David Thomson

Vishal Sachdev highlights the strategic integration of open source and proprietary tech in architecting tech stacks, developer ecosystems and resulting business models. The world class companies effectively balance value commoditization in open source and value capture in proprietary tech. This is the strategic challenge for companies operating in #blockchain and #AI. I believe those who operate at the intersection of blockchain *and* AI stand to win this strategic battle...

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💭 𝗥𝗲𝗳𝗹𝗲𝗰𝘁𝗶𝗼𝗻𝘀 𝗼𝗻 𝗔𝗜'𝘀 𝗣𝗮𝘁𝗵 𝗙𝗼𝗿𝘄𝗮𝗿𝗱: 𝗕𝗮𝗹𝗮𝗻𝗰𝗶𝗻𝗴 𝗖𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗛𝘂𝗺𝗮𝗻 𝗗𝗲𝘀𝗶𝗴𝗻 In 2019, 𝗥𝗶𝗰𝗵 𝗦𝘂𝘁𝘁𝗼𝗻 made a statement that still echoes in the AI world: let computation, not human intuition, take the lead. This idea laid the groundwork for models like GPT-3 and GPT-4, yet Rodney Brooks’ perspective also resonates – sometimes, practical AI needs a bit of human-designed insight to keep things efficient. Lately, I’ve been thinking about how AI is evolving beyond just scaling up models. We’re moving towards 𝗮𝗴𝗲𝗻𝘁 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 that iterate and refine, making our outputs closer to the thoughtful processes humans use. At Creao AI, we’re exploring what it means to truly balance these visions. Can we create agents that design, adapt, and operate on their own, yet still draw on the best of human insight? This blog captures some of my thoughts on how AI might get there. 🔗 Check out my latest blog post for more on these reflections as CREAO takes steps toward a more 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀, 𝗮𝗱𝗮𝗽𝘁𝗮𝗯𝗹𝗲 𝗔𝗜 future. 👉 https://lnkd.in/gxqWC7Wh #AGI #CREAO #AgentWorkflows #ArtificialIntelligence #AutonomousAI

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Insightful look into bioplatform strategy, and what it takes to raise a Series A from my partner, Omri Amirav-Drory: https://lnkd.in/dFv7GbF6

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How do we design funding mechanisms that are regenerative and built to last? In the latest Rehash episode, Sophia Dew from Celo Foundation joins me to talk about what blockchain enables for public goods funding, frameworks for designing regenerative onchain funding apps, and what it takes to build and maintain a layer 2 blockchain. Tune into our full conversation at the links below:

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The future of tech is here, and it's wearing glasses 🕶️ Here is an intriguing article about how Snap's CEO, Evan Spiegel, believes his company is leading the charge in AR smart glasses, with Meta and Apple set to follow. As someone who’s been following the AR space closely, I find it exciting to see companies like Snap pushing the boundaries of what smart glasses can do. Spiegel’s vision of using hands and voice to interact with augmented reality is a game-changer. Snap’s Spectacles, now in their 5th generation, are already making waves among developers. The goal is clear: to bring computing back into the real world, away from screens and closer to our daily lives. While Meta’s Ray-Ban Stories and Apple’s Vision Pro are also making significant strides, Snap’s approach to natural interaction and developer-friendly pricing could be the key to mainstream adoption. It’s an exciting time for AR, and I’m eager to see how these innovations shape our future. #AR #SmartGlasses #TechInnovation #FutureOfTech

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AI is paradoxically killing the Minimum Viable Product. The speed of change in the pace of product development we are experiencing due to AI is making it faster than ever to create early proof of concept products. The challenge this presents is that the value of these early products is trending towards zero. They're still valuable from a customer learning perspective, but no longer can startups expect to begin to generate and start to scale revenue from an MVP. Startups must now simultaneously expand product complexity and market penetration. In other words, the "land and expand" of start with a small part of functionality and expand to own the category is dead. You MUST have a plan to own the category (and be working on it) from the outset.

