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PODCAST

Practical AI

Practical AI LLC

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). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest

technology

All Episodes

01:30

Welcome to Practical AI

Practical AI ·

2020/03/25

Practical AI is a weekly podcast that’s marking artificial intelligence practical, productive, and accessible to everyone. If world of AI affects your daily life, this show is for you. From the practitioner wanting to keep up with the latest tools & trends… (clip from episode #68) To the AI curious trying to understand the concepts at play and their implications on our lives… (clip from episode #39) Expert hosts Chris Benson and Daniel Whitenack are here to keep you fully-connected with the world of

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49:14

Speech recognition to say it just right

Practical AI ·

2020/03/23

Catherine Breslin of Cobalt joins Daniel and Chris to do a deep dive on speech recognition. She also discusses how the technology is integrated into virtual assistants (like Alexa) and is used in other non-assistant contexts (like transcription and captioning). Along the way, she teaches us how to assemble a lexicon, acoustic model, and language model to bring speech recognition to life.

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51:08

Building a career in Data Science

Practical AI ·

2020/03/16

Emily Robinson, co-author of the book Build a Career in Data Science, gives us the inside scoop about optimizing the data science job search. From creating one’s resume, cover letter, and portfolio to knowing how to recognize the right job at a fair compensation rate. Emily’s expert guidance takes us from the beginning of the process to conclusion, including being successful during your early days in that fantastic new data science position.

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48:40

What exactly is "data science" these days?

Practical AI ·

2020/03/09

Matt Brems from General Assembly joins us to explain what “data science” actually means these days and how that has changed over time. He also gives us some insight into how people are going about data science education, how AI fits into the data science workflow, and how to differentiate yourself career-wise.

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47:37

TensorFlow in the cloud

Practical AI ·

2020/03/02

Craig Wiley, from Google Cloud, joins us to discuss various pieces of the TensorFlow ecosystem along with TensorFlow Enterprise. He sheds light on how enterprises are utilizing AI and supporting AI-driven applications in the Cloud. He also clarifies Google’s relationship to TensorFlow and explains how TensorFlow development is impacting Google Cloud Platform.

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54:50

NLP for the world's 7000+ languages

Practical AI ·

2020/02/24

Expanding AI technology to the local languages of emerging markets presents huge challenges. Good data is scarce or non-existent. Users often have bandwidth or connectivity issues. Existing platforms target only a small number of high-resource languages. Our own Daniel Whitenack (data scientist at SIL International) and Dan Jeffries (from Pachyderm) discuss how these and related problems will only be solved when AI technology and resources from industry are combined with linguistic expertise from

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51:46

Real-time conversational insights from phone call data

Practical AI ·

2020/02/17

Daniel and Chris hang out with Mike McCourt from Invoca to learn about the natural language processing model architectures underlying Signal AI. Mike shares how they process conversational data, the challenges they have to overcome, and the types of insights that can be harvested.

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42:33

AI-powered scientific exploration and discovery

Practical AI ·

2020/02/10

Daniel and Chris explore Semantic Scholar with Doug Raymond of the Allen Institute for Artificial Intelligence. Semantic Scholar is an AI-backed search engine that uses machine learning, natural language processing, and machine vision to surface relevant information from scientific papers.

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44:32

Insights from the AI Index 2019 Annual Report

Practical AI ·

2020/02/03

Daniel and Chris do a deep dive into The AI Index 2019 Annual Report, which provides unbiased rigorously-vetted data that one can use “to develop intuitions about the complex field of AI”. Analyzing everything from R&D and technical advancements to education, the economy, and societal considerations, Chris and Daniel lay out this comprehensive report’s key insights about artificial intelligence.

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47:33

Testing ML systems

Practical AI ·

2020/01/27

Production ML systems include more than just the model. In these complicated systems, how do you ensure quality over time, especially when you are constantly updating your infrastructure, data and models? Tania Allard joins us to discuss the ins and outs of testing ML systems. Among other things, she presents a simple formula that helps you score your progress towards a robust system and identify problem areas.

