Omar Tawakol

AI, Longevity and Love - how are they all connected? They make each other better and are essential to each other’s success Lots of fantastic discussions about how AI will bring out the best in humans including augmenting our time and ability to connect at DOC in Napa and Wisdom 2.0 in SF this past week. Huge thanks to Jordan Shlain, MD, Kevin Ryan and John Battelle for organizing leaders across traditional medicine, longevity, academic research, and biotech and Soren Gordhamer and Mark Hyman, MD for bringing together the best of AI and longevity AI shows incredible promise for healing humans and increasing longevity, here are my key takeaways from these events: We can live to 95 today if we focus on longevity and healthspan, there are biotech solutions using AI to epigenetically reprogram cells to reverse aging and disease that will enable us to extend lifespan by 20+ years but it will take for these to be real Fun to see Mark Hyman, MD interview Eric Verdin, they both discussed how they lowered their biological age by 10+ years and feel the best ever There are so many simple things we can do, walking 30 minutes a day reduces cardiovascular, alzheimer’s and cancer risk by 40% but 80% of the US doesn’t even do this Within 5 years we will have a whole new set of FDA approved psychedelic drugs for depression, anxiety, PTSD, etc. Immunotherapies will also expand so we can avoid chemo and living cancer free will be in reach We need the US to move to a functional medicine, integrative care model and get out of this sick care model, this level of innovation is more likely to come from upstarts, the incumbents have too much revenues to lose in this transition AI will not replace physicians, instead those physicians that don’t use AI will be replaced. 50% of physicians are burned out, AI can help! Fantastic connecting with so many brilliant minds, including Mark Hyman, MD, Eric Verdin Neal Khosla Laura Esserman Abby Levy Sheila Lirio Marcelo Leonard Zon Arjun Desai David Eagleman Lois Quam Vinod Khosla Emi Gal and many others #healthcare #longevity #ai

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NVIDIA tops the Axios Harris Poll 100, which ranks company reputations. FYI, this poll is done using this three-step process: 1. January 2024 Survey: 6,273 Americans identified the 100 most visible companies. 2. March 2024 Survey: 16,500 Americans rated these companies on nine reputation dimensions, creating a Reputational Quotient (RQ®) score. 3. May 2024 Surveys: Two waves of surveys provided additional context on brands and politics.

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Was chatting with another investor today on a call, and mentioned Tim Urban's Wait But Why Blog post, "The AI Revolution" and how prescient it was. Given that it was written in 2015, decided to flex AI's latest muscles to give it a new venue: a podcast. Podcast here: https://lnkd.in/gW8Dh89U Pretty easy to do: Step 1: Save the posts as PDFs. Step 2: Upload to NotebookLM, have it create a podcast. Step 3: Upload to Descript, give it captions. Step 4: Export, publish to Youtube. Total time to create the podcast: ~25 minutes. To generate this podcast and publish it even a few years ago would have taken >8 hours. Love the future (Original posts: https://lnkd.in/gW-PQXE7, https://lnkd.in/gg-nRvxz) #AIRevolution #GenerativeAI #WaitButWhy #TimUrban #NotebookLM #AIContentCreation #Podcasting #Descript #ArtificialIntelligence #ContentFlex #ProductivityHacks #FutureOfAI #AIinMinutes #TechEfficiency #AIandCreativity #YouTubePodcast #InnovationInContent #vibecap #vibecapital

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TRUST TAKES YEARS TO BUILD SECONDS TO BREAK, & FOREVER TO REPAIR One of the biggest risks posed by Gen AI is a further & irreversible erosion of trust. How can technology help counter this risk?

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🤯 Imagine the CEO of the world’s hottest company says the next trillion-dollar opportunity is something your startup has already been delivering results with for over a year in stealth! #JensenHuang and #MarkBenioff have the world buzzing about #AIAgents. 🐝  But at #CalvinBallTech, we've been quietly delivering game-changing results with them for over a year!  🤫 Don't get caught up in the hype 🙅‍♂️ Stay tuned. CalvinBall Tech is about to come out of stealth, and we're bringing proven AI Agents that have already solved critical problems for real businesses. 💪 Here’s a quick couple of questions for anyone showing you fancy roadmaps and dazzling demos: Do they have proven results already? Can they start delivering tomorrow? Gurnoor Dhillon Ratu Nadiah KhairunnisaSahal ZainEva ZuliyaFaris -Yoga Wigardo Dharnesh GordhonAntoine de CarbonnelFrançois Walewski #AICanSolveThat #AISuperAgents #AIRevolution #FutureOfWork #EnterpriseAI #CalvinBallTech #StartupJourney  #CalvinballerCode

