Vinay Bhargava

As the discourse shifts from models to compound AI systems / agents, we need better AI benchmarks to evaluate multi-modal and multi-step task performance, especially in healthcare and life sciences. When we wrote the first paper demonstrating ChatGPT's performance on the USMLE, we chose the US Medical Licensing Exam as a benchmark for accessibility, speed, and ease. This benchmark was never intended to represent AI model performance on real-world clinical tasks. Today, I still see so many research teams and startups using benchmarks (like the USMLE) that are ill-fitted for assessing the true clinical or scientific performance and utility of the models they are developing for real-world contexts. Benchmark development may be seen as a "less sexy" area of research, but it is of paramount importance. Years after the rise of the transformer, we still lack adequate benchmarks for so many single-step tasks in biomedicine. With compound AI systems (i.e., architectures that integrate multiple AI models to perform complex tasks) emerging, we need new benchmarks for agentic behaviors. I'd argue that developing an agent with novel capabilities without at least proposing a companion benchmark (if an industry standard does not yet exist) may hinder the adoption of said agent, especially for high-stakes workflows. Designing more benchmarks that capture/simulate real-world clinical and scientific workflows will help us mitigate the major discrepancies observed between in silico and in vivo performance and better support safe + effective deployment of AI in biomedicine. There are already brilliant people focused here, and we need more. DMs are open if you're researching or working in this area of multi-step/multi-modal benchmarking in healthcare and life sciences! #healthcare #ai #artificialintelligence #generativeai

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Open-source models can be a strong lever for increasing gross margins at AI companies, especially those that have hefty cost structures (e.g., enterprise sales orgs that require significant customer success or implementation resources, as well forward-deployed AI services models common in healthcare and life sciences). One of many reasons to maintain a modular and flexible stack with minimal dependencies when building an AI company. More on the importance of flexibility in the AI stack: https://lnkd.in/eA2XATRk h/t Delip Rao #ai #artificialintelligence #generativeai #healthcare

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One key reason why healthcare technologies like AI, telemedicine, and software haven't structurally lowered costs or broadened access for the entire system after decades of experimentation (excluding pure financial engineering of payer contracts) is the limited reimagining of care delivery itself, with asynchronous telemedicine as a notable exception. In the same way that digitizing physical paper failed to exploit the capabilities of a new computing medium for word processing, hosting physician-patient conversations over video does not transform the actual delivery of care. In telemedicine, many of the inputs (e.g., clinician time) and therefore cost structures of in-person care persist, which is why we often see fee-for-service telemedicine companies struggle to achieve economies of scale (i.e., growing revenues non-linearly while growing costs linearly). Until we deconstruct the components of a medical appointment – from intake and triage, to chart review, history gathering, physical examination, diagnosis, treatment, and follow-up – we will continue to be underwhelmed by the disconnect between the transformative potential of these technologies and real-world patient/system impact. I’m optimistic that the emergence of reliable and performant medical AI agents will urge us to perform this deconstruction and redesign the fundamental building blocks of a “medical appointment.”

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The healthcare landscape is rapidly evolving, driven by advancements in technology and a deeper understanding of patient care. I had the pleasure of speaking with Ambar Bhattacharyya, Co-Managing Partner at Maverick Ventures, on the latest episode of The Full Ratchet. Ambar has partnered with numerous billion-dollar companies like hims & hers, Cityblock Health, Devoted Health, and ConcertAI. His unique journey from rural America to becoming a prominent figure in venture capital offers invaluable insights into the future of healthcare and technology. We discuss his investment strategy at Maverick Ventures, the megatrends shaping healthcare, the impact of AI on the industry, and the importance of integrated care. Ambar also shares his thoughts on the challenges and opportunities in healthcare investment, offering a comprehensive view of what lies ahead. Check out TFR Episode 438 to catch our conversation. You'll be glad you listened.

