Making artificial intelligence practical, productive, and 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, and more). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!
89 Subscribers
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Practical AI: Machine Learning, Data Science
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89 Subscribers
Reviews
4.5 out of 5 stars
Based on 10 reviews
sulemanb
1 out of 5 stars
Not practical at all
Useless podcast, these just siting around talking about their history.
luckychaparro
5 out of 5 stars
Excellent for beginners!
I’ve just begun my journey into researching machine learning and AI more widely, and Practical AI has been a light in the dark! Friendly, level, engaged, and interesting. Can’t wait for the next episode.
Josben73
5 out of 5 stars
My favorite pod
These two really bring a complicated topic around AI and try to ensure that even the casual AI practitioner can understand. Love it!!!
Juliet montag
5 out of 5 stars
Great discussions on AI
I love listening to Practical AI when I go for a walk or run. Staying up to date on AI trends and getting the perspectives of industry leaders on the how AI is used, where it’s headed, and how to be ethical is a real treat. I learn something new every time I tune in!
ninevolt
5 out of 5 stars
Learn something new every episode
I've been listening to Practical AI for a while now -- I've found it to be a useful way to keep up to date with current developments in industry regarding AI and machine learning. Highly recommended.
Meditative-Silence
5 out of 5 stars
As a college student, love it
I'm currently majoring in Computer Systems Technology & wanting to pursue a career in Data Science using machine learning and things like that in the field. It's been hard to figure out what kinds of things I should be learning in my own time to better prepare for my future career. This podcast has really given me tremendous help in conceptualizing what it is that I want to do post-college. I highly recommend it to anyone and everyone.
devMailey
5 out of 5 stars
Fun and interesting!
A great listen if you're interested in data science and everything that goes into it! Fun to listen to and so many interesting topics covered!
mtokudome
5 out of 5 stars
Invaluable content
A must-listen if you are interested in the topic of data science, machine learning, and artificial intelligence. Great interviews and conversations. I'm learning a lot!
atxbg
4 out of 5 stars
Grass roots detector of great open source AI projects
Impressive work on spotting upcoming open source AI projects and interviewing their founders.
doij790
5 out of 5 stars
Great scope and content of AI related topics
I’ve been listening to this podcast lately on my way to work, and I want to say I really enjoy the its scope and the practical aspects that it covers. I especially enjoyed episode 51 with Joel Grus as he shared a lot of his insights for programming for good science and have tried to embody his practices as well as watching some of his live coding sessions on Youtube, which are great. I’m doing research in NLP at a university and I’ve always felt like my research code was not quite professional and reader-friendly, and I made good use of the learning resources that this podcast always provides.
Podcast information
- Amount of episodes
- 197
- Subscribers
- 89
- Verified
- No
- Website
- Explicit content
- No
- Episode type
- episodic
- Podcast link
- https://podvine.com/link/..
- Last upload date
- September 27, 2022
- Last fetch date
- October 7, 2022 7:06 PM
- Upload range
- WEEKLY
- Author
- Changelog Media
- Copyright
- All rights reserved
susbcribers
- Production data labeling workflowsIt’s one thing to gather some labels for your data. It’s another thing to integrate data labeling into your workflows and infrastructure in a scalable, secure, and useful way. Mark from Xelex joins us to talk through some of what he has learned after helping companies scale their data annotation efforts. We get into workflow management, labeling instructions, team dynamics, and quality assessment. This is a super practical episode!0 comments0
- Evaluating models without test dataWeightWatcher, created by Charles Martin, is an open source diagnostic tool for analyzing Neural Networks without training or even test data! Charles joins us in this episode to discuss the tool and how it fills certain gaps in current model evaluation workflows. Along the way, we discuss statistical methods from physics and a variety of practical ways to modify your training runs.0 comments0
- Stable DiffusionThe new stable diffusion model is everywhere! Of course you can use this model to quickly and easily create amazing, dream-like images to post on twitter, reddit, discord, etc., but this technology is also poised to be used in very pragmatic ways across industry. In this episode, Chris and Daniel take a deep dive into all things stable diffusion. They discuss the motivations for the work, the model architecture, and the differences between this model and other related releases (e.g., DALL·E 2). (Image from stability.ai)0 comments0
- Licensing & automating creativityAI is increasingly being applied in creative and artistic ways, especially with recent tools integrating models like Stable Diffusion. This is making some artists mad. How should we be thinking about these trends more generally, and how can we as practitioners release and license models anticipating human impacts? We explore this along with other topics (like AI models detecting swimming pools 😊) in this fully connected episode.0 comments0
