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Brian Rogers shared thisI love what I do! Having worked in AI/ML for many years now, I can tell you how hard it is to just "spin-up" a ready-to-go HPC cluster/AI Factory. Doing this on your own you're faced with so many steps and painfully long negotiations. Among many other cool things we are doing at Acasia, we have essentially created the "Easy Button" for spinning up an AI factory. Boy would I have loved this years ago! I speak from first-hand experience from back in my neurothink days...those of you that worked with me know exactly what I am talking about! To name a few of the challenges; - Power availability. - Data center readiness. - Networking. - Financing. - Deployment timelines. - Operational execution. We have built a ready to go workflow from financing to flipping the switch on. You can reach out to me directly or learn more here https://lnkd.in/gvR-b5JA #acasia #AIInfrastructure #AIFactory #GPUCompute #DataCenters #EnterpriseAI #AICompute
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Brian Rogers shared thisBig call out to the community from one of our founders Matthew David Renner at Acasia. This is such a unique offering for the right offtake renter. We make large-scale GPU capacity easier (arguably one the first to do it this way) to finance and deploy by packaging hardware access, data center readiness, deployment execution, and operating software into one integrated solution. For an offtake renter seeking a 256-node, 2,048-GPU Blackwell cluster like this, Acasia reduces the complexity of coordinating vendors, capital, power, and operations. Instead of the customer managing a fragmented procurement and deployment process, Acasia structures the cluster as a complete, financeable infrastructure asset backed by offtake demand. #AI #Infrastructure #Acasia #Compute #inference #datacenterBrian Rogers shared thisAnyone want to fully deployed 256 node, 2048 GPU NVIDIA Blackwell cluster fully financed off balance sheet in 6 MW of power in a mint Tier 3 data centers around in Phoenix? We can deploy within 12-16 weeks of placing the order. Looking for the right, credit worthy, US based offtake deal. Fine to work with brokers or Neo clouds, but final offtake has to be investment grade. No banned companies, must comply with KYC up front. Let Me know!
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Brian Rogers shared thisMany of you have likely been following Anthropic’s Fable 5 closely, and some may have even had a chance to experiment with it before access was shut down over national security concerns. Here are my thoughts on it. The shutdown has generated a lot of discussion around national security, regulation, and model access. But to me and for those of us that had a chance to briefly play around with it, the shutdown is not the headline. The capabilities are. Among so many use cases I came across (It's hard to say which was more impressive), one of them that stood out was watching Nate Herk give Fable 5 a goal, leave for the gym, and return to a completed YouTube video. Yeah, a single one-shot goal prompt and this is what was generated…remarkable! Not just a script. A finished video — with the voice, visuals, sound effects, and editing handled end to end. The funny thing is, he says in his YouTube video to be careful because it used up 40% of his monthly $200 tokens...let that sink in...this video production and final product cost only $80! Think what this would have costed you to produce and publish less than a year ago! And think about how stress-free this became! The video itself was impressive, but the real breakthrough was the autonomy. We are moving from AI that responds to prompts to AI that pursues objectives. From tool to operator. Governments can restrict access to a specific model. They can regulate providers, infrastructure, and exports. Those actions may slow deployment. But once capabilities are demonstrated, they rarely remain isolated for long. Researchers, startups, open-source communities, and competing organizations will keep moving toward similar outcomes...and yes, at a cost lower than foundation models. That is the larger signal from Fable 5. We are entering an era where AI systems can increasingly transform goals into outcomes with diminishing human supervision. Today that may mean creating a video. Tomorrow it may mean launching a campaign, building software, conducting research, or coordinating complex business operations. The Fable 5 shutdown may be remembered by some as a policy event. But I think it will also be remembered as one of the clearest signals yet of where AI is heading. #AI #Fable5 #Anthropic #ClaudeBrian Rogers shared thisClaude Fable 5 Made This Entire Video By Itself. I opened Claude, gave it one goal, went to the gym, and came back to a finished video. The video I came back to was not filmed. → The avatar is AI (HeyGen Avatar 5) → The voice is an ElevenLabs clone of mine → The script was written by Claude I didn't see a single frame while it was being made. One prompt in, a fully edited YouTube video out the other side. Even all the sound effects. The whole thing took about an hour and roughly 380k tokens. It spun up a dynamic workflow of subagents to verify the frames, so it ate up almost half of my $200/mo max plan. I just dropped a short YouTube video showing you the finished result and breaking down exactly how it got made. Two honest caveats. Copying my exact prompt won't give you the same result because I've got HyperFrames skills already built into my setup. And you don't actually need Fable for this. Now that I've built the style once, I could probably rebuild it with Sonnet. The model matters less than the system you wrap around it. Link to the full video is in the comments 👇