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Introducing Ocular AI (YC W24) 2.0 (rebranded and refreshed) and our first-ever Launch Week: https://lnkd.in/gAzPpBJa We stand at the chiasm of a technological renaissance, driven by the symbiotic partnership between humans and machines. This dynamic relationship has ushered in an era where Artificial Intelligence augments human intelligence, creating technologies that are more sophisticated, accurate, and practical—all while preserving human oversight and expertise. AI enhances human capabilities, empowering us to solve complex problems while maintaining agency and control. At the heart of this advancement is real-world data, enriched by human intelligence. Together, they form the foundation for cutting-edge AI that is both impactful and ethical. When Louis Murerwa and I started Ocular AI (YC W24) as an Open-Source Enterprise Search project during Y Combinator, our goal was to make information retrieval more intelligent. Early on, we realized that data quality was the decisive factor in achieving meaningful AI results. Over the past few months, we’ve engaged with hundreds of founders, executives, and engineers from startups, enterprises, research labs, and companies in robotics and self-driving cars. The message is clear: data is the lifeblood of AI. That’s why Ocular AI (YC W24) is building the Data Foundry for the Multi-Modal AI Era. By combining AI scalability with human insight, we’re creating golden datasets that go beyond training models, paving the way for AI breakthroughs. We’re excited to announce Ocular AI (YC W24)’s first-ever Launch Week, from December 2-6! Our team (Vivek Lahole, Louis Murerwa) will unveil two flagship products, Ocular Foundry and Ocular Bolt, which lay the foundation of our vision. Foundry and Bolt will strengthen the AI-human intelligence bond, enabling teams to create, refine, and deploy data with precision, efficiency, and speed. Companies spend huge amounts on training data, but Foundry and Bolt are AI-native tools that will lower costs, reduce manual effort, and accelerate high-quality data collection. We’re replacing outdated, clunky, and expensive data software! 💡 What to Expect: - Daily announcements and product demos - Insights into tackling AI’s biggest challenges - Opportunities to connect with our team 🎯 Be part of the journey: - Explore the Launch Week page: https://lnkd.in/gAzPpBJa If you’re working on AI for: 1. Computer Vision 2. Robotics 3. Self-Driving Cars 4. Foundational Models - Join our Slack community for live updates: https://lnkd.in/gVSeGTC2 - Sign up for our Beta Waitlist: https://lnkd.in/gsgkwsBB We’re already powering data for robotics companies and would love to hear and learn from you!

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My latest episode is about what you need to know about AI!

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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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It's been 100 years since Hans Berger made the first EEG recording of the brain, but we still don't fully understand what those brainwaves are telling us. That's why I was so excited to talk with Dimitris Fotis Sakellariou and Kris Pahuja, the co-founders of Piramidal (YC W24), a Y Combinator company building an AI model to unlock the secrets of brainwaves. Dimitris, a neuroscientist with a PhD, and Kris, a tech executive, have a unique story. They've combined their expertise to turn their groundbreaking idea into a thriving startup. On this episode of Lobster Talks - Y Combinator Secrets, we talked about Piramidal's journey, including: - The challenges of building a groundbreaking AI model for brainwaves. - The importance of data access and the ethical considerations surrounding this sensitive technology. - How Y Combinator has accelerated their growth. - Their ambitious vision for the future of brainwave AI, including expanding beyond EEG to create personalized AI solutions. Listen to the full episode to learn about Piramidal's mission and their vision for a future where AI can unlock the secrets of the human brain: Listen to the full episode now: https://lnkd.in/eaJuUZ-Q #ycombinator #venturecapital #investing #startup #growth #neuroscience #ai #artificialintelligence #brainwaves #lobstercapital #piramidal

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AI Integration vs. Standalone Products | Product vs. Feature As a CTO, I'm constantly evaluating emerging technologies for client projects. The recent hype around dedicated AI hardware has me intrigued, but Marques Brownlee's video on "AI the Product vs AI the Feature" raises a compelling point. Video Link: https://lnkd.in/gbJw5UQN Is AI destined to be the "Clubhouse" of tech – a flash in the pan overshadowed by established players integrating similar features? Here's why I believe Brownlee might be right: • Frictionless User Experience: Consumers have a limited amount of mental space for new devices. Integrating AI into existing products they already use creates a seamless experience. • Power of the Platform: Established platforms have vast user bases and data – fertile ground for training powerful AI models. Dedicated hardware struggles to compete. We're already seeing this with Apple's WWDC announcements. Enhanced Siri, on-device image generation – these are powerful AI features woven into the fabric of the iOS experience. Of course, there will always be exceptions. But for most businesses, focusing on integrating AI to enhance existing products is likely the smarter move. What are your thoughts? Is dedicated AI hardware a fad, or is there room for it in the future? #AI #Technology #DigitalTransformation #ArtificialIntelligence #Apple #ClubHouse #MKBHD

