Practical AI – Détails, épisodes et analyse

How can every single person build a personal AI protégé and then accumulate (and share) a host of other assistants? In this episode, we dive into the world of no-code AI with Scott Meyer from Chipp.ai. We discuss AI tooling for people that can't code, the cultural shift that needs to happen for widespread AI adoption in businesses, and the predicted growth trajectory of AI assistant that you can own.

Featuring:

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

Sponsors:

• Domo – The AI and data products platform. Strengthen your entire data journey with Domo’s AI and data products.

Show Notes:

• Chipp.ai
• Chipp.ai's Discord

It seems like all we hear about are the great use cases for GenAI, but where should you NOT be using the technology? On this episode Chris and Daniel share their hot takes and bad use cases. Some may surprise you!

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Sponsors:

• Domo – The AI and data products platform. Strengthen your entire data journey with Domo’s AI and data products. 
• Fly.io – The home of Changelog.com — Deploy your apps close to your users — global Anycast load-balancing, zero-configuration private networking, hardware isolation, and instant WireGuard VPN connections. Push-button deployments that scale to thousands of instances. Check out the speedrun to get started in minutes. 

Featuring:

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

Show Notes:

Something missing or broken? PRs welcome!

It can be frustrating to get an AI application working amazingly well 80% of the time and failing miserably the other 20%. How can you close the gap and create something that you rely on? Chris and Daniel talk through this process, behavior testing, and the flow from prototype to production in this episode. They also talk a bit about the apparent slow down in the release of frontier models.

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Sponsors:

• Fly.io – The home of Changelog.com — Deploy your apps close to your users — global Anycast load-balancing, zero-configuration private networking, hardware isolation, and instant WireGuard VPN connections. Push-button deployments that scale to thousands of instances. Check out the speedrun to get started in minutes. 
• Timescale – Purpose-built performance for AI Build RAG, search, and AI agents on the cloud and with PostgreSQL and purpose-built extensions for AI: pgvector, pgvectorscale, and pgai. 
• Eight Sleep – Up to $600 off Pod 4 Ultra Go to eightsleep.com/changelog and use the code CHANGELOG. You can try it for free for 30 days - but we’re confident you will not want to return it (we love ours). Once you experience AI-optimized sleep, you’ll wonder how you ever slept without it. Currently shipping to: United States, Canada, United Kingdom, Europe, and Australia. 

Featuring:

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

Show Notes:

• MLOps Community “Agents in Production” event

Something missing or broken? PRs welcome!

While at EMNLP 2022, Daniel got a chance to sit down with an amazing group of researchers creating NLP technology that actually works for their local language communities. Just Zwennicker (Universiteit van Amsterdam) discusses his work on a machine translation system for Sranan Tongo, a creole language that is spoken in Suriname. Andiswa Bukula (SADiLaR), Rooweither Mabuya (SADiLaR), and Bonaventure Dossou (Lanfrica, Mila) discuss their work with Masakhane to strengthen and spur NLP research in African languages, for Africans, by Africans.

The group emphasized the need for more linguistically diverse NLP systems that work in scenarios of data scarcity, non-Latin scripts, rich morphology, etc. You don’t want to miss this one!

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Featuring:

• Just Zwennicker – LinkedIn
• Andiswa Bukula – X
• Rooweither Mabuya – X
• Bonaventure Dossou – Website, GitHub, LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

Show Notes:

EMNLP 2022 papers from the guests:

• Towards a general purpose machine translation system for Sranantongo
• MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition
• AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages

Other links relevant to the discussion:

• Masakhane
• Lanfrica
• The South African Centre for Digital Language Resources (SADiLaR)

Something missing or broken? PRs welcome!

José and Ricardo joined Daniel at EMNLP 2022 to discuss state-of-the-art machine translation, the WMT shared tasks, and quality estimation. Among other things, they talk about Unbabel’s innovations in quality estimation including COMET, a neural framework for training multilingual machine translation (MT) evaluation models.

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Featuring:

• Ricardo Rei – X
• José Souza – X
• Daniel Whitenack – Website, GitHub, X

Show Notes:

• Unbabel
• COMET
• The WMT workshop/ conference
• EMNLP

Something missing or broken? PRs welcome!

In this special episode, we interview some of the sponsors and teams from a recent case competition organized by Purdue University, Microsoft, INFORMS, and SIL International. 170+ teams from across the US and Canada participated in the competition, which challenged students to create AI-driven systems to caption images in three languages (Thai, Kyrgyz, and Hausa).

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Featuring:

• Matthew Lanham – Website, X
• Mark Tabladillo – LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

Show Notes:

• Purdue University’s Krannert School of Business
• Master the basics of Azure: AI Fundamentals
• Azure Architecture Center
• SIL International
• The bloom-captioning dataset

Books

• “Applied Machine Learning and AI for Engineers” by Jeff Prosise

Something missing or broken? PRs welcome!

There are some big AI-related controversies swirling, and it’s time we talk about them. A lawsuit has been filed against GitHub, Microsoft, and OpenAI related to Copilot code suggestions, and many people have been disturbed by the output of Meta AI’s Galactica model. Does Copilot violate open source licenses? Does Galactica output dangerous science-related content? In this episode, we dive into the controversies and risks, and we discuss the benefits of these technologies.

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Featuring:

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

Show Notes:

Related to Copilot:

• Article - “GitHub Copilot Isn’t Worth the Risk”
• Tabnine
• Big Code Project

Related to Galactica:

• Model website
• Article: “Galactica: the AI knowledge base that makes stuff up”

Books

• “Interpretable Machine Learning” by Christoph Molnar
• “Modeling Mindsets” by Christoph Molnar

Something missing or broken? PRs welcome!

Online platforms and their users are susceptible to a barrage of threats – from disinformation to extremism to terror. Daniel and Chris chat with Matar Haller, VP of Data at ActiveFence, a leader in identifying online harm – is using a combination of AI technology and leading subject matter experts to provide Trust & Safety teams with precise, real-time data, in-depth intelligence, and automated tools to protect users and ensure safe online experiences.

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Featuring:

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

Show Notes:

• ActiveFence

Something missing or broken? PRs welcome!

It’s been a while since we’ve touched on quantum computing. It’s time for an update! This week we talk with Yonatan from Quantum Machines about real progress being made in the practical construction of hybrid computing centers with a mix of classical processors, GPUs, and quantum processors. Quantum Machines is building both hardware and software to help control, program, and integrate quantum processors within a hybrid computing environment.

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Featuring:

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

Show Notes:

Quantum Machines

Something missing or broken? PRs welcome!

Recently Chris and Daniel briefly discussed the Open RAIL-M licensing and model releases on Hugging Face. In this episode, Daniel follows up on this topic based on some recent practical experience. Also included is a discussion about graph neural networks, message passing, and tweaking synthesized voices!

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Featuring:

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

Show Notes:

• Daniel’s team license from recent work
• Graph Neural Network courses from Zak Jost
• Coqui voice studio

Something missing or broken? PRs welcome!