Podcasts about ethical issues

Dr. Lisa Rubin, professor in the College of Education at Kansas State University and Dr. Ashley Thomas, assistant director of resources and managing editor at NACADA discuss Rubin's upcoming book, Ethical Issues in Academic Advising, a new guidebook shaped by her journey from athletic advisor to professor at Kansas State University. This conversation dives into the ethical challenges advisors face every day with clarity, compassion, and real-world insight. From foundational ethical concepts to decision-making frameworks, Rubin and Thomas discuss how this book offers practical tools for academic and faculty advisors, as well as administrators. Pre-order Ethical Issues in Academic Advising! Higher Listenings: Joy for EducatorsA new podcast from Top Hat delivering ideas, relief, and joy to the future of teaching.Listen on: Apple Podcasts SpotifySubscribe to the podcast on your favorite podcast platform!The X, Instagram, and Facebook handle for the podcast is @AdvisingPodcastAlso, subscribe to our Adventures in Advising YouTube Channel!Connect with Matt and Ryan on LinkedIn.

What if doing the most good was simpler—and more within reach—than you ever imagined? In this powerful episode of The Greatness Machine, Darius is joined by world-renowned moral philosopher Peter Singer for a conversation that will challenge how you think about ethics, generosity, and your role in making the world better. Peter, best known for his groundbreaking work “The Life You Can Save,” shares thought-provoking insights on effective altruism, the moral obligations of those living in affluence, and how small, intentional actions can create ripple effects of real change. From fighting global poverty to advocating for animal rights, Peter's work has inspired millions to rethink their impact—and today, he might just do the same for you. In this episode, Darius and Peter will discuss: (00:00) Introduction to Effective Altruism (06:11) Understanding Effective Altruism (11:57) The Life You Can Save: A Nonprofit Overview (18:05) Philanthropy and Meaning in Life (23:55) Profit for Good: Business and Altruism (24:54) Profit for Good Conference: A New Business Paradigm (30:01) The Role of Bioethics in Modern Society (37:32) Activism and Personal Motivation in Ethical Issues (38:35) Reflections on Global Issues: Past and Present (41:42) Making a Difference: Individual Impact and Career Choices (47:07) Overcoming Barriers to Greatness Peter Singer is an Australian moral philosopher known for his work in applied ethics from a utilitarian perspective. He is Emeritus Professor of Bioethics at Princeton University and author of Animal Liberation and the influential essay “Famine, Affluence, and Morality.” Singer has shifted from preference to hedonistic utilitarianism over his career. He founded Monash University's Centre for Human Bioethics, co-founded Animals Australia, and established the nonprofit The Life You Can Save. Recognized as Australian Humanist of the Year in 2004, he is considered one of Australia's most influential public intellectuals. Sponsored by: Huel: Try Huel with 15% OFF + Free Gift for New Customers today using my code greatness at https://huel.com/greatness. Fuel your best performance with Huel today! Indeed: Get a $75 sponsored job credit to boost your job's visibility at Indeed.com/DARIUS. Notion: Get Notion Mail for free right now at notion.com/machine. ShipStation: Go to shipstation.com and use code GREATNESS to sign up for your FREE trial. Shopify: Sign up for a $1/month trial period at shopify.com/darius.  Connect with Peter: Website: https://www.petersinger.info/ Website: http://thelifeyoucansave.org/  Podcast: https://podcasts.apple.com/ee/podcast/lives-well-lived/id1743702376  Connect with Darius: Website: https://therealdarius.com/ Linkedin: https://www.linkedin.com/in/dariusmirshahzadeh/ Instagram: https://www.instagram.com/imthedarius/ YouTube: https://therealdarius.com/youtube Book: The Core Value Equation https://www.amazon.com/Core-Value-Equation-Framework-Limitless/dp/1544506708 Write a review for The Greatness Machine using this link: https://ratethispodcast.com/spreadinggreatness.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Hello, and welcome to the progress theory where we discuss scientific principles for optimising human performance. I am Dr Phil Price and in this episode, we are joined by a roundtable of researchers in forensic psychiatry. We have Jill Colangelo, Dr Alexander Smith, and Professor Michael Liebrenz, all who are researchers in forensic psychiatry from the University of Bern. Now if you take the whole population, we know that a very small subset of them probably have psychopathic traits. Now if we took that subset not from the whole population, but from certain environments or professions such as surgeons or CEOs, we start to see that they have a higher prevalence of psychopathic traits. What about elite sport? How prevalent is psychopathy in elite sport? So that's where we brought this roundtable together so we learn a bit more around psychopathy. What are the pros and cons of psychopathy in certain environments, and how can we identify if we have psychopathic traits? This is quite a serious discussion. So if you feel that you have been affected by any of these topics in this discussion, please check out our show notes because we have several links there which can help. In this episode, we discuss:00:00 Exploring Psychopathy in Elite Sport04:34 Sports Psychiatry Research Journey08:17 Distinguishing Traits from Disorders10:16 Psychopathy: Subset of Antisocial Disorder14:32 "Inevitable Duality of Psychopathic Traits"18:13 Athletes' Traits and Mental Health23:19 Research Limitations on Athlete Privacy24:25 Ethical Issues in Mental Health Diagnosis30:14 Media's Heroic Portrayal Critiqued32:48 Narcissism in Amateur Athletes35:48 Mental Health Awareness vs. Advertising41:00 Increased Accountability in Public Life43:28 Surprising Lack of Psychopathy Awareness45:56 "Charisma and Its Impact"50:32 Charismatic Traits and Social Disruption53:20 "Recognising and Understanding Abusive Traits"TakeawaysPsychopathic traits aren't always what you think: While often misunderstood, these traits include charm, manipulativeness, and a lack of empathy. Importantly, possessing traits is not the same as having a clinical diagnosis. The spectrum is wide, and some traits, like fearlessness or dominance, can sometimes benefit performance—but rarely exist without downsides.The ‘bad boy' image may have a cost: Media and cultural narratives often glamorise ruthlessness and rule-breaking in sport. While these can lead to short-term wins or headlines, the same traits can spill over into negative behaviours—impacting both personal relationships and the integrity of sport.Awareness and education are critical: There's a growing need for coaches, organisations, and athletes themselves to recognise these patterns—not just to improve performance, but to create healthier sporting environments. It's also vital not to make "armchair diagnoses" but rather understand the complexity and seek professional guidance when needed.FOLLOW OUR PODCASTFollow our Host / Guest@theprogresstheory@drphilprice@jillcolangelo

In today's podcast, Claire and Rachel chat with Dr. Quentin Genuis, an Emergency Physician at St. Paul's Hospital in Vancouver. Quentin weaves together his experience in the emergency room with theological reflection, responding to tough and tender issues that face all of us, whether we like to admit it or not: human dignity, death and dying, and addiction. Quentin repeatedly invites us into the place of compassion, or co-suffering, with human persons. He will teach Healthcare and the Christian Life (June 9-13) in just a few weeks. There's still time to join us!BioDr. Quentin Genuis is an Emergency Physician at St. Paul's Hospital in Vancouver and serves as the Physician Ethicist for Providence Health Care. He holds a Master of Letters in Theology from the University of St. Andrews in Scotland, focusing his research on bioethics. His academic interests include palliative care, end-of-life care, biomedical ethics, personal autonomy, addiction, and theology. Dr. Genuis has contributed to scholarly discussions on the autonomy debates, end-of-life care, compassion, human dignity, and theological anthropology. He is the author of a forthcoming book on Addiction and the Church. Quentin will be with us this summer, teaching "Healthcare and the Christian Life" from June 9-13.Regent College Podcast Thanks for listening. Please like, rate and review us on your podcast platform of choice and share this episode with a friend. Follow Us on Social Media Facebook Instagram Youtube Keep in Touch Regent College Summer Programs Regent College Newsletter

Has the White House gone completely "pay for play"? While experts debate the ethics of U.S. President Donald Trump's latest actions including accepting a plane from Qatar, others are watching his foray into cryptocurrency closely. While many in the space have called for more regulation of crypto, "Trump coin" is causing issues for those trying to build cryptocurrencies as a legitimate financial instrument.Host Mike Eppel discusses this with Erica Pimental, Assistant Professor at the Smith School of Business at Queen's University. We love feedback at The Big Story, as well as suggestions for future episodes. You can find us:Through email at hello@thebigstorypodcast.ca Or @thebigstoryfpn on Twitter

This week on The Beat, CTSNet Editor-in-Chief Joel Dunning speaks with Dr. Dibin Mohammed, a consultant at Government Medical College, Kozhikode, Kerala, India, about his WhatsApp group, Young CVTS Surgeons Kerala. Chapters 00:00 Intro 01:22 CTSNet Updates 03:44 Dr. Mohammed Guest 05:20 Allogeneic Mitral Valve Transplant 08:45 Multiple vs Single Arterial Grafting 11:50 AI & Machine Learning in CT Surgery 17:57 3-Port vs 4-Port Robotic Lobectomy 21:28 Redo Pulm Valve Replacement w RAA 24:32 Mitral Ann Disjunction Presentation 27:09 How-To LVOTE & CABG 29:22 Dr. Mohammed, Academic Group Chat 42:30 Upcoming Events 43:43 Closing They discuss the group's goal and the topics its covers, such as recent academic papers and innovative surgical solutions, as well as the reasons Dr. Mohammed created it. Dr. Mohammed also shares insights into working in India and the training systems for residents in the country.   Joel also highlights recent JANS articles on allogeneic mitral valve transplants, survival outcomes after multiple vs single arterial grafting among patients with reduced ejection fraction, artificial intelligence and machine learning in cardiothoracic surgery, and a comparative study of three-port vs. four-port robotic-assisted lobectomy for NSCLC.   In addition, Joel explores redo pulmonary valve replacement with right atrial appendage, how to perform a left ventricular outflow tract enlargement and CABG, and reviews a presentation from the Society for Cardiothoracic Surgery in Great Britain and Ireland Annual Meeting on mitral annular disjunction and mitral valve repair.   JANS Items Mentioned  1.) Allogeneic Mitral Valve Transplant: Historical Precedent, Current Considerations, and Future Implementation  2.) Survival Outcomes After Multiple vs Single Arterial Grafting Among Patients With Reduced Ejection Fraction  3.) Artificial Intelligence and Machine Learning in Cardiothoracic Surgery: Future Prospects and Ethical Issues  4.) Optimizing Surgical Precision: A Comparative Study of Three-Port vs. Four-Port Robotic-Assisted Lobectomy for NSCLC  CTSNET Content Mentioned  1.) Redo Pulmonary Valve Replacement With Right Atrial Appendage  2.) SCTS 2025 | Mitral Annular Disjunction and Mitral Valve Repair   3.) How to Perform a Left Ventricular Outflow Tract Enlargement and CABG  Other Items Mentioned  1.) Aortic Valve Replacement Series   2.) Career Center   3.) CTSNet Events Calendar  Disclaimer The information and views presented on CTSNet.org represent the views of the authors and contributors of the material and not of CTSNet. Please review our full disclaimer page here.

EASY LISTENING DEP'T.: This is only about “dueling perspectives” in the same sense that New York City and Al-Qaeda had different ideas about the best use for the World Trade Center. Please visit, read, and support INDIGNITY! https://www.indignity.net/

A fertility industry conference held in Singapore last weekend has considered some of the ethical issues for donor conceived people.

EP 383 - Jonathan MacDonald is back on the show and keener than ever to get you interested in Ethical Tech.We discuss why now, more than ever, people need to be given the tools, and moral frameworks to inform their interactions with increasingly opaque technology. How things like social media are seemingly set up to keep us amused, distracted and rob us of our critical thinking faculties and what that means for humanity in the long term.Jonathan isn't an anarchist in a tin foil hat (or a cryptoevangelist in a blonde wig come to that) but he is very compelling on why we need to question whether Big Tech algorithms and the people who control them actually have our best interests at heart.He's pretty convinced that they don't, or at least don't care about us beyond what we can do for them. Which is why he has set up SELF - a personal privacy filter - and also ETHICS TV to help people discuss, understand and control their own moral choices around tech.We also chat about the Roman Empire and its attitude to analogous situations. We know plenty of you like to think about that kind of thing quite a lot.*For Apple Podcast chapters, access them from the menu in the bottom right corner of your player*Spotify Video Chapters:00:00 BWB with Jonathan MacDonald02:23 Meet Jonathan03:18 The Mission: Alternative Future for Technology04:44 Humans Are Batteries05:05 The Reality of Free Services05:58 The Normalisation of Surveillance06:29 The Impact of Social Media on Society07:33 The Coercion of Media and Politics08:37 The Evolution of SELF: Personal Privacy Filter09:50 The Demand for Privacy in AI Tools10:50 The Future of Privacy: Self-Sovereign Mechanisms11:47 The Physicality of Data Privacy12:37 The Ineffectiveness of GDPR13:09 The Dark Side of Data Exploitation14:53 The Post-COVID Awareness Shift34:02 Ethics in Technology37:28 The Problem with Modern Democracy39:18 The Importance of Critical Thinking39:58 The Role of Media in Critical Thinking42:30 Education and Critical Thinking46:15 Ethical Issues in AI and Media46:41 The Dystopian Future of AI53:37 Building Ethical Technology01:04:36 Personal Reflections and Advice01:11:08 Quickfire - Get To Know Jonathanbusinesswithoutbullshit.meWatch and subscribe to us on YouTubeFollow us:InstagramTikTokLinkedinTwitterFacebookIf you'd like to be on the show, get in contact - mail@businesswithoutbullshit.meBWB is powered by Oury Clark

Send us a textJoin James and Drey as they tackle ethical issues, such as capital punishment and IVF, through the lens of theology and scripture.

Dark Patterns in Recommendation Systems: Beyond Technical Capabilities1. Engagement Optimization PathologyMetric-Reality Misalignment: Recommendation engines optimize for engagement metrics (time-on-site, clicks, shares) rather than informational integrity or societal benefitEmotional Gradient Exploitation: Mathematical reality shows emotional triggers (particularly negative ones) produce steeper engagement gradientsBusiness-Society KPI Divergence: Fundamental misalignment between profit-oriented optimization and societal needs for stability and truthful informationAlgorithmic Asymmetry: Computational bias toward outrage-inducing content over nuanced critical thinking due to engagement differential2. Neurological Manipulation VectorsDopamine-Driven Feedback Loops: Recommendation systems engineer addictive patterns through variable-ratio reinforcement schedulesTemporal Manipulation: Strategic timing of notifications and content delivery optimized for behavioral conditioningStress Response Exploitation: Cortisol/adrenaline responses to inflammatory content create state-anchored memory formationAttention Zero-Sum Game: Recommendation systems compete aggressively for finite human attention, creating resource depletion3. Technical Architecture of ManipulationFilter Bubble ReinforcementVector similarity metrics inherently amplify confirmation biasN-dimensional vector space exploration increasingly constrained with each interactionIdentity-reinforcing feedback loops create increasingly isolated information ecosystemsMathematical challenge: balancing cosine similarity with exploration entropyPreference Falsification AmplificationSupervised learning systems train on expressed behavior, not true preferencesEngagement signals misinterpreted as value alignmentML systems cannot distinguish performative from authentic interactionTraining on behavior reinforces rather than corrects misinformation trends4. Weaponization MethodologiesCoordinated Inauthentic Behavior (CIB)Troll farms exploit algorithmic governance through computational propagandaInitial signal injection followed by organic amplification ("ignition-propagation" model)Cross-platform vector propagation creates resilient misinformation ecosystemsCost asymmetry: manipulation is orders of magnitude cheaper than defenseAlgorithmic Vulnerability ExploitationReverse-engineered recommendation systems enable targeted manipulationContent policy circumvention through semantic preservation with syntactic variationTime-based manipulation (coordinated bursts to trigger trending algorithms)Exploiting engagement-maximizing distribution pathways5. Documented Harm Case StudiesMyanmar/Facebook (2017-present)Recommendation systems amplified anti-Rohingya contentAlgorithmic acceleration of ethnic dehumanization narrativesEngagement-driven virality of violence-normalizing contentRadicalization PathwaysYouTube's recommendation system demonstrated to create extremism pathways (2019 research)Vector similarity creates "ideological proximity bridges" between mainstream and extremist contentInterest-based entry points (fitness, martial arts) serving as gateways to increasingly extreme ideological contentAbsence of epistemological friction in recommendation transitions6. Governance and Mitigation ChallengesScale-Induced Governance FailureContent volume overwhelms human review capabilitiesSelf-governance models demonstrably insufficient for harm preventionInternational regulatory fragmentation creates enforcement gapsProfit motive fundamentally misaligned with harm reductionPotential CountermeasuresRegulatory frameworks with significant penalties for algorithmic harmInternational cooperation on misinformation/disinformation preventionTreating algorithmic harm similar to environmental pollution (externalized costs)Fundamental reconsideration of engagement-driven business models7. Ethical Frameworks and Human RightsEthical Right to Truth: Information ecosystems should prioritize veracity over engagementFreedom from Algorithmic Harm: Potential recognition of new digital rights in democratic societiesAccountability for Downstream Effects: Legal liability for real-world harm resulting from algorithmic amplificationWealth Concentration Concerns: Connection between misinformation economies and extreme wealth inequality8. Future OutlookIncreased Regulatory Intervention: Forecast of stringent regulation, particularly from EU, Canada, UK, Australia, New ZealandDigital Harm Paradigm Shift: Potential classification of certain recommendation practices as harmful like tobacco or environmental pollutantsMobile Device Anti-Pattern: Possible societal reevaluation of constant connectivity modelsSovereignty Protection: Nations increasingly viewing algorithmic manipulation as national security concernNote: This episode examines the societal implications of recommendation systems powered by vector databases discussed in our previous technical episode, with a focus on potential harms and governance challenges.

