Daniel and Chris explore the intersection of Kaggle and real-world data science in this illuminating conversation with Christof Henkel, Senior Deep Learning Data Scientist at NVIDIA and Kaggle Grandmaster. Christof offers a very lucid explanation into how participation in Kaggle can positively impact a data scientist’s skill and career aspirations. He also shared some of his insights and approach to maximizing AI productivity uses GPU-accelerated tools like RAPIDS and DALI.

We’re super excited to welcome Jay Alammar to the show. Jay is a well-known AI educator, applied NLP practitioner at co:here, and author of the popular blog, “The Illustrated Transformer.” In this episode, he shares his ideas on creating applied NLP solutions, working with large language models, and creating educational resources for state-of-the-art AI.

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!

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.

Chris sits down with Ankur Goyal to talk about DocQuery, Impira’s new open source ML model. DocQuery lets you ask questions about semi-structured data (like invoices) and unstructured documents (like contracts) using Large Language Models (LLMs). Ankur illustrates many of the ways DocQuery can help people tame documents, and references Chris’s real life tasks as a non-profit director to demonstrate that DocQuery is indeed practical AI.

Like the data-centric sibling of your favorite programming environment. It provides an easy-to-use interface for weak supervision as well as extensive data management, neural search and monitoring to ensure that the quality of your training data is as good as possible.

This won’t rid you of the need to manually label, but it’ll save you time in the process!

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?

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.

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.

From MIT researchers who have an AI system that rapidly predicts how two proteins will attach, to Facebook’s first high-performance self-supervised algorithm that works for speech, vision, and text, Daniel and Chris survey the AI landscape for notable milestones in the application of AI in industry and research.

In the third of the “AI in Africa” spotlight episodes, we welcome Kathleen Siminyu, who is building Kiswahili voice tools at Mozilla. We had a great discussion with Kathleen about creating more diverse voice and language datasets, involving local language communities in NLP work, and expanding grassroots ML/AI efforts across Africa.

From drug discovery at the Quebec AI Institute to improving capabilities with low-resourced languages at the Masakhane Research Foundation and Google AI, Bonaventure Dossou looks for opportunities to use his expertise in natural language processing to improve the world - and especially to help his homeland in the Benin Republic in Africa.

In this Fully-Connected episode, Daniel and Chris ponder whether in-person AI conferences are on the verge of making a post-pandemic comeback. Then on to BigScience from Hugging Face, a year-long research workshop on large multilingual models and datasets. Specifically they dive into the T0, a series of natural language processing (NLP) AI models specifically trained for researching zero-shot multitask learning. Daniel provides a brief tour of the possible with the T0 family. They finish up with a couple of new learning resources.

This is the first time I’ve heard of a reverse dictionary, but now that I have… so cool!

Opposite to a regular (forward) dictionary that provides definitions for query words, a reverse dictionary returns words semantically matching the query descriptions.

Ever had a word on the tip of your tongue and you Just. Can’t. Think of it?! Reverse dictionary!

When is the last time you had a eureka moment? Chris had a chat with Nicholas Mohnacky, CEO and Cofounder of bundleIQ, where they use natural language processing algorithms like GPT-3 to connect your Google GSuite with other personal data sources to find deeper connections, go beyond the obvious, and create eureka moments.

We’re back with another Fully Connected episode – Daniel and Chris dive into a series of articles called ‘A New AI Lexicon’ that collectively explore alternate narratives, positionalities, and understandings to the better known and widely circulated ways of talking about AI. The fun begins early as they discuss and debate ‘An Electric Brain’ with strong opinions, and consider viewpoints that aren’t always popular.

In Kenya, 33% of maternal deaths are caused by delays in seeking care, and 55% of maternal deaths are caused by delays in action or inadequate care by providers. Jacaranda Health is employing NLP and dialogue system techniques to help mothers experience childbirth safely and with respect and to help newborns get a safe start in life. Jay and Sathy from Jacaranda join us in this episode to discuss how they are using AI to prioritize incoming SMS messages from mothers and help them get the care they need.

That’s a big addition. Here’s what Hillary Juma (Common Voice’s community mgr) had to say about it:

Internet access is increasingly mediated through speech: Voice assistants and smart speakers give us directions, search for information, connect us to friends, used in assistive technology and much more. Yet this technology doesn’t work for millions of people. For example, neither Amazon’s Alexa, Apple’s Siri, nor Google Home support a single native African language.

By giving individuals the ability to share their speech, we can help ensure all communities have access to voice technology and the opportunity it unlocks.

What a great initiative! (I first heard about Common Voice on Practical AI.)

Texthero is a python package to work with text data efficiently. It empowers NLP developers with a tool to quickly understand any text-based dataset and it provides a solid pipeline to clean and represent text data, from zero to hero.

To say that Jeff Adams is a trailblazer when it comes to speech technology is an understatement. Along with many other notable accomplishments, his team at Amazon developed the Echo, Dash, and Fire TV changing our perception of how we could interact with devices in our home. Jeff now leads Cobalt Speech and Language, and he was kind enough to join us for a discussion about human computer interaction, multimodal AI tasks, the history of language modeling, and AI for social good.

Nhung Ho joins Daniel and Chris to discuss how data science creates insights into financial operations and economic conditions. They delve into topics ranging from predictive forecasting to aid small businesses, to learning about the economic fallout from the COVID-19 Pandemic.

Dave Lacey takes Daniel and Chris on a journey that connects the user interfaces that we already know - TensorFlow and PyTorch - with the layers that connect to the underlying hardware. Along the way, we learn about Poplar Graph Framework Software. If you are the type of practitioner who values ‘under the hood’ knowledge, then this is the episode for you.

Nikola Mrkšić, CEO & Co-Founder of PolyAI, takes Daniel and Chris on a deep dive into conversational AI, describing the underlying technologies, and teaching them about the next generation of voice assistants that will be capable of handling true human-level conversations. It’s an episode you’ll be talking about for a long time!

geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.

Use OpenAI’s CLIP neural network to search inside YouTube videos. You can try it by running the notebook on Google Colab.

The README has a bunch of examples of things you might search for and the results you’d get back. (“The Transamerica Pyramid”, anyone?)

The author also has another related project where you can search Unsplash in like manner.