, visit www.nature.org/colorado --- TOPICS DISCUSSED: 3:30 - Why Dr. Hayhoe wrote "Saving Us" 5:45 - Regarding Dr. Hayhoe's TED Talk 8:15 - Discussing The Six Americas of Global Warming 12:00 - The relationship between Dr. Hayhoe's faith and climate work 17:45 - When religion and climate change dismissal historically became tied together 21:30 - Discussing the balance between fear and guilt as motivating and stagnating forces 28:00 - What surprised Dr. Hayhoe in writing the book 33:45 - Role playing how to interact with intelligent people who doubt climate science 37:30 - Applying lessons learned from COVID-19 to climate change 41:30 - Dr. Hayhoe's time as 9-year-old abroad in Columbia and how it influenced her thinking and career 46:15 - Why Dr. Hayhoe decided to work with The Nature Conservancy, and the impacts she hopes to make 50:15 - The stats Dr. Hayhoe would want to see to feel she has had an impact in five years 54:45 - The challenges and opportunities facing the arid West amidst climate change 57:00 - Dr. Hayhoe's reading habits and some books she has loved --- ABOUT MOUNTAIN & PRAIRIE: Mountain & Prairie - All Episodes Mountain & Prairie Shop Mountain & Prairie on Instagram Upcoming Events About Ed Roberson Support Mountain & Prairie Leave a Review on Apple Podcasts

In today's show, we bring on Ben Jones, Chief Scientist of the Optimism Foundation, Karl Floersch, CTO at OP Labs, and Jing Wang, Executive Director of Optimism Foundation  The five discuss Coinbase's Base launch, the OP Stack integration, and what it means for the Superchains vision!  ------  MetaMask Learn  https://bankless.cc/metamaskshow  ------  JOIN BANKLESS PREMIUM:  https://newsletter.banklesshq.com/subscribe  ------ BANKLESS SPONSOR TOOLS:  KRAKEN | MOST-TRUSTED CRYPTO EXCHANGE https://bankless.cc/kraken  UNISWAP | ON-CHAIN MARKETPLACE https://bankless.cc/uniswap  ️ ARBITRUM | SCALING ETHEREUM https://bankless.cc/Arbitrum   EARNIFI | CLAIM YOUR UNCLAIMED AIRDROPS https://bankless.cc/earnifi   ------ Timestamps: 0:00 Intro 6:20 Sentiment at Optimism 7:00 Biggest Deal with the News? 11:28 Reflection on Coinbase's Base 15:45 OP Stack 17:15 Is Base a Competitor? 20:53 Puberty State of Chains 33:30 Superchains 40:35 Security of the Superchains 44:35 Superchain Standards  51:51 Base Decentralization Timeline? 57:10 Closing & Disclaimers  ------ Resources: Coinbase Base Announcement https://www.coinbase.com/blog/introducing-base  Optimism + OP STack Details https://optimism.mirror.xyz/2jk3D1Y8-hid8YOCUUa6yXmsyzNCYYyFJP0Nhaey9x0  Ben Jones  https://twitter.com/ben_chain  Karl Floersch https://twitter.com/karl_dot_tech  Jing Wang https://twitter.com/jinglejamop  ----- Not financial or tax advice. This channel is strictly educational and is not investment advice or a solicitation to buy or sell any assets or to make any financial decisions. This video is not tax advice. Talk to your accountant. Do your own research. Disclosure. From time-to-time I may add links in this newsletter to products I use. I may receive commission if you make a purchase through one of these links. Additionally, the Bankless writers hold crypto assets. See our investment disclosures here: https://www.bankless.com/disclosures 

Gary Conley, the Chief Scientist at 2NDNATURE, joins the podcast to discuss how he uses his expertise in hydrology, pollution dynamics, and applied math to tackle water pollution problems. With a goal of improving watershed stewardship and reducing the cost of clean water in US communities, Gary draws from nearly 20 years of experience in his field to mitigate the challenges of water pollution… 2NDNATURE is a company that designs and builds software to simplify stormwater resource management, planning, and reporting. Want to know how 2NDNATURE is helping the water quality in US communities? Listen now to learn for yourself! In this episode, we cover: Where water pollution typically occurs. The state of our water quality in US municipalities. The metrics used to measure water quality. The benefits of limiting urban runoff. To discover more about 2NDNATURE and their work, visit www.2ndnaturewater.com now! Episode also available on Apple Podcast: http://apple.co/30PvU9C

On this week's Industrial Talk we're onsite at IoT Solutions World Congress and talking to Dr. Michael Grieves, Executive Director and Chief Scientist, Digital Twin Institute about "Digital Twin and where it's headed". Learn from this Digital Twin pioneer along with and Dr. Grieves's unique insight into the future of Digital Twin on this Industrial Talk interview! Finally, get your exclusive free access to the Industrial Academy and a series on “Why You Need To Podcast” for Greater Success in 2023. All links designed for keeping you current in this rapidly changing Industrial Market. Learn! Grow! Enjoy! MICHAEL GRIEVES' CONTACT INFORMATION: Personal LinkedIn: https://www.linkedin.com/in/michael-grieves-6165719/ PODCAST VIDEO: https://youtu.be/FEu5GJRvamQ THE STRATEGIC REASON "WHY YOU NEED TO PODCAST": OTHER GREAT INDUSTRIAL RESOURCES: NEOM: https://www.neom.com/en-us Hitachi Vantara: https://www.hitachivantara.com/en-us/home.html Industrial Marketing Solutions:  https://industrialtalk.com/industrial-marketing/ Industrial Academy: https://industrialtalk.com/industrial-academy/ Industrial Dojo: https://industrialtalk.com/industrial_dojo/ We the 15: https://www.wethe15.org/ YOUR INDUSTRIAL DIGITAL TOOLBOX: LifterLMS: Get One Month Free for $1 – https://lifterlms.com/ Active Campaign: Active Campaign Link Social Jukebox: https://www.socialjukebox.com/ Industrial Academy (One Month Free Access And One Free License For Future Industrial Leader): Business Beatitude the Book Do you desire a more joy-filled, deeply-enduring sense of accomplishment and success? Live your business the way you want to live with the BUSINESS BEATITUDES...The Bridge connecting sacrifice to success. YOU NEED THE BUSINESS BEATITUDES! TAP INTO YOUR INDUSTRIAL SOUL, RESERVE YOUR COPY NOW! BE BOLD. BE BRAVE. DARE GREATLY AND CHANGE THE WORLD. GET THE BUSINESS BEATITUDES!