In this episode, we begin by discussing the counselling issues and interventions raised in episode 1: Ethical Conflicts. We'll then present this week's case, where the genetic counsellor encountered countertransference. Support us by buying a coffee: https://buymeacoffee.com/gcchatpod Sound engineer: Shaun Allen You will find suggestions for support, our privacy statement and disclaimer, and more information about topics referenced in our discussion on our website. https://gcchatpodcast.libsyn.com/  You can find us on Instagram, Facebook and Bluesky. Join the discussion with #GCchatpodcast References mentioned in our discussion: Crook, et al., (2022). Genetic counseling and diagnostic genetic testing for familial amyotrophic lateral sclerosis and/or frontotemporal dementia: A qualitative study of client experiences. Journal of Genetic Counseling,  https://doi.org/10.1002/jgc4.1591   Crook, et al., (2021). Patient and relative experiences and decision-making about genetic testing and counseling for familial ALS and FTD: A systematic scoping review. Alzheimer Disease & Associated Disorders https://doi.org/10.1097/WAD.0000000000000458   May & Spellecy, (2006). Autonomy, full information and the right not to know. European journal of health law, 6(2), 119-132 World Health Organisation Meeting on Ethical Issues in Medical Genetics (‎1997: Geneva, Switzerland)‎ & WHO Human Genetics Programme. (‎1998)‎. Proposed international guidelines on ethical issues in medical genetics and genetic services: report of WHO meeting on Ethical Issues in Medical Genetics. https://iris.who.int/handle/10665/63910. Vears et al., (2020). Human Genetics Society of Australasia Position Statement: Predictive and Pre-symptomatic Genetic Testing in Adults and Children. Twin Research and Human Genetics.https://doi.org/10.1017/thg.2020.51

Aging Sucks: Unless You Cross the Bridge by Dr. Barbara G. MelamedDr. Barbara Melamed is 80 years of age and marveling at getting smarter and happier every day. Her book Aging Sucks…Unless you Cross the BRIDGE is her fourth major book. It invites you the readers to do self-care for yourselves, your parents, other relatives and tells their children how to preserve their Legacies. Dr. Barbara Melamed is a Clinical Affiliate Professor at the University of Hawaii's Department of Psychology. She has also held professional positions at numerous universities including, University of Florida, Max Planck Institute for Psychiatry and Tubingen University. She served as Dean at Albert Einstein College of Medicine. Numerous international conferences have extended invitations to her. She is also on the Editorial Boards of journals including the Australasia Medical Journal, The International Journal of Legal and Ethical Issues and the International Journal of Human Resilience and Mental Health.A noted therapist and researcher with decades of experience in clinical and health psychology.  In the area of Again, Dr. Melamed was awarded the Biogenesis Health Cluster Award for her research and studies in aging by the Gerontological Society of America.Dr. Melamed is the author of POW: Peace Over War: Using Mediation and Conflict Resolution to Reconcile International and Local Disputes.  A compelling exploration of how mediation can address and resolve some of the world's most challenging conflicts based on her own activism in the Gandhi International Institute of Peace and Mediators Beyond Borders.https://www.peaceendswar.com/https://drmelamed.net/https://www.peaceendswar.com/single-projectwww.amazon.com    http://www.bluefunkbroadcasting.com/root/twia/121924dbmamg.mp3    