- Privacy in the age of AIIn this Fully-Connected episode, Daniel and Chris discuss concerns of privacy in the face of ever-improving AI / ML technologies. Evaluating AI’s impact on privacy from various angles, they note that ethical AI practitioners and data scientists have an enormous burden, given that much of the general population may not understand the implications of the data privacy decisions of everyday life. This intentionally thought-provoking conversation advocates consideration and action from each listener when it comes to evaluating how their own activities either protect or violate the privacy of those whom they impact.0 comments0
- Practical, positive uses for deep fakesDifferentiating between what is real versus what is fake on the internet can be challenging. Historically, AI deepfakes have only added to the confusion and chaos, but when labeled and intended for good, deepfakes can be extremely helpful. But with all of the misinformation surrounding deepfakes, it can be hard to see the benefits they bring. Lior Hakim, CTO at Hour One, joins Chris and Daniel to shed some light on the practical uses of deepfakes. He addresses the AI technology behind deepfakes, how to make positive use of deep fakes such as breaking down communications barriers, and shares how Hour One specializes in the development of virtual humans for use in professional video communications.0 comments0
- CMU's AI pilot lands in the news 🗞Daniel and Chris cover the AI news of the day in this wide-ranging discussion. They start with Truss from Baseten while addressing how to categorize AI infrastructure and tools. Then they move on to transformers (again!), and somehow arrive at an AI pilot model from CMU that can navigate crowded airspace (much to Chris’s delight).0 comments0
- AlphaFold is revolutionizing biologyAlphaFold is an AI system developed by DeepMind that predicts a protein’s 3D structure from its amino acid sequence. It regularly achieves accuracy competitive with experiment, and is accelerating research in nearly every field of biology. Daniel and Chris delve into protein folding, and explore the implications of this revolutionary and hugely impactful application of AI.0 comments0
- AI IRL & Mozilla's Internet Health ReportEvery year Mozilla releases an Internet Health Report that combines research and stories exploring what it means for the internet to be healthy. This year’s report is focused on AI. In this episode, Solana and Bridget from Mozilla join us to discuss the power dynamics of AI and the current state of AI worldwide. They highlight concerning trends in the application of this transformational technology along with positive signs of change.0 comments0
- The geopolitics of artificial intelligenceIn this Fully-Connected episode, Chris and Daniel explore the geopolitics, economics, and power-brokering of artificial intelligence. What does control of AI mean for nations, corporations, and universities? What does control or access to AI mean for conflict and autonomy? The world is changing rapidly, and the rate of change is accelerating. Daniel and Chris look behind the curtain in the halls of power.0 comments0
- 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?0 comments0
- Cloning voices with CoquiCoqui 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.0 comments0
- AI's role in reprogramming immunityDrausin 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.0 comments0
- Machine learning in your databaseWhile 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!0 comments0
- Digital humans & detecting emotionsCould 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.0 comments0
- Generalist models & Iceman's voiceIn 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).0 comments0
- 🤗 The AI community building the futureHugging 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!0 comments0
- Active learning & endangered languagesDon’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.0 comments0
- Learning the language of lifeAI 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.0 comments0
- MLOps is NOT RealWe 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.0 comments0
- 🌍 AI in Africa - AgricultureIn the fourth “AI in Africa” spotlight episode, we welcome Leonida Mutuku and Godliver Owomugisha, two experts in applying advanced technology in agriculture. We had a great discussion about ending poverty, hunger, and inequality in Africa via AI innovation. The discussion touches on open data, relevant models, ethics, and more.0 comments0
- Quick, beautiful web UIs for ML appsAbubakar Abid joins Daniel and Chris for a tour of Gradio and tells them about the project joining Hugging Face. What’s Gradio? The fastest way to demo your machine learning model with a friendly web interface, allowing non-technical users to access, use, and give feedback on models.0 comments0
- "Foundation" modelsThe term “foundation” model has been around since about the middle of last year when a research group at Stanford published the comprehensive report On the Opportunities and Risks of Foundation Models. The naming of these models created some strong reactions, both good and bad. In this episode, Chris and Daniel dive into the ideas behind the report.0 comments0
- Clothing AI in a data fabricWhat happens when your data operations grow to Internet-scale? How do thousands or millions of data producers and consumers efficiently, effectively, and productively interact with each other? How are varying formats, protocols, security levels, performance criteria, and use-case specific characteristics meshed into one unified data fabric? Chris and Daniel explore these questions in this illuminating and Fully-Connected discussion that brings this new data technology into the light.0 comments0
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