Suman Talukdar

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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For those of you still doubting Artificial Intelligence....wake the f$%& up!!! Go walk around downtown San Francisco and maybe all of Google's Waymo driverless cars on the streets may be a wake up call for you. If you need more proof take a look at Y Combinator's current cohort of companies as well as all the AI and AI-Enabled companies in the MedTech Innovator current cohort of companies or the ones pitching at LSI and LSI Europe!

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💲The Founders Weekly BOOST - the 12 Rules to 10x your Business, All the New Minted Ca$h from VCs for you to Pitch for, AI 🤖 Lots on AI & so much more 🔥 💲 Another Jam Packed edition from Rubén & I to help you Raise Capital and Grow Revenues 📈 💲Gen AI - Whats Coming Next According to Sequoia 🤔 💲or lack of 💲- Whats happening in a World With No Exits as we're still 90% (😱) off of Peak! There are green shoots 🌱 💲You Founders in Pro Services - Convert to an AI Business 🤖 It's All in Here 💙 💲Dig in, share with friends & colleagues BUT also ask questions too - we have loads of experts who can join the conversation 📣 🎯 Don't Forget To Subscribe so you Never Miss A Single 💲of Value 💙 "The Founders Corner"

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M13 is thrilled to lead the Series A in RadiantGraph which is focused on personalization in healthcare. As we continue to invest in early stage companies it is abundantly clear that the biggest indicator of success is the founder and his or her ability to execute on their vision of the future. In this case, I don't think I have seen much better founder-market fit than we have with founder and CEO Anmol Madan. We believe in his vision: in order to have the best patient outcomes in healthcare we need increased personalization and AI is the breakthrough to get us there. Anmol started one of the pioneering digital health companies Ginger and then was Chief Data Scientist at Livongo and Teledoc. He has done it all: early stage, late stage, public company. And he deeply understands the nuances of the healthcare market from all angles which is critical for success. While there are many players building healthcare-specific AI capabilities, RadiantGraph is focused on outcomes: The platform is already processing personalization models for more than 3.5 million people, despite launching just last year. Excited to partner with my friend Adam D'Augelli and the great True Ventures again and Morgan Blumberg who has been deep in the healthcare market with me for many years. More on our thesis in the blog below. https://lnkd.in/evDDmC3W

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Some VC investors believe that brick and mortar - referring to a physical presence of some kind - should be avoided at all costs. Yet, the track record of clinic and hybrid care businesses in health care indicates otherwise. ==> One Medical (sold for $3.9 billion to Amazon), Oak Street (bought by CVS for $10.6 billion), Lifestance (IPO at $7.5 billion market cap), and PE-backed Premise Health (acquired by OMERS Private Equity for $1.1 billion) If a clinic is indicated as the optimal way to deliver care for that patient population, there are creative ways to build and operate them. Full article below with advice and strategies on how to build and operate hybrid clinics from my teammate Anarghya Vardhana from Maveron, Amir Dan Rubin from OneMedical Group, Steven Eidelman from Modern Animal and more!

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Sharing a sanitized version of the mu ventures Q2 q'ly LP update. Included musings: 👉 SEOs shrinking impact, and the rise of LLMO (large language model optimization) 👉 examples of the Commerce AI application layer coming to life 👉 a modern fund strategy that accepts companies require less capital, time, and people to trigger the power law 👉 Mu's guide to investing in AI 👉 all 30 companies in the Mu-niverse (and several others we admire) Founders, VCs, LPs - if you like how we think and suspect we can partner, hit us up! https://lnkd.in/dTJ2zjav

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Science-fiction is inherently speculative. Author George #Orwell of ‘#1984’ predicted concepts such as doublethink, little earbuds and society’s obsession with the black mirror screens that dominate our lives — and according to the BBC, novelist and short story author JG Ballard, of “High-Rise” and “Crash” fame, has predicted the current tool and cultural fixation of #GenerativeAI in the modern society — only he didn’t just speculate them within a story, he is actually one of the first use-cases of a generative AI used in a creative context — Ballard was so fascinated with the growing technological advancement of computers that he used one to compose poems, essentially the precursor to what we have now with ChatGPT. Today, the debate about the creative use of generative AI and its value on creative industries is an extremely fraught and controversial topic, but if controlled in a space that doesn’t replace human labor or try to equate itself to traditional art forms, it is interesting to see what computers can do and how they are creatively limited in comparison. Ballard’s two poems, The Yellow Back Novels and Machine Gun City are generated, and both include notes on how Ballard achieved producing them. Regardless of quality (Ballard himself probably wouldn’t describe these two poems as his best work), it is interesting to see primitive versions of the technology that we utilize on the daily today, and how these moral conversations that concern them would continuously evolve.