Applications for the 2025 AI Engineer Summit are up, and you can save the date for AIE Singapore in April and AIE World's Fair 2025 in June.Happy new year, and thanks for 100 great episodes! Please let us know what you want to see/hear for the next 100!Full YouTube Episode with Slides/ChartsLike and subscribe and hit that bell to get notifs!Timestamps* 00:00 Welcome to the 100th Episode!* 00:19 Reflecting on the Journey* 00:47 AI Engineering: The Rise and Impact* 03:15 Latent Space Live and AI Conferences* 09:44 The Competitive AI Landscape* 21:45 Synthetic Data and Future Trends* 35:53 Creative Writing with AI* 36:12 Legal and Ethical Issues in AI* 38:18 The Data War: GPU Poor vs. GPU Rich* 39:12 The Rise of GPU Ultra Rich* 40:47 Emerging Trends in AI Models* 45:31 The Multi-Modality War* 01:05:31 The Future of AI Benchmarks* 01:13:17 Pionote and Frontier Models* 01:13:47 Niche Models and Base Models* 01:14:30 State Space Models and RWKB* 01:15:48 Inference Race and Price Wars* 01:22:16 Major AI Themes of the Year* 01:22:48 AI Rewind: January to March* 01:26:42 AI Rewind: April to June* 01:33:12 AI Rewind: July to September* 01:34:59 AI Rewind: October to December* 01:39:53 Year-End Reflections and PredictionsTranscript[00:00:00] Welcome to the 100th Episode![00:00:00] Alessio: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co host Swyx for the 100th time today.[00:00:12] swyx: Yay, um, and we're so glad that, yeah, you know, everyone has, uh, followed us in this journey. How do you feel about it? 100 episodes.[00:00:19] Alessio: Yeah, I know.[00:00:19] Reflecting on the Journey[00:00:19] Alessio: Almost two years that we've been doing this. We've had four different studios. Uh, we've had a lot of changes. You know, we used to do this lightning round. When we first started that we didn't like, and we tried to change the question. The answer[00:00:32] swyx: was cursor and perplexity.[00:00:34] Alessio: Yeah, I love mid journey. It's like, do you really not like anything else?[00:00:38] Alessio: Like what's, what's the unique thing? And I think, yeah, we, we've also had a lot more research driven content. You know, we had like 3DAO, we had, you know. Jeremy Howard, we had more folks like that.[00:00:47] AI Engineering: The Rise and Impact[00:00:47] Alessio: I think we want to do more of that too in the new year, like having, uh, some of the Gemini folks, both on the research and the applied side.[00:00:54] Alessio: Yeah, but it's been a ton of fun. I think we both started, I wouldn't say as a joke, we were kind of like, Oh, we [00:01:00] should do a podcast. And I think we kind of caught the right wave, obviously. And I think your rise of the AI engineer posts just kind of get people. Sombra to congregate, and then the AI engineer summit.[00:01:11] Alessio: And that's why when I look at our growth chart, it's kind of like a proxy for like the AI engineering industry as a whole, which is almost like, like, even if we don't do that much, we keep growing just because there's so many more AI engineers. So did you expect that growth or did you expect that would take longer for like the AI engineer thing to kind of like become, you know, everybody talks about it today.[00:01:32] swyx: So, the sign of that, that we have won is that Gartner puts it at the top of the hype curve right now. So Gartner has called the peak in AI engineering. I did not expect, um, to what level. I knew that I was correct when I called it because I did like two months of work going into that. But I didn't know, You know, how quickly it could happen, and obviously there's a chance that I could be wrong.[00:01:52] swyx: But I think, like, most people have come around to that concept. Hacker News hates it, which is a good sign. But there's enough people that have defined it, you know, GitHub, when [00:02:00] they launched GitHub Models, which is the Hugging Face clone, they put AI engineers in the banner, like, above the fold, like, in big So I think it's like kind of arrived as a meaningful and useful definition.[00:02:12] swyx: I think people are trying to figure out where the boundaries are. I think that was a lot of the quote unquote drama that happens behind the scenes at the World's Fair in June. Because I think there's a lot of doubt or questions about where ML engineering stops and AI engineering starts. That's a useful debate to be had.[00:02:29] swyx: In some sense, I actually anticipated that as well. So I intentionally did not. Put a firm definition there because most of the successful definitions are necessarily underspecified and it's actually useful to have different perspectives and you don't have to specify everything from the outset.[00:02:45] Alessio: Yeah, I was at um, AWS reInvent and the line to get into like the AI engineering talk, so to speak, which is, you know, applied AI and whatnot was like, there are like hundreds of people just in line to go in.[00:02:56] Alessio: I think that's kind of what enabled me. People, right? Which is what [00:03:00] you kind of talked about. It's like, Hey, look, you don't actually need a PhD, just, yeah, just use the model. And then maybe we'll talk about some of the blind spots that you get as an engineer with the earlier posts that we also had on on the sub stack.[00:03:11] Alessio: But yeah, it's been a heck of a heck of a two years.[00:03:14] swyx: Yeah.[00:03:15] Latent Space Live and AI Conferences[00:03:15] swyx: You know, I was, I was trying to view the conference as like, so NeurIPS is I think like 16, 17, 000 people. And the Latent Space Live event that we held there was 950 signups. I think. The AI world, the ML world is still very much research heavy. And that's as it should be because ML is very much in a research phase.[00:03:34] swyx: But as we move this entire field into production, I think that ratio inverts into becoming more engineering heavy. So at least I think engineering should be on the same level, even if it's never as prestigious, like it'll always be low status because at the end of the day, you're manipulating APIs or whatever.[00:03:51] swyx: But Yeah, wrapping GPTs, but there's going to be an increasing stack and an art to doing these, these things well. And I, you know, I [00:04:00] think that's what we're focusing on for the podcast, the conference and basically everything I do seems to make sense. And I think we'll, we'll talk about the trends here that apply.[00:04:09] swyx: It's, it's just very strange. So, like, there's a mix of, like, keeping on top of research while not being a researcher and then putting that research into production. So, like, people always ask me, like, why are you covering Neuralibs? Like, this is a ML research conference and I'm like, well, yeah, I mean, we're not going to, to like, understand everything Or reproduce every single paper, but the stuff that is being found here is going to make it through into production at some point, you hope.[00:04:32] swyx: And then actually like when I talk to the researchers, they actually get very excited because they're like, oh, you guys are actually caring about how this goes into production and that's what they really really want. The measure of success is previously just peer review, right? Getting 7s and 8s on their um, Academic review conferences and stuff like citations is one metric, but money is a better metric.[00:04:51] Alessio: Money is a better metric. Yeah, and there were about 2200 people on the live stream or something like that. Yeah, yeah. Hundred on the live stream. So [00:05:00] I try my best to moderate, but it was a lot spicier in person with Jonathan and, and Dylan. Yeah, that it was in the chat on YouTube.[00:05:06] swyx: I would say that I actually also created.[00:05:09] swyx: Layen Space Live in order to address flaws that are perceived in academic conferences. This is not NeurIPS specific, it's ICML, NeurIPS. Basically, it's very sort of oriented towards the PhD student, uh, market, job market, right? Like literally all, basically everyone's there to advertise their research and skills and get jobs.[00:05:28] swyx: And then obviously all the, the companies go there to hire them. And I think that's great for the individual researchers, but for people going there to get info is not great because you have to read between the lines, bring a ton of context in order to understand every single paper. So what is missing is effectively what I ended up doing, which is domain by domain, go through and recap the best of the year.[00:05:48] swyx: Survey the field. And there are, like NeurIPS had a, uh, I think ICML had a like a position paper track, NeurIPS added a benchmarks, uh, datasets track. These are ways in which to address that [00:06:00] issue. Uh, there's always workshops as well. Every, every conference has, you know, a last day of workshops and stuff that provide more of an overview.[00:06:06] swyx: But they're not specifically prompted to do so. And I think really, uh, Organizing a conference is just about getting good speakers and giving them the correct prompts. And then they will just go and do that thing and they do a very good job of it. So I think Sarah did a fantastic job with the startups prompt.[00:06:21] swyx: I can't list everybody, but we did best of 2024 in startups, vision, open models. Post transformers, synthetic data, small models, and agents. And then the last one was the, uh, and then we also did a quick one on reasoning with Nathan Lambert. And then the last one, obviously, was the debate that people were very hyped about.[00:06:39] swyx: It was very awkward. And I'm really, really thankful for John Franco, basically, who stepped up to challenge Dylan. Because Dylan was like, yeah, I'll do it. But He was pro scaling. And I think everyone who is like in AI is pro scaling, right? So you need somebody who's ready to publicly say, no, we've hit a wall.[00:06:57] swyx: So that means you're saying Sam Altman's wrong. [00:07:00] You're saying, um, you know, everyone else is wrong. It helps that this was the day before Ilya went on, went up on stage and then said pre training has hit a wall. And data has hit a wall. So actually Jonathan ended up winning, and then Ilya supported that statement, and then Noam Brown on the last day further supported that statement as well.[00:07:17] swyx: So it's kind of interesting that I think the consensus kind of going in was that we're not done scaling, like you should believe in a better lesson. And then, four straight days in a row, you had Sepp Hochreiter, who is the creator of the LSTM, along with everyone's favorite OG in AI, which is Juergen Schmidhuber.[00:07:34] swyx: He said that, um, we're pre trading inside a wall, or like, we've run into a different kind of wall. And then we have, you know John Frankel, Ilya, and then Noam Brown are all saying variations of the same thing, that we have hit some kind of wall in the status quo of what pre trained, scaling large pre trained models has looked like, and we need a new thing.[00:07:54] swyx: And obviously the new thing for people is some make, either people are calling it inference time compute or test time [00:08:00] compute. I think the collective terminology has been inference time, and I think that makes sense because test time, calling it test, meaning, has a very pre trained bias, meaning that the only reason for running inference at all is to test your model.[00:08:11] swyx: That is not true. Right. Yeah. So, so, I quite agree that. OpenAI seems to have adopted, or the community seems to have adopted this terminology of ITC instead of TTC. And that, that makes a lot of sense because like now we care about inference, even right down to compute optimality. Like I actually interviewed this author who recovered or reviewed the Chinchilla paper.[00:08:31] swyx: Chinchilla paper is compute optimal training, but what is not stated in there is it's pre trained compute optimal training. And once you start caring about inference, compute optimal training, you have a different scaling law. And in a way that we did not know last year.[00:08:45] Alessio: I wonder, because John is, he's also on the side of attention is all you need.[00:08:49] Alessio: Like he had the bet with Sasha. So I'm curious, like he doesn't believe in scaling, but he thinks the transformer, I wonder if he's still. So, so,[00:08:56] swyx: so he, obviously everything is nuanced and you know, I told him to play a character [00:09:00] for this debate, right? So he actually does. Yeah. He still, he still believes that we can scale more.[00:09:04] swyx: Uh, he just assumed the character to be very game for, for playing this debate. So even more kudos to him that he assumed a position that he didn't believe in and still won the debate.[00:09:16] Alessio: Get rekt, Dylan. Um, do you just want to quickly run through some of these things? Like, uh, Sarah's presentation, just the highlights.[00:09:24] swyx: Yeah, we can't go through everyone's slides, but I pulled out some things as a factor of, like, stuff that we were going to talk about. And we'll[00:09:30] Alessio: publish[00:09:31] swyx: the rest. Yeah, we'll publish on this feed the best of 2024 in those domains. And hopefully people can benefit from the work that our speakers have done.[00:09:39] swyx: But I think it's, uh, these are just good slides. And I've been, I've been looking for a sort of end of year recaps from, from people.[00:09:44] The Competitive AI Landscape[00:09:44] swyx: The field has progressed a lot. You know, I think the max ELO in 2023 on LMSys used to be 1200 for LMSys ELOs. And now everyone is at least at, uh, 1275 in their ELOs, and this is across Gemini, Chadjibuti, [00:10:00] Grok, O1.[00:10:01] swyx: ai, which with their E Large model, and Enthopic, of course. It's a very, very competitive race. There are multiple Frontier labs all racing, but there is a clear tier zero Frontier. And then there's like a tier one. It's like, I wish I had everything else. Tier zero is extremely competitive. It's effectively now three horse race between Gemini, uh, Anthropic and OpenAI.[00:10:21] swyx: I would say that people are still holding out a candle for XAI. XAI, I think, for some reason, because their API was very slow to roll out, is not included in these metrics. So it's actually quite hard to put on there. As someone who also does charts, XAI is continually snubbed because they don't work well with the benchmarking people.[00:10:42] swyx: Yeah, yeah, yeah. It's a little trivia for why XAI always gets ignored. The other thing is market share. So these are slides from Sarah. We have it up on the screen. It has gone from very heavily open AI. So we have some numbers and estimates. These are from RAMP. Estimates of open AI market share in [00:11:00] December 2023.[00:11:01] swyx: And this is basically, what is it, GPT being 95 percent of production traffic. And I think if you correlate that with stuff that we asked. Harrison Chase on the LangChain episode, it was true. And then CLAUD 3 launched mid middle of this year. I think CLAUD 3 launched in March, CLAUD 3. 5 Sonnet was in June ish.[00:11:23] swyx: And you can start seeing the market share shift towards opening, uh, towards that topic, uh, very, very aggressively. The more recent one is Gemini. So if I scroll down a little bit, this is an even more recent dataset. So RAM's dataset ends in September 2 2. 2024. Gemini has basically launched a price war at the low end, uh, with Gemini Flash, uh, being basically free for personal use.[00:11:44] swyx: Like, I think people don't understand the free tier. It's something like a billion tokens per day. Unless you're trying to abuse it, you cannot really exhaust your free tier on Gemini. They're really trying to get you to use it. They know they're in like third place, um, fourth place, depending how you, how you count.[00:11:58] swyx: And so they're going after [00:12:00] the Lower tier first, and then, you know, maybe the upper tier later, but yeah, Gemini Flash, according to OpenRouter, is now 50 percent of their OpenRouter requests. Obviously, these are the small requests. These are small, cheap requests that are mathematically going to be more.[00:12:15] swyx: The smart ones obviously are still going to OpenAI. But, you know, it's a very, very big shift in the market. Like basically 2023, 2022, To going into 2024 opening has gone from nine five market share to Yeah. Reasonably somewhere between 50 to 75 market share.[00:12:29] Alessio: Yeah. I'm really curious how ramped does the attribution to the model?[00:12:32] Alessio: If it's API, because I think it's all credit card spin. . Well, but it's all, the credit card doesn't say maybe. Maybe the, maybe when they do expenses, they upload the PDF, but yeah, the, the German I think makes sense. I think that was one of my main 2024 takeaways that like. The best small model companies are the large labs, which is not something I would have thought that the open source kind of like long tail would be like the small model.[00:12:53] swyx: Yeah, different sizes of small models we're talking about here, right? Like so small model here for Gemini is AB, [00:13:00] right? Uh, mini. We don't know what the small model size is, but yeah, it's probably in the double digits or maybe single digits, but probably double digits. The open source community has kind of focused on the one to three B size.[00:13:11] swyx: Mm-hmm . Yeah. Maybe[00:13:12] swyx: zero, maybe 0.5 B uh, that's moon dream and that is small for you then, then that's great. It makes sense that we, we have a range for small now, which is like, may, maybe one to five B. Yeah. I'll even put that at, at, at the high end. And so this includes Gemma from Gemini as well. But also includes the Apple Foundation models, which I think Apple Foundation is 3B.[00:13:32] Alessio: Yeah. No, that's great. I mean, I think in the start small just meant cheap. I think today small is actually a more nuanced discussion, you know, that people weren't really having before.[00:13:43] swyx: Yeah, we can keep going. This is a slide that I smiley disagree with Sarah. She's pointing to the scale SEAL leaderboard. I think the Researchers that I talked with at NeurIPS were kind of positive on this because basically you need private test [00:14:00] sets to prevent contamination.[00:14:02] swyx: And Scale is one of maybe three or four people this year that has really made an effort in doing a credible private test set leaderboard. Llama405B does well compared to Gemini and GPT 40. And I think that's good. I would say that. You know, it's good to have an open model that is that big, that does well on those metrics.[00:14:23] swyx: But anyone putting 405B in production will tell you, if you scroll down a little bit to the artificial analysis numbers, that it is very slow and very expensive to infer. Um, it doesn't even fit on like one node. of, uh, of H100s. Cerebras will be happy to tell you they can serve 4 or 5B on their super large chips.[00:14:42] swyx: But, um, you know, if you need to do anything custom to it, you're still kind of constrained. So, is 4 or 5B really that relevant? Like, I think most people are basically saying that they only use 4 or 5B as a teacher model to distill down to something. Even Meta is doing it. So with Lama 3. [00:15:00] 3 launched, they only launched the 70B because they use 4 or 5B to distill the 70B.[00:15:03] swyx: So I don't know if like open source is keeping up. I think they're the, the open source industrial complex is very invested in telling you that the, if the gap is narrowing, I kind of disagree. I think that the gap is widening with O1. I think there are very, very smart people trying to narrow that gap and they should.[00:15:22] swyx: I really wish them success, but you cannot use a chart that is nearing 100 in your saturation chart. And look, the distance between open source and closed source is narrowing. Of course it's going to narrow because you're near 100. This is stupid. But in metrics that matter, is open source narrowing?[00:15:38] swyx: Probably not for O1 for a while. And it's really up to the open source guys to figure out if they can match O1 or not.[00:15:46] Alessio: I think inference time compute is bad for open source just because, you know, Doc can donate the flops at training time, but he cannot donate the flops at inference time. So it's really hard to like actually keep up on that axis.[00:15:59] Alessio: Big, big business [00:16:00] model shift. So I don't know what that means for the GPU clouds. I don't know what that means for the hyperscalers, but obviously the big labs have a lot of advantage. Because, like, it's not a static artifact that you're putting the compute in. You're kind of doing that still, but then you're putting a lot of computed inference too.[00:16:17] swyx: Yeah, yeah, yeah. Um, I mean, Llama4 will be reasoning oriented. We talked with Thomas Shalom. Um, kudos for getting that episode together. That was really nice. Good, well timed. Actually, I connected with the AI meta guy, uh, at NeurIPS, and, um, yeah, we're going to coordinate something for Llama4. Yeah, yeah,[00:16:32] Alessio: and our friend, yeah.[00:16:33] Alessio: Clara Shi just joined to lead the business agent side. So I'm sure we'll have her on in the new year.[00:16:39] swyx: Yeah. So, um, my comment on, on the business model shift, this is super interesting. Apparently it is wide knowledge that OpenAI wanted more than 6. 6 billion dollars for their fundraise. They wanted to raise, you know, higher, and they did not.[00:16:51] swyx: And what that means is basically like, it's very convenient that we're not getting GPT 5, which would have been a larger pre train. We should have a lot of upfront money. And [00:17:00] instead we're, we're converting fixed costs into variable costs, right. And passing it on effectively to the customer. And it's so much easier to take margin there because you can directly attribute it to like, Oh, you're using this more.[00:17:12] swyx: Therefore you, you pay more of the cost and I'll just slap a margin in there. So like that lets you control your growth margin and like tie your. Your spend, or your sort of inference spend, accordingly. And it's just really interesting to, that this change in the sort of inference paradigm has arrived exactly at the same time that the funding environment for pre training is effectively drying up, kind of.[00:17:36] swyx: I feel like maybe the VCs are very in tune with research anyway, so like, they would have noticed this, but, um, it's just interesting.[00:17:43] Alessio: Yeah, and I was looking back at our yearly recap of last year. Yeah. And the big thing was like the mixed trial price fights, you know, and I think now it's almost like there's nowhere to go, like, you know, Gemini Flash is like basically giving it away for free.[00:17:55] Alessio: So I think this is a good way for the labs to generate more revenue and pass down [00:18:00] some of the compute to the customer. I think they're going to[00:18:02] swyx: keep going. I think that 2, will come.[00:18:05] Alessio: Yeah, I know. Totally. I mean, next year, the first thing I'm doing is signing up for Devin. Signing up for the pro chat GBT.[00:18:12] Alessio: Just to try. I just want to see what does it look like to spend a thousand dollars a month on AI?[00:18:17] swyx: Yes. Yes. I think if your, if your, your job is a, at least AI content creator or VC or, you know, someone who, whose job it is to stay on, stay on top of things, you should already be spending like a thousand dollars a month on, on stuff.[00:18:28] swyx: And then obviously easy to spend, hard to use. You have to actually use. The good thing is that actually Google lets you do a lot of stuff for free now. So like deep research. That they just launched. Uses a ton of inference and it's, it's free while it's in preview.[00:18:45] Alessio: Yeah. They need to put that in Lindy.[00:18:47] Alessio: I've been using Lindy lately. I've been a built a bunch of things once we had flow because I liked the new thing. It's pretty good. I even did a phone call assistant. Um, yeah, they just launched Lindy voice. Yeah, I think once [00:19:00] they get advanced voice mode like capability today, still like speech to text, you can kind of tell.[00:19:06] Alessio: Um, but it's good for like reservations and things like that. So I have a meeting prepper thing. And so[00:19:13] swyx: it's good. Okay. I feel like we've, we've covered a lot of stuff. Uh, I, yeah, I, you know, I think We will go over the individual, uh, talks in a separate episode. Uh, I don't want to take too much time with, uh, this stuff, but that suffice to say that there is a lot of progress in each field.[00:19:28] swyx: Uh, we covered vision. Basically this is all like the audience voting for what they wanted. And then I just invited the best people I could find in each audience, especially agents. Um, Graham, who I talked to at ICML in Vienna, he is currently still number one. It's very hard to stay on top of SweetBench.[00:19:45] swyx: OpenHand is currently still number one. switchbench full, which is the hardest one. He had very good thoughts on agents, which I, which I'll highlight for people. Everyone is saying 2025 is the year of agents, just like they said last year. And, uh, but he had [00:20:00] thoughts on like eight parts of what are the frontier problems to solve in agents.[00:20:03] swyx: And so I'll highlight that talk as well.[00:20:05] Alessio: Yeah. The number six, which is the Hacken agents learn more about the environment, has been a Super interesting to us as well, just to think through, because, yeah, how do you put an agent in an enterprise where most things in an enterprise have never been public, you know, a lot of the tooling, like the code bases and things like that.[00:20:23] Alessio: So, yeah, there's not indexing and reg. Well, yeah, but it's more like. You can't really rag things that are not documented. But people know them based on how they've been doing it. You know, so I think there's almost this like, you know, Oh, institutional knowledge. Yeah, the boring word is kind of like a business process extraction.[00:20:38] Alessio: Yeah yeah, I see. It's like, how do you actually understand how these things are done? I see. Um, and I think today the, the problem is that, Yeah, the agents are, that most people are building are good at following instruction, but are not as good as like extracting them from you. Um, so I think that will be a big unlock just to touch quickly on the Jeff Dean thing.[00:20:55] Alessio: I thought it was pretty, I mean, we'll link it in the, in the things, but. I think the main [00:21:00] focus was like, how do you use ML to optimize the systems instead of just focusing on ML to do something else? Yeah, I think speculative decoding, we had, you know, Eugene from RWKB on the podcast before, like he's doing a lot of that with Fetterless AI.[00:21:12] swyx: Everyone is. I would say it's the norm. I'm a little bit uncomfortable with how much it costs, because it does use more of the GPU per call. But because everyone is so keen on fast inference, then yeah, makes sense.[00:21:24] Alessio: Exactly. Um, yeah, but we'll link that. Obviously Jeff is great.[00:21:30] swyx: Jeff is, Jeff's talk was more, it wasn't focused on Gemini.[00:21:33] swyx: I think people got the wrong impression from my tweet. It's more about how Google approaches ML and uses ML to design systems and then systems feedback into ML. And I think this ties in with Lubna's talk.[00:21:45] Synthetic Data and Future Trends[00:21:45] swyx: on synthetic data where it's basically the story of bootstrapping of humans and AI in AI research or AI in production.[00:21:53] swyx: So her talk was on synthetic data, where like how much synthetic data has grown in 2024 in the pre training side, the post training side, [00:22:00] and the eval side. And I think Jeff then also extended it basically to chips, uh, to chip design. So he'd spend a lot of time talking about alpha chip. And most of us in the audience are like, we're not working on hardware, man.[00:22:11] swyx: Like you guys are great. TPU is great. Okay. We'll buy TPUs.[00:22:14] Alessio: And then there was the earlier talk. Yeah. But, and then we have, uh, I don't know if we're calling them essays. What are we calling these? But[00:22:23] swyx: for me, it's just like bonus for late in space supporters, because I feel like they haven't been getting anything.[00:22:29] swyx: And then I wanted a more high frequency way to write stuff. Like that one I wrote in an afternoon. I think basically we now have an answer to what Ilya saw. It's one year since. The blip. And we know what he saw in 2014. We know what he saw in 2024. We think we know what he sees in 2024. He gave some hints and then we have vague indications of what he saw in 2023.[00:22:54] swyx: So that was the Oh, and then 2016 as well, because of this lawsuit with Elon, OpenAI [00:23:00] is publishing emails from Sam's, like, his personal text messages to Siobhan, Zelis, or whatever. So, like, we have emails from Ilya saying, this is what we're seeing in OpenAI, and this is why we need to scale up GPUs. And I think it's very prescient in 2016 to write that.[00:23:16] swyx: And so, like, it is exactly, like, basically his insights. It's him and Greg, basically just kind of driving the scaling up of OpenAI, while they're still playing Dota. They're like, no, like, we see the path here.[00:23:30] Alessio: Yeah, and it's funny, yeah, they even mention, you know, we can only train on 1v1 Dota. We need to train on 5v5, and that takes too many GPUs.[00:23:37] Alessio: Yeah,[00:23:37] swyx: and at least for me, I can speak for myself, like, I didn't see the path from Dota to where we are today. I think even, maybe if you ask them, like, they wouldn't necessarily draw a straight line. Yeah,[00:23:47] Alessio: no, definitely. But I think like that was like the whole idea of almost like the RL and we talked about this with Nathan on his podcast.[00:23:55] Alessio: It's like with RL, you can get very good at specific things, but then you can't really like generalize as much. And I [00:24:00] think the language models are like the opposite, which is like, you're going to throw all this data at them and scale them up, but then you really need to drive them home on a specific task later on.[00:24:08] Alessio: And we'll talk about the open AI reinforcement, fine tuning, um, announcement too, and all of that. But yeah, I think like scale is all you need. That's kind of what Elia will be remembered for. And I think just maybe to clarify on like the pre training is over thing that people love to tweet. I think the point of the talk was like everybody, we're scaling these chips, we're scaling the compute, but like the second ingredient which is data is not scaling at the same rate.[00:24:35] Alessio: So it's not necessarily pre training is over. It's kind of like What got us here won't get us there. In his email, he predicted like 10x growth every two years or something like that. And I think maybe now it's like, you know, you can 10x the chips again, but[00:24:49] swyx: I think it's 10x per year. Was it? I don't know.[00:24:52] Alessio: Exactly. And Moore's law is like 2x. So it's like, you know, much faster than that. And yeah, I like the fossil fuel of AI [00:25:00] analogy. It's kind of like, you know, the little background tokens thing. So the OpenAI reinforcement fine tuning is basically like, instead of fine tuning on data, you fine tune on a reward model.[00:25:09] Alessio: So it's basically like, instead of being data driven, it's like task driven. And I think people have tasks to do, they don't really have a lot of data. So I'm curious to see how that changes, how many people fine tune, because I think this is what people run into. It's like, Oh, you can fine tune llama. And it's like, okay, where do I get the data?[00:25:27] Alessio: To fine tune it on, you know, so it's great that we're moving the thing. And then I really like he had this chart where like, you know, the brain mass and the body mass thing is basically like mammals that scaled linearly by brain and body size, and then humans kind of like broke off the slope. So it's almost like maybe the mammal slope is like the pre training slope.[00:25:46] Alessio: And then the post training slope is like the, the human one.[00:25:49] swyx: Yeah. I wonder what the. I mean, we'll know in 10 years, but I wonder what the y axis is for, for Ilya's SSI. We'll try to get them on.