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One of my proudest moments as an investor occurred today as Alaffia Health announced its series A because it shows how the Aperture® Venture Capital vision of multi-level, multi-generational #impactinvesting is succeeding in the marketplace. Here’s the model in its most basic form : ✅As diverse fund managers with meaningful capital to allocate, we are changing the VC landscape every day just by doing our day jobs. ✅As Black/Brown investors with ~40 years experience collectively, Aperture GPs have access to talent /excellence that others do not, so our portfolio *organically* is more inclusive by race, gender and geography even while optimizing for financial outcomes (all about the alpha). ✅Our most successful portco’s are using financial #innovation to solve market problems that impact underrepresented demographics and underserved communities. Alaffia Health is a shining example of the impact portion of our overall fund thesis, and we couldn’t be prouder of TJ Ademiluyi and Adun Akanni, MPH, PMP - the dynamic brother-sister founder duo whose vision we have steadfastly supported on their journey. Congratulations to TJ and Adun from William Crowder and myself, as well as the whole Aperture team- Marjorie King Philip McKenzie Yves Louis-Jacques Tanvi Lal Michelle Dhansinghani Lisha Bell Katie Kelly Amy Chung Cindy Chong, CFA Brian Fernandes-Halloran Monroe France Jayden Pantel Darren Herman Evan Wladis Neal Triplett Thomas Scriven Peter Ammon Irina Bit-Babik Tim Milanich Rob Rahbari

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I used to spend 2-3 hours daily on clinic notes, skeptical of AI scribe technology. However, I've been impressed with RevMaxx, a generative AI company transforming clinical note creation by listening to physician-patient conversations and automatically generating comprehensive notes. This platform accurately captures crucial ICD-10 codes, saving valuable time ⏰. 👉 Why This Matters: - **Reducing Physician Burnout:** Administrative tasks are a significant contributor to physician burnout. Innovations like RevMaxx alleviate this burden effectively. #HealthcareInnovation #AI #PhysicianBurnout #MedicalDocumentation #HealthTech #RevMaxx

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To all the new or #expecting #parents, Ubenwa Health has developed a unique #AI-powered app designed for those who are still learning how to intuit their infant’s emotions. Through listening/studying to various different baby cries, #NanniAI is here to help you distinguish between their wants and needs, and which decisions is the most likely to soothing them in the meantime. Yes, it is named "Nanni," and yes it is AI powered — however it’s not intended to replace parents, it’s more of a #supplement to help support and encourage good #parenting skills. Nanni AI is the culmination of years of research and data collection in Nigeria, Montreal, Canada and Brazil, which was used to train an algorithm that sorts "thousands and thousands" of cries and tries to categorize your baby's needs accurately. The developer mentioned earlier, Ubenwa Health raised a $2.5 million pre seed financing round led by AI-focused funds. What do you think of this app? If you are a parent, would you consider using Nanni AI?

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🎙️ Thrilled to share that V. Tyrone Lam, COO of GATC Health, was recently featured on the Innovation Wave Podcast! In this insightful 20’ episode with Bob McGriff and me, Ty delves into how AI-driven predictive analytics can transform our approach to disease treatment, making it more proactive and less risky. He shared compelling insights on the future of healthcare and how predictive tools can lead to earlier interventions and better patient outcomes. A must-listen for anyone interested in the cutting-edge of medical technology and AI! 👉 Check out the episode to learn more about Tyrone's vision and GATC Health's pioneering work in this exciting field. Let's discuss how these innovations are reshaping the landscape of healthcare! #HealthTech #AI #PredictiveAnalytics #Innovation

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Abby Levy talks about venture's role in US healthcare and what we can expect to see as technology impacts the space on TFR. Check out the rest of the conversation with Abby & Alan Patricof of Primetime Partners on Episode 433.