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Boston's vibrant health tech scene is fueled by world-class accelerators and incubators, empowering startups to drive digital health, biotech, and life sciences breakthroughs. Here’s a look at some key players: MassChallenge HealthTech—This accelerator helps startups transform health solutions across digital and biotech. It connects entrepreneurs with resources and mentors to drive meaningful change. LabCentral – A coworking lab space offering shared resources and lab facilities, LabCentral supports biotech and health tech startups by providing them with an innovative, collaborative environment. #Pagliuca Harvard Life Lab – Located at Harvard, this incubator offers lab and office space to promising biotech and life sciences startups, helping them scale groundbreaking health tech solutions. Richi Entrepreneurs – With a global outlook, Richi Entrepreneurs offers a unique two-week immersion for international health tech startups, connecting them with Boston’s local mentors, investors, and industry leaders. Xontogeny – Specializing in life sciences, Xontogeny partners with early-stage health tech companies, providing strategic guidance and operational support to accelerate their journey from concept to market. These incubators and accelerators are not just nurturing innovation—they’re powering the next generation of health solutions! 🌟 #BostonHealthTech #InnovationEcosystem #Biotech #HealthTech #StartupAccelerators

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-Founders should avoid overuse of revenue multiple: what it really means in startups’ valuation- Traditional valuation methods rely on a company's financial statements. If founders use revenue multiples in dealing with potential investors, they should understand the basics of valuation. Otherwise, it might appear as a lack of common sense. Here's a breakdown of the basic approaches and why revenue multiple was invented. https://lnkd.in/gbYqTpAC #Hypergrowth #Valuation #HITSERIESCAPITAL #TANAAKK

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The perception that deep tech startups (like those in robotics, space, and biotech) are prohibitively expensive to build is increasingly outdated... Advances in tech infrastructure, better access to startup talent, and an abundance of funding options (both VC and non-dilutive government grants) are making it easier and more affordable to launch deep tech companies than ever before. Costs for key components have dramatically dropped, and supportive macroeconomic and political tailwinds are driving demand for new technologies. With the right approach, ideas that once required tens of millions of dollars and years to develop can now be realized with smaller teams and seed funding, making deep tech a prime opportunity for today’s founders. But what’s impressive about YC is how they push even deep tech startups to generate revenue within the short span of the program. This challenges the notion that hardware and science-based startups need years before showing market traction. Take a look at some from S24: 1. Spaceium: Developing automated space stations for spacecraft refueling and repair. They secured $86.1 million in binding commercial contracts and have an additional $230 million in the pipeline. 2. Network Ocean: Building underwater data centers to reduce power usage and improve GPU efficiency. They already have GPUs available. 3. Theseus: Creating unjammable drones. They've sold units to multiple customers, obtained six-figure LOIs from large drone manufacturers, and have eight-figure funding requests from the DoD for FY25. 4. Ionworks: Offering battery-simulation-as-a-service to accelerate design cycles. With batteries projected to represent 4% of global GDP by 2030, they've gained significant traction with some huge companies across several industries like automative and aerospace .

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We're launching the inaugural edition of Beyond Benchmarks, a deep dive into the metrics and trends observed across the early-stage enterprise cloud market. This is the first look at some of the business data around GenAI in SaaS. Some initial observations: 1) 60% of SaaS companies have already integrated GenAI into their offerings (60% of these as part of their current product and 40% as a new product), and an additional 20% are planning to do so this year. Almost half aren't monetizing these features. Those that are are primarily experimenting with both usage-based and flat fee pricing models. 2) Most companies are utilizing OpenAI as their primary LLM, but many are experimenting with multiple models - and we are noticing an early trend towards intelligently routing GenAI inference requests to different models based on cost, performance, and security. 3) Though we are in the initial innings of GenAI, we are seeing some positive signals - companies that implemented GenAI had 7% higher NDR than those that did not. Still early days, but we'll be doing this benchmarking report regularly to track and share how things progress in this new era. Link to report in comments.

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One conversation we should be having more, especially in healthcare: is this an AI problem or a policy problem? A big challenge in American healthcare stems from the reality that our healthcare strategy changes with every administration. Throwing AI at problems that are well-addressed by policy innovation (e.g., AI for payer-provider RCM war) feels like a gross misallocation of resources. Solution sets are rarely zero sum – in truth, most problems will require policy, tech, and human interventions, but it's worth asking ourselves whether AI is the best solve when we have a multitude of options.