[00:25:57] Alessio: Ilya, if you're listening, you're [00:26:00] welcome here. Yeah, and then he had, you know, what comes next, like agent, synthetic data, inference, compute, I thought all of that was like that.[00:26:05] Alessio: I don't[00:26:05] swyx: think he was dropping any alpha there. Yeah, yeah, yeah.[00:26:07] Alessio: Yeah. Any other new reps? Highlights?[00:26:10] swyx: I think that there was comparatively a lot more work. Oh, by the way, I need to plug that, uh, my friend Yi made this, like, little nice paper. Yeah, that was really[00:26:20] swyx: nice.[00:26:20] swyx: Uh, of, uh, of, like, all the, he's, she called it must read papers of 2024.[00:26:26] swyx: So I laid out some of these at NeurIPS, and it was just gone. Like, everyone just picked it up. Because people are dying for, like, little guidance and visualizations And so, uh, I thought it was really super nice that we got there.[00:26:38] Alessio: Should we do a late in space book for each year? Uh, I thought about it. For each year we should.[00:26:42] Alessio: Coffee table book. Yeah. Yeah. Okay. Put it in the will. Hi, Will. By the way, we haven't introduced you. He's our new, you know, general organist, Jamie. You need to[00:26:52] swyx: pull up more things. One thing I saw that, uh, Okay, one fun one, and then one [00:27:00] more general one. So the fun one is this paper on agent collusion. This is a paper on steganography.[00:27:06] swyx: This is secret collusion among AI agents, multi agent deception via steganography. I tried to go to NeurIPS in order to find these kinds of papers because the real reason Like NeurIPS this year has a lottery system. A lot of people actually even go and don't buy tickets because they just go and attend the side events.[00:27:22] swyx: And then also the people who go and end up crowding around the most popular papers, which you already know and already read them before you showed up to NeurIPS. So the only reason you go there is to talk to the paper authors, but there's like something like 10, 000 other. All these papers out there that, you know, are just people's work that they, that they did on the air and they failed to get attention for one reason or another.[00:27:42] swyx: And this was one of them. Uh, it was like all the way at the back. And this is a deep mind paper that actually focuses on collusion between AI agents, uh, by hiding messages in the text that they generate. Uh, so that's what steganography is. So a very simple example would be the first letter of every word.[00:27:57] swyx: If you Pick that out, you know, and the code sends a [00:28:00] different message than that. But something I've always emphasized is to LLMs, we read left to right. LLMs can read up, down, sideways, you know, in random character order. And it's the same to them as it is to us. So if we were ever to get You know, self motivated, underlined LLMs that we're trying to collaborate to take over the planet.[00:28:19] swyx: This would be how they do it. They spread messages among us in the messages that we generate. And he developed a scaling law for that. So he marked, I'm showing it on screen right now, the emergence of this phenomenon. Basically, for example, for Cypher encoding, GPT 2, Lama 2, mixed trial, GPT 3. 5, zero capabilities, and sudden 4.[00:28:40] swyx: And this is the kind of Jason Wei type emergence properties that people kind of look for. I think what made this paper stand out as well, so he developed the benchmark for steganography collusion, and he also focused on shelling point collusion, which is very low coordination. For agreeing on a decoding encoding format, you kind of need to have some [00:29:00] agreement on that.[00:29:00] swyx: But, but shelling point means like very, very low or almost no coordination. So for example, if I, if I ask someone, if the only message I give you is meet me in New York and you're not aware. Or when you would probably meet me at Grand Central Station. That is the Grand Central Station is a shelling point.[00:29:16] swyx: And it's probably somewhere, somewhere during the day. That is the shelling point of New York is Grand Central. To that extent, shelling points for steganography are things like the, the, the common decoding methods that we talked about. It will be interesting at some point in the future when we are worried about alignment.[00:29:30] swyx: It is not interesting today, but it's interesting that DeepMind is already thinking about this.[00:29:36] Alessio: I think that's like one of the hardest things about NeurIPS. It's like the long tail. I[00:29:41] swyx: found a pricing guy. I'm going to feature him on the podcast. Basically, this guy from NVIDIA worked out the optimal pricing for language models.[00:29:51] swyx: It's basically an econometrics paper at NeurIPS, where everyone else is talking about GPUs. And the guy with the GPUs is[00:29:57] Alessio: talking[00:29:57] swyx: about economics instead. [00:30:00] That was the sort of fun one. So the focus I saw is that model papers at NeurIPS are kind of dead. No one really presents models anymore. It's just data sets.[00:30:12] swyx: This is all the grad students are working on. So like there was a data sets track and then I was looking around like, I was like, you don't need a data sets track because every paper is a data sets paper. And so data sets and benchmarks, they're kind of flip sides of the same thing. So Yeah. Cool. Yeah, if you're a grad student, you're a GPU boy, you kind of work on that.[00:30:30] swyx: And then the, the sort of big model that people walk around and pick the ones that they like, and then they use it in their models. And that's, that's kind of how it develops. I, I feel like, um, like, like you didn't last year, you had people like Hao Tian who worked on Lava, which is take Lama and add Vision.[00:30:47] swyx: And then obviously actually I hired him and he added Vision to Grok. Now he's the Vision Grok guy. This year, I don't think there was any of those.[00:30:55] Alessio: What were the most popular, like, orals? Last year it was like the [00:31:00] Mixed Monarch, I think, was like the most attended. Yeah, uh, I need to look it up. Yeah, I mean, if nothing comes to mind, that's also kind of like an answer in a way.[00:31:10] Alessio: But I think last year there was a lot of interest in, like, furthering models and, like, different architectures and all of that.[00:31:16] swyx: I will say that I felt the orals, oral picks this year were not very good. Either that or maybe it's just a So that's the highlight of how I have changed in terms of how I view papers.[00:31:29] swyx: So like, in my estimation, two of the best papers in this year for datasets or data comp and refined web or fine web. These are two actually industrially used papers, not highlighted for a while. I think DCLM got the spotlight, FineWeb didn't even get the spotlight. So like, it's just that the picks were different.[00:31:48] swyx: But one thing that does get a lot of play that a lot of people are debating is the role that's scheduled. This is the schedule free optimizer paper from Meta from Aaron DeFazio. And this [00:32:00] year in the ML community, there's been a lot of chat about shampoo, soap, all the bathroom amenities for optimizing your learning rates.[00:32:08] swyx: And, uh, most people at the big labs are. Who I asked about this, um, say that it's cute, but it's not something that matters. I don't know, but it's something that was discussed and very, very popular. 4Wars[00:32:19] Alessio: of AI recap maybe, just quickly. Um, where do you want to start? Data?[00:32:26] swyx: So to remind people, this is the 4Wars piece that we did as one of our earlier recaps of this year.[00:32:31] swyx: And the belligerents are on the left, journalists, writers, artists, anyone who owns IP basically, New York Times, Stack Overflow, Reddit, Getty, Sarah Silverman, George RR Martin. Yeah, and I think this year we can add Scarlett Johansson to that side of the fence. So anyone suing, open the eye, basically. I actually wanted to get a snapshot of all the lawsuits.[00:32:52] swyx: I'm sure some lawyer can do it. That's the data quality war. On the right hand side, we have the synthetic data people, and I think we talked about Lumna's talk, you know, [00:33:00] really showing how much synthetic data has come along this year. I think there was a bit of a fight between scale. ai and the synthetic data community, because scale.[00:33:09] swyx: ai published a paper saying that synthetic data doesn't work. Surprise, surprise, scale. ai is the leading vendor of non synthetic data. Only[00:33:17] Alessio: cage free annotated data is useful.[00:33:21] swyx: So I think there's some debate going on there, but I don't think it's much debate anymore that at least synthetic data, for the reasons that are blessed in Luna's talk, Makes sense.[00:33:32] swyx: I don't know if you have any perspectives there.[00:33:34] Alessio: I think, again, going back to the reinforcement fine tuning, I think that will change a little bit how people think about it. I think today people mostly use synthetic data, yeah, for distillation and kind of like fine tuning a smaller model from like a larger model.[00:33:46] Alessio: I'm not super aware of how the frontier labs use it outside of like the rephrase, the web thing that Apple also did. But yeah, I think it'll be. Useful. I think like whether or not that gets us the big [00:34:00] next step, I think that's maybe like TBD, you know, I think people love talking about data because it's like a GPU poor, you know, I think, uh, synthetic data is like something that people can do, you know, so they feel more opinionated about it compared to, yeah, the optimizers stuff, which is like,[00:34:17] swyx: they don't[00:34:17] Alessio: really work[00:34:18] swyx: on.[00:34:18] swyx: I think that there is an angle to the reasoning synthetic data. So this year, we covered in the paper club, the star series of papers. So that's star, Q star, V star. It basically helps you to synthesize reasoning steps, or at least distill reasoning steps from a verifier. And if you look at the OpenAI RFT, API that they released, or that they announced, basically they're asking you to submit graders, or they choose from a preset list of graders.[00:34:49] swyx: Basically It feels like a way to create valid synthetic data for them to fine tune their reasoning paths on. Um, so I think that is another angle where it starts to make sense. And [00:35:00] so like, it's very funny that basically all the data quality wars between Let's say the music industry or like the newspaper publishing industry or the textbooks industry on the big labs.[00:35:11] swyx: It's all of the pre training era. And then like the new era, like the reasoning era, like nobody has any problem with all the reasoning, especially because it's all like sort of math and science oriented with, with very reasonable graders. I think the more interesting next step is how does it generalize beyond STEM?[00:35:27] swyx: We've been using O1 for And I would say like for summarization and creative writing and instruction following, I think it's underrated. I started using O1 in our intro songs before we killed the intro songs, but it's very good at writing lyrics. You know, I can actually say like, I think one of the O1 pro demos.[00:35:46] swyx: All of these things that Noam was showing was that, you know, you can write an entire paragraph or three paragraphs without using the letter A, right?[00:35:53] Creative Writing with AI[00:35:53] swyx: So like, like literally just anything instead of token, like not even token level, character level manipulation and [00:36:00] counting and instruction following. It's, uh, it's very, very strong.[00:36:02] swyx: And so no surprises when I ask it to rhyme, uh, and to, to create song lyrics, it's going to do that very much better than in previous models. So I think it's underrated for creative writing.[00:36:11] Alessio: Yeah.[00:36:12] Legal and Ethical Issues in AI[00:36:12] Alessio: What do you think is the rationale that they're going to have in court when they don't show you the thinking traces of O1, but then they want us to, like, they're getting sued for using other publishers data, you know, but then on their end, they're like, well, you shouldn't be using my data to then train your model.[00:36:29] Alessio: So I'm curious to see how that kind of comes. Yeah, I mean, OPA has[00:36:32] swyx: many ways to publish, to punish people without bringing, taking them to court. Already banned ByteDance for distilling their, their info. And so anyone caught distilling the chain of thought will be just disallowed to continue on, on, on the API.[00:36:44] swyx: And it's fine. It's no big deal. Like, I don't even think that's an issue at all, just because the chain of thoughts are pretty well hidden. Like you have to work very, very hard to, to get it to leak. And then even when it leaks the chain of thought, you don't know if it's, if it's [00:37:00] The bigger concern is actually that there's not that much IP hiding behind it, that Cosign, which we talked about, we talked to him on Dev Day, can just fine tune 4.[00:37:13] swyx: 0 to beat 0. 1 Cloud SONET so far is beating O1 on coding tasks without, at least O1 preview, without being a reasoning model, same for Gemini Pro or Gemini 2. 0. So like, how much is reasoning important? How much of a moat is there in this, like, All of these are proprietary sort of training data that they've presumably accomplished.[00:37:34] swyx: Because even DeepSeek was able to do it. And they had, you know, two months notice to do this, to do R1. So, it's actually unclear how much moat there is. Obviously, you know, if you talk to the Strawberry team, they'll be like, yeah, I mean, we spent the last two years doing this. So, we don't know. And it's going to be Interesting because there'll be a lot of noise from people who say they have inference time compute and actually don't because they just have fancy chain of thought.[00:38:00][00:38:00] swyx: And then there's other people who actually do have very good chain of thought. And you will not see them on the same level as OpenAI because OpenAI has invested a lot in building up the mythology of their team. Um, which makes sense. Like the real answer is somewhere in between.[00:38:13] Alessio: Yeah, I think that's kind of like the main data war story developing.[00:38:18] The Data War: GPU Poor vs. GPU Rich[00:38:18] Alessio: GPU poor versus GPU rich. Yeah. Where do you think we are? I think there was, again, going back to like the small model thing, there was like a time in which the GPU poor were kind of like the rebel faction working on like these models that were like open and small and cheap. And I think today people don't really care as much about GPUs anymore.[00:38:37] Alessio: You also see it in the price of the GPUs. Like, you know, that market is kind of like plummeted because there's people don't want to be, they want to be GPU free. They don't even want to be poor. They just want to be, you know, completely without them. Yeah. How do you think about this war? You[00:38:52] swyx: can tell me about this, but like, I feel like the, the appetite for GPU rich startups, like the, you know, the, the funding plan is we will raise 60 million and [00:39:00] we'll give 50 of that to NVIDIA.[00:39:01] swyx: That is gone, right? Like, no one's, no one's pitching that. This was literally the plan, the exact plan of like, I can name like four or five startups, you know, this time last year. So yeah, GPU rich startups gone.[00:39:12] The Rise of GPU Ultra Rich[00:39:12] swyx: But I think like, The GPU ultra rich, the GPU ultra high net worth is still going. So, um, now we're, you know, we had Leopold's essay on the trillion dollar cluster.[00:39:23] swyx: We're not quite there yet. We have multiple labs, um, you know, XAI very famously, you know, Jensen Huang praising them for being. Best boy number one in spinning up 100, 000 GPU cluster in like 12 days or something. So likewise at Meta, likewise at OpenAI, likewise at the other labs as well. So like the GPU ultra rich are going to keep doing that because I think partially it's an article of faith now that you just need it.[00:39:46] swyx: Like you don't even know what it's going to, what you're going to use it for. You just, you just need it. And it makes sense that if, especially if we're going into. More researchy territory than we are. So let's say 2020 to 2023 was [00:40:00] let's scale big models territory because we had GPT 3 in 2020 and we were like, okay, we'll go from 1.[00:40:05] swyx: 75b to 1. 8b, 1. 8t. And that was GPT 3 to GPT 4. Okay, that's done. As far as everyone is concerned, Opus 3. 5 is not coming out, GPT 4. 5 is not coming out, and Gemini 2, we don't have Pro, whatever. We've hit that wall. Maybe I'll call it the 2 trillion perimeter wall. We're not going to 10 trillion. No one thinks it's a good idea, at least from training costs, from the amount of data, or at least the inference.[00:40:36] swyx: Would you pay 10x the price of GPT Probably not. Like, like you want something else that, that is at least more useful. So it makes sense that people are pivoting in terms of their inference paradigm.[00:40:47] Emerging Trends in AI Models[00:40:47] swyx: And so when it's more researchy, then you actually need more just general purpose compute to mess around with, uh, at the exact same time that production deployments of the old, the previous paradigm is still ramping up,[00:40:58] swyx: um,[00:40:58] swyx: uh, pretty aggressively.[00:40:59] swyx: So [00:41:00] it makes sense that the GPU rich are growing. We have now interviewed both together and fireworks and replicates. Uh, we haven't done any scale yet. But I think Amazon, maybe kind of a sleeper one, Amazon, in a sense of like they, at reInvent, I wasn't expecting them to do so well, but they are now a foundation model lab.[00:41:18] swyx: It's kind of interesting. Um, I think, uh, you know, David went over there and started just creating models.[00:41:25] Alessio: Yeah, I mean, that's the power of prepaid contracts. I think like a lot of AWS customers, you know, they do this big reserve instance contracts and now they got to use their money. That's why so many startups.[00:41:37] Alessio: Get bought through the AWS marketplace so they can kind of bundle them together and prefer pricing.[00:41:42] swyx: Okay, so maybe GPU super rich doing very well, GPU middle class dead, and then GPU[00:41:48] Alessio: poor. I mean, my thing is like, everybody should just be GPU rich. There shouldn't really be, even the GPU poorest, it's like, does it really make sense to be GPU poor?[00:41:57] Alessio: Like, if you're GPU poor, you should just use the [00:42:00] cloud. Yes, you know, and I think there might be a future once we kind of like figure out what the size and shape of these models is where like the tiny box and these things come to fruition where like you can be GPU poor at home. But I think today is like, why are you working so hard to like get these models to run on like very small clusters where it's like, It's so cheap to run them.[00:42:21] Alessio: Yeah, yeah,[00:42:22] swyx: yeah. I think mostly people think it's cool. People think it's a stepping stone to scaling up. So they aspire to be GPU rich one day and they're working on new methods. Like news research, like probably the most deep tech thing they've done this year is Distro or whatever the new name is.[00:42:38] swyx: There's a lot of interest in heterogeneous computing, distributed computing. I tend generally to de emphasize that historically, but it may be coming to a time where it is starting to be relevant. I don't know. You know, SF compute launched their compute marketplace this year, and like, who's really using that?[00:42:53] swyx: Like, it's a bunch of small clusters, disparate types of compute, and if you can make that [00:43:00] useful, then that will be very beneficial to the broader community, but maybe still not the source of frontier models. It's just going to be a second tier of compute that is unlocked for people, and that's fine. But yeah, I mean, I think this year, I would say a lot more on device, We are, I now have Apple intelligence on my phone.[00:43:19] swyx: Doesn't do anything apart from summarize my notifications. But still, not bad. Like, it's multi modal.[00:43:25] Alessio: Yeah, the notification summaries are so and so in my experience.[00:43:29] swyx: Yeah, but they add, they add juice to life. And then, um, Chrome Nano, uh, Gemini Nano is coming out in Chrome. Uh, they're still feature flagged, but you can, you can try it now if you, if you use the, uh, the alpha.[00:43:40] swyx: And so, like, I, I think, like, you know, We're getting the sort of GPU poor version of a lot of these things coming out, and I think it's like quite useful. Like Windows as well, rolling out RWKB in sort of every Windows department is super cool. And I think the last thing that I never put in this GPU poor war, that I think I should now, [00:44:00] is the number of startups that are GPU poor but still scaling very well, as sort of wrappers on top of either a foundation model lab, or GPU Cloud.[00:44:10] swyx: GPU Cloud, it would be Suno. Suno, Ramp has rated as one of the top ranked, fastest growing startups of the year. Um, I think the last public number is like zero to 20 million this year in ARR and Suno runs on Moto. So Suno itself is not GPU rich, but they're just doing the training on, on Moto, uh, who we've also talked to on, on the podcast.[00:44:31] swyx: The other one would be Bolt, straight cloud wrapper. And, and, um, Again, another, now they've announced 20 million ARR, which is another step up from our 8 million that we put on the title. So yeah, I mean, it's crazy that all these GPU pores are finding a way while the GPU riches are also finding a way. And then the only failures, I kind of call this the GPU smiling curve, where the edges do well, because you're either close to the machines, and you're like [00:45:00] number one on the machines, or you're like close to the customers, and you're number one on the customer side.[00:45:03] swyx: And the people who are in the middle. Inflection, um, character, didn't do that great. I think character did the best of all of them. Like, you have a note in here that we apparently said that character's price tag was[00:45:15] Alessio: 1B.[00:45:15] swyx: Did I say that?[00:45:16] Alessio: Yeah. You said Google should just buy them for 1B. I thought it was a crazy number.[00:45:20] Alessio: Then they paid 2. 7 billion. I mean, for like,[00:45:22] swyx: yeah.[00:45:22] Alessio: What do you pay for node? Like, I don't know what the game world was like. Maybe the starting price was 1B. I mean, whatever it was, it worked out for everybody involved.[00:45:31] The Multi-Modality War[00:45:31] Alessio: Multimodality war. And this one, we never had text to video in the first version, which now is the hottest.[00:45:37] swyx: Yeah, I would say it's a subset of image, but yes.[00:45:40] Alessio: Yeah, well, but I think at the time it wasn't really something people were doing, and now we had VO2 just came out yesterday. Uh, Sora was released last month, last week. I've not tried Sora, because the day that I tried, it wasn't, yeah. I[00:45:54] swyx: think it's generally available now, you can go to Sora.[00:45:56] swyx: com and try it. Yeah, they had[00:45:58] Alessio: the outage. Which I [00:46:00] think also played a part into it. Small things. Yeah. What's the other model that you posted today that was on Replicate? Video or OneLive?[00:46:08] swyx: Yeah. Very, very nondescript name, but it is from Minimax, which I think is a Chinese lab. The Chinese labs do surprisingly well at the video models.[00:46:20] swyx: I'm not sure it's actually Chinese. I don't know. Hold me up to that. Yep. China. It's good. Yeah, the Chinese love video. What can I say? They have a lot of training data for video. Or a more relaxed regulatory environment.[00:46:37] Alessio: Uh, well, sure, in some way. Yeah, I don't think there's much else there. I think like, you know, on the image side, I think it's still open.[00:46:45] Alessio: Yeah, I mean,[00:46:46] swyx: 11labs is now a unicorn. So basically, what is multi modality war? Multi modality war is, do you specialize in a single modality, right? Or do you have GodModel that does all the modalities? So this is [00:47:00] definitely still going, in a sense of 11 labs, you know, now Unicorn, PicoLabs doing well, they launched Pico 2.[00:47:06] swyx: 0 recently, HeyGen, I think has reached 100 million ARR, Assembly, I don't know, but they have billboards all over the place, so I assume they're doing very, very well. So these are all specialist models, specialist models and specialist startups. And then there's the big labs who are doing the sort of all in one play.[00:47:24] swyx: And then here I would highlight Gemini 2 for having native image output. Have you seen the demos? Um, yeah, it's, it's hard to keep up. Literally they launched this last week and a shout out to Paige Bailey, who came to the Latent Space event to demo on the day of launch. And she wasn't prepared. She was just like, I'm just going to show you.[00:47:43] swyx: So they have voice. They have, you know, obviously image input, and then they obviously can code gen and all that. But the new one that OpenAI and Meta both have but they haven't launched yet is image output. So you can literally, um, I think their demo video was that you put in an image of a [00:48:00] car, and you ask for minor modifications to that car.[00:48:02] swyx: They can generate you that modification exactly as you asked. So there's no need for the stable diffusion or comfy UI workflow of like mask here and then like infill there in paint there and all that, all that stuff. This is small model nonsense. Big model people are like, huh, we got you in as everything in the transformer.[00:48:21] swyx: This is the multimodality war, which is, do you, do you bet on the God model or do you string together a whole bunch of, uh, Small models like a, like a chump. Yeah,[00:48:29] Alessio: I don't know, man. Yeah, that would be interesting. I mean, obviously I use Midjourney for all of our thumbnails. Um, they've been doing a ton on the product, I would say.[00:48:38] Alessio: They launched a new Midjourney editor thing. They've been doing a ton. Because I think, yeah, the motto is kind of like, Maybe, you know, people say black forest, the black forest models are better than mid journey on a pixel by pixel basis. But I think when you put it, put it together, have you tried[00:48:53] swyx: the same problems on black forest?[00:48:55] Alessio: Yes. But the problem is just like, you know, on black forest, it generates one image. And then it's like, you got to [00:49:00] regenerate. You don't have all these like UI things. Like what I do, no, but it's like time issue, you know, it's like a mid[00:49:06] swyx: journey. Call the API four times.[00:49:08] Alessio: No, but then there's no like variate.[00:49:10] Alessio: Like the good thing about mid journey is like, you just go in there and you're cooking. There's a lot of stuff that just makes it really easy. And I think people underestimate that. Like, it's not really a skill issue, because I'm paying mid journey, so it's a Black Forest skill issue, because I'm not paying them, you know?[00:49:24] Alessio: Yeah,[00:49:25] swyx: so, okay, so, uh, this is a UX thing, right? Like, you, you, you understand that, at least, we think that Black Forest should be able to do all that stuff. I will also shout out, ReCraft has come out, uh, on top of the image arena that, uh, artificial analysis has done, has apparently, uh, Flux's place. Is this still true?[00:49:41] swyx: So, Artificial Analysis is now a company. I highlighted them I think in one of the early AI Newses of the year. And they have launched a whole bunch of arenas. So, they're trying to take on LM Arena, Anastasios and crew. And they have an image arena. Oh yeah, Recraft v3 is now beating Flux 1. 1. Which is very surprising [00:50:00] because Flux And Black Forest Labs are the old stable diffusion crew who left stability after, um, the management issues.[00:50:06] swyx: So Recurve has come from nowhere to be the top image model. Uh, very, very strange. I would also highlight that Grok has now launched Aurora, which is, it's very interesting dynamics between Grok and Black Forest Labs because Grok's images were originally launched, uh, in partnership with Black Forest Labs as a, as a thin wrapper.[00:50:24] swyx: And then Grok was like, no, we'll make our own. And so they've made their own. I don't know, there are no APIs or benchmarks about it. They just announced it. So yeah, that's the multi modality war. I would say that so far, the small model, the dedicated model people are winning, because they are just focused on their tasks.[00:50:42] swyx: But the big model, People are always catching up. And the moment I saw the Gemini 2 demo of image editing, where I can put in an image and just request it and it does, that's how AI should work. Not like a whole bunch of complicated steps. So it really is something. And I think one frontier that we haven't [00:51:00] seen this year, like obviously video has done very well, and it will continue to grow.[00:51:03] swyx: You know, we only have Sora Turbo today, but at some point we'll get full Sora. Oh, at least the Hollywood Labs will get Fulsora. We haven't seen video to audio, or video synced to audio. And so the researchers that I talked to are already starting to talk about that as the next frontier. But there's still maybe like five more years of video left to actually be Soda.[00:51:23] swyx: I would say that Gemini's approach Compared to OpenAI, Gemini seems, or DeepMind's approach to video seems a lot more fully fledged than OpenAI. Because if you look at the ICML recap that I published that so far nobody has listened to, um, that people have listened to it. It's just a different, definitely different audience.[00:51:43] swyx: It's only seven hours long. Why are people not listening? It's like everything in Uh, so, so DeepMind has, is working on Genie. They also launched Genie 2 and VideoPoet. So, like, they have maybe four years advantage on world modeling that OpenAI does not have. Because OpenAI basically only started [00:52:00] Diffusion Transformers last year, you know, when they hired, uh, Bill Peebles.[00:52:03] swyx: So, DeepMind has, has a bit of advantage here, I would say, in, in, in showing, like, the reason that VO2, while one, They cherry pick their videos. So obviously it looks better than Sora, but the reason I would believe that VO2, uh, when it's fully launched will do very well is because they have all this background work in video that they've done for years.[00:52:22] swyx: Like, like last year's NeurIPS, I already was interviewing some of their video people. I forget their model name, but for, for people who are dedicated fans, they can go to NeurIPS 2023 and see, see that paper.[00:52:32] Alessio: And then last but not least, the LLMOS. We renamed it to Ragops, formerly known as[00:52:39] swyx: Ragops War. I put the latest chart on the Braintrust episode.[00:52:43] swyx: I think I'm going to separate these essays from the episode notes. So the reason I used to do that, by the way, is because I wanted to show up on Hacker News. I wanted the podcast to show up on Hacker News. So I always put an essay inside of there because Hacker News people like to read and not listen.[00:52:58] Alessio: So episode essays,[00:52:59] swyx: I remember [00:53:00] purchasing them separately. You say Lanchain Llama Index is still growing.[00:53:03] Alessio: Yeah, so I looked at the PyPy stats, you know. I don't care about stars. On PyPy you see Do you want to share your screen? Yes. I prefer to look at actual downloads, not at stars on GitHub. So if you look at, you know, Lanchain still growing.[00:53:20] Alessio: These are the last six months. Llama Index still growing. What I've basically seen is like things that, One, obviously these things have A commercial product. So there's like people buying this and sticking with it versus kind of hopping in between things versus, you know, for example, crew AI, not really growing as much.[00:53:38] Alessio: The stars are growing. If you look on GitHub, like the stars are growing, but kind of like the usage is kind of like flat. In the last six months, have they done some[00:53:4