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Finished off 2024 with this book which completely exceeded my expectations. I couldn't put it down, the cycle of near deaths and incredible achievements that Nvidia has been through demonstrates how important resilience, perseverance, and execution matter. That is not to say they were prescient, strategic, and fiercely competitive but they went through a lot of ups and downs especially in the early years. The almost went bankrupt twice. The first two chips missed the mark and they barely had enough capital to make the 3rd chip let along test it. The 3rd chip miraculously saved them and was a runaway success. The company lost 80% of their market cap at least twice in its history and Jensen remained steadfast. They created the GPU market and then bet early on AI so much so they had to engage academics to start using their chips outside of gaming and build the market. The bet on AI looks genius know but it was a lot of capital and it was very uncertain. At one point Starboard took an activist position thankfully Jensen was able to buyback shares, increase the share price by 20%, and make them go away. He believed in AI way ahead of the market. Tons of great lessons and a riveting read. Highly recommend this book if you like business and entrepreneurship. #entrepreneurship #business #AI

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Building on the momentum from Google I/O, we're announcing important updates to the Gemini API and Google AI Studio, including: ✅ Gemini 1.5 Flash and 1.5 Pro stable release and billing ✅ Higher rate limits on Gemini 1.5 Flash ✅ Gemini 1.5 Flash tuning ✅ JSON schema mode ✅ Mobile support and light mode in Google AI Studio 🚀 We’re incredibly excited to see what you build with these new models and are committed to building towards a world class developer experience. You can get started with Gemini 1.5 Flash and 1.5 Pro free of charge in Google AI Studio. #BuildwithGemini Google Cloud

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Introducing Airtable HyperDB. Airtable can now scale up to 100M+ records to serve the largest enterprise use cases in the AI era. As we’ve journeyed upmarket, we’ve been pulled into digital operations use cases revolving around high-value, large-scale datasets (e.g., product SKUs, media content assets, marketing performance data). Airtable can now directly house those datasets, or connect to Databricks/Snowflake/systems of record, and run end-to-end processes like content production, product lifecycle management, or marketing operations. We also launched App Library, which enables enterprises to standardize processes with centrally-managed, AI-enabled components and apps that can be forked and adapted by groups within the enterprise, while receiving live updates when needed. All this adds up to Airtable enabling enterprises to rapidly stand up and deploy LLMs into the enterprise operations that enable winning execution in the AI era. https://lnkd.in/gwiqkx34

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https://lnkd.in/ecuZDqKz. https://lnkd.in/ecuZDqKz Liquid AI Introduces New Class of Foundational Models, Advancing AI Performance and Efficiency Boston, September 30, 2024—Liquid AI, a pioneer in artificial intelligence innovation, is set to redefine the AI landscape with the launch of its Liquid Foundational Models (LFMs). These models bring unprecedented levels of performance and efficiency to generative AI, offering powerful solutions for industries looking to harness artificial intelligence more effectively on device or on server. A technical whitepaper about model performance will be available on September 30, 2024, at 11 am EST. Key Highlights: ● LFMs Introduce a New Scaling Law for Generative AI: Markedly improving quality, cost-effectiveness, and power efficiency compared to current GPT models. ● Innovative Architecture: Leveraging dynamical systems and advanced mathematics, LFMs achieve superior performance with fewer parameters. ● Initial Model Release: The lineup includes models with 1B, 3B, and 40B parameters, each setting new benchmarks in their respective categories. ○ LFM-1B: A 1.3-billion-parameter model achieving the highest scores across benchmarks in its class. ○ LFM-3B: A 3.1-billion-parameter model that outperforms many 7B and 13B models, making it ideal for edge deployment and resource-constrained environments. ○ LFM-40B: A 40.3-billion-parameter Mixture of Experts (MoE) model designed for complex tasks, offering performance comparable to much larger models while remaining cost-effective. Real-World Applications: • Enterprise: LFMs enable the design of more powerful AI assistants and analytics tools that can run efficiently on existing infrastructure, reducing operational costs. • On-Device: LFMs prioritize privacy, low latency, security and offline accessibility, making them suitable for mobile and edge deployments. These models have demonstrated impressive results on standard LLM evaluation benchmarks. Additionally, LFMs maintain near-constant inference time and memory complexity, allowing for longer input sequences without significant increases in computational resources. Advancements in AI Architecture: LFMs introduce a new design space for foundational models by employing adaptive linear operators rooted in dynamical systems and signal processing. This approach unifies and extends existing computational methods in deep learning, providing a systematic way to explore architectural possibilities. The models are highly adaptable, optimized for various hardware platforms including NVIDIA, AMD, Qualcomm, Cerebras, and Apple devices.

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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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How should OpenAI price Strawberry or o1 as it is now known. Flash poll results. Total of 74 responses from Friday Sept. 13. Interested in how generative AI applications are being monetized? Join Kyle Poyar from OpenView and Growth Unhinged, Michael Mansard from Zuora and Steven Forth from Ibbaka for an engaging roundtable on Sept. 19. Please register here. https://lnkd.in/gZNZqS6u My own thoughts is that this depends on strategic intent. Strawberry is a very different application than vanilla ChatGPT and it will provide value in new ways. It should not be tied to ChatGPT pricing. I would position it as a separate offer. However, part of the intent of Strawberry seems to be to provide training data for future reasoning models. In that case the more people that use o1 the better and pricing should be neutral. #Strawberry #Openai #generativeAI #genAI #pricing #monetization #o1