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47:20

AI-driven automation in manufacturing

Practical AI ·

2020/01/20

One of the things people most associate with AI is automation, but how is AI actually shaping automation in manufacturing? Costas Boulis from Bright Machines joins us to talk about how they are using AI in various manufacturing processes and in their “microfactories.” He also discusses the unique challenges of developing AI models based on manufacturing data.

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48:52

How the U.S. military thinks about AI

Practical AI ·

2020/01/13

Chris and Daniel talk with Greg Allen, Chief of Strategy and Communications at the U.S. Department of Defense (DoD) Joint Artificial Intelligence Center (JAIC). The mission of the JAIC is “to seize upon the transformative potential of artificial intelligence technology for the benefit of America’s national security… The JAIC is the official focal point of the DoD AI Strategy.” So if you want to understand how the U.S. military thinks about artificial intelligence, then this is the episode for

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58:05

2019's AI top 5

Practical AI ·

2020/01/06

Wow, 2019 was an amazing year for AI! In this fully connected episode, Chris and Daniel discuss their list of top 5 notable AI things from 2019. They also discuss the “state of AI” at the end of 2019, and they make some predictions for 2020.

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46:14

AI for search at Etsy

Practical AI ·

2019/12/23

We have all used web and product search technologies for quite some time, but how do they actually work and how is AI impacting search? Andrew Stanton from Etsy joins us to dive into AI-based search methods and to talk about neuroevolution. He also gives us an introduction to Rust for production ML/AI and explains how that community is developing.

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50:00

Escaping the "dark ages" of AI infrastructure

Practical AI ·

2019/12/16

Evan Sparks, from Determined AI, helps us understand why many are still stuck in the “dark ages” of AI infrastructure. He then discusses how we can build better systems by leveraging things like fault tolerant training and AutoML. Finally, Evan explains his optimistic outlook on AI’s economic and environmental health impact.

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56:25

Modern NLP with spaCy

Practical AI ·

2019/12/09

SpaCy is awesome for NLP! It’s easy to use, has widespread adoption, is open source, and integrates the latest language models. Ines Montani and Matthew Honnibal (core developers of spaCy and co-founders of Explosion) join us to discuss the history of the project, its capabilities, and the latest trends in NLP. We also dig into the practicalities of taking NLP workflows to production. You don’t want to miss this episode!

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59:04

Making GANs practical

Practical AI ·

2019/12/02

GANs are at the center of AI hype. However, they are also starting to be extremely practical and be used to develop solutions to real problems. Jakub Langr and Vladimir Bok join us for a deep dive into GANs and their application. We discuss the basics of GANs, their various flavors, and open research problems.

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44:15

Build custom ML tools with Streamlit

Practical AI ·

2019/11/25

Streamlit recently burst onto the scene with their intuitive, open source solution for building custom ML/AI tools. It allows data scientists and ML engineers to rapidly build internal or external UIs without spending time on frontend development. In this episode, Adrien Treuille joins us to discuss ML/AI app development in general and Streamlit. We talk about the practicalities of working with Streamlit along with its seemingly instant adoption by AI2, Stripe, Stitch Fix, Uber, and Twitter.

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57:10

Intelligent systems and knowledge graphs

Practical AI ·

2019/11/18

There’s a lot of hype about knowledge graphs and AI-methods for building or using them, but what exactly is a knowledge graph? How is it different from a database or other data store? How can I build my own knowledge graph? James Fletcher from Grakn Labs helps us understand knowledge graphs in general and some practical steps towards creating your own. He also discusses graph neural networks and the future of graph-augmented methods.

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44:33

Robot hands solving Rubik's cubes

Practical AI ·

2019/11/11

Everyone is talking about it. OpenAI trained a pair of neural nets that enable a robot hand to solve a Rubik’s cube. That is super dope! The results have also generated a lot of commentary and controversy, mainly related to the way in which the results were represented on OpenAI’s blog. We dig into all of this in on today’s Fully Connected episode, and we point you to a few places where you can learn more about reinforcement learning.

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323 results

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