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Brian Rogers shared thisThe future of work will not be defined by who works the hardest inside the old system. It will be defined by who builds the better one. AI is no longer just a tool for answering questions. It is becoming a new operating system for how we think, remember, write, code, research, communicate, and execute. The real divide is not human vs. machine. It is people trapped in manual work vs. people using AI to move above it. AI-native workers are capturing more context, preserving more memory, delegating more execution, and applying their judgment at a higher level. The best people will not be valuable because they let AI think for them. They will be valuable because they know how to direct AI with clarity, taste, judgment, and accountability. The new work OS is here. And AI-native people are already pulling ahead. #AI #FutureOfWork #ArtificialIntelligence
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Brian Rogers shared thisBig update at Acasia. We have a large and unique opportunity for organizations looking for significant GPU capacity. We have the hosts, financing, and power lined up. See Matt’s post below.Brian Rogers shared thisWe get calls all of the time from looking for compute on a short time line. The reality is these are large, complex deals that require an entire infrastructure team + deep partnerships to execute. We have been working on a cluster and have the pieces in place for qualified off-take renters. A sovereign 250 Node Cluster of NVIDIA B300 GPUs ready to ship with multiple data center options for power within 3-4 months from contract signing at significantly less cost than hyper-scale providers. Details and inquiry here https://lnkd.in/gkcxBivZ
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Brian Rogers shared thisSignificant news for digital currency in the traditional banking sector. SoFi is now the first bank to offer a stablecoin on a public blockchain and with a swappable interest bearing tokenized deposit. I thought this day would never come!😀 To clarify, this is not just a faster wire. A traditional bank transaction moves money after a business process happens. A programmable stablecoin transaction can become part of the business process itself. So let me break this down into a use case - and yes I know there will be slight nuances to this process once SoFi has this in mainstream use. Imagine a US-based enterprise needs to buy GPU capacity from a data center provider in Singapore. 1. The enterprise holds cash inside the bank as an interest-bearing, FDIC-insured tokenized deposit. 2. When GPU capacity is needed, the enterprise converts part of that tokenized deposit into a bank-issued USD stablecoin. 3. The stablecoin is sent on-chain into a programmable escrow wallet tied to the compute agreement. 4. The provider begins provisioning GPU capacity immediately because the dollar-denominated payment asset is already there. 5. As compute is consumed, payment can be released automatically based on agreed conditions: hours used, jobs completed, GPU utilization, inference volume, service-level performance, or other verifiable usage data. 6. If the buyer uses less capacity than expected, the unused amount can be refunded automatically. 7. If the provider fails to meet the agreed service terms, payment can be paused, reduced, or routed into a dispute workflow. 8. The provider receives a dollar-denominated digital asset almost immediately. If they are comfortable holding or reusing digital dollars, settlement is effectively complete. 9. If the provider needs local currency, such as Singapore dollars, FX conversion and local bank payout happen separately as a treasury step. The power is that the two instruments are instantly convertible: one is where value safely rests, the other is how value moves. Now imagine this happening between to AI agents…that’s a whole other post! #banking #digitalcurrency #stablecoins https://lnkd.in/d873Tk49
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Brian Rogers shared thisOver the long and much needed Memorial Day weekend, I found myself reflecting on what it really means for Acasia to be a Human AI Company. That reflection led me to write “The AI Takeover is Overhyped. The Human Upgrade is Real.” I looked at two ideas that, together, say something important about where AI is heading: Andon Labs' “Vending-Bench,” which shows how even capable AI agents can lose coherence over time, and Vishal Sikka's hallucination argument, which suggests that plausible AI outputs are not the same as verified truth. Both point to the same conclusion: AI is becoming incredibly powerful, but intelligence alone is not the same as coherence, agency, or accountability. #AI #inference #humanity That is why I believe the future is not simply bigger models or more raw compute. The real shift is toward inference as a human amplifier — AI that continuously interprets context, sharpens judgment, expands creativity, and improves execution. The future is not human versus machine. It is human agency amplified by machine intelligence.The AI Takeover Is Overhyped. The Human Upgrade Is Real.The AI Takeover Is Overhyped. The Human Upgrade Is Real.
