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    News

    The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

    Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.

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    Copyright: © All rights reserved

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    Latest Episodes:
    Common Sense as an Algorithmic Framework with Dileep George - #430 Nov 23, 2020
    Show notes

    Today we’re joined by Dileep George, Founder and the CTO of Vicarious.

    Dileep, who was also a co-founder of Numenta, works at the intersection of AI research and neuroscience, and famously pioneered the hierarchical temporal memory. In our conversation, we explore the importance of mimicking the brain when looking to achieve artificial general intelligence, the nuance of “language understanding” and how all the tasks that fall underneath it are all interconnected, with or without language.

    We also discuss his work with Recursive Cortical Networks, Schema Networks, and what’s next on the path towards AGI!


    Scaling Enterprise ML in 2020: Still Hard! with Sushil Thomas - #429 Nov 19, 2020
    Show notes

    Today we’re joined by Sushil Thomas, VP of Engineering for Machine Learning at Cloudera.

    Over the summer, I had the pleasure of hosting Sushil and a handful of business leaders across industries at the Cloudera Virtual Roundtable. In this conversation with Sushil, we recap the roundtable, exploring some of the topics discussed and insights gained from those conversations. Sushil gives us a look at how COVID19 has impacted business throughout the year, and how the pandemic is shaping enterprise decision making moving forward.

    We also discuss some of the key trends he’s seeing as organizations try to scale their machine learning and AI efforts, including understanding best practices, and learning how to hybridize the engineering side of ML with the scientific exploration of the tasks. Finally, we explore if organizational models like hub vs centralized are still organization-specific or if that’s changed in recent years, as well as how to get and retain good ML talent with giant companies like Google and Microsoft looming large.

    The complete show notes for this episode can be found at https://twimlai.com/go/429.


    Enabling Clinical Automation: From Research to Deployment with Devin Singh - #428 Nov 16, 2020
    Show notes

    Today we’re joined by Devin Singh, a Physician Lead for Clinical Artificial Intelligence & Machine Learning in Pediatric Emergency Medicine at the Hospital for Sick Children (SickKids) in Toronto, and Founder and CEO of HeroAI.

    In our conversation with Devin, we discuss some of the interesting ways that Devin is deploying machine learning within the SickKids hospital, the current structure of academic research, including how much research and publications are currently being incentivized, how little of those research projects actually make it to deployment, and how Devin is working to flip that system on it's head.

    We also talk about his work at Hero AI, where he is commercializing and deploying his academic research to build out infrastructure and deploy AI solutions within hospitals, creating an automated pipeline with patients, caregivers, and EHS companies. Finally, we discuss Devins's thoughts on how he’d approach bias mitigation in these systems, and the importance of having proper stakeholder engagement and using design methodology when building ML systems.

    The complete show notes for this episode can be found at twimlai.com/go/428.


    Pixels to Concepts with Backpropagation w/ Roland Memisevic - #427 Nov 12, 2020
    Show notes

    Today we’re joined by Roland Memisevic, return podcast guest and Co-Founder & CEO of Twenty Billion Neurons.

    We last spoke to Roland in 2018, and just earlier this year TwentyBN made a sharp pivot to a surprising use case, a companion app called Fitness Ally, an interactive, personalized fitness coach on your phone.

    In our conversation with Roland, we explore the progress TwentyBN has made on their goal of training deep neural networks to understand physical movement and exercise. We also discuss how they’ve taken their research on understanding video context and awareness and applied it in their app, including how recent advancements have allowed them to deploy their neural net locally while preserving privacy, and Roland’s thoughts on the enormous opportunity that lies in the merging of language and video processing.

    The complete show notes for this episode can be found at twimlai.com/go/427.


    Fighting Global Health Disparities with AI w/ Jon Wang - #426 Nov 09, 2020
    Show notes

    Today we’re joined by Jon Wang, a medical student at UCSF, and former Gates Scholar and AI researcher at the Bill and Melinda Gates Foundation.