Like many parts of travel, in recent years I've started to rethink some aspects of museum that I just took for granted in my early years of travel. In this episode, I chat with three guests on a variety of aspects of the ethics of museums, which all gave me great food for thought. First up, I spoke with Chris Christou, who articulates some of the key ethical issues many museums face, especially those that are focused on archaeological artefacts - some of which might not have been acquired in the most ethical of ways! Next, Dylan Thuras of Atlas Obscura tells me about his particular interest in medical museums, and some of the questions surrounding these, and includes an interesting example of a museum he visited in Mexico. Artist Carol McQuaid highlights a recent art gallery scandal involving MONA in Tasmania, Australia, which she had the opportunity to visit recently. While chatting galleries, I was reminded of my recent experience at the Manchester Art Gallery in England, which has recently had a significant rethink of how they run their displays. Links: Chris Christou - The End of Tourism podcast - https://www.theendoftourism.com/ Dylan Thuras - Atlas Obscura podcast https://www.atlasobscura.com/podcast Atlas Obscura article about the Mummies of Guanajuato - https://www.atlasobscura.com/places/museo-de-las-momias-de-guanajuato Carol McQuaid - https://www.theillustratedvagabond.com/ Carol’s World Voyage Sketchbook - https://www.theillustratedvagabond.com/shop/p/illustrated-vagabonds-world-voyage-sketchbook-pre-sale Catherine’s article about the Ladies Lounge in Mona - https://www.smh.com.au/traveller/inspiration/mona-ladies-lounge-high-tea-inside-the-secretive-new-womenonly-experience-20220530-h243zx.html Join our Facebook group for Thoughtful Travellers - https://www.facebook.com/groups/thoughtfultravellers Join our LinkedIn group for Thoughtful Travellers - https://notaballerina.com/linkedin Sign up for the Thoughtful Travellers newsletter at Substack - https://thoughtfultravel.substack.com Show notes: https://notaballerina.com/329 See omnystudio.com/listener for privacy information.