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Last week I had the pleasure of being on The Exit, which is hosted by Steve McGarry and presented by Flippa.com. In this episode, I talk about my exits from MeMD and NextCare. At the end of the episode, I discuss how I time my ventures and how I live life as a serial entrepreneur. #businessexit #exitstrategy #entrepreneur #businesstips #healthcareleadership

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#hiring If anyone knows an awesome engineer that would be interested in joining an emerging #AI company doing important work in #healthcare, please drop me a line! Andy AI is backed by General Catalyst, YCombinator, Greater Ventures, and others, and they’re looking to hire a full stack engineer (US based) who's excited about using AI to improve healthcare and reduce nurse burnout. Andy is AI software that automates clinical documentation for nurses who do home visits. A nurse makes an audio recording of the visit and Andy automatically generates a form that usually takes nurses 90 minutes to complete. Nurses love the product because it potentially saves them 15 hours of charting a week! The founders previously built healthcare AI at Google Health and Apple, and are now building their vision to transform home health. More about Andy AI: https://with-andy.com/ Nurses love it: https://lnkd.in/g9XqZrUq #GenAI #digitalhealth #hiring #engineers #healthtech

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On the latest Vital Signs, Nikhil Krishnan and I had a ton of fun chatting with Dr. Atul Butte. Dr. Butte is a professor at UCSF, Chief Data Scientist of the UC Health System, and a co-founder of numerous healthcare startups. In our conversation, Dr. Butte shared his takes on healthcare AI opportunities, challenges, hype, and more. A few highlights: ⚡LLM use cases, data, and growth LLMs are already helping to solve the “drudgery” aspects of medicine, such as automatically drafting SOAP notes and patient messages. Dr. Butte is excited about future applications of LLMs that can help with the “cognitive” aspects: with difficult medical problems an LLM might be able to stitch together disparate pieces of information to generate a potentially novel solution. He also highlights that prompt engineering will become the next “coding language” as so much of leveraging LLMs is knowing how to ask them the right questions. Additionally, Dr. Butte discusses how since 2016, UCSF has been working to deidentify its patient notes so that it can query them to answer clinical questions and ultimately enhance patient care. ⚡The need for patient-facing AI As patients are increasingly able to access their own personal health data in nicely structured formats (e.g., EHRs, wearables), they desperately need more tools to help them interpret and make decisions using that data. Dr. Butte understands that these patient-facing solutions are challenging to get funded but he emphasizes that patients need to receive the benefits of AI sooner. ⚡Evaluating healthcare AI solutions In order to evaluate AI solutions, we often put human specialists – such as medical professionals – on the same tasks. Understanding that specialists often disagree with each other, a significant challenge arises in figuring out how we can evaluate AI considering we can’t just “average” all the specialist opinions. Dr. Butte points out that there still remains a massive gap in AI evaluation tools. Additionally, there are so many organizations that want to have a say in how healthcare AI is regulated that the landscape is uncertain. An awesome conversation with an expert on all things AI meets healthcare. Listen to the full episode below: Spotify: https://spoti.fi/3Wr3643 Apple: https://apple.co/4acwgan

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Someone broke down the estimated costs of a $15 Sweetgreen salad. We need these cost graphics for digital health to help future founders. Especially for tech enabled cos, the greatest cost is labor. Much of the "value created" is in curation and matching, which means the gross margins are reliant on labor arbitrage. Pay someone $X, but get paid $X+Y% per visit. The challenge with healthcare is that you often have to pick one of two business models: 1. specialized, low volume, high cost, low gross margin % 2. generalized, high volume, low cost, high gross margin % I'd argue founders should focus on gross dollars over the lifetime of the customer (like Jeff Bezos said) instead of gross margin %'s, but we'll leave that for another time. The challenge is that many tech enabled digital health cos have high cost of goods sold (labor) and moderately high product, design, and engineering budgets. We must build differentiated solutions for patients, clinicians, and clients to be out incumbents, however, we're realizing that companies are ultimately valued on the discounted value of future cash flows. And the high SG&A costs at most organizations might be inbalanced to the unit economics of the business. I'm not sure the math pencils out for everyone unfortunately. But I'm just a guy on the internet, would love to hear the thoughts from those smarter than I (you!). Comment below. --- p.s. I have no idea the accuracy of the graphic and not an investor in Sweetgreen. Cheers. Credit: David Crowther