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Brian Rogers shared thisAcasia has been out at Dell Technologies World in Las Vegas this week, and the timing could not be more relevant. Dell’s latest AI Factory announcements point to where enterprise AI is heading next: Not just bigger models. Not just more GPUs. Not just another round of AI pilots. The real challenge is turning AI ambition into AI outcomes. That requires infrastructure that is deployable, governed, observable, secure, and ready for real workloads. That is exactly where Acasia fits. Acasia's three core areas help organizations move from raw GPU capacity to usable AI infrastructure: Fabric provides the control plane for managing GPU capacity, clusters, organizations, users, credentials, and operational visibility. ARIA helps turn that capacity into managed inference services teams can use in production. AIX adds the marketplace layer for discovering, pricing, reserving, and monetizing AI compute. Dell is validating the broader shift from fragmented infrastructure toward full-stack, production-ready AI systems. And Acasia is building for that same future: helping enterprises operationalize AI compute, deploy advanced models, and move from infrastructure access to real AI outcomes. https://lnkd.in/gMf8kAc5 #AI #Infrastructure #Dell #Acasia2026.05.18 | Dell Technologies Closes the Gap Between AI Ambition and AI Outcomes2026.05.18 | Dell Technologies Closes the Gap Between AI Ambition and AI Outcomes
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Brian Rogers shared thisOne of the best explanations I’ve seen on transformers. Well done!Brian Rogers shared thisAfter all this time, nobody has explained transformers better than this 👇 Transformers are able to predict the next word…but for everything. Text. Images. Audio. Code. The secret? Self-attention. Every token looks at every other token and asks: “how relevant are you to me right now?” “The cat sat on the mat because it was tired.” What does “it” refer to? The cat. Not the mat. Attention figures that out by assigning weights. High weight = high relevance. Low weight = ignore. And it does this in parallel, not sequentially like old RNNs. That’s why transformers scale. That’s why there is not other architecture can compete to this…. Yet. Add positional encoding so the model knows word order. Stack multiple attention heads to capture different relationships simultaneously. Run it through a feed-forward layer. Repeat. That’s exactly the same architecture powering every frontier model you use today. The rest is compute, data and talent to find new horizons within this architecture. #ai #transformers #learn
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Brian Rogers liked thisBrian Rogers liked thisHonored to be named one of the 100 most influential people in AI by TIME right on the heels of the public launch of our company Accelerated Understanding Bringing the power of AI+Science together has been the focus of my life for the past decade. I believe the greatest impact AI can have on science and engineering is its ability to massively accelerate simulation and understanding of the physical world. We started this journey with the invention of Neural Operators at Caltech to have a powerful foundation for AI modeling physical phenomena at multiple scales. Together with my team at NVIDIA and support from Jensen Huang himself we built FourCastNet, the first high-resolution AI-weather model that is tens of thousands of times faster than existing systems. Following up on this success we have applied Neural Operators to accelerating simulation of nuclear fusion to detect disruptions before they happen in the real world. Just this week, we announced how Neural Operators can enable density functional theory simulation in quantum chemistry quasi-linear time. We have also used Neural Operators to invent better medical devices like a catheter that reduces bacterial contamination by 100x and we have been able to design better masks for chips and optimized gate layouts for quantum dots. More recently we have been asking ourselves what would happen if we aggressively scale our models and put multiple areas of physics in the same model, teaching it physics in full 4D (3D space + time). This requires massive scale and that is exactly what we have been able to do at Accelerated Understanding We have pre-trained models up to 1 Trillion parameters, and we are able to train at 4D context lengths of up to 1 Trillion and run inference at 5 Trillion context. I am particularly excited about self-improvement: a limiting