Matt Ellis

Ready for an #Agentic future where AI agents collaborate, adapt, and act autonomously? OpenAI announced the next frontier in Enterprise AI: "Swarm." It introduces the concept of agent chaining: If an agent cannot complete a task independently, it can delegate the task to another agent through a handoff. Want to learn more about Agentic AI? Attend the IIT Bay Area Leadership Conference 2024 this Saturday (October 19, 2024). Jeremiah Owyang will give a talk on "Agentic AI: Shaping Autonomous Future." The article mentions: "Swarm’s release has also rekindled debates about the ethical implications of advanced AI systems." You can attend Brian Green's "Ethical Decision Making In the Age of Data and AI" talk to learn more. It mentions: "Security experts stress the need for robust safeguards to prevent misuse or malfunction in networks of autonomous agents." You can attend two sessions: (1) "Driving Business Innovation: AI, Zero-Trust, and Investment Insights" by Mario Espinoza (CPO of Illumio), Dr. Vipin Chaudhary (Prof and Chair at Case Western University), Hitesh Sheth (CEO of Vectra AI), and Pramod Gosavi (Venture Partner at Blumberg Capital) and (2) "Gen AI: Data Security and Privacy" by Dr. Anand Kashyap (CEO at Fortanix), Nilesh Thakker (President at Zinnov), and Dr. Anirban Ghosh (AI/ML Consultant at Infosys). The article mentions: "The specter of job displacement adds another layer of complexity," and you can attend the session "Future of Work in the Age of Data and AI: VCs' Perspectives" by Ashmeet Sidana (Engineering Capital), Raviraj Jain (Lightspeed Ventures), Apoorva Pandhi (Zetta Ventures) and Lochan Alagh (VC Nest). And, of course, there are many more sessions. Register here: ttps://lnkd.in/gRUVzbfA #Leadership #IITBayArea #TechIcon Speaker Affiliations: Databricks, Glean, Sapphire Ventures, Accenture, Illumio, SAP, Okta, Birlasoft, Infosys, Vectra AI, Fortanix, Postman, Workato, and many more Nidhi Kannoujia, Arnab Debnath, Ashis Khan, Anshu Agarwal, Swapnil Sinvhal, Lochan Alagh, Rao Charagondla (CNR), Dipty Desai, Ph.D., Praveen Vayalamkuzhi, PhD, FRSA, Surbhi Kaul, Ishita Sharan, Hrishikesh Sathawane, Bidyut Parruck https://lnkd.in/gJwa_ZXJ.

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Loved bringing together a group of research-centric, product-minded technologists building the future of AI tonight in the 🅱️🍎, incl. product / eng leadership @ NVIDIA, Pinecone, Datadog; founding eng @ Abnormal Security, Modal, Counsel Health; applied AI @ OpenAI, Anthropic; research eng @ Meta (FAIR), Harvey, Google DeepMind; founders @ Sapien and some of NYC's greatest stealth AI co's ☄ We covered a lot of ground over 4 hours - some of the recurring themes in our conversations: - Agents:🕴Model inference is getting so much faster, which will unlock AI agents' potential. That said, agents should be trained to handle very narrow tasks, reliably, first vs. an open-ended approach many startups are attempting today - Robotics: 🤖 While the science is not there yet, the robotics market and its impact will be much bigger than LLM. The introduction of humanoids will fundamentally change how we live. That said, the U.S. is in a vulnerable position due to lack of supply chain independence, compared to rivals like China - Value creation: ✨ AI personalization is overrated as consumers mostly care about status (i.e., ‘whatever is the best’) vs. what's tailored to them. Delivering great UX is still hugely undervalued, for both enterprise and consumer use cases. Cost and reliability remain enterprise buyers' front-and-center priorities. AI can preserve endangered rare languages by documenting and creating digital archives / databases cc: our amazing sponsor Arc (Brendan Bettencourt, Erika Bricky, Eric Lo), Visible Ventures

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🤖 The future of AI isn't about staring at screens—it's about living in intelligent environments. In my latest piece "The Symbiotic Future: Human-AI Integration in Spatial Computing," I explore how spatial AI will fundamentally transform our relationship with technology. Drawing from theories of extended cognition and environmental intelligence, I argue that we're moving beyond mere human-computer interaction toward true human-AI symbiosis. Key insights: —AI is evolving from tools we use to environments we inhabit —Intelligence will become distributed across our physical spaces —The future is not screen-based but world-embedded —Human and machine intelligence will form recursive feedback loops —This isn't just about better technology: it's about a new chapter in human evolution. Read the full article to discover how spatial computing might reshape what it means to be human in an AI-enabled world. #AI #SpatialComputing #FutureOfTech #Innovation #HumanAI #CognitiveScience #EmergingTech Thoughts? 🤔