Send us a textAs AI becomes more integrated into our lives, many believe it will revolutionize nearly every industry, with healthcare being one of them. Ed Zitron is not one of those people.In this episode of CareTalk, David Williams speaks with Ed Zitron, CEO of EZPR, on why he believes AI is a bubble ready to burst and the ramifications of AI on everything from patient care to climate change.This episode is brought to you by BetterHelp. Give online therapy a try at https://betterhelp.com/caretalk and get on your way to being your best self.As a BetterHelp affiliate, we may receive compensation from BetterHelp if you purchase products or services through the links provided.TOPICS(0:24) Intro(0:43) Sponsorship(1:58) Should We Be Optimistic About AI?(2:52) Will AI Investments Be Worth It?(4:42) Why Are People Excited About AI?(6:34) AI's Role in Capitalism(8:24) Are You the Customer or the Product?(9:34) Is It AI or Just a Chatbot?(11:47) Can AI Improve Healthcare Efficiency?(14:55) Can AI Improve After-Appointment Care?(17:29) The Ethical Issues with AI(19:32) Will Nuclear Power Fix AI's Eco-Damage?(20:42) Will the AI Bubble Pop?(23:11) Is There a Role for Regulators in AI?(24:18) How Should the Public Think About AI?

This episode focuses on the ethical issues for defense counsel in a New York Workers' Compensation Case and discusses conflicts of interest relating to insured clients. Greg Lois (https://loisllc.com/attorney/greg-lois/) also discuss legal billing guidelines, representation that exceeds boundaries of workers' compensation act (particularly in the context of release and resignation requests), candor to the tribunal and adversary, sworn pleadings, and contact and co-operation with adversary. How to attend these webinars live and ask questions Join us for our monthly webinars on New York and New Jersey workers' compensation law. Register for a New York Workers' Compensation Webinar (https://attendee.gotowebinar.com/register/8126129122765451535) Register for a New Jersey Workers' Compensation Webinar (https://register.gotowebinar.com/register/5291331929217948419) Register for a Civil Litigation Webinar (https://register.gotowebinar.com/register/2939203908210686476) Schedules and Information Handout materials are provided in advance of each session. The webinar courses follow the "life cycle" of a claim and correspond to chapters in the Workers' Compensation Handbooks (https://loisllc.com/publications/) offered by the Firm. Webinar Archive View archive of prior Workers' Compensation and Civil Litigation webinars (https://loisllc.com/webinars/archive/) Disclaimer This webinar is not legal advice! The materials presented by this webinar/podcast and any affiliated website are for informational purposes only and are not offered as legal advice as to any particular matter. No viewer/listener/reader should act on the basis of these materials without seeking appropriate professional advice as to the particular facts and applicable law involved. The materials are not represented to be correct, complete, or up-to-date. Opinions presented by this video/podcast are the opinions of the author. Neither the use of this web site nor the transfer of information to or from this web site shall create or constitute an attorney-client relationship between Greg Lois, the presenter in the video/podcast, or LOIS LAW FIRM LLC and any person. You should not send any confidential information to this web site until after you have entered into a written agreement for the performance of legal services.

In this episode of CISO Tradecraft, hosts G Mark Hardy and Mark Rasch discuss the intersection of artificial intelligence and the law. Recorded at the COSAC computer conference in Dublin, this episode covers the legal implications of AI, copyright issues, AI-generated content, privacy concerns, and ethical considerations. They explore the nuances between directed and undirected AI, the importance of training data, and the potential risks and liabilities associated with AI-driven systems. Tune in for a deep dive into how AI is reshaping cybersecurity and legal landscapes. Transcripts: https://docs.google.com/document/d/1s_eDwz-FPuyxYZRJaOknWi2Ozjqmodrl Chapters 00:00 Introductions 01:13 Diving into Artificial Intelligence 04:04 Directed vs. Undirected AI 11:02 Legal and Ethical Issues of AI 23:47 AI and Copyright: Who Owns the Creation? 26:59 The Role of AI in Information Security 32:51 Ethical Dilemmas in AI Decision-Making 39:18 Future Challenges and Recommendations for AI

A proposal in Congress would offer a tax credit for Americans who donate kidneys. We discuss the pros and cons of financial incentives for kidney donation. Plus, there's a new TikTok fashion trend that hits home here in the desert. That and more on The Show.

Chapter 9: Criminal Law in Practice delves into the real-world applications of criminal law, examining the roles of defense attorneys and prosecutors, the broader impact of criminal law on society, and the ethical challenges faced by legal professionals. The chapter is divided into several key sections, each focusing on different aspects of criminal law practice. 1. Case Studies and Practical Applications. This section highlights the importance of understanding how criminal law principles are applied in real-world situations. Through the analysis of landmark cases like Miranda v Arizona, Gideon v Wainwright, and Roper v Simmons, the chapter illustrates how these rulings have shaped the legal landscape and the protection of defendants' rights. Additionally, hypothetical scenarios are used to explore complex legal issues such as self-defense, entrapment, and consent in sexual offenses, providing practical insights into how legal concepts are tested and applied. 2. Ethical Issues in Criminal Law. Ethical considerations are a central theme in criminal law practice. This section discusses the ethical responsibilities of defense attorneys, prosecutors, and judges. Defense attorneys must navigate client confidentiality, conflicts of interest, and ethical advocacy while zealously representing their clients. Prosecutors, on the other hand, are tasked with seeking justice rather than merely securing convictions, ensuring fair treatment of defendants, and disclosing exculpatory evidence. Judges are responsible for maintaining impartiality, avoiding conflicts of interest, and upholding the integrity of the judicial process. 3. The Role of the Defense Attorney and Prosecutor. The defense attorney and prosecutor play pivotal roles in the criminal justice system. Defense attorneys are responsible for protecting the rights of the accused, providing legal counsel, and advocating for the best possible outcomes for their clients. Prosecutors represent the government, presenting evidence to prove the defendant's guilt while ensuring that justice is served. Both roles involve complex decision-making, from plea negotiations to charging decisions, and require a balance between legal strategy and ethical considerations. 4. Impact of Criminal Law on Society. This section explores the broader impact of criminal law on individuals, communities, and society as a whole. Criminal law serves as a deterrent to crime, maintaining public safety by establishing clear consequences for unlawful behavior. However, the chapter also addresses the issues of social justice and inequality, highlighting how racial and economic disparities can influence the outcomes of criminal cases. Efforts to address these inequalities, such as bail reform and sentencing reform, are discussed. Victims' rights and restitution are also examined, emphasizing the need to balance the rights of victims with those of defendants. The chapter highlights the importance of treating victims with dignity and ensuring their voices are heard in the criminal justice process. Finally, the chapter discusses the role of rehabilitation and reintegration in reducing recidivism and promoting positive outcomes for former offenders. Rehabilitation programs, support services, and strategies to ease the reintegration process are explored as essential components of a just and effective criminal justice system. Conclusion. Chapter 9 provides a comprehensive overview of the practical aspects of criminal law, emphasizing the importance of ethical conduct, effective advocacy, and a commitment to justice. The chapter underscores the critical role of criminal law in shaping societal norms, protecting public safety, and addressing issues of social justice and inequality. Through this exploration, legal professionals are equipped with the knowledge and skills needed to navigate the complexities of criminal law practice and contribute to a fair and equitable justice system. --- Support this podcast: https://podcasters.spotify.com/pod/show/law-school/support

Chapter 9: Criminal Law in Practice delves into the real-world applications of criminal law, examining the roles of defense attorneys and prosecutors, the broader impact of criminal law on society, and the ethical challenges faced by legal professionals. The chapter is divided into several key sections, each focusing on different aspects of criminal law practice. 1. Case Studies and Practical Applications. This section highlights the importance of understanding how criminal law principles are applied in real-world situations. Through the analysis of landmark cases like Miranda v Arizona, Gideon v Wainwright, and Roper v Simmons, the chapter illustrates how these rulings have shaped the legal landscape and the protection of defendants' rights. Additionally, hypothetical scenarios are used to explore complex legal issues such as self-defense, entrapment, and consent in sexual offenses, providing practical insights into how legal concepts are tested and applied. 2. Ethical Issues in Criminal Law. Ethical considerations are a central theme in criminal law practice. This section discusses the ethical responsibilities of defense attorneys, prosecutors, and judges. Defense attorneys must navigate client confidentiality, conflicts of interest, and ethical advocacy while zealously representing their clients. Prosecutors, on the other hand, are tasked with seeking justice rather than merely securing convictions, ensuring fair treatment of defendants, and disclosing exculpatory evidence. Judges are responsible for maintaining impartiality, avoiding conflicts of interest, and upholding the integrity of the judicial process. 3. The Role of the Defense Attorney and Prosecutor. The defense attorney and prosecutor play pivotal roles in the criminal justice system. Defense attorneys are responsible for protecting the rights of the accused, providing legal counsel, and advocating for the best possible outcomes for their clients. Prosecutors represent the government, presenting evidence to prove the defendant's guilt while ensuring that justice is served. Both roles involve complex decision-making, from plea negotiations to charging decisions, and require a balance between legal strategy and ethical considerations. 4. Impact of Criminal Law on Society. This section explores the broader impact of criminal law on individuals, communities, and society as a whole. Criminal law serves as a deterrent to crime, maintaining public safety by establishing clear consequences for unlawful behavior. However, the chapter also addresses the issues of social justice and inequality, highlighting how racial and economic disparities can influence the outcomes of criminal cases. Efforts to address these inequalities, such as bail reform and sentencing reform, are discussed. Victims' rights and restitution are also examined, emphasizing the need to balance the rights of victims with those of defendants. The chapter highlights the importance of treating victims with dignity and ensuring their voices are heard in the criminal justice process. Finally, the chapter discusses the role of rehabilitation and reintegration in reducing recidivism and promoting positive outcomes for former offenders. Rehabilitation programs, support services, and strategies to ease the reintegration process are explored as essential components of a just and effective criminal justice system. Conclusion. Chapter 9 provides a comprehensive overview of the practical aspects of criminal law, emphasizing the importance of ethical conduct, effective advocacy, and a commitment to justice. The chapter underscores the critical role of criminal law in shaping societal norms, protecting public safety, and addressing issues of social justice and inequality. Through this exploration, legal professionals are equipped with the knowledge and skills needed to navigate the complexities of criminal law practice and contribute to a fair and equitable justice system. --- Support this podcast: https://podcasters.spotify.com/pod/show/law-school/support

Chapter 9: Criminal Law in Practice delves into the real-world applications of criminal law, examining the roles of defense attorneys and prosecutors, the broader impact of criminal law on society, and the ethical challenges faced by legal professionals. The chapter is divided into several key sections, each focusing on different aspects of criminal law practice. 1. Case Studies and Practical Applications. This section highlights the importance of understanding how criminal law principles are applied in real-world situations. Through the analysis of landmark cases like Miranda v Arizona, Gideon v Wainwright, and Roper v Simmons, the chapter illustrates how these rulings have shaped the legal landscape and the protection of defendants' rights. Additionally, hypothetical scenarios are used to explore complex legal issues such as self-defense, entrapment, and consent in sexual offenses, providing practical insights into how legal concepts are tested and applied. 2. Ethical Issues in Criminal Law. Ethical considerations are a central theme in criminal law practice. This section discusses the ethical responsibilities of defense attorneys, prosecutors, and judges. Defense attorneys must navigate client confidentiality, conflicts of interest, and ethical advocacy while zealously representing their clients. Prosecutors, on the other hand, are tasked with seeking justice rather than merely securing convictions, ensuring fair treatment of defendants, and disclosing exculpatory evidence. Judges are responsible for maintaining impartiality, avoiding conflicts of interest, and upholding the integrity of the judicial process. 3. The Role of the Defense Attorney and Prosecutor. The defense attorney and prosecutor play pivotal roles in the criminal justice system. Defense attorneys are responsible for protecting the rights of the accused, providing legal counsel, and advocating for the best possible outcomes for their clients. Prosecutors represent the government, presenting evidence to prove the defendant's guilt while ensuring that justice is served. Both roles involve complex decision-making, from plea negotiations to charging decisions, and require a balance between legal strategy and ethical considerations. 4. Impact of Criminal Law on Society. This section explores the broader impact of criminal law on individuals, communities, and society as a whole. Criminal law serves as a deterrent to crime, maintaining public safety by establishing clear consequences for unlawful behavior. However, the chapter also addresses the issues of social justice and inequality, highlighting how racial and economic disparities can influence the outcomes of criminal cases. Efforts to address these inequalities, such as bail reform and sentencing reform, are discussed. Victims' rights and restitution are also examined, emphasizing the need to balance the rights of victims with those of defendants. The chapter highlights the importance of treating victims with dignity and ensuring their voices are heard in the criminal justice process. Finally, the chapter discusses the role of rehabilitation and reintegration in reducing recidivism and promoting positive outcomes for former offenders. Rehabilitation programs, support services, and strategies to ease the reintegration process are explored as essential components of a just and effective criminal justice system. --- Support this podcast: https://podcasters.spotify.com/pod/show/law-school/support

In this special episode of Hashtag Trending, host Jim Love (and his deepfake counterpart) delve into the intriguing world of deepfakes and their impact on cybersecurity. Joined by a panel featuring Marcel Gagné, David Shipley, and Andréanne Bergeron, the discussion covers the evolution of deepfake technology, its potential risks at individual and corporate levels, and the broader implications for society. From insightful debates on AI's progression to critical thinking in the face of misinformation, this episode is a must-watch for anyone interested in the intersection of technology and security. 00:00 Introduction to Deepfakes 00:40 Meet the Panel 02:26 CrowdStrike's Humility at DEF CON 04:11 Elon Musk and Infrastructure Failures 12:23 The Importance of Digital Identification 21:20 Deepfakes: The New Frontier 24:12 Emergence of Digital Avatars 24:46 Open Source and Security Concerns 25:12 Commercial Availability and Ethical Issues 26:26 Media Influence and Anecdotal Evidence 27:14 Deepfakes in Politics and Business 28:15 Real-Time Deepfakes and Security Measures 31:46 Human Vulnerability and Psychological Factors 35:44 The Role of Education in Critical Thinking 40:04 AI vs Human Intelligence 42:06 Practical Advice for Organizations 46:26 Final Thoughts and Future Discussions

In today's episode of the HN Haus Podcast, our host Hannah Nieves, sits down with Kelsey Ogletree to dive deep into her journey from a top freelance writer to the founder and CEO of the innovative tech startup, Pitchcraft.Discover how Kelsey navigates the challenging landscape of building a tech company without a tech background, the innovative use of AI in media, and balancing the demands of motherhood and entrepreneurship.