factor for scaling physical AI so far has been the availability of high quality training data. As the old saying goes: your model is only as good as your data. But that no longer holds true: for our models we have the laws of physics themselves that let us measure and improve the quality of our outputs exceeding what was present in the training data. But the improvement loop doesn’t stop at the models themselves. We can also use our models and their ability to understand physics and give directional feedback to break down one of the biggest barriers to innovation: the reliance on lab experiments as a bottleneck in the improvement loop. As intelligence gets more abundant this bottleneck is only increasing in importance. Putting our models and their physical simulation capabilities in that loop instead and taking advantage of their directional feedback means we only need the lab all the way in the end to double check. Excited to see new inventions and discoveries this will unlock! #TIME100AI
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Brian Rogers liked thisBrian Rogers liked thisI’m hiring a Head of Treasury Markets at OpenAI. This is a rare chance to sit at the center of one of the biggest transformations underway: how AI changes companies, markets, capital needs, risk management, and the way finance itself gets built. We’re looking for a senior markets leader to help shape Treasury across investments, FX, rates, debt markets, and market risk while building the AI-native workflows that will define the next generation of finance. If this sounds like you, or someone exceptional in your network, please reach out.
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Brian Rogers liked thisBrian Rogers liked thisI will never leave Texas. To me it’s the best state to live and raise a family and do business in. However, Silicon Valley will always be one of my Favorite places. It is so special. The innovation engine keeps churning day after day. The hustle and grit is evident everywhere you turn. We need the people running California to protect the entrepreneurs and businesses so they can continue to innovate and drive growth for the USA. A strong California is great for our Union. Thank you to the Dell Technologies team for the hospitality on our visit.
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Brian Rogers liked thisBrian Rogers liked this🔦 Member Spotlight: Joe Fuqua, Head of Enterprise Intelligent Automation Architecture and Governance, Truist Joe joined The Identity Underground because to him, identity is the connective tissue of modern computing. Not just authentication and access management, but the foundation for AI agents, machine identities, trust, governance, and digital interactions across enterprises. He found in this community one of the few places where those disciplines are beginning to converge. Over three decades across data, enterprise architecture, cloud, automation, and AI, the work he's most proud of is helping organizations navigate major technology shifts responsibly. Building bridges between technical teams, executives, and governance so organizations can adopt new technologies with confidence instead of fear. Seeing ideas move from whiteboard discussions into enterprise-scale capabilities, he says, never gets old. 🏛️ Here’s what Joe predicts for the identity landscape in the next five years: 🟠 AI will reshape identity as organizations move to managing millions of software agents, autonomous workflows, and machine identities alongside humans 🟠 That changes everything: authentication, authorization, trust, auditability, delegated authority, and governance 🟠 Identity will become the policy layer for AI, determining not just who can access a resource, but what an autonomous system is allowed to decide and act upon 🟠 Identity is no longer just an IT function Grateful to have someone with Joe's depth and range in The Identity Underground. Thanks for sharing! #IAM #IdentitySecurity #NHI #AIGovernance #EnterpriseArchitecture #AgenticAI #IdentityLeadership #IdentityCommunity #DigitalTrust
