Practical AI

Practical AI

By Daniel Whitenack and Chris BensonTechnology
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    48 min

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Practical AI episodes

  • DALL-E is one giant leap for raccoons! 🔭

    In this Fully-Connected episode, Daniel and Chris explore DALL-E 2, the amazing new model from Open AI that generates incredibly detailed novel images from text captions for a wide range of concepts expressible in natural language. Along the way, they acknowledge that some folks in the larger AI community are suggesting that sophisticated models may be approaching sentience, but together they pour cold water on that notion. But they can’t seem to get away from DALL-E’s images of raccoons in space, and of course, who would want to?


    Featuring:

    • Chris Benson – Website, GitHub, LinkedIn, X
    • Daniel Whitenack – Website, GitHub, X

    Show Notes:

    • DALL·E: Creating Images from Text
    • How DALL-E 2 Actually Works
    • Google - Raccoons in Space!
    • On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜

    Upcoming Events: 

    • Register for upcoming webinars here!
    41 min
  • Cloning voices with Coqui

    Coqui is a speech technology startup that making huge waves in terms of their contributions to open source speech technology, open access models and data, and compelling voice cloning functionality. Josh Meyer from Coqui joins us in this episode to discuss cloning voices that have emotion, fostering open source, and how creators are using AI tech.


    Featuring:

    • Josh Meyer – GitHub, X
    • Chris Benson – Website, GitHub, LinkedIn, X
    • Daniel Whitenack – Website, GitHub, X

    Show Notes:

    • Coqui
    • BibleTTS - Data and models for African langauges
    • Coqui TTS Hugging Face Space
    • Coqui on Github
    • Joshua’s previous Practical AI episode about Common Voice

    Upcoming Events: 

    • Register for upcoming webinars here!
    52 min
  • AI's role in reprogramming immunity

    Drausin Wulsin, Director of ML at Immunai, joins Daniel & Chris to talk about the role of AI in immunotherapy, and why it is proving to be the foremost approach in fighting cancer, autoimmune disease, and infectious diseases.

    The large amount of high dimensional biological data that is available today, combined with advanced machine learning techniques, creates unique opportunities to push the boundaries of what is possible in biology.

    To that end, Immunai has built the largest immune database called AMICA that contains tens of millions of cells. The company uses cutting-edge transfer learning techniques to transfer knowledge across different cell types, studies, and even species.


    Featuring:

    • Drausin Wulsin – LinkedIn
    • Chris Benson – Website, GitHub, LinkedIn, X
    • Daniel Whitenack – Website, GitHub, X

    Show Notes:

    • Immunai
    • Immunai Fact Sheet
    • Drausin Wulsin | LinkedIn
    • Drausin Wulsin | Google Scholar

    Upcoming Events: 

    • Register for upcoming webinars here!
    49 min
  • Machine learning in your database

    While scaling up machine learning at Instacart, Montana Low and Lev Kokotov discovered just how much you can do with the Postgres database. They are building on that work with PostgresML, an extension to the database that lets you train and deploy models to make online predictions using only SQL. This is super practical discussion that you don’t want to miss!


    Featuring:

    • Montana Low – GitHub, LinkedIn, X
    • Lev Kokotov – GitHub, LinkedIn
    • Chris Benson – Website, GitHub, LinkedIn, X
    • Daniel Whitenack – Website, GitHub, X

    Show Notes:

    • PostgresML website
    • PostgresML on GitHub

    Upcoming Events: 

    • Register for upcoming webinars here!
    50 min
  • Digital humans & detecting emotions

    Could we create a digital human that processes data in a variety of modalities and detects emotions? Well, that’s exactly what NTT DATA Services is trying to do, and, in this episode, Theresa Kushner joins us to talk about their motivations, use cases, current systems, progress, and related ethical issues.


    Featuring:

    • Theresa Kushner – LinkedIn, X
    • Daniel Whitenack – Website, GitHub, X

    Show Notes:

    Digital Humans videos:

    • Kia Showroom
    • Learning Assistant
    • Telco Retail
    • Kia, in car
    • Japan Concierge

    Virtual Learning Buddy teaching kids to read:

    • Related blog post
    • More information about NTT DATA’s work with MIT Media Lab

    Upcoming Events: 

    • Register for upcoming webinars here!
    43 min
  • Generalist models & Iceman's voice

    In this “fully connected” episode of the podcast, we catch up on some recent developments in the AI world, including a new model from DeepMind called Gato. This generalist model can play video games, caption images, respond to chat messages, control robot arms, and much more. We also discuss the use of AI in the entertainment industry (e.g., in new Top Gun movie).


