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Practical AI: Machine Learning, Data Science, LLM

Latest episodes

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Jan 21, 2019 • 42min

IBM's AI for detecting neurological state

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. Join the discussionChangelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!Sponsors:Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com. Rollbar – We catch our errors before our users do because of Rollbar. Resolve errors in minutes, and deploy your code with confidence. Learn more at rollbar.com/changelog. Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Algolia – Our search partner. Algolia’s full suite search APIs enable teams to develop unique search and discovery experiences across all platforms and devices. We’re using Algolia to power our site search here at Changelog.com. Get started for free and learn more at algolia.com. Featuring:Ajay Royyuru – WebsiteGuillermo Cecchi – Chris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, WebsiteShow Notes: IBM 5 in 5: With AI, our words will be a window into our mental health Predicting Cognitive Impairments with a Mobile Application Automated analysis of recent-onset and prodromal schizophrenia Prediction of psychosis across protocols and risk cohorts using automated language analysis Something missing or broken? PRs welcome!
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Jan 14, 2019 • 42min

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. Join the discussionChangelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!Sponsors:Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com. Rollbar – We catch our errors before our users do because of Rollbar. Resolve errors in minutes, and deploy your code with confidence. Learn more at rollbar.com/changelog. Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Algolia – Our search partner. Algolia’s full suite search APIs enable teams to develop unique search and discovery experiences across all platforms and devices. We’re using Algolia to power our site search here at Changelog.com. Get started for free and learn more at algolia.com. Featuring:Chris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, WebsiteShow Notes:2018 in Review Focus on more challenging ML problems Semi-supervised learning Domain adaptation Generative models Reinforcement learning NLP ELMO BERT Fear about AI GDPR, trust and privacy Cambridge analytica Facial recognition Tons of open sourced tooling, models Predictions for 2019 Focus on trust and transparency Bias Regulation GDPR and transparency, interpretability What will other countries do regarding regulation? AI for good Better voice and conversational results AI assistants Voice interfaces NLP advances More focus on product development, less on research Deep learning will explode in production product / service development Computer vision, NLP, speech recognition will be table stakes Increased accessibility of DL to software engineers / developers More testing/tooling Better training for data scientists Better integrations and infrastructure AutoML Organizational / Cultural Shifts New roles for data-based leadership - CDO, CAIO, etc., Strategy - AI becoming first-class concern Competitive Analysis - AI and data assessments mandatory Fragmentation into distinct subfields - AI, analytics, data science, prognostics A changing relationship between humans and automation AI + robotics - first steps Pervasive AI + IoT - first steps The importance of creative expertise for humans How to school your child today to prep for tomorrow Narrowly-scoped, highly-specific job functions at most risk Something missing or broken? PRs welcome!
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Dec 17, 2018 • 41min

Finding success with AI in the enterprise

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. Join the discussionChangelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!Sponsors:Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com. Rollbar – We catch our errors before our users do because of Rollbar. Resolve errors in minutes, and deploy your code with confidence. Learn more at rollbar.com/changelog. Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Algolia – Our search partner. Algolia’s full suite search APIs enable teams to develop unique search and discovery experiences across all platforms and devices. We’re using Algolia to power our site search here at Changelog.com. Get started for free and learn more at algolia.com. Featuring:Susan Etlinger – TwitterChris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, WebsiteShow Notes: Machine Learning for fair decisions Bias examples - programmer, black male Increasing Trust in AI Services through Supplier’s Declarations of Conformity Introducing AI Fairness 360 The AI Maturity Playbook: Five Pillars of Enterprise Success AI Now - Algorithmic Impact Assessments: A Practical Framework for Public Agency Accountability Amazon’s Facial Recognition Wrongly Identifies 28 Lawmakers, A.C.L.U. Says General Data Protection Regulation Something missing or broken? PRs welcome!
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Dec 10, 2018 • 40min

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. Join the discussionChangelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!Sponsors:DigitalOcean – DigitalOcean is simplicity at scale. Whether your business is running one virtual machine or ten thousand, DigitalOcean gets out of your way so your team can build, deploy, and scale faster and more efficiently. New accounts get $100 in credit to use in your first 60 days. Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com. Rollbar – We catch our errors before our users do because of Rollbar. Resolve errors in minutes, and deploy your code with confidence. Learn more at rollbar.com/changelog. Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Featuring:Chris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, WebsiteShow Notes:News: NVIDIA’s open sourcing of TensorRT Amazon launches a machine learning chip The recently announced ONNX JS project Snapdragon Neural Processing Engine SDK Learning resources: Rise of the model servers TensorRT server tutorial ONNX JS on GitHub TensorFlow JS tutorials Something missing or broken? PRs welcome!
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Dec 3, 2018 • 42min

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. Join the discussionChangelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!Sponsors:DigitalOcean – DigitalOcean is simplicity at scale. Whether your business is running one virtual machine or ten thousand, DigitalOcean gets out of your way so your team can build, deploy, and scale faster and more efficiently. New accounts get $100 in credit to use in your first 60 days. Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com. Rollbar – We catch our errors before our users do because of Rollbar. Resolve errors in minutes, and deploy your code with confidence. Learn more at rollbar.com/changelog. Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Featuring:Joe Doliner – Twitter, GitHub, WebsiteChris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, WebsiteShow Notes: Pachyderm Pachyderm on GitHub Pachyderm tutorials DoD challenge built using Pachyderm Something missing or broken? PRs welcome!
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Nov 27, 2018 • 39min

