Impact AI

著者： Heather D. Couture
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  • Learn how to build a mission-driven machine learning company from the innovators and entrepreneurs who are leading the way. A weekly show about the intersection of ML and business – particularly startups. We discuss the challenges and best practices for working with data, mitigating bias, dealing with regulatory processes, collaborating across disciplines, recruiting and onboarding, maximizing impact, and more.
    © 2023 Pixel Scientia Labs, LLC
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  • Foundation Model Series: Understanding Brain Activity with Dimitris Sakellariou from Piramidal

    Foundation Model Series: Understanding Brain Activity with Dimitris Sakellariou from Piramidal
    2024/09/16

    What if we could understand brain activity in real-time to better diagnose neurological conditions? In this episode, part of a special mini-series on domain-specific foundation models, I sit down with Dimitris Sakellariou, the founder and CEO of Piramidal, to talk about their groundbreaking work in automating EEG interpretation. Piramidal is focused on democratizing brain health insights, making interpreting brainwave data more accessible and accurate. With a strong foundation in neuroscience and AI, Dimitris and his team are developing models that could revolutionize how we understand brain activity and diagnose neurological conditions.

    In our conversation, Dimitris explains the challenges of building a foundation model for brain activity, the role of data diversity, and the future potential for personalized brain health monitoring. Discover the implications of Piramidal’s technology beyond healthcare and its application in cognitive enhancement and stress management. Tune in as we explore how Piramidal is paving the way for personalized brain health monitoring and why this could be a game-changer for the future of medicine!


    Key Points:

    • Dimitris discusses his journey from physics to a career in neuroscience.
    • Explore Piramidal's mission to automate EEG interpretation.
    • Learn about the complexity and variability of brainwave patterns
    • Hear how machine learning can better analyze brain activity.
    • Uncover the challenges of building a foundation model for EEG data.
    • Why diverse data sets are vital for training the foundational model.
    • Piramidal's plans for making EEG analysis more accessible.
    • Future use cases for Piramidal’s model in healthcare and beyond.
    • Discover why domain knowledge for model building is essential.
    • He shares advice for AI startup founders.


    Quotes:

    “Piramidal is primarily focused at the moment in automating, or otherwise democratizing the interpretation of these tests, these brainwave recordings so that patients and people that have issues with their brain can get access to the diagnosis much, much, much faster.” — Dimitris Sakellariou

    “It's very important to have discussions with neuroscientists and clinical experts in order to understand what is the end-to-end pipeline from receiving data all the way to inference.” — Dimitris Sakellariou


    “Finding the right person. Someone that is very keen to build together with you and make important and difficult decisions can change massively a trajectory of your company.” — Dimitris Sakellariou


    Links:

    Dimitris Sakellariou on LinkedIn

    Dimitris Sakellariou on X

    Piramidal

    Piramidal on LinkedIn


    Resources for Computer Vision Teams:

    LinkedIn – Connect with Heather.

    Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

    Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.
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    24 分
  • Foundation Model Series: Better, Faster, Cheaper Earth Observation with Bruno Sánchez-Andrade Nuño from Clay

    Foundation Model Series: Better, Faster, Cheaper Earth Observation with Bruno Sánchez-Andrade Nuño from Clay
    2024/09/09
    Can AI be applied to enhance geospatial data for climate, nature and people? This episode kicks off a miniseries about domain-specific foundation models. Following the trends in language processing, domain-specific foundation models are enabling new possibilities for a variety of applications, including Earth observation. During this conversation, I am joined by Bruno Sánchez-Andrade Nuño, Executive Director of Clay, a nonprofit organization harnessing the power of AI for satellite images, spatial data, and more. Bruno shares the functionality and concept behind Clay, and his journey to building it. He goes on to unpack the tool’s foundation model in broad strokes, before explaining why it's important, and sharing the challenges he has faced along the way. We discuss the legal aspects of building Clay, and it’s primary goal to make it as easy as possible for any user to achieve their goals. We also touch on what the future might hold for Clay and the future of Earth observation. Thanks for listening!Key Points:Introducing guest, Bruno Sánchez-Andrade Nuño, Executive Director at Clay.His journey from NASA astrophysicist to climate change, social development, and AI researcher.What Clay focuses on: using remote sensing maps to interpret the Earth’s data.The mechanics of how Clay is used and how different feature sets compare to one another.A broad explanation of the tool’s foundation model and why it is quicker, cheaper, and more environmentally friendly.Two main benefits of the tool that Bruno finds most exciting. Data and infrastructure required to build Clay including 70 million satellite and aerial images.Measuring what the model understands and the process of compressing an image into 700 numbers.Privacy and intellectual property in the realm of satellite imaging and mapping. What commercial imagery could add to the model and how it might be integrated in the future. Clay’s partnerships with university and company groupsWhy the focus of Clay is to make it as easy as possible for anyone to use the tool for anything they want to do. Challenges encountered on the road to building Clay: explaining what it is.The complexity of benchmarking foundation models and how this relates to Clay. Working with partners to build Clay and the rest of the ecosystem. Lessons from building Clay that may apply to other foundation models.Bruno’s predictions for the future of foundation models and Clay. What is certain about the future of Clay and our understanding of Earth. Quotes:“Clay is trying to figure out how to finally increase the adoption of remote sensing by leveraging a tool that itself is very complex, but the result of that tool is very easy to use.” — Bruno Sánchez-Andrade Nuño“If you start with a foundational model that gets you most of the way there, [then] you can create those trials much quicker, much cheaper, and much more environmentally friendly.” — Bruno Sánchez-Andrade Nuño“This is so new, we get the chance, those of us working on it, that we can save the whole industry, if you will, the whole space of AI for it.” — Bruno Sánchez-Andrade Nuño“Clay, I believe, is not only the largest and most efficient model AI for Earth, for any kind of like foundational model. It is also completely open source.” — Bruno Sánchez-Andrade Nuño“What we try to focus on is how can we make it as simple as possible for anyone anywhere to use this model for anything they want to do.” — Bruno Sánchez-Andrade NuñoLinks:Bruno Sánchez-AndradeBruno Sánchez-Andrade Nuño on XBruno Sánchez-Andrade Nuño on LinkedInClayClay on LinkedInResources for Computer Vision Teams:LinkedIn – Connect with Heather.Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.
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    36 分
  • Evolutionary Insights for Drug Discovery with Ashley Zehnder from Fauna Bio