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☕ Freshly Brewed Quantum News | August 14th, 2024 Qubernetes for reduced cost/increased speed in quantum software dev, new fermion-to-qubit mapping reduces entanglement, the connection between qubit materials and energy loss, and aperiodic/Penrose tilings inspire QEC codes ⚆ Researchers at the University of Jyväskylä are helping quantum developers experiment more efficiently with Qubernetes, a Kubernetes-based platform, and custom Jupyter kernels that allow seamless switching between local and remote environments, optimizing cost and speed in quantum software development ⚆ A new fermion-to-qubit mapping presented by ICFO and ICREA reduces entanglement in quantum simulations, making these simulations more practical and efficient on current quantum hardware, particularly for small molecules and electronic structure problems ⚆ Researchers from Yale University and Brookhaven National Laboratory have developed new quantum device and materials analysis techniques that significantly reduce energy loss, enhancing qubit coherence and overall quantum device performance ⚆ Spectral Capital Corporation's Quantum Bridge Program accelerates quantum startups by providing technical support, funding, and industry connection -- accelerating research toward real-world applications ⚆ BTQ joins QuINSA as a founding member alongside IBM and AWS to develop international standards for quantum communication, computing, and sensing ⚆ Researchers at Indira Gandhi Centre for Atomic Research (IGCAR) demonstrate Parrondo's paradox in quantum walks, where combining losing strategies can yield a winning outcome, offering new possibilities for quantum algorithm development ⚆ Researchers from North South University in Bangladesh propose a multi-layered security system combining quantum key distribution with classical cryptography to enhance the security of steganographic images against quantum and classical attacks ⚆ A Quanta Magazine podcast explores how the non-repeating patterns of aperiodic tilings, like Penrose tiles, could inspire new quantum error-correcting codes to protect quantum information ⚆ Anna Knörr's experience in the Perimeter Institute Perimeter Scholars International program highlights the importance of curiosity and openness in advancing quantum science and innovation ⚆ Don't miss a single qubit -- follow me & subscribe to the free newsletter for your daily quantum computing news & research insights. #quantumcomputing #quantumtechnology #innovation #quantumscience #quantumphysics

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2023 was a breakout year for investment in generative AI startups, with equity funding of almost $22B across 426 deals. The 5 largest rounds all went to companies focused on core generative AI infrastructure: * OpenAI, AI poster child and maker of ChatGPT ($10B corporate minority) * Inflection AI, which focuses on human-computer interfaces ($1.3B Series B) * Anthropic, an AI model developer and research outfit ($1.8B across 2 corporate minorities) * Databricks, a data integration and analytics platform ($504M Series I) * Aleph Alpha, Germany-based LLM developer ($500M Series B) When coupled with the pace of change and the compression of time and cost, makes anyone wonder, given the apparent speed of the commoditization of these LLM engines, what will the ROIC on funds deployed actually look like over time?

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In a world full of LLMs Google DeepMind quietly releases a new version of AlphaFold, a model that predicts structure and interactions of all life’s molecules (proteins, DNA, RNA, ligands) with unprecedented accuracy. For the interactions of proteins with other molecule types we see at least a 50% improvement compared with existing prediction methods. https://lnkd.in/dJkNghUY

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AI isn't just about replacing humans—it's about empowering them. 💪 AssuranceIQ, an innovative insurance startup, is pioneering a groundbreaking approach to leveraging generative AI: 1. They're using Large Language Models (LLMs) to score customer conversations. 2. This AI-powered system structures unstructured data from interactions. 3. The goal? Enhance the performance of human sales and support teams. 4. It's not about AI vs. humans, but AI amplifying human capabilities. 5. This could revolutionize how we train and develop customer-facing teams. This use case showcases the true potential of AI in business: not as a replacement, but as a powerful tool to augment human skills and drive performance. What other innovative ways could we use AI to empower rather than replace human workers? #AIInnovation #CustomerExperience #FutureOfWork #BusinessAI #TechTrends Share your thoughts on AI augmentation in the comments below!