    In our conversation with Jon, we explore a few of the different ways he’s attacking various public health issues, including improving the electronic health records system through automating clinical order sets, and exploring how the lack of literature and AI talent in the non-profit and healthcare spaces, and bad data have further marginalized undersupported communities.

    We also discuss his work at the Gates Foundation, which included understanding how AI can be helpful in lower-resource and lower-income countries, and building digital infrastructure, and much more.

    The complete show notes for this episode can be found at twimlai.com/go/426.


    Accessibility and Computer Vision - #425 Nov 05, 2020
    Show notes

    Digital imagery is pervasive today. More than a billion images per day are produced and uploaded to social media sites, with many more embedded within websites, apps, digital documents, and eBooks. Engaging with digital imagery has become fundamental to participating in contemporary society, including education, the professions, e-commerce, civics, entertainment, and social interactions.

    However, most digital images remain inaccessible to the 39 million people worldwide who are blind. AI and computer vision technologies hold the potential to increase image accessibility for people who are blind, through technologies like automated image descriptions.

    The speakers share their perspectives as people who are both technology experts and are blind, providing insight into future directions for the field of computer vision for describing images and videos for people who are blind.

    To check out the video of this panel, visit here!

    The complete show notes for this episode can be found at twimlai.com/go/425


    NLP for Equity Investing with Frank Zhao - #424 Nov 02, 2020
    Show notes

    Today we’re joined by Frank Zhao, Senior Director of Quantamental Research at S&P Global Market Intelligence.

    In our conversation with Frank, we explore how he came to work at the intersection of ML and finance, and how he navigates the relationship between data science and domain expertise. We also discuss the rise of data science in the investment management space, examining the largely under-explored technique of using unstructured data to gain insights into equity investing, and the edge it can provide for investors.

    Finally, Frank gives us a look at how he uses natural language processing with textual data of earnings call transcripts and walks us through the entire pipeline.

    The complete show notes for this episode can be found at twimlai.com/go/424.


    The Future of Education and AI with Salman Khan - #423 Oct 28, 2020
    Show notes

    In the final #TWIMLfest Keynote Interview, we’re joined by Salman Khan, Founder of Khan Academy.

    In our conversation with Sal, we explore the amazing origin story of the academy, and how coronavirus is shaping the future of education and remote and distance learning, for better and for worse. We also explore Sal’s perspective on machine learning and AI being used broadly in education, the potential of injecting a platform like Khan Academy with ML and AI for course recommendations, and if they’re planning on implementing these features in the future.

    Finally, Sal shares some great stories about the impact of community and opportunity, and what advice he has for learners within the TWIML community and beyond!

    The complete show notes for this episode can be found at twimlai.com/go/423.


    Why AI Innovation and Social Impact Go Hand in Hand with Milind Tambe - #422 Oct 23, 2020
    Show notes

    In this special #TWIMLfest Keynote episode, we’re joined by Milind Tambe, Director of AI for Social Good at Google Research India, and Director of the Center for Research in Computation and Society (CRCS) at Harvard University.

    In our conversation, we explore Milind’s various research interests, most of which fall under the umbrella of AI for Social Impact, including his work in public health, both stateside and abroad, his conservation work in South Asia and Africa, and his thoughts on the ways that those interested in social impact can get involved.

    The complete show notes for this episode can be found at twimlai.com/go/422.


    What's Next for Fast.ai? w/ Jeremy Howard - #421 Oct 21, 2020
    Show notes

    In this special #TWIMLfest episode of the podcast, we’re joined by Jeremy Howard, Founder of Fast.ai.

    In our conversation with Jeremy, we discuss his career path, including his journey through the consulting world and how those experiences led him down the path to ML education, his thoughts on the current state of the machine learning adoption cycle, and if we’re at maximum capacity for deep learning use and capability.

    Of course, we dig into the newest version of the fast.ai framework and course, the reception of Jeremy’s book ‘Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD,’ and what’s missing from the machine learning education landscape. If you’ve missed our previous conversations with Jeremy, I encourage you to check them out here and here.

    The complete show notes for this episode can be found at https://twimlai.com/go/421.


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