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What meeting AI is recommended by Tom's Guide for entrepreneur's? Read AI "Another of my fave tools is the clever Read AI. This cloud based service offers automated AI meeting recording, transcription and assistant. That sounds boring, but in reality the tool delivers a bunch of cool automated meeting functions. This includes identifying audience reactions, AI coaching, and intelligent wrap-up summaries." https://lnkd.in/gFGuJe2t

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Three years ago, Stage Venture Partners backed Ariyan Kabir, Brual Shah , and Satyandra K. (SK) Gupta's startup, GrayMatter Robotics. Today, GrayMatter revealed their $45 million Series B, led by Wellington. In the past three years, GrayMatter's robots have handled 7.5 million square feet of products, streamlining tasks such as sanding, grinding, and finishing high-performance surfaces. This innovative automation addresses urgent labor shortages, enabling U.S. manufacturers to meet demand efficiently. Technology like GrayMatter's is crucial for American factories, and the company is just scratching the surface in revolutionizing high-tech production processes. https://lnkd.in/gJaUfDZq

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Proud to debut the AI Index, a first-of-its-kind index of true AI companies in the public market! To make this list, we built a system that leverages a fine-tuned LLM to analyze earnings and regulatory filings as well as data from a variety of sources to determine levels of AI investment, hiring, team composition, and employee contributions to AI research and open source models and tools. Identifying true AI innovators is hard. That’s true in the VC world, and it’s also true in the public markets – where over six in ten tech companies tout AI initiatives but fewer back it up with real investment, hiring, and R&D. More on what we’re debuting; would love your thoughts! https://lnkd.in/gFbY6eMJ

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(1) Powerful and sophisticated (2) Fast time to value (3) Easy to maintain Generative AI has been a "CHOOSE ONE" world for the past couple of years. With an enterprise generative AI platform like Writer, it's a CHOOSE THREE world. Great example of this from the healthcare space from Sam Julien — a powerful, fast, and easy to scale app built on Palmyra-Med to develop SOAP notes functionality alongside patient / clinician transcripts / live chats.

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Many assumed that the industry would be well on its way to AGI or superintelligence before AI model builders’ efforts to take advantage of scaling laws might hit a wall. Recent headlines are chipping away at that assumption. One question I've been getting in my inbox: is this the era of diminishing returns for AI? We don't think so. Even if an avalanche of new clusters and synthetic data fail to deliver significantly better model performance, there are good reasons to believe that AI is still going to become orders of magnitude more powerful in the coming years — powering a new generation of startups and ultimately productivity growth and positive benefits for mankind. In fact, with agents and reasoning just beginning to scale and thousands of industry-specific models coming online, it's about to get really exciting. Read our latest blog post on the topic: https://lnkd.in/gFhniNX8

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Friday and Saturday Fun with Water. It's mildly interesting - so 100 words for a GPT-4 question “consumes" 3 water bottles. What to do with this information? Need to use AI? Use less AI? Deploy innovative cooling technologies for data centers? What is the integrated view of AI - the value of AI in solving economic, environmental, and social problems vs the complete footprint of AI applications (water, carbon, energy, materials, etc.) of AI? We need a more sophisticated conversation to develop holistic strategies, not "sound bites" (bytes). #water #carbon #AI #handprint #gesi Thoughts? Tom Freyberg Garrett Kephart Victoria Edwards Taylor Cox Reuven Carlyle Kat Hunt Rylan Dobson Colin Herron Alex Money Stuart Orr James Dalton Gaetane Suzenet Jacob Tompkins Imran Jaferey John Hoholik Maeve Hall James Harvey

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India is not just catching up in the AI race; we're innovating and leading in ways that are uniquely ours. The Economic Times recently highlighted how our approach to Generative AI goes beyond just Large Language Models (LLMs), addressing the specific challenges and opportunities within our diverse market. Rahul Agarwalla, Managing Partner at SenseAI Ventures, shared his invaluable insights into this AI revolution. His leadership and vision are truly driving innovation in the field, and it's an honour to be part of this journey with him. For anyone interested in the developments in AI and how India is making its mark on the global stage, this is a must-read.

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