Practical AI

Yonatan Geifman of Deci makes Daniel and Chris buckle up, and takes them on a tour of the ideas behind his amazing new inference platform. It enables AI developers to build, optimize, and deploy blaz…

In this episode, Peter Wang from Anaconda joins us again to go over their latest “State of Data Science” survey. The updated results include some insights related to data science work during COVID al…

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 unders…

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…

SLICED is like the TV Show Chopped but for data science. Competitors get a never-before-seen dataset and two-hours to code a solution to a prediction challenge. Meg and Nick, the SLICED show hosts, j…

AI is being used to transform the most personal instrument we have, our voice, into something that can be “played.” This is fascinating in and of itself, but Yotam Mann from Never Before Heard Sounds…

Inspired by a recent article from Erik Bernhardsson titled “Building a data team at a mid-stage startup: a short story”, Chris and Daniel discuss all things AI/data team building. They share some sto…

9 out of 10 AI projects don’t end up creating value in production. Why? At least partly because these projects utilize unstable models and drifting data. In this episode, Roey from BeyondMinds gives …

How did we get from symbolic AI to deep learning models that help you write code (i.e., GitHub and OpenAI’s new Copilot)? That’s what Chris and Daniel discuss in this episode about the history and fu…

Pinecone is the first vector database for machine learning. Edo Liberty explains to Chris how vector similarity search works, and its advantages over traditional database approaches for machine learn…

William Falcon wants AI practitioners to spend more time on model development, and less time on engineering. PyTorch Lightning is a lightweight PyTorch wrapper for high-performance AI research that l…

Chris and Daniel sit down to chat about some exciting new AI developments including wav2vec-u (an unsupervised speech recognition model) and meta-learning (a new book about “How To Learn Deep Learnin…

Tuhin Srivastava tells Daniel and Chris why BaseTen is the application development toolkit for data scientists. BaseTen’s goal is to make it simple to serve machine learning models, write custom busi…

Today we’re sharing a special crossover episode from The Changelog podcast here on Practical AI. Recently, Daniel Whitenack joined Jerod Santo to talk with José Valim, Elixir creator, about Numerical…

90% of AI / ML applications never make it to market, because fine tuning models for maximum performance across disparate ML software solutions and hardware backends requires a ton of manual labor and…

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 T…

Smart home data is complicated. There are all kinds of devices, and they are in many different combinations, geographies, configurations, etc. This complicated data situation is further exacerbated d…

Ro Gupta from CARMERA teaches Daniel and Chris all about road intelligence. CARMERA maintains the maps that move the world, from HD maps for automated driving to consumer maps for human navigation.

Jo…

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…

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…