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Brian Rogers liked thisBrian Rogers liked thisAureum Leaders Circle presents the Grand Summer Gala. What if one evening could introduce you to the people who shape your future? Join us on August 20 for an unforgettable oceanfront experience in Half Moon Bay, where you’ll be surrounded by an exceptional community of founders, investors, executives, creators, athletes, and industry leaders. With over $1 billion in assets under management (AUM) represented in one room, this is more than an event—it’s an opportunity to build relationships with the people behind capital, innovation, and industry-leading companies. Whether you’re looking for your next investor, strategic partner, client, mentor, or lifelong connection, this is where meaningful conversations begin. Expect an extraordinary evening featuring distinguished guests, thought-provoking discussions, world-class entertainment, exceptional dining, and an atmosphere designed to create lasting memories. The biggest opportunities often come from being in the right room with the right people. Don’t be the one watching from the sidelines while others make the introductions and connections that could shape their future. Secure your spot today using the link below, and experience an evening where relationships, opportunities, and unforgettable moments come together. Sign up here —> https://lnkd.in/eMhQz2KV Katerina Abdrashitova Imad Ansari 📈Michael J. Blankenship Aalim A. Moor, II Stefanie Miller Lina C. Julie Amelie Real Harold Vandoorne
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Brian Rogers liked thisBrian Rogers liked thisThis month we are celebrating our 5 Year Anniversary at Vu Technologies! It's been an incredible journey these past few years, starting out with one studio in Tampa in 2021 to now over 100 studios across the globe, built for some of the biggest brands in the world! It wasn't easy and there's been a ton of ups and downs trying to build a new business with a new technology in a new market but I wouldn't trade it for the world. I'm so grateful for all our team and the hard work they've put in to make Vu what it is today! There is a still a lot of work to be done but we are 5 years closer today then we once were. I'm looking forward to what the next 5 years looks like continuing to build toward the vision of 'Content at the Speed of Thought'! Thank you Jonathan Davila Natalie Piekarski Kristy Reed Tracy Mitchell, SHRM-CP Shannon Talley, CPA, MBA Mark Swanson Steve Lux Brian Model Richard Cant Charlie Lewis Megan Hill Jeffrey McKown Erin Cullaro Anthony Santa Cris Coffey Brianne Dijamco Judah Mantell Gabby Mckessey Sam Schneidmiller Sam VanTassel Blake Hallman Danielle Mason Daniel Mallek Terence (Terry) Finkelstein Sarah Lowther John Womble
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Brian Rogers liked thisBrian Rogers liked thisIt is hard to wrap my head around the AI boom. As someone who has spent most of my life as an operator / entrepreneur / investor in technology, primarily software, there is no scale + speed like AI. The market is absolutely bonkers. Hope y’all are having fun out there.
Experience & Education
Licenses & Certifications
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Lean Six Sigma White Belt
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Volunteer Experience
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Co-Chairman, of the Class Gift
Columbia University in the City of New York
- 5 months
Education
Delivered a record-breaking campaign and created the first peer-driven outreach. Raised $14,300 in under three months, nearly doubling the funds of the previous year and tripling participation. Managed and trained a team of over 20 gift officers across 12 programs.
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Chairman & Co-Founder
Columbia Blockchain Alliance
- Present 9 years 7 months
Science and Technology
Private Columbia University group for Blockchain, distributed ledger, cryptocurrency and related technologies. The community includes all skill levels and representation from researchers, students, entrepreneurs, investors, academia, practitioners and beyond. CBA now has 650 members.
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Advisor NY Chapter
Machine Learning Society
- Present 9 years 8 months
Science and Technology
National data science, machine learning, and artificial Intelligence community, with groups in San Diego and New York. The groups focus on providing resources for learning, networking, and hiring opportunities.
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Advisor & Mentor
IBM Columbia Blockchain LAUNCH Accelerator
- 3 months
IBM Columbia Blockchain LAUNCH is a pre-seed accelerator for founders to explore their blockchain concepts and turn them into reality. The program, operated by Columbia’s Lab-to-Market Accelerator Network. The 10-week program exposes founders to a network of industry, technical, and business mentors focused on innovation and blockchain. I am currently a mentor for a genetics startup.