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The GLP-1 space has continued to explode, with the potential for impact expanding to cardiovascular risk, sleep apnea, and liver disease. So who are the emerging players poised to challenge Lilly and Novo? The incoming players to watch are a mix of startups and incumbents. In the startup realm, Viking Therapeutics, Inc., and Altimmune, Inc. have gained significant attention as their GLP-1 candidates demonstrate solid weight-loss outcomes. For San Diego based Viking, weekly doses of VK2735 delivered weight loss of up to 13% compared to placebo in a Phase 2 trial. Perhaps most exciting, the weight loss did not plateau at any time during the 13 week study, suggesting longer duration doses would result in further weight loss. Meanwhile, Altimmune's Pemvidutide (being studied for both obesity and MASH) is on track for an end of phase 2 FDA meeting in Q3 of this year. Notably, Pemvidutide has showed promise in limiting the amount of weight loss derived from muscle, which is a notable problem with the existing GLP-1s. A recent phase 2 trial showed only ~25% of weight loss was from lean mass, more in line with the ratio seen in typical diet & exercise programs. There are also several incumbents working hard to establish their presence. Roche's $2.7B acquisition of California-based Carmot Therapeutics, Inc. Therapeutics in December and Amgen's MariTide are both notable. Roche recently announced data from a Phase 1B study for CT-388 showing placebo-adjusted weight loss of ~19%, with 85% of participants seeing weight loss of more than 10%. Not to be left out, Amgen has recently advanced MariTide into Phase 2 studies, with Phase 1 results published in February showing weight loss of up to 15% in 12 weeks, with some dosage levels only required once a month. To have a credible chance at challenging the existing market leaders, new GLP-1s will have to demonstrate meaningful improvements on the following: 1. Dosage - most approved therapies today (with the exception of Rybelsus) are subcutaneous injections, given weekly. Having an easier form (tablet) or frequency (bi-weekly or even monthly) would be a big advantage. 2. Preservation of lean muscle mass - helping patients derive weight gain from regular adipose tissue instead of muscle mass. 3. Benefits beyond weight loss. Novo's recent FDA label expansion for Wegovy for reducing the risk of serious cardiovascular events provides a blueprint of how to expand the area these medicines can be helpful in. While there are many companies active in the space, it's worth noting just how large a lead Lilly and Novo have in this future $100B+ market. A recent GlobalData report noted that even by 2029, these two giants will have ~80% of the market between them. That said, 20% of a $100B market is still a sizable prize for other innovators, and continued innovation will only help patients.

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Is your company on track with Gen AI? Use this checklist to see where you are. Subscribe to ‘Siliconnector’ Telegram channel for insights and news from Tech world and Silicon Valley: https://t.me/siliconnector

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No founder wants to pitch a VC with no cash.  That’s why we’re sharing the list of firms below that have fresh capital to deploy. 🔴 Barcelona based Asabys Partners closed its second $201.3M fund to invest in biotech, med-tech, and digital health companies. 🔴 Chicago based ARCH Venture Partners closed its thirteenth $3B fund to focus on biotechnology companies. 🔴 Palo Alto based DCVC closed its third $400M biotech fund to back data-driven life science businesses. 🔴 Miami based Boldstart Ventures raised its seventh $250M fund to invest in enterprise infra and SaaS startups. 🔴 New York based The Fintech Fund raised its second $10M fund to focus on founders with strong backgrounds in building financial products.

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Just finished reading "The Next Giant Leap" by Space Capital - a pioneering VC investing in the emerging Space Economy. The report speaks to how SpaceX’s Starship is more than just the most powerful rocket ever built—it is poised to reshape the global space economy in profound ways. With its immense payload capacity, reusable design, and lower cost per launch, Starship will unlock entirely new industries and transform existing business models. But how should industries and businesses evolve to align with this paradigm shift? 📈 Rethinking Business Strategies & Supply Chains - For businesses, Starship represents an era of mass-production over precision engineering. This means moving away from the focus on mass efficiency toward cost-effective, redundant, and scalable production. - In terms of supply chains, this opens opportunities for new players in manufacturing, materials, and space components. The demand for off-the-shelf parts and non-aerospace suppliers will rise dramatically. 💡 New Use Cases & Opportunities   The opportunities Starship unlocks go beyond launching satellites. - In-space manufacturing of high-value products like pharmaceuticals and advanced materials that cannot be created on Earth. - Mega-constellations of satellites for global broadband, expanding on what Starlink has already begun. - In-orbit assembly and servicing, allowing for larger space structures like telescopes or even habitats to be built in orbit, radically reducing costs. - Lunar infrastructure and resource extraction will become more viable, paving the way for sustainable human presence on the Moon and, eventually, Mars. 📊 What Should Businesses Do Now?   1. Embrace Redundancy & Scale – Instead of focusing on one-off, high-cost solutions, businesses should embrace redundancy and mass production.    2. Simplify Design – With Starship’s payload capacity, there is less pressure to optimize for mass efficiency. Simplified, scalable designs will allow for faster production and iteration cycles, akin to how SpaceX rapidly tests and evolves Starship itself. 3. Develop Strategic Partnerships – Collaborating with forward-thinking space startups, suppliers, and even non-aerospace sectors will be essential to capitalize on the opportunities Starship provides. 🌌 A New Era of Innovation   Starship will democratize access to space, lowering the barriers for businesses to create and scale. The next decade will witness breakthroughs in scientific exploration, energy production, and in-space transportation that we can only begin to imagine today. #SpaceEconomy #Starship #Innovation #SupplyChain #Manufacturing #SpaceTech #Entrepreneurship #FutureOfSpace https://lnkd.in/gNdbwXdq

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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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💡Benchmarks in the investment industry serve as a standard for measuring the performance of securities, mutual funds, or investment managers. They provide a reference point for analyzing allocation, risk, and return of a portfolio, enabling investors to make informed decisions. Thanks Peter Walker for keeping us all informed!! Can’t wait for this!! Follow and get on the waitlist for this one! #benchmarks #fundraising #Capitalraise #founders #womenshealth #femhealth #medtech #wellness

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