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 TV changing our perception of how we could interact with devices in our home. Jeff now leads Cobalt Speech and Language, and he was kind enough to join us for a discussion about human computer interaction, multimodal AI tasks, the history of language modeling, and AI for social good. Join the discussi...
May 11, 2021•43 min•Ep. 133
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 during a pandemic when time series data seems to be filled with anomalies. Evan Welbourne joins us to discuss how Amazon is synthesizing this disparate data into functionality for the next generation of smart homes. He discusses the challenges of working with smart home technology, and he describes ho...
May 04, 2021•43 min•Ep. 132
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. Join the discussion Changelog++ members get a bonus 1 minute at the end of this episode and zero ads. Join today! Sponsors: O'Reilly Media – Learn by doing — Python, data, AI, machine learning, Kubernetes, Docker, and more. Just open your browser and dive in. Learn more and keep your teams’ skills sha...
Apr 27, 2021•53 min•Ep. 131
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 businesses, to learning about the economic fallout from the COVID-19 Pandemic. Join the discussion Changelog++ members get a bonus 1 minute at the end of this episode and zero ads. Join today! Sponsors: O'Reilly Media – Learn by doing — Python, data, AI, machine learning, Kubernetes, Docker, and mor...
Apr 20, 2021•53 min•Ep. 130
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, we learn about Poplar Graph Framework Software. If you are the type of practitioner who values ‘under the hood’ knowledge, then this is the episode for you. Join the discussion Changelog++ members save 3 minutes on this episode because they made the ads disappear. Join today! Sponsors: O'Reilly Med...
Apr 13, 2021•44 min•Ep. 129
Nikola Mrkšić, CEO & Co-Founder of PolyAI, takes Daniel and Chris on a deep dive into conversational AI, describing the underlying technologies, and teaching them about the next generation of voice assistants that will be capable of handling true human-level conversations. It’s an episode you’ll be talking about for a long time! Join the discussion Changelog++ members save 3 minutes on this episode because they made the ads disappear. Join today! Sponsors: O'Reilly Media – Learn by doing — P...
Apr 06, 2021•51 min•Ep. 128
Chris has the privilege of talking with Stanford Professor Margot Gerritsen, who co-leads the Women in Data Science (WiDS) Worldwide Initiative. This is a conversation that everyone should listen to. Professor Gerritsen’s profound insights into how we can all help the women in our lives succeed - in data science and in life - is a ‘must listen’ episode for everyone, regardless of gender. Join the discussion Changelog++ members save 3 minutes on this episode because they made the ads disappear. J...
Mar 30, 2021•57 min•Ep. 127
David Sweet, author of “Tuning Up: From A/B testing to Bayesian optimization”, introduces Dan and Chris to system tuning, and takes them from A/B testing to response surface methodology, contextual bandit, and finally bayesian optimization. Along the way, we get fascinating insights into recommender systems and high-frequency trading! Join the discussion Changelog++ members get a bonus 1 minute at the end of this episode and zero ads. Join today! Sponsors: O'Reilly Media – Learn by doing — Pytho...
Mar 23, 2021•43 min•Ep. 126
Our Slack community wanted to hear about AI-driven drug discovery, and we listened. Abraham Heifets from Atomwise joins us for a fascinating deep dive into the intersection of deep learning models and molecule binding. He describes how these methods work and how they are beginning to help create drugs for “undruggable” diseases! Join the discussion Changelog++ members save 4 minutes on this episode because they made the ads disappear. Join today! Sponsors: O'Reilly Media – Learn by doing — Pytho...
Mar 09, 2021•57 min•Ep. 125
Empirical analysis from Roy Schwartz (Hebrew University of Jerusalem) and Jesse Dodge (AI2) suggests the AI research community has paid relatively little attention to computational efficiency. A focus on accuracy rather than efficiency increases the carbon footprint of AI research and increases research inequality. In this episode, Jesse and Roy advocate for increased research activity in Green AI (AI research that is more environmentally friendly and inclusive). They highlight success stories a...
Mar 02, 2021•1 hr•Ep. 124
In this Fully-Connected episode, Chris and Daniel discuss low code / no code development, GPU jargon, plus more data leakage issues. They also share some really cool new learning opportunities for leveling up your AI/ML game! Join the discussion Changelog++ members get a bonus 3 minutes at the end of this episode and zero ads. Join today! Sponsors: Changelog++ – You love our content and you want to take it to the next level by showing your support. We’ll take you closer to the metal with no ads,...
Feb 23, 2021•48 min•Ep. 123
Elad Walach of Aidoc joins Chris to talk about the use of AI for medical imaging interpretation. Starting with the world’s largest annotated training data set of medical images, Aidoc is the radiologist’s best friend, helping the doctor to interpret imagery faster, more accurately, and improving the imaging workflow along the way. Elad’s vision for the transformative future of AI in medicine clearly soothes Chris’s concern about managing his aging body in the years to come. ;-) Join the discussi...
Feb 16, 2021•46 min•Ep. 122
John Myers of Gretel puts on his apron and rolls up his sleeves to show Dan and Chris how to cook up some synthetic data for automated data labeling, differential privacy, and other purposes. His military and intelligence community background give him an interesting perspective that piqued the interest of our intrepid hosts. Join the discussion Changelog++ members save 5 minutes on this episode because they made the ads disappear. Join today! Sponsors: Code-ish by Heroku – A podcast from the tea...