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🧩 One thing we've noticed with #VentureIQ technology is how well it can distill and communicate complex technical material 🧩 Whether it's a #deeptech venture, a novel #AI application, or even a patent submission, we can quickly distill the business and strategic implications for investors...and sometimes even the founders/PIs themselves! 🤯 Based on our work so far, the tech can handle a wide array of research areas and technological sectors -- anything from blockchain algorithms to vaccine development. It handles the nuance of the field, the specific terminology, and extracts the key concepts which matter for venture-building. 🤓 To demonstrate, I took a patent I helped write with Eric Laber on reinforcement learning. I ran it through #Ventureiq to build a commercial assessment (key differentiators, target markets). Then for fun I had #NotebookLM make a podcast out of it. I've uploaded the result it here (DM me if you'd like the actual report): https://lnkd.in/eiTejsny This is more than just automation or streamlining operations - it's about unlocking clarity and insight when it was previously unattainable, and the ability to do it over and over again no matter the sector or vertical. Interested in more info? DM me so we can chat.

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💥Google's new Med-Gemini for healthcare outperforming GPT-4 Med-Gemini is a family of multimodal AI models built upon their Gemini models, specifically designed for the healthcare industry. From what I've read, these models are built on Google's existing Gemini AI architecture, but they've been specifically designed and trained for medical and clinical applications. It can process long-form medical records and research papers, and it can output text, images and videos to help explain things. Google is claiming that Med-Gemini has even outperformed OpenAI's powerful GPT-4 model on certain medical reasoning tasks, which is pretty impressive. On standard medical benchmarks like the MedQA exam, the Med-Gemini-L 1.0 model has scored really high, beating out even Google's own previous Med-PaLM 2 model. One cool feature is that Med-Gemini integrates web search, so it can pull in reliable information from the internet to provide more nuanced and factual responses. The models aren't publicly available yet - Google is still working on improving them and making sure they adhere to responsible AI principles around privacy and fairness before they release them. But from what I've seen, Med-Gemini is shaping up to be a really powerful set of medical AI tools.

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From where I sit in the SF Bay Area, cradle of innovation for at least the last 30 years, I'm a true believer in the promise of the #AI revolution. That said, I find it fascinating to consider views on the opposing side. I'm sharing below two opinion pieces from the last two weeks suggesting that the AI revolution is fundamentally overhyped and a bubble ripe for bursting, and that AI tools are actually not useful or transformative. Contrast this with venture capitalist Kai-Fu Lee's prognostication that 50% of white collar jobs will be displaced by #AI within three years, and that OpenAI and the other cutting edge movers in the space are headed to a trillion+ dollar valuation. Which side will win out? Where will we be by 2030 in the AI race? I'd love to hear your thoughts in the comments.

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Google Cloud and Anthropic made some exciting announcements: 📣 Claude 3 Opus, Anthropic’s most intelligent model, is now generally available on Vertex AI ⚙️ Tool use is available for the Claude 3 model family on Vertex AI, enabling Claude to act as an autonomous agent 📈Provisioned throughput is available for the Claude 3 model family on Vertex AI

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Elon Musk’s xAI and the Surprise Launch of Grok-2 Elon Musk's company xAI has launched Grok-2 and Grok-2 mini in beta, positioning xAI as a formidable competitor against AI giants like OpenAI and Google. Previously seen as a minor player, Grok-2 now reportedly surpasses GPT-4 and Claude 3.5 Opus in key benchmarks. Grok-2 boasts significant improvements in reasoning, reading, math, and science, particularly excelling in visual tasks. A strategic partnership with Black Forest Labs, known for their cutting-edge image generation technology, further enhances Grok-2’s capabilities. Independent validation is needed, but this move heightens the pressure on OpenAI and Google, making the industry eager to see their next steps. Link: https://x.ai/

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It has been my view for the last few months that the next big change in LLMs will be algorthmic optimization. Now comes this article. Don't sell your nvidia stock just yet, but remember that LxM technology is not just GPUs. https://lnkd.in/gyifxnHd