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Severe mental illness remains one of the most underserved areas in mental health, possibly because it is difficult to address with the type of virtual, easy-to-scale models that VCs love to back. We're so excited that Sonia Priscilla García and Stas Sokolin at Amae Health have been able to break the mold, bringing better in-person solutions for patients and families dealing with SMI, and attracting strong venture partners to do so cc: Lisa Jacobs Blau, Alison Ryu, Claire Akkan Quiet Capital, Healthier Capital, Jan Ellison Baszucki, Karin Kissane, Mike Volpi

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The opioid crisis was a sad hallmark of my years working for the Baker Administration. In a time of extreme partisanship at the federal level, this was one area where public policy, civil discourse, and private enterprise seemed aligned and sufficiently motivated to find a solution. What we learned, however, is that dollars and access only go so far in combatting a disease that knows no so specific demographic. Instead, it's apparent that a battery of tools is needed to combat and prevent addiction--ranging from strong safety nets, to novel non-addictive pain therapies, and better technology. Introducing Marigold Health. Shrenik Jain, Ravi Shah, Tracey Cohen, MD, FASAM and team have built a proprietary NLP-based platform that--most significantly--improves the lives of those suffering from SUD/SMI. One customer we spoke with noted, "We needed a unique treatment intervention that had supportive research, fit into a CMS established model with a recognized service code, and that would provide positive clinical outcomes in an efficacious and fiscally responsible manner”. Another plainly said: "Marigold is our best hope to reach into the lives and help those who many have already given up on." Honored to join Bill Evans, Sean Day, and the entire syndicate in doing our part to scale a tool we believe will become essential in the fight against addiction. Marigold Health Innospark Ventures Rock Health KdT Ventures Matt Fates Lily Zarrella Venkat Srinivasan

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Perfect example of solving for a customer pain point, not innovation for #innovation’s sake. The founder is a physician and hated spending >2 hours daily on summarizing his day’s work, as required by law. This burden is driving people to leave the profession. So, Abridge built an AI app to automate a lot of this admin work and summarization for docs and hospitals. Now, Abridge is blowing up, rightfully so! Their customers (doctors) call the product ‘magical’ and ‘life changing’. A few lessons here: - Starting from real customer pain points is a winning strategy - #AI can add enromous value by solving mundane problems (not every AI application needs to be futuristic) - People with deep experience in an industry can leverage not just their expertise, but their tactical experience with daily hassles, to build great ventures Congrats Shiv and team Abridge, well deserved! 237 Ventures MENA FINTECH ASSOCIATION https://lnkd.in/dwE6nfKJ

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Is private equity owned healthcare a positive or a negative in regard to real health outcomes for patients? I asked Ambar Bhattacharyya of Maverick Ventures this question and more on Episode 438 of The Full Ratchet. Tune into the show to catch our discussion.

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Article in today’s WSJ highlights the skyrocketing cost of healthcare bills for payors and patients. 4L FWA Prevention powered by Integr8 AI can detect these schemes to incrementally ratchet up claims cost in mear real-time. Stop abusive billing schemes when thet start. Find, Fight and Prevent FWA Fast!

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🚀 𝐔𝐧𝐥𝐨𝐜𝐤 𝐒𝐭𝐚𝐫𝐭𝐮𝐩 𝐒𝐮𝐜𝐜𝐞𝐬𝐬 𝐰𝐢𝐭𝐡 𝐔𝐫𝐢 𝐋𝐞𝐯𝐢𝐧𝐞’𝐬 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬! 🚀 Uri Levine, co-founder of Waze and Moovit, shares invaluable lessons in his book “𝘍𝘢𝘭𝘭 𝘪𝘯 𝘓𝘰𝘷𝘦 𝘸𝘪𝘵𝘩 𝘵𝘩𝘦 𝘗𝘳𝘰𝘣𝘭𝘦𝘮, 𝘕𝘰𝘵 𝘵𝘩𝘦 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯.” Key takeaways include the importance of passionately embracing the problem you’re solving, the necessity of customer retention as a marker of product-market fit, and the strategic use of pitch deck slides. He also emphasises the significance of hiring and firing correctly and observing user behaviour to refine your product. These principles can transform your startup journey, ensuring resilience and growth. 🌟 #StartupSuccess #Entrepreneurship #ProductMarketFit #Innovation

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