Feb 02, 2021•48 min•Ep. 121
Daniel and Chris sniff out the secret ingredients for collecting, displaying, and analyzing odor data with Terri Jordan and Yanis Caritu of Aryballe. It certainly smells like a good time, so join them for this scent-illating episode! Join the discussion Changelog++ members get a bonus 1 minute at the end of this episode and zero ads. Join today! Sponsors: Knowable – Learn from the world’s best minds, anytime, anywhere, and at your own pace through audio. Get unlimited access to every Knowable au...
Jan 26, 2021•55 min•Ep. 120
MLCommons launched in December 2020 as an open engineering consortium that seeks to accelerate machine learning innovation and broaden access to this critical technology for the public good. David Kanter, the executive director of MLCommons, joins us to discuss the launch and the ambitions of the organization. In particular we discuss the three pillars of the organization: Benchmarks and Metrics (e.g. MLPerf), Datasets and Models (e.g. People’s Speech), and Best Practices (e.g. MLCube). Join the...
Jan 19, 2021•51 min•Ep. 119
American Express is running what is perhaps the largest commercial ML model in the world; a model that automates over 8 billion decisions, ingests data from over $1T in transactions, and generates decisions in mere milliseconds or less globally. Madhurima Khandelwal, head of AMEX AI Labs, joins us for a fascinating discussion about scaling research and building robust and ethical AI-driven financial applications. Join the discussion Changelog++ members get a bonus 2 minutes at the end of this ep...
Jan 11, 2021•49 min•Ep. 118
Braden Hancock joins Chris to discuss Snorkel Flow and the Snorkel open source project . With Flow, users programmatically label, build, and augment training data to drive a radically faster, more flexible, and higher quality end-to-end AI development and deployment process. Join the discussion Changelog++ members get a bonus 2 minutes at the end of this episode and zero ads. Join today! Sponsors: DigitalOcean – Get apps to market faster. Build, deploy, and scale apps quickly using a simple, ful...
Dec 21, 2020•47 min•Ep. 117
At this year’s Government & Public Sector R Conference (or R|Gov) our very own Daniel Whitenack moderated a panel on how AI practitioners can engage with governments on AI for good projects. That discussion is being republished in this episode for all our listeners to enjoy! The panelists were Danya Murali from Arcadia Power and Emily Martinez from the NYC Department of Health and Mental Hygiene. Danya and Emily gave some great perspectives on sources of government data, ethical uses of data...
Dec 14, 2020•26 min•Ep. 116
Bharat Sandhu, Director of Azure AI and Mixed Reality at Microsoft, joins Chris and Daniel to talk about how Microsoft is making AI accessible and productive for users, and how AI solutions can address real world challenges that customers face. He also shares Microsoft’s research-to-product process, along with the advances they have made in computer vision, image captioning, and how researchers were able to make AI that can describe images as well as people do. Join the discussion Changelog++ me...
Dec 07, 2020•49 min•Ep. 115
Unsplash has released the world’s largest open library dataset, which includes 2M+ high-quality Unsplash photos, 5M keywords, and over 250M searches. They have big ideas about how the dataset might be used by ML/AI folks, and there have already been some interesting applications. In this episode, Luke and Tim discuss why they released this data and what it take to maintain a dataset of this size. Join the discussion Changelog++ members get a bonus 1 minute at the end of this episode and zero ads...
Dec 01, 2020•44 min•Ep. 114
Lucy D’Agostino McGowan, cohost of the Casual Inference Podcast and a professor at Wake Forest University, joins Daniel and Chris for a deep dive into causal inference. Referring to current events (e.g. misreporting of COVID-19 data in Georgia) as examples, they explore how we interact with, analyze, trust, and interpret data - addressing underlying assumptions, counterfactual frameworks, and unmeasured confounders (Chris’s next Halloween costume). Join the discussion Changelog++ members get a b...
Nov 24, 2020•51 min•Ep. 113
What’s it like to try and build your own deep learning workstation? Is it worth it in terms of money, effort, and maintenance? Then once built, what’s the best way to utilize it? Chris and Daniel dig into questions today as they talk about Daniel’s recent workstation build. He built a workstation for his NLP and Speech work with two GPUs, and it has been serving him well (minus a few things he would change if he did it again). Join the discussion Changelog++ members get a bonus 1 minute at the e...
Nov 17, 2020•49 min•Ep. 112
Weights & Biases is coming up with some awesome developer tools for AI practitioners! In this episode, Lukas Biewald describes how these tools were a direct result of pain points that he uncovered while working as an AI intern at OpenAI. He also shares his vision for the future of machine learning tooling and where he would like to see people level up tool-wise. Join the discussion Changelog++ members support our work, get closer to the metal, and make the ads disappear. Join today! Featurin...
Nov 09, 2020•51 min•Ep. 111
Hamish from Sajari blows our mind with a great discussion about AI in search. In particular, he talks about Sajari’s quest for performant AI implementations and extensive use of Reinforcement Learning (RL). We’ve been wanting to make this one happen for a while, and it was well worth the wait. Join the discussion Changelog++ members support our work, get closer to the metal, and make the ads disappear. Join today! Featuring: Hamish Ogilvy – X Chris Benson – Website , GitHub