    Featuring:

    • Chris Benson – Website, GitHub, LinkedIn, X
    • Daniel Whitenack – Website, GitHub, X

    Show Notes:

    DeepMind’s Gato:

    • DeepMind article
    • TNW article

    Iceman’s voice in Top Gun:

    • Variety article
    • Sonantic - the company behind the synthetic voice

    Responsible AI review processes: From a developer’s point of view


    Upcoming Events: 

    • Register for upcoming webinars here!
    41 min
  • 🤗 The AI community building the future

    Hugging Face is increasingly becomes the “hub” of AI innovation. In this episode, Merve Noyan joins us to dive into this hub in more detail. We discuss automation around model cards, reproducibility, and the new community features. If you are wanting to engage with the wider AI community, this is the show for you!


    Featuring:

    • Merve Noyan – GitHub, X
    • Chris Benson – Website, GitHub, LinkedIn, X
    • Daniel Whitenack – Website, GitHub, X

    Show Notes:

    • The Hugging Face hub
    • New Hugging Face community features

    Upcoming Events: 

    • Register for upcoming webinars here!
    48 min
  • Active learning & endangered languages

    Don’t all AI methods need a bunch of data to work? How could AI help document and revitalize endangered languages with “human-in-the-loop” or “active learning” methods? Sarah Moeller from the University of Florida joins us to discuss those and other related questions. She also shares many of her personal experiences working with languages in low resource settings.


    Featuring:

    • Sarah Moeller – Website, GitHub, LinkedIn
    • Chris Benson – Website, GitHub, LinkedIn, X
    • Daniel Whitenack – Website, GitHub, X

    Show Notes:

    • Sarah’s academic website
    • An article about Sarah’s journey into this work

    Upcoming Events: 

    • Register for upcoming webinars here!
    50 min
  • Learning the language of life

    AI is discovering new drugs. Sound like science fiction? Not at Absci! Sean and Joshua join us to discuss their AI-driven pipeline for drug discovery. We discuss the tech along with how it might change how we think about healthcare at the most fundamental level.


    Sponsors:

    • Changelog++ – You love our content and you want to take it to the next level by showing your support. We’ll take you closer to the metal with extended episodes, make the ads disappear, and increment your audio quality with higher bitrate mp3s. Let’s do this! 

    Featuring:

    • Sean McClain – LinkedIn, X
    • Joshua Meier – GitHub, LinkedIn, X
    • Chris Benson – Website, GitHub, LinkedIn, X
    • Daniel Whitenack – Website, GitHub, X

    Show Notes:

    • View Absci’s AI Lead Scientist Joshua Meier’s presentation at NVIDIA GTC 2022
    • Learn more about Absci’s machine learning breakthroughs presented at GTC
    • Learn more about Absci AI Research (AAIR) Lab
    • View career opportunities at Absci
    • Absci AI drug discovery technology
    • Watch the Truist AI Symposium Podcast to get help demystifying the use of AI in drug discovery
    • Absci website

    Upcoming Events: 

    • Register for upcoming webinars here!
    48 min
  • MLOps is NOT Real

    We all hear a lot about MLOps these days, but where does MLOps end and DevOps begin? Our friend Luis from OctoML joins us in this episode to discuss treating AI/ML models as regular software components (once they are trained and ready for deployment). We get into topics including optimization on various kinds of hardware and deployment of models at the edge.


    Sponsors:

    • Changelog++ – You love our content and you want to take it to the next level by showing your support. We’ll take you closer to the metal with extended episodes, make the ads disappear, and increment your audio quality with higher bitrate mp3s. Let’s do this! 
    • Ship It! – A podcast about getting your best ideas into the world and seeing what happens. Listen to an episode that interests you and subscribe today. 

    Featuring:

    • Luis Ceze – LinkedIn, X
    • Chris Benson – Website, GitHub, LinkedIn, X
    • Daniel Whitenack – Website, GitHub, X

    Show Notes:

    • OctoML

    Upcoming Events: 

    • Register for upcoming webinars here!
    46 min

About Practical AI

From the publisher's feed

Making artificial intelligence practical, productive & accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs & more).

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