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India’s entrepreneurial ecosystem is thriving, offering vast, untapped potential. Unlike China, where state control has tightened, India provides a more supportive environment for startups. Here are some key points: ✅ 1. Growing Startup Ecosystem India’s startup ecosystem is the third-largest globally, with over 100 unicorns valued at around $340 billion. The surge in new businesses is driven by a young population, increasing internet use, and supportive government policies. ✅ 2. Untapped Markets The “Bharat” segment, referring to the population outside major cities, presents significant opportunities. Startups are targeting this segment with affordable products and services, bridging the digital divide between urban and rural areas. ✅ 3. Deep Science and Technology India’s deep science tech ecosystem is ripe for investment. Innovations in biotechnology, renewable energy, and advanced manufacturing are set to make global impacts. 📶 Recent Examples ✅ Zepto: Offers 10-minute grocery delivery, quickly becoming a unicorn. Jio Financial Services: Partnered with BlackRock to revolutionize wealth management in India. ✅ Semiconductor Startups: AGNIT Semiconductors and Aura Semiconductor are leading the industry. ✅ Dharaksha Ecosolutions: Converts crop residue into biodegradable packaging. ✅ Digital Payments and Agri-tech: Paytm and Ninjacart are transforming digital transactions and agricultural supply chains. India’s startup ecosystem is not just about financial growth but also societal progress. With the right investments, India is poised to become a global leader in innovation and entrepreneurship. if you are looking for corporate venture strategies or you are a startup or innovation looking for corporate ventures funding in India. Feel free to connect. [email protected]

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Stability AI have introduced significant improvements through the development of Scaling Rectified Flow Transformers (RFTs) a key component of the StableDiffusion 3 architecture. This research enhances generative models for text-to-image synthesis by leveraging rectified flow models, which connect data and noise in a straight line, offering better theoretical properties, prompt stability, and conceptual simplicity compared to traditional diffusion models.   The team shows improved noise sampling techniques for training rectified flow models, biased towards perceptually relevant scales, which demonstrate superior performance over established diffusion formulations. A novel diffusion-transformer based architecture is presented, using separate weights for image and text modalities, enabling a bidirectional flow of information. The backbone, MM-DiT, is designed to handle different domains using separate sets of trainable model weights, outperforming existing transformer-based diffusion backbones.   The study also showcases the scalability of this architecture, with predictable scaling trends correlating lower validation loss with improved text-to-image synthesis. The largest models outperform current state-of-the-art models and improves upon text comprehension, typography, and overall image quality, as confirmed by human preference ratings.  Arxiv: https://lnkd.in/e7dhHAt8

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Former Google CEO Eric Schmidt is walking back his (highly questionable) claim that remote work is to blame for Google slipping behind in the AI race. "Google decided that work-life balance and going home early and working from home was more important than winning. And the reason startups work is because people work like hell." The comment sparked A LOT of criticism, especially given Google isn't a startup anymore; more so because they have one of the largest and best AI development teams on the planet! According to the Alphabet Employee Union, understaffing, shifting priorities, constant layoffs, stagnant wages and lack of follow-through from management on projects, these factors slow Google workers down every day. So not sleeping on the floors and working horrendous hours isn't the problem. Instead, the consensus seems to be that, amongst other things, coming late to market with a chatbot well after OpenAI, served to refocus users on Google’s competitors. Additionally, investing the least dollars of their Big 4 competitors (eg only a few percent compared to Apple) doesn’t help. Blaming your workforce, especially a predominantly very committed one, for an enterprise’s failures, is never good for cordial employee relations. #ai #google #futureofwork https://lnkd.in/gsHSRYXx?

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The Nobel Prize winning ‘Godfather of AI’, Geoffrey Hinton, on the potential for AI “exceeding human intelligence” and “trying to take over.” He explains how it's in many ways a 'superior form of intelligence' because it can share and replicate knowledge so quickly. He worries that it will lead to greater inequality, kill off many mid-level white collar jobs, and current regulation having no 'teeth'. The 'arms race' between the big tech companies (something I describe in my talk here https://lnkd.in/eeApCDF3) means that profits are being put before safety. Finally, what's a safe job in the Age of AI: 'plumbing'. More on AI risk at... AI Risk

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🏔 Had a great chat with Daphné Leprince-Ringuet and Robert Sutor about the future of quantum, scaling capital in Europe, and how we are moving into the next phase of quantum computing. The title is provocative 🚀 - ‘Quantum computing is taking longer than going to the moon’: Ex-IBM exec Robert Sutor on Europe’s quantum computing startups 🌙 - but the key point is that building good Quantum Processing Units (QPUs) of ~1000s of qubits each IS the absolutely critical foundation, but sadly cannot get us all the way there, and that, just like with the space programme, new technologies and approaches such as Nu Quantum 's networking technology are urgently needed if we want to avoid slowing down or failing. Here is my favourite quote: “My view ranges from that of a massive company pumping millions and millions of dollars in their quantum programmes, to that of smaller companies,” Sutor tells Sifted. “And the teaser here is that quantum computing is simply not going to scale unless we have the types of technologies that [startups like] Nu Quantum are pioneering.” Sifted https://lnkd.in/ecnQQ-yH

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