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Recently I've watch the WWDC...And, let's talk about Apple Intelligence. Just using Tim Cook words and mixing with some thoughts about their new product rationale. ✨Tim :"It has to be intuitive and easy to use." ✨Tim: "It has to be deeply integrated into your product experiences. " 🤓 Me: Diggin a bit on this, many people assumed that Apple would just call OpenAI for all AI tasks. Instead, at WWDC, they revealed their own: ➜On-device model for simple tasks such as writing and summarizing content, including an on-device semantic index enabling Siri to take actions across apps. This means offline AI, many users will opt for Apple's on-device model for simple AI queries, avoiding public LLMs. ➜Private cloud model for advanced AI queries, ensuring your data remains secure. This means AI integrated across apps, OS, private cloud, and Apple devices ✨Tim: "Most importantly, it needs to understand you and be deeply rooted in your personal context, including your daily routine, relationships, communications, and other aspects of your life." ✨Tim: "And, of course, it has to be built with privacy from the ground up. " 🤓 Me: Unlike other AI players, Apple’s business model doesn’t require monetizing your data. Put simply, people don’t trust any other AI player with their data: ➜Google and Meta make money from targeted ads. ➜OpenAI has a lot of drama. ➜Microsoft is dealing with the fallout from its Recall feature. In contrast, Apple has long emphasized privacy. People’s trust in Apple to protect their data is a huge strategic advantage, as always I have my doubts but, let's see what happens.

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"Our goal is to create operating leverage through AI. ... One of the ways I look at it is, our total people costs will go down, our cost per head will go up, and my GPU per researcher will go up." — Satya Nadella. I finished listening to the BG2 podcast with the Microsoft CEO last night. Extremely interesting conversation with Brad Gerstner and Bill Gurley, and a lot to chew on. I found myself skipping back repeatedly to listen to certain parts again, to make sure I understood exactly what Satya was saying. One example was the quote above, in the context of the long-term implications of AI for the workforce, specifically at Microsoft in this case. I'd be very interested in hearing what everyone thinks of this. Here's that specific portion of the show: https://lnkd.in/gcPjHpeg Here's the full podcast: https://lnkd.in/gHAquZpD

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Get ready for the coming of the great wallet squeeze as AI-based tools and Agentic AI go after budgets. Kyle Poyar has an incredible post on substack that lays out the pricing model for AI-based tools. I'm quoting a sample but he has a mega list, below that you can scan... "The most disruptive AI pricing models so far ⤵ 1. Salesforce: $2 per conversation (Agentforce) 2. Intercom: $0.99 per AI resolution (FinAI agent) 3. Intercom: 10 free tickets per agent, per month (FinAI copilot) 4. Zendesk: Per successful autonomous resolution (Zendesk AI) 5. Microsoft: $4 per hour of usage (AI copilot for security) 6. OpenAI: Per input/output token (GPT-4o) 7. 11x: Per task completed by the AI SDR 8. Clay: Per credit with a credit = a data point or action 9. copy.ai: Per workflow credit 10. relay.app: Per workflow step" The net of it is that all these tools require wallet expansion. You still need your systems of record that you use today like CRM, ERP, HCM, etc. It's going to get messy and a lot of promising applications wont be able to bear the weight of their COGS in the face of fierce competition for static budgets. And don't underestimate the overlapping of AI add-ons when they come as discrete products. That is until we see the emergence of true Systems of Outcomes I recently wrote about where we have one application that does the work of systems of record and delivers an outcome. https://lnkd.in/g7tfrYgE

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In a recent Office Hours, Baris Gultekin, Head of AI at Snowflake & a friend from Google, shared his insights into Snowflake’s approach to AI. It was a great conversation to understand how one of the leading data companies is pushing AI forward. The video for the session is here : https://lnkd.in/gfBesq35 & the audio is here : https://lnkd.in/gUK8hR66. There are four major pushes for Snowflake within AI. 1. Bringing AI to Data with Cortex. Cortex is a suite of AI building blocks that enable customers to leverage large language models (LLMs) & build applications. Both structured data & unstructured data (extracting information from presentations & pdfs) can be built using Cortex. 2. Developing open source initiatives including a data catalog, Polaris, & an open LLM Model Arctic which focuses on SQL performance. Open source is a new motion for Snowflake. 3. Securing data sharing to bring data into customers’ accounts for AI. Data sharing across customers enables a marketing organization to use data from a credit card company to build a model for customer marketing. 4. Developing a platform atop Snowflake with native apps to enable a retailer to provide a search experience to their wholesalers, for example. We also chatted about the importance of data access security for AI applications. For many data leaders, this is one of the top priorities to understand before deploying AI. Thanks, Baris, for sharing your perspectives!

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Check out Quantum Metric's latest benchmark report. In collaboration with Brad Douglas, we implemented Spline and GSAP to creative a more interactive scroll experience. We were able to create a visual treat packed with excellent data sourced from the talented Lori Niquette. The Fall of Peak, digs into the why behind these habits and what they mean for peak strategies for the holidays and into 2025. So, what did we uncover? Check out the entire report here: https://lnkd.in/g2P2Kbcr

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