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. Join the discussionChangelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!Sponsors:Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com. Rollbar – We catch our errors before our users do because of Rollbar. Resolve errors in minutes, and deploy your code with confidence. Learn more at rollbar.com/changelog. Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Algolia – Our search partner. Algolia’s full suite search APIs enable teams to develop unique search and discovery experiences across all platforms and devices. We’re using Algolia to power our site search here at Changelog.com. Get started for free and learn more at algolia.com. Featuring:Chris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, WebsiteShow Notes:News/Discussion: Is artificial intelligence set to become art’s next medium? BERT (a new method for obtaining rich contextual language representations during pre-training): Google research article TensorFlow BERT BERT paper PyTorch BERT NY Times article Example Colab notebook BERT explained article Transformer paper Google Open Sources BERT to Train Natural Language Models Without Breaking the Bank Horizon: The first open source reinforcement learning platform for large-scale products and services Does Synthetic Data Hold The Secret To Artificial Intelligence? AI Experts: Moving forward with AI likely a series of small steps, not giant leaps Learning resources: The Backpropagation Algorithm Demystified Books “Grokking Deep Learning” by Andrew Trask Something missing or broken? PRs welcome!
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Nov 19, 2018 • 29min

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. Join the discussionChangelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!Sponsors:DigitalOcean – DigitalOcean is simplicity at scale. Whether your business is running one virtual machine or ten thousand, DigitalOcean gets out of your way so your team can build, deploy, and scale faster and more efficiently. New accounts get $100 in credit to use in your first 60 days. Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com. Rollbar – We catch our errors before our users do because of Rollbar. Resolve errors in minutes, and deploy your code with confidence. Learn more at rollbar.com/changelog. Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Featuring:Cormac Brick – Twitter, WebsiteMike Del Balso – WebsiteChris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, WebsiteShow Notes: Intel’s Movidius Group OpenVINO Toolkit ngraph Uber’s Michelangelo Something missing or broken? PRs welcome!
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Nov 12, 2018 • 44min

Analyzing AI's impact on society through art and film

Brett Gaylor joins Chris and Daniel to chat about the recently announced winners of Mozilla’s creative media awards, which focuses on exposing the impact of AI on society. These winners include a film that responds to the audience (via AI recognized emotions) and an interesting chatbot called Wanda. Join the discussionChangelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!Sponsors:DigitalOcean – DigitalOcean is simplicity at scale. Whether your business is running one virtual machine or ten thousand, DigitalOcean gets out of your way so your team can build, deploy, and scale faster and more efficiently. New accounts get $100 in credit to use in your first 60 days. Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com. Rollbar – We catch our errors before our users do because of Rollbar. Resolve errors in minutes, and deploy your code with confidence. Learn more at rollbar.com/changelog. Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Featuring:Brett Gaylor – Twitter, WebsiteChris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, WebsiteShow Notes: Winners of the Creative Media Awards Do not track movie The Science behind Cambridge Analytica Mozilla manifesto Machine bias article from ProPublica Practical AI episode from Lindsey Zuloaga about bias Something missing or broken? PRs welcome!
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Nov 5, 2018 • 30min

Getting into data science and AI

Himani Agrawal joins Daniel and Chris to talk about how she got into data science and artificial intelligence, and offers advice to others getting into these fields. She goes on to describe the role of artificial intelligence and machine learning within AT&T and telecom in general. Join the discussionChangelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!Sponsors:DigitalOcean – DigitalOcean is simplicity at scale. Whether your business is running one virtual machine or ten thousand, DigitalOcean gets out of your way so your team can build, deploy, and scale faster and more efficiently. New accounts get $100 in credit to use in your first 60 days. Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com. Rollbar – We catch our errors before our users do because of Rollbar. Resolve errors in minutes, and deploy your code with confidence. Learn more at rollbar.com/changelog. Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Featuring:Himani Agrawal – GitHub, WebsiteChris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, WebsiteShow Notes: MLConf SF Grace Hopper Celebration Galvanize Fast.ai Thinkful bootcamp Magenta project Something missing or broken? PRs welcome!
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Oct 31, 2018 • 35min

AIs that look human and create portraits of humans

In this new and updates show, Daniel and Chris discuss, among other things, efforts to use AI in art and efforts to make AI interfaces look human. They also discuss some learning resources related to neural nets, AI fairness, and reinforcement learning. Join the discussionChangelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!Sponsors:DigitalOcean – DigitalOcean is simplicity at scale. Whether your business is running one virtual machine or ten thousand, DigitalOcean gets out of your way so your team can build, deploy, and scale faster and more efficiently. New accounts get $100 in credit to use in your first 60 days. Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com. Rollbar – We catch our errors before our users do because of Rollbar. Resolve errors in minutes, and deploy your code with confidence. Learn more at rollbar.com/changelog. Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Featuring:Chris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, WebsiteShow Notes:News from Daniel: AI portrait up for auction Graph ML related things: Deepmind Graphnet library Knowledge Graphs and ML Semantic Scholar CSV conf News from Chris: Magic Leap’s new AI assistant looks alarmingly human MIT Stephen A. Schwarzman College of Computing Deep-learning algorithm identifies dense tissue in mammograms Learning resources: Neural network playground IBM AI Fairness 360 Towards Data Science Artificial Intelligence: What’s The Difference Between Deep Learning And Reinforcement Learning? Something missing or broken? PRs welcome!

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