Languages
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English
Native or bilingual proficiency
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French
Limited working proficiency
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3 people have recommended Brian
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Jamal MEVE
🚀 SBIR/STTR reauthorization momentum is real. Proposals include longer authorization windows + increased set-asides, which would finally give startups predictable, multi-year R&D support. This could reshape early-stage deep tech funding. 👉 Subscribe to my newsletter for SBIR updates + strategy.
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Jon Brewton
Thanks to Walter Bacon for having me. This conversation captures something I've been thinking about for years: the real question isn't whether AI works. It's whether you can prove it works. The M&A example is telling. 25 analysts doing what 3 can now do with reView, but the real shift isn't about headcount reduction. It's about confidence. When you can audit the complete chain of reasoning behind every recommendation, when you know with certainty that the insight comes solely from your data and nothing was fabricated, that changes everything. The black box works until the consequences of being wrong become unacceptable. And we're operating in an era where those consequences are increasingly high stakes. What's driving adoption right now isn't novelty. It's necessity. Government agencies need auditability. Financial institutions need traceability. Healthcare organizations need to prove they're not operating on hallucinated data. These sectors can't afford the S3 bucket lesson applied to AI. Time to value matters. But sometimes trustworthy AI matters more. The horizon for data² is clear, enterprise grade AI infrastructure for every organization that can't afford to fail. Not black boxes that work "most of the time." Systems where every decision is defensible, traceable, and verifiable. If you're evaluating AI systems, ask one question: can you prove why it recommended what it recommended? If not, you're not ready for whats coming, and we're here to help you discover a better way. #ExplainableAI #EnterpriseAI #TrustworthyAI #DataIntelligence
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Bozidar Jovicevic MD, MBA
Medical associations were created ~170 years ago to raise standards and protect patients. AI just raised the stakes. I recently had a fascinating conversation with Dr. Ami Bhatt, Chief Innovation Officer at the American College of Cardiology, about what that actually means in practice. 👉 Link to the full episode here https://lnkd.in/evKKzR3c Here are 5 themes that stood out: 𝗧𝗵𝗲 𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝘄𝗮𝘀 𝗼𝗻 𝘁𝗵𝗲 𝘄𝗮𝗹𝗹: A decade ago, ACC created a Chief Innovation Officer role to bridge the gap between what tech companies build and what cardiologists actually need. Four strategic focus areas were defined. 𝗪𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗔𝗜 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘄𝗼𝗿𝗸: It must solve a real problem, fit into clinical workflow, and be ready to scale across infrastructure. Dr. Bhatt shares examples that work, such as voice-to-text for reducing documentation burden, AI that detects heart conditions not visible on a standard EKG, and population screening that finds patients earlier. 𝗔𝗜-𝗲𝗻𝗮𝗯𝗹𝗲𝗱 𝗰𝗹𝗶𝗻𝗶𝗰𝗶𝗮𝗻—𝘀𝘆𝗻𝗲𝗿𝗴𝘆 𝗮𝗻𝗱 𝗰𝗮𝘂𝘁𝗶𝗼𝗻𝘀: The promise is real, but so are the trade-offs. Dr. Bhatt discusses data gaps, the risk of overreliance on AI, and why we must decide when to use AI rather than default to always or never. 𝗧𝗿𝘂𝘀𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗲𝘃𝗲𝗿: 170 years later and with AI growing fast, associations’ mission is even more critical - they can build on their core strength of credibility by ensuring what scales in the AI era is reliable and vetted. 𝗧𝗵𝗲 𝗡𝗲𝘁𝗳𝗹𝗶𝘅 𝗺𝗼𝗺𝗲𝗻𝘁 𝗶𝗻 𝗺𝗲𝗱𝗶𝗰𝗮𝗹 𝗲𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻: ACC had a vision for personalized education 10 years ago. In 2023, it launched a Netflix-style platform with short-form learning (12–20 minutes) and AI-personalization. Result: 30,000+ hours watched by 5,000+ clinicians in year one. 📌 If you're thinking about AI's role in medicine and medical associations, this is a must-watch (or must-listen) episode.
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