David Rodnitzky is the founder of David Rodnitzky Consulting, a boutique firm dedicated to helping agency founders navigate complex acquisition, scaling, and M&A opportunities. He also founded 3Q Digital, a media management company managing over$2 billion in ad spend annually, which subsequently became part of DEPT.  Rodnitzky has written a book called “Selling Your Marketing Agency: Making the Most of Your Most Important Deal” that helps guide agency founders through one of the biggest decisions in their careers. In this episode, Matt and David discuss what it takes to build a successful business, the importance of thinking long term with client relationships, and the emotional and strategic complexities of selling a company, as well as some key insights into the world of M&A   Chapters: (0:01) David Rodnitzky's Journey from Iowa to San Francisco (1:58) From Dot-Com Boom to Founding Three Q Digital (7:13) Scaling a Digital Marketing Agency from Coffee Shop to Acquisition (12:44) Navigating Mergers and Acquisitions with Strategic Earnouts (20:07) Selling and Reacquiring a Company Multiple Times (25:56) Balancing Culture and Performance in the Workplace (32:11) Common Pitfalls and Ethical Issues in Advertising Agencies (40:45) Selling Your Business: Emotional and Practical Considerations (45:26) Boeing's Merger with McDonnell Douglas and Resulting Hostile Takeover (46:51) The Importance of Strategic Thinking in Legal and Business Decisions (50:30) Strategic Thinking and Due Diligence in Business Acquisitions (52:42) Building Long-Term Value in Agencies for Successful M&A   Link to Podcast Transcript

A Note from James:Is our military way behind other countries in terms of using the latest technology with AI, with drones, with biotech, with cybersecurity? I think for many years we know we're behind on supersonic weapons. Are we behind on AI? How did Hamas send undetected a thousand or so paragliders into Israel without Israel detecting it? Are we behind on the AI that's in sensors? What is going on?So, with the help of Chris Kirchhoff, who wrote the book "Unit X: How the Pentagon and Silicon Valley are Transforming the Future of War," we answer these questions and more.Episode Description:In this episode, James Altucher hosts Christopher Kirchhoff to explore the critical question: Is the US military lagging behind in technology? They discuss the current technological shortcomings of the military, historical contexts, and how metrics of military power are evolving. Kirchhoff provides an insightful analysis of the Hamas attack as a case study to highlight technological vulnerabilities and failures. The conversation expands to cover the rise of drones, the innovative Replicator Initiative, and the crucial role of AI and machine learning in military operations. Kirchhoff shares his experiences bridging the gap between Silicon Valley and the Pentagon, offering a rare glimpse into the challenges and successes of modern military technology integration.What You'll Learn:Technological Shortcomings: Understand the areas where the US military is currently falling behind other nations in technology.Impact of Drones: Learn about the transformative role drones play in modern warfare and their potential to change military strategies.Replicator Initiative: Discover the Pentagon's innovative approach to building low-cost autonomous weapon systems.AI in Military Operations: Gain insights into how AI and machine learning are being integrated into military strategies and operations.Bridging Technology Gaps: Explore the challenges and successes of connecting Silicon Valley's rapid innovation with the Pentagon's strategic needs.Chapters:01:30 Introduction: Is the US Military Lagging in Technology?02:15 Current Technological Shortcomings03:20 Historical Context of Military Superiority03:59 Changing Metrics of Military Power06:42 Hamas Attack: A Case Study08:15 Technological Vulnerabilities and Failures10:22 US Military's Technological Lag11:42 The Rise of Drones in Modern Warfare14:52 The Replicator Initiative17:54 Bridging the Gap Between Silicon Valley and the Pentagon24:39 Challenges in Government Contracting28:35 Innovative Contracting Solutions31:17 Discovering Joby Aviation: The Future of Flying Cars32:24 Military Applications and Collaboration with Joby34:53 The Rise of Drones in Modern Warfare37:12 Rogue Squadron: The Military's First Commercial Drone Unit39:32 Anduril and the Future of Combat Collaborative Aircraft45:14 AI and Machine Learning in Military Operations51:31 Ethical Issues in Military Technology01:04:02 Strategic Stability and the Future of Warfare01:09:35 Conclusion: Bridging Silicon Valley and the MilitaryAdditional Resources:Unit X: How the Pentagon and Silicon Valley are Transforming the Future of WarJoby AviationAnduril IndustriesDefense Innovation Unit (DIU)DARPA ------------What do YOU think of the show? Head to JamesAltucherShow.com/listeners and fill out a short survey that will help us better tailor the podcast to our audience!Are you interested in getting direct answers from James about your question on a podcast? Go to JamesAltucherShow.com/AskAltucher and send in your questions to be answered on the air!------------Visit Notepd.com to read our idea lists & sign up to create your own!My new book, Skip the Line, is out! Make sure you get a copy wherever books are sold!Join the You Should Run for President 2.0 Facebook Group, where we discuss why you should run for President.I write about all my podcasts! Check out the full post and learn what I learned at jamesaltuchershow.com------------Thank you so much for listening! If you like this episode, please rate, review, and subscribe to “The James Altucher Show” wherever you get your podcasts: Apple PodcastsiHeart RadioSpotifyFollow me on social media:YouTubeTwitterFacebookLinkedIn

A Note from James:Is our military way behind other countries in terms of using the latest technology with AI, with drones, with biotech, with cybersecurity? I think for many years we know we're behind on supersonic weapons. Are we behind on AI? How did Hamas send undetected a thousand or so paragliders into Israel without Israel detecting it? Are we behind on the AI that's in sensors? What is going on?So, with the help of Chris Kirchhoff, who wrote the book "Unit X: How the Pentagon and Silicon Valley are Transforming the Future of War," we answer these questions and more.Episode Description:In this episode, James Altucher hosts Christopher Kirchhoff to explore the critical question: Is the US military lagging behind in technology? They discuss the current technological shortcomings of the military, historical contexts, and how metrics of military power are evolving. Kirchhoff provides an insightful analysis of the Hamas attack as a case study to highlight technological vulnerabilities and failures. The conversation expands to cover the rise of drones, the innovative Replicator Initiative, and the crucial role of AI and machine learning in military operations. Kirchhoff shares his experiences bridging the gap between Silicon Valley and the Pentagon, offering a rare glimpse into the challenges and successes of modern military technology integration.What You'll Learn:Technological Shortcomings: Understand the areas where the US military is currently falling behind other nations in technology.Impact of Drones: Learn about the transformative role drones play in modern warfare and their potential to change military strategies.Replicator Initiative: Discover the Pentagon's innovative approach to building low-cost autonomous weapon systems.AI in Military Operations: Gain insights into how AI and machine learning are being integrated into military strategies and operations.Bridging Technology Gaps: Explore the challenges and successes of connecting Silicon Valley's rapid innovation with the Pentagon's strategic needs.Chapters:01:30 Introduction: Is the US Military Lagging in Technology?02:15 Current Technological Shortcomings03:20 Historical Context of Military Superiority03:59 Changing Metrics of Military Power06:42 Hamas Attack: A Case Study08:15 Technological Vulnerabilities and Failures10:22 US Military's Technological Lag11:42 The Rise of Drones in Modern Warfare14:52 The Replicator Initiative17:54 Bridging the Gap Between Silicon Valley and the Pentagon24:39 Challenges in Government Contracting28:35 Innovative Contracting Solutions31:17 Discovering Joby Aviation: The Future of Flying Cars32:24 Military Applications and Collaboration with Joby34:53 The Rise of Drones in Modern Warfare37:12 Rogue Squadron: The Military's First Commercial Drone Unit39:32 Anduril and the Future of Combat Collaborative Aircraft45:14 AI and Machine Learning in Military Operations51:31 Ethical Issues in Military Technology01:04:02 Strategic Stability and the Future of Warfare01:09:35 Conclusion: Bridging Silicon Valley and the MilitaryAdditional Resources:Unit X: How the Pentagon and Silicon Valley are Transforming the Future of WarJoby AviationAnduril IndustriesDefense Innovation Unit (DIU)DARPA ------------What do YOU think of the show? Head to JamesAltucherShow.com/listeners and fill out a short survey that will help us better tailor the podcast to our audience!Are you interested in getting direct answers from James about your question on a podcast? Go to JamesAltucherShow.com/AskAltucher and send in your questions to be answered on the air!------------Visit Notepd.com to read our idea lists & sign up to create your own!My new book, Skip the Line, is out! Make sure you get a copy wherever books are sold!Join the You Should Run for President 2.0 Facebook Group, where we discuss why you should run for...

In this episode, hosts Mark Thompson and Steve Little dive into Perplexity's big upgrade, enhancing research capabilities for family historians. They tackle pressing ethical concerns in AI, exploring copyright issues and training data controversies that impact genealogists. The show introduces a new series on building better prompts, offering practical tips to maximize AI tools. In the rapid-fire segment, they cover open-source developments, geopolitical influences on AI, and exciting updates from industry leaders like Anthropic, OpenAI, Google, and Apple. Whether you're a tech-savvy genealogist or new to AI, this episode provides valuable insights to navigate the evolving landscape of family history research in the digital age. Tune in for expert analysis and practical advice on leveraging AI in your genealogical pursuits.Timestamps:Welcome and introduction2:12 AI In the News2:30 Story 1: Perplexity upgrade7:20 Story 2: Ethical issues in AI13:55 Tip of the Week: Build Better Prompts21:40 AI Rapid Fire21:40 Open source developments in AI24:08 Geopolitical issues affecting AI tools26:38 Anthropic's Claude and new features29:08 Changes in OpenAI board membership32:35 Google Pixel 9 AI features37:20 Delay in Apple's Siri upgrades38:53 Tout Fini!Resource Links• Perplexity: https://www.perplexity.ai/• OpenAI: https://openai.com/• Microsoft: https://www.microsoft.com/• Google: https://www.google.com/• Anthropic: https://www.anthropic.com/• Apple: https://www.apple.com/• ChatGPT: https://chat.openai.com/• Claude AI: https://www.anthropic.com/• Google Gemini: https://deepmind.google/technologies/gemini/• NVIDIA: https://www.nvidia.com/• Meta (Facebook): https://about.meta.com/• Amazon: https://www.amazon.com/

In this episode I will be discussing the topic of abortion with a philosopher who has studied the moral arguments on both sides of the issue. I am interested in rational bases of moral decision making. I'd like to be able to work out moral rules from a set of socially acceptable first principles, but often I find that my moral intuition conflicts with what I derive as a rational morality. Is our morality wrong if it is not totally consistent, or is morality not derivable from precepts? I'd like to understand how these ideas apply to the topic of abortion ethics. Bonnie Steinbock is professor emerita of the Department of Philosophy at the University at Albany/State University of New York. A Fellow of the Hastings Center, she has been a visiting professor at Santa Clara University (2012), the Chinese University of Hong Kong (2015) and Monash University in Melbourne, Australia (2017). In addition to 70 articles, she is the author of Life Before Birth: The Moral and Legal Status of Embryos (Oxford University Press, 1992, 2011) and the editor or co-editor of several collections, including Killing and Letting Die (1980, 1994), New Ethics for the Public's Health (1999), Public Health Ethics: Theory, Policy, and Practice (2006), the Oxford Handbook of Bioethics (2008), and Ethical Issues in Modern Medicine, 4th - 8th editions. Her latest book, co-written with Paul Menzel, is Bioethics: What Everyone Needs to Know (Oxford University Press, 2023). Please support the podcast at patron.podbean.com/TheRationalView Join the Facebook discussion @TheRationalView Instagram @The_Rational_View Twix @AlScottRational

In this episode of Right to Life Radio, host John Gerardi and guest Jonathan Keller dive into the recent Supreme Court ruling on the abortion pill, discussing its implications and the broader landscape of abortion regulations. They unpack the 9-0 decision, exploring the concept of legal standing and its role in this case. The conversation also touches on the growing prevalence of medication abortions and the challenges facing the pro-life movement in a changing regulatory environment. Additionally, John and Jonathan critique the political maneuvers surrounding IVF legislation and the seeming inconsistencies in the pro-life stance of many Republican leaders.   Show Notes:   1. Introduction: • Host: John Gerardi • Guest: Jonathan Keller from California Family Council • Overview of the Supreme Court's decision regarding the abortion pill. 2. Supreme Court Ruling: • Explanation of the 9-0 decision. • Legal standing and its importance. • Historical context of the FDA's approval and regulation of the abortion pill. 3. Implications of the Decision: • The impact of the ruling on pro-life efforts. • Increased accessibility of the abortion pill and its consequences. • Discussion on the ethics and safety concerns related to medication abortions. 4. Political and Legal Analysis: • Critique of the Republican approach to FDA regulations. • The role of the Supreme Court in adjudicating actual lawsuits versus advisory opinions. 5. IVF Legislation Debate: • Examination of recent political focus on IVF. • Analysis of competing bills and their implications. • The moral and ethical considerations surrounding IVF practices. 6. Closing Thoughts: • Reflections on the broader pro-life movement. • Discussion on the importance of consistency in pro-life advocacy.

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Temu is now the temple for cheap and cheerful products you probably don't need but buy anyway, but the downsides are that European regulators claim that it uses manipulative sales techniques illegal under EU law and fails to protect European consumers. Bobby is joined by Conor Pope, Consumer Affairs Correspondent for the Irish Times to discuss.

  On a regular basis in sports medicine, we are faced with ethical dilemmas. Whether or not we should allow kids to play certain sports […]

In the quiet suburb of Cherry Hill, a respected rabbi orchestrates the brutal murder of his wife to pursue an affair with a radio host, unraveling a community's trust and exposing a tangled web of deceit and betrayal. Subscribe on your favorite podcasting apps: https://talkmurder.com/subscribeSupport us on patreon: https://patreon.com/talkmurderSee our technology: https://talkmurder.com/gearContent warning: the true crime stories discussed on this podcast can involve graphic and disturbing subject matter. Listener discretion is strongly advised.Fair use disclaimer: some materials used in this work are included under the fair use doctrine for educational purposes. Any copyrighted materials are owned by their respective copyright holders. Questions regarding use of copyrighted materials may be directed to legal [@] Talkocast.com

In the quiet suburb of Cherry Hill, a respected rabbi orchestrates the brutal murder of his wife to pursue an affair with a radio host, unraveling a community's trust and exposing a tangled web of deceit and betrayal. Subscribe on your favorite podcasting apps: https://talkmurder.com/subscribeSupport us on patreon: https://patreon.com/talkmurderSee our technology: https://talkmurder.com/gearContent warning: the true crime stories discussed on this podcast can involve graphic and disturbing subject matter. Listener discretion is strongly advised.Fair use disclaimer: some materials used in this work are included under the fair use doctrine for educational purposes. Any copyrighted materials are owned by their respective copyright holders. Questions regarding use of copyrighted materials may be directed to legal [@] Talkocast.com

That Solo Life: Episode 246 Ethical and Legal Challenges of the Modern PR Pro with Special Guest, Cayce Myers New episodes every Monday In this Episode "That Solo Life" podcast hosts  Karen Swim, APR and Michelle Kane sit down with Cayce Myers, Ph.D., LL.M., J.D., APR,  an experienced public relations professional and author. In this episode, Myers discusses his latest book, "The Rules of Public Relations, Legal and Ethical Issues and Contemporary Practice," which tackles the intersection of public relations, law, and ethics. Myers emphasizes the importance of understanding the legal implications of PR crises and the need for transparency when using artificial intelligence (AI) in PR. He stresses that PR professionals have a responsibility to navigate the challenges of disinformation and misinformation during election years. Brands are advised to align their communication strategies with their mission, vision, and values. Throughout the episode, Myers draws from his extensive experience in the field to offer valuable insights into the ever-changing landscape of PR.  Whether you're a seasoned PR professional or just starting out in the industry, this episode is packed with practical advice and thought-provoking conversations about the legal and ethical challenges surrounding public relations. Don't miss out on this fascinating discussion! Cayce Myers, Ph.D., LL.M., J.D., APR Cayce Myers is a professor of public relations and director of graduate studies at the School of Communication at Virginia, where he researches and teaches about the legal, regulatory, and ethical aspects of public relations. As a lawyer who also holds a Ph.D. in mass communication, Myers has authored five books and sixty publications including peer-reviewed articles, book chapters, law review articles, and trade press pieces, covering topics such as public relations history, strategy, political campaigns, and related laws and policies. His newest publication, "The Rules of Public Relations," delves into the current laws and ethical challenges in the field of PR practice. The release is scheduled for this July. Episode Highlights: [01:58] Risk and reputation. Lawyers and communicators view crises through a different lens, but do not have to be in opposition.  [06:37] Oh my AI. The murkiness of AI and what PR pros need to navigate this new technology. [11:27] I'll just wait it out. PR Pros are reluctant to use AI, fearing it could create issues. [14:29] Embracing the future. The bright future of PR and what companies need to know when they hire younger workers. [18:56] The politics of it all. Elections, elections all over the globe and the impact on PR pros in 2024. Resources: The Rules of Public Relations: Legal and Ethical Issues in Contemporary Practice (Publisher) (Use RLFANDF25 to save 25% off print book ) The Rules of Public Relations: Legal and Ethical Issues in Contemporary Practice (Amazon) Enjoyed the episode?  Please leave a review here - even a sentence helps. Share and tag us (@SoloPR, @SoloPRPro) on social media so that we can thank you personally! Your support helps us keep bringing you insightful content every week. Thank you for tuning in! Looking for more insights and support for your solo PR biz?  Head over to Solo PR Pro and become part of our community. Don't forget to sign up for our newsletter for the latest tips and trends. Say Thanks to Cayce Myers!  If you liked this episode with Cayce Myers, please say thanks on LinkedIn and follow his author page on Amazon. Listen to the episode on our website, Apple Podcasts, Spotify, Amazon Music, or on your favorite podcast platform. You can watch the interview on YouTube here.