    Evolutionary Insights for Drug Discovery with Ashley Zehnder from Fauna Bio
    2024/09/02

    In a world where conventional drug discovery methods frequently fall short, today's guest addresses the critical challenge of fighting human diseases by drawing inspiration from nature’s most resilient creatures. Could the secret to overcoming our most stubborn illnesses lie in the extraordinary adaptability of extreme mammals? Veterinarian-scientist Ashley Zehnder, the Co-founder and CEO of AI-driven drug discovery company Fauna Bio, believes so.

    By leveraging data from 100 million years of evolved disease resistance in mammals, Ashley sees a unique opportunity at the crossroads of genomics and emerging model species to improve health for all species, including humans. In this episode, she explores how harnessing the biological secrets of these animals using AI and machine learning could revolutionize medicine, leading to breakthroughs that benefit us all. Tune in to discover how Fauna Bio is pioneering a new frontier in drug discovery and how understanding the resilience of these creatures could reshape the future of healthcare!


    Key Points:

    • Insight into the diverse backgrounds of Fauna Bio’s founding members.
    • Ways that Fauna Bio uses AI and genomics to identify key targets for new therapeutics.
    • The role machine learning plays in analyzing and annotating large volumes of data.
    • Gene expression and other data inputs that drive Fauna Bio’s discoveries.
    • The collaborative effort required to collate datasets from 400+ mammals.
    • Challenges of working with genomic data and training ML models on it.
    • How Fauna Bio rigorously validates their AI-driven discoveries.
    • Cooperation between ML developers and domain experts to advance this technology.
    • Technological advancements that enable Fauna Bio’s innovations.
    • Ashely’s advice on differentiation for leaders of AI-powered startups.
    • Where she sees Fauna Bio making the biggest impact in the future.


    Quotes:

    “[Fauna Bio uses] AI and genomics as a way to identify the most impactful targets for new therapeutic programs across a broad number of diseases.” — Ashley Zehnder


    “It’s certainly easier than it has been in the past to generate very high-quality single-cell RNA sequencing. We’re doing a lot of that. The challenges on the technical side are getting much easier. The challenges on the interpretation side are still there.” — Ashley Zehnder


    “There are many points along the drug discovery path where AI companies can differentiate. But that story has to be clear because, otherwise, it's very hard to get out of the signal-to-noise that is the AI discovery landscape in biopharma” — Ashley Zehnder


    Links:

    Fauna Bio

    Ashley Zehnder on LinkedIn

    Ashley Zehnder on X

    Ashley Zehnder Email

    Zoonomia Project

    Science Issue dedicated to the Zoonomia Project


    Resources for Computer Vision Teams:

    LinkedIn – Connect with Heather.

    Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

    Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.
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    27 分

あらすじ・解説

Learn how to build a mission-driven machine learning company from the innovators and entrepreneurs who are leading the way. A weekly show about the intersection of ML and business – particularly startups. We discuss the challenges and best practices for working with data, mitigating bias, dealing with regulatory processes, collaborating across disciplines, recruiting and onboarding, maximizing impact, and more.
© 2023 Pixel Scientia Labs, LLC
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