Practical AI

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Making artificial intelligence practical, productive, and accessible to everyone.

Practical AI Practical AI #35

Social AI with Hugging Face

Clément Delangue, the co-founder and CEO of Hugging Face, joined us to discuss fun, social, and conversational AI. Clem explained why social AI is important, what products they are building (social AIs who learn to chit-chat, talk sassy and trades selfies with you), and how this intersects with the latest research in AI for natural language. He also shared his vision for how AI for natural language with develop over the next few years.

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Practical AI Practical AI #34

The White House Executive Order on AI

The White House recently published an “Executive Order on Maintaining American Leadership in Artificial Intelligence.” In this fully connected episode, we discuss the executive order in general and criticism from the AI community. We also draw some comparisons between this US executive order and other national strategies for leadership in AI.

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Practical AI Practical AI #33

Staving off disaster through AI safety research

While covering Applied Machine Learning Days in Switzerland, Chris met El Mahdi El Mhamdi by chance, and was fascinated with his work doing AI safety research at EPFL. El Mahdi agreed to come on the show to share his research into the vulnerabilities in machine learning that bad actors can take advantage of. We cover everything from poisoned data sets and hacked machines to AI-generated propaganda and fake news, so grab your James Bond 007 kit from Q Branch, and join us for this important conversation on the dark side of artificial intelligence.

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Practical AI Practical AI #32

OpenAI's new "dangerous" GPT-2 language model

This week we discuss GPT-2, a new transformer-based language model from OpenAI that has everyone talking. It’s capable of generating incredibly realistic text, and the AI community has lots of concerns about potential malicious applications. We help you understand GPT-2 and we discuss ethical concerns, responsible release of AI research, and resources that we have found useful in learning about language models.

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Practical AI Practical AI #31

AI for social good at Intel

While at Applied Machine Learning Days in Lausanne, Switzerland, Chris had an inspiring conversation with Anna Bethke, Head of AI for Social Good at Intel. Anna reveals how she started the AI for Social Good program at Intel, and goes on to share the positive impact this program has had - from stopping animal poachers, to helping the National Center for Missing & Exploited Children. Through this AI for Social Good program, Intel clearly demonstrates how a for-profit business can effectively use AI to make the world a better place for us all.

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Practical AI Practical AI #30

GirlsCoding.org empowers young women to embrace computer science

Chris sat down with Marta Martinez-Cámara and Miranda Kreković to learn how GirlsCoding.org is inspiring 9–16-year-old girls to learn about computer science. The site is successfully empowering young women to recognize computer science as a valid career choice through hands-on workshops, role models, and by smashing prevalent gender stereotypes. This is an episode that you’ll want to listen to with your daughter!

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Practical AI Practical AI #29

How Microsoft is using AI to help the Earth

Chris caught up with Jennifer Marsman, Principal Engineer on the AI for Earth team at Microsoft, right before her speech at Applied Machine Learning Days 2019 in Lausanne, Switzerland. She relayed how the team came into being, what they do, and some of the good deeds they have done for Mother Earth. They are giving away $50 million (US) in grants over five years! It was another excellent example of AI for good!

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Practical AI Practical AI #28

New year’s resolution: dive into deep learning!

Fully Connected – a series where Chris and Daniel keep you up to date with everything that’s happening in the AI community. If you’re anything like us, your New Year’s resolutions probably included an AI section, so this week we explore some of the learning resources available for artificial intelligence and deep learning. Where you go with it depends upon what you want to achieve, so we discuss academic versus industry career paths, and try to set you on the Practical AI path that will help you level up.

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Practical AI Practical AI #26

2018 in review and bold predictions for 2019

Fully Connected – a series where Chris and Daniel keep you up to date with everything that’s happening in the AI community. This week we look back at 2018 - from the GDPR and the Cambridge Analytica scandal, to advances in natural language processing and new open source tools. Then we offer our predications for what we expect in the year ahead, touching on just about everything in the world of AI.

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Practical AI Practical AI #24

So you have an AI model, now what?

Fully Connected – a series where Chris and Daniel keep you up to date with everything that’s happening in the AI community. This week we discuss all things inference, which involves utilizing an already trained AI model and integrating it into the software stack. First, we focus on some new hardware from Amazon for inference and NVIDIA’s open sourcing of TensorRT for GPU-optimized inference. Then we talk about performing inference at the edge and in the browser with things like the recently announced ONNX JS.

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Practical AI Practical AI #23

Pachyderm's Kubernetes-based infrastructure for AI

Joe Doliner (JD) joined the show to talk about productionizing ML/AI with Pachyderm, an open source data science platform built on Kubernetes (k8s). We talked through the origins of Pachyderm, challenges associated with creating infrastructure for machine learning, and data and model versioning/provenance. He also walked us through a process for going from a Jupyter notebook to a production data pipeline.

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Practical AI Practical AI #22

BERT: one NLP model to rule them all

Fully Connected – a series where Chris and Daniel keep you up to date with everything that’s happening in the AI community. This week we discuss BERT, a new method of pre-training language representations from Google for natural language processing (NLP) tasks. Then we tackle Facebook’s Horizon, the first open source reinforcement learning platform for large-scale products and services. We also address synthetic data, and suggest a few learning resources.

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Practical AI Practical AI #21

UBER and Intel’s Machine Learning platforms

We recently met up with Cormac Brick (Intel) and Mike Del Balso (Uber) at O’Reilly AI in SF. As the director of machine intelligence in Intel’s Movidius group, Cormac is an expert in porting deep learning models to all sorts of embedded devices (cameras, robots, drones, etc.). He helped us understand some of the techniques for developing portable networks to maximize performance on different compute architectures. In our discussion with Mike, we talked about the ins and outs of Michelangelo, Uber’s machine learning platform, which he manages. He also described why it was necessary for Uber to build out a machine learning platform and some of the new features they are exploring.

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Practical AI Practical AI #15

Artificial intelligence at NVIDIA

NVIDIA Chief Scientist Bill Dally joins Daniel Whitenack and Chris Benson for an in-depth conversation about ‘everything AI’ at NVIDIA. As the leader of NVIDIA Research, Bill schools us on GPUs, and then goes on to address everything from AI-enabled robots and self-driving vehicles, to new AI research innovations in algorithm development and model architectures. This episode is so packed with information, you may want to listen to it multiple times.

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