In this unique, new conversation, I talk to professor Toby Green, and professor Reginald Oduor about the impact of lockdown policies on the global South. We also discuss the WHO treaty and its potential impact on the sovereignty of countries in the global South. Prof. Reginald Oduor raises several issues, including the ideology of treating the health of individuals, the environment, and everything equally, the problem of misinformation and disinformation, emergency use authorization of pharmaceutical products, centralization of medical care, and the imposition of a Western approach to disease management. They both argue that the treaty undermines the sovereignty of poorer countries and perpetuates neocolonialism. They criticize the elitism and narrow focus of Western experts and the imposition of Western medicine on the global South. The conversation concludes with a call for a more inclusive and equitable approach to global health.Chapters:00:00 Introduction and Background01:02 The Catastrophic Impact of Lockdowns in the Global South06:33 The Cruelty of Lockdown Policies in India08:57 The Global South's Experience of Lockdowns11:36 The Violation of the Implicit Promise of Globalization21:51 The Impact of Propaganda and Fear of Death26:13 Opposition to the WHO Treaty and Neo-Colonial Imposition31:07 Impact on the Sovereignty of the Global South34:05 Ethical Issues with Vaccine Policies39:35 Xenophobia and Movement Restrictions46:23 Imposition of Western Medicine and Knowledge51:05 Critique of Neoliberalism and Colonialism51:58 Maintaining Integrity in the Face of Pandemic53:23 Closing RemarksOur sponsor Alcami Elements:Our new blend uses high-quality, organic Peruvian cacao, enhancing the delicious flavour of our original mix. True raw cacao is high in antioxidants and minerals such as magnesium which also can have calming effects.Illusion of Consensus readers can get 10% off their first order or 30% off a monthly subscription using the code "illusionconsensus” here:https://www.alcamielements.com/products/alcami-elements-life-enhancing-beverage This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.illusionconsensus.com/subscribe

A new MP3 sermon from South Haven Baptist Church is now available on SermonAudio with the following details: Title: Ethical Issues Part 1 Subtitle: Proverbial Living Speaker: Taten Wagner Broadcaster: South Haven Baptist Church Event: Midweek Service Date: 3/21/2024 Bible: Proverbs 19:1 Length: 33 min.

Dave Chokshi is a professor at the Colin Powell School for Civic and Global Leadership at the City College of New York and a physician at Bellevue Hospital. Stephen Morrissey, the interviewer, is the Executive Managing Editor of the Journal. D.A. Chokshi and F.P. Cerise. Ethical Issues in Providing Care in Safety-Net Health Systems. N Engl J Med 2024;390:581-584.

To get the latest from Lorine Pendleton, you can follow her below!LinkedIn - https://www.linkedin.com/in/lorinependleton/https://www.portfolia.co/https://125ventures.vc Sign up for Marcia's newsletter to receive tips and the latest on Angel Investing!Website: www.marciadawood.com And don't forget to follow us wherever you are!Apple Podcasts: https://pod.link/1586445642.appleSpotify: https://pod.link/1586445642.spotifyLinkedIn: https://www.linkedin.com/company/angel-next-door-podcast/Instagram: https://www.instagram.com/theangelnextdoorpodcast/TikTok: https://www.tiktok.com/@marciadawood

In this episode of the Celebrate Kids podcast, Dr. Kathy talks about the importance of establishing a family code of conduct when it comes to technology, specifically artificial intelligence (AI). She discusses a new bill proposed by lawmakers to make AI literacy accessible through public schools, colleges, universities, and libraries. Dr. Kathy highlights the need for families to think through digital decorum and ethics surrounding AI, shedding light on how it can impact our lives and the world our children are growing up in. Tune in for valuable insights on navigating the digital landscape with AI.

The Illusion of Consensus is a reader-supported publication. To receive new posts and support our work, consider becoming a paid subscriber:https://www.illusionconsensus.com/The conversation with Molly and Ben Kingsley focuses on the government's mishandling of the pandemic and its impact on children. They discuss the government's failure to prioritize children's needs in policy-making, the systematic attacks on advocacy groups, and the unethical treatment of children during school closures. The role of local districts and central government in school closure decisions is examined, as well as the influence of unions and the media blackout on dissenting voices. The conversation also delves into the role of Pharma funding and the spread of smears and misinformation. The chapter concludes with a discussion on the rollout of child vaccines and the ethical issues surrounding it. The conversation explores the themes of regulatory capture, ethics, and media suppression in the context of pandemic policies.Buy Molly Kingsley, Arabella Skinner and Ben Kingsley's new book:https://www.amazon.co.uk/Accountability-Deficit-ministers-officials-accountability-ebook/dp/B0CNPWS79PChapters00:00 Introduction and Background01:52 Government Malfeasance and Attacks on Advocacy Groups04:05 School Closures and the Treatment of Children07:48 Role of Local Districts and Central Government in School Closure Decisions13:00 Role of Unions and Smearing Campaigns17:27 Government's Role in Censorship and Media Blackout22:12 Pharma Funding and Influence on Media28:57 Smears and Attacks on Advocates39:46 Rollout of Child Vaccines in the UK50:44 Ethical Issues and Treatment of Children52:53 Regulatory Capture58:17 Ethics and Advisory Group01:06:07 Suppression of Ethical Advice01:09:46 Media Suppression This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.illusionconsensus.com/subscribe

In the second hour of "Connections with Evan Dawson" on Monday, December 11, 2023, we discuss how AI developers should be addressing ethical issues as they create new technology.

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In Part 3 of this All Things Crime series, we dive into the intriguing world of government corruption and the dark underbelly of politics. Neama Rahmani, sheds light on his experience as a former ethics prosecutor for the city of Los Angeles. From overseeing elections to battling public corruption, Neama takes us behind the scenes, uncovering the deep-seated issues that plagued the city during the '80s and '90s. We also explore the economics of corruption, the impact of the infamous CSI effect on jurors' expectations, and even take a quick detour to discuss the brilliant Netflix series, The Lincoln Lawyer. So, get ready for a captivating conversation that will keep you on the edge of your seat. Tune in as we unveil the secrets and scandals of a world where power and greed collide in All Things Crime.Neama Rahmani is a prestigious California personal injury attorney, and the President and co-founder of West Coast Trial Lawyers. Neama graduated from UCLA at the age of 19 and Harvard Law School at the age of 22, making him one of the youngest graduates in the 200-year history of the law school.—-------------------------------This episode is Sponsored by M-Vac Systems, the innovative wet vacuum DNA collection system that has helped solve numerous cases. Make sure to check out their YouTube channel or head to their website at https://www.m-vac.com for more information.—-------------------------------Takeaways:Enhance government transparency and accountability to fight corruption.Address economic drivers of bribery at their roots.Manage juror expectations in cases lacking strong forensic evidence.Connect:Neama RahmaniLinkedIn: www.linkedin.com/in/neama-rahmani-84799874Website: www.westcoasttriallawyers.comJared BradleyLinkedIn: www.linkedin.com/in/jaredvbradleySupport the showAll Things Crime is a new, comprehensive video series that will explore every aspect of crime and the ensuing investigation, one video interview at a time. The host, Jared Bradley, is the President of M-Vac Systems, which is a wet-vacuum based forensic DNA collection system, and has experience traveling the world training all levels of law enforcement and crime lab DNA analysts in using the M-Vac to help solve crime. Along the way he has met people from all walks of life and experience in investigating crimes, so is putting that knowledge to use in another way by sharing it in these videos. If you are interested in more videos about the M-Vac, DNA and investigations, also check out the M-Vac's channel @https://www.youtube.com/c/MVacSystems...

278 – How to Deal with Ethical Issues in Counselling Registering with the ICO – Embracing Emotions In Episode 278 of the Counselling Tutor Podcast, your hosts Rory Lees-Oakes and Ken Kelly are back with this week's three topics: Firstly in ‘Student Services', we look at how to deal with ethical issues in counselling. Then […] The post 278 – How to Deal with Ethical Issues in Counselling appeared first on Counselling Tutor.

278 – How to Deal with Ethical Issues in Counselling Registering with the ICO – Embracing Emotions In Episode 278 of the Counselling Tutor Podcast, your hosts Rory Lees-Oakes and Ken Kelly are back with this week's three topics: Firstly in ‘Student Services', we look at how to deal with ethical issues in counselling. Then … 278 – How to Deal with Ethical Issues in Counselling Read More »

There is a long standing history of therapists making the mistake of pathologizing human behavior through the lens of their own religious bias. Maurice Harker, founder of Sons of Helaman: Eternal Warriors, is such an example. He has created programs and written books mostly focused on “sexual self-mastery” which align with his beliefs as a member of The Church of Jesus Christ of Latter-day Saints (aka the Mormon Church). Braxton and Natasha discuss the ethical and problematic issues for the public to be aware of in this episode of the Natasha Helfer Podcast. Research shows repeatedly that folks from conservative and high demand religions are more vulnerable to these types of unethical services, and are more apt to internalize the shame of identifying as “diseased” for sexual practices or orientations that are considered normal and even healthy in the clinical sexological field. It does not escape us that therapists like this are also often in the public eye for much more egregious behavior, which is the current case with Maurice Harker who is being investigated for serious clinical abuses.  Braxton Dutson, LCSW, CST graduated with his masters of Social Work degree and is an AASECT Certified Sex Therapist in Salt Lake City Utah. He is the creator of Birds and Bees Podcast (iTunes and Stitcher), a popular sexual/relationship health podcast for couples and parents, and works for The Healing Group. He works with couples, individuals and teens largely in the intersection of sexuality and mental health.  birdsandbeespodcast.com Intro ("Fisher's Hornpipe") and outro by Otter Creek Podcast edited by: Ashley Pacini

Branden Collins, founder of the design studio The Young Never Sleep, is a deep thinker. I had such a blast during our conversation about the complex and thought-provoking world of tech, creativity, and the endless possibilities they hold. As an interdisciplinary designer, Branden has worked at Cartoon Network and Snap, but he's also been heads down in the Atlanta creative community as well, which he's just returning to after a stint in Los Angeles.We talked about the ever-evolving landscape of social media, including the rise of microblogging platforms (as a response to Twitter's X-ification), the cautiousness in navigating the digital realm, and some potential ethical issues surrounding AI and VR. Branden also shared his philosophy of technoculture, and we explored world building, information science, issues sex workers face in online platforms, and the parallels between past technological shifts and the emergence of the metaverse.This episode will definitely make you think twice about the tech we build, how we use it, and how it affects our world!LinksThe Young Never SleepThe Young Never Sleep on InstagramFor a full transcript of this interview, visit revisionpath.com.==========Donate to Revision PathFor 10 years, Revision Path has been dedicated to showcasing Black designers and creatives from all over the world. In order to keep bringing you the content that you love, we need your support now more than ever.Click or tap here to make either a one-time or monthly donation to help keep Revision Path running strong.Thank you for your support!==========Follow and SubscribeLike this episode? Then subscribe to us on Apple Podcasts, Spotify, or wherever you find your favorite shows. Follow us, and leave us a 5-star rating and a review!You can also follow Revision Path on Instagram and Twitter.==========CreditsRevision Path is brought to you by Lunch, a multidisciplinary creative studio in Atlanta, GA.Executive Producer and Host: Maurice CherryEditor and Audio Engineer: RJ BasilioIntro Voiceover: Music Man DreIntro and Outro Music: Yellow SpeakerTranscripts are provided courtesy of Brevity and Wit.☎️ Call ‪626-603-0310 and leave us a message with your comments on this episode!Thank you for listening!==========Sponsored by Brevity & WitBrevity & Wit is a strategy and design firm committed to designing a more inclusive and equitable world. They are always looking to expand their roster of freelance design consultants in the U.S., particularly brand strategists, copywriters, graphic designers and Web developers.If you know how to deliver excellent creative work reliably, and enjoy the autonomy of a virtual-based, freelance life (with no non-competes), check them out at brevityandwit.com.Brevity & Wit — creative excellence without the grind.==========Sponsored by the School of Visual Arts - BFA Design & BFA AdvertisingThe BFA Design program at the School of Visual Arts consistently produces innovative and acclaimed work that is rooted in a strong foundational understanding of visual communication. It encourages creativity through cutting-edge tools, visionary design techniques, and offers burgeoning creatives a space to find their voice.Students in BFA Advertising are prepared for success in the dynamic advertising industry in a program led by faculty from New York's top ad agencies. Situated at the center of the advertising capital of the world, the program inspires the next generation of creative thinkers and elite professionals to design the future.School of Visual Arts has been a leader in the education of artists, designers and creative professionals for over seven decades. Comprising 7,000 students at its Manhattan campus and more than 41,000 alumni from 128 countries, SVA also represents one of the most influential artistic communities in the world. For information about the College's 30 undergraduate and graduate degree programs, visit sva.edu.

Imagine that you were scrolling through a social media site and someone you worked with or one of your family members posted an image or video of you that was less than flattering. Everyone not only saw it but started commenting on it and sharing it. How would this make you feel?   Now consider a person who not only never sees something like this posted about them but doesn't even understand that they are being ridiculed or exploited. This is what it is like for someone living with dementia. They don't have the ability to approve or consent to have images, videos and other identifying posts to be shared in this social media-crazed world. These people need to be protected.   It could be you. Every 3 seconds a new case of dementia is diagnosed somewhere in the world, joining the already more than 55 million people living with the disease. Dementia, a general term for a group of similar diseases including Alzheimer's, is a progressive disease that destroys memory and other important mental functions. While there is no cure, medications and management strategies may temporarily improve symptoms.   We live in a world now where anyone can take a photo or record a video of someone and put it out on social media. But I am capable of making that decision because I understand what is being posted and shared and I understand what social media is. A person suffering with dementia does not and they need to be protected. We need to remember that every person with dementia is still a person and deserves and is entitled to respect and dignity.    This topic will be the subject of an upcoming “Ethics of Dementia and Social Media” forum featuring nine of the world's leading dementia experts on the ethics of dementia and social media and will air on YouTube and other podcast providers worldwide on Feb. 14.