Chris Benson Avatar

Chris Benson

Chris Benson is Principal Artificial Intelligence Strategist at Lockheed Martin. He came to Lockheed Martin from Honeywell SPS, where he was Chief Scientist for Artificial Intelligence & Machine Learning. Chris built and operationalized Honeywell’s first dedicated AI team from the ground up. Before that he was on the AI Team at Accenture.

As a strategist and thought leader, Chris is among the world’s most in-demand professional keynote speakers on artificial intelligence, machine learning, emerging technologies, and visionary futurism. His inspirational keynotes are known for their passion, energy, and clarity. He is a seasoned storyteller who delights in captivating his audiences with inspiring narratives and insightful analysis at conferences, broadcasts, interviews, forums, and corporate events around the world.

Chris is an innovative hands-on solutions architect for artificial intelligence and machine learning - and the emerging technologies they intersect - robotics, IoT, augmented reality, blockchain, mobile, edge, and cloud.

He is Co-Host of the Practical AI podcast, which reaches thousands of AI enthusiasts each week, and is also the Founder & Organizer of the Atlanta Deep Learning Meetup - one of the largest AI communities in the world.

Chris and his family are committed animal advocates who are active in animal rescue, and strive to make strategic improvements on specific animal welfare issues through advocacy for non-partisan, no-kill, and vegan legislation and regulation.

Chris Benson’s opinions are his own.

https://chrisbenson.com

Atlanta · Website · GitHub · LinkedIn · X
276 episodes

Practical AI Practical AI #36

Growing up to become a world-class AI expert

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2019-03-25T21:00:00Z #ai +3 🎧 7,265

While at the NVIDIA GPU Technology Conference 2019 in Silicon Valley, Chris enjoyed an inspiring conversation with Anima Anandkumar. Clearly a role model - not only for women - but for anyone in the world of AI, Anima relayed how her lifelong passion for mathematics and engineering started when she was only 3 years old in India, and ultimately led to her pioneering deep learning research at Amazon Web Services, CalTech, and NVIDIA.

Practical AI Practical AI #35

Social AI with Hugging Face

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2019-03-18T17:00:00Z #ai 🎧 6,924

Clément Delangue, the co-founder & 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.

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.

Practical AI Practical AI #33

Staving off disaster through AI safety research

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2019-03-04T18:00:00Z #ai +3 🎧 6,331

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.

Practical AI Practical AI #32

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

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2019-02-25T20:15:00Z #ai +1 🎧 7,813

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.

Practical AI Practical AI #31

AI for social good at Intel

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2019-02-20T12:00:00Z #ai +1 🎧 6,541

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.

Practical AI Practical AI #30

GirlsCoding.org empowers young women to embrace computer science

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2019-02-13T16:11:16Z #ai +1 🎧 5,965

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!

Practical AI Practical AI #29

How Microsoft is using AI to help the Earth

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2019-02-04T18:06:16Z #ai +3 🎧 6,889

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!

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.

Practical AI Practical AI #27

IBM's AI for detecting neurological state

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2019-01-21T12:00:00Z #ai 🎧 6,516

Ajay Royyuru and Guillermo Cecchi from IBM Healthcare join Chris and Daniel to discuss the emerging field of computational psychiatry. They talk about how researchers at IBM are applying AI to measure mental and neurological health based on speech, and they give us their perspectives on things like bias in healthcare data, AI augmentation for doctors, and encodings of language structure.

Practical AI Practical AI #26

2018 in review and bold predictions for 2019

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2019-01-14T12:00:00Z #ai +2 🎧 6,534

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.

Practical AI Practical AI #25

Finding success with AI in the enterprise

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2018-12-17T12:00:00Z #ai 🎧 7,575

Susan Etlinger, an Industry Analyst at Altimeter, a Prophet company, joins us to discuss The AI Maturity Playbook: Five Pillars of Enterprise Success. This playbook covers trends affecting AI, and offers a maturity model that practitioners can use within their own organizations - addressing everything from strategy and product development, to culture and ethics.

Practical AI Practical AI #24

So you have an AI model, now what?

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2018-12-10T12:00:00Z #ai +1 🎧 6,851

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.

Practical AI Practical AI #23

Pachyderm's Kubernetes-based infrastructure for AI

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2018-12-03T15:59:15Z #ai +1 🎧 6,177

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.

Practical AI Practical AI #22

BERT: one NLP model to rule them all

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2018-11-27T16:11:57Z #ai +3 🎧 8,446

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.

Practical AI Practical AI #21

UBER and Intel’s Machine Learning platforms

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2018-11-19T12:00:00Z #ai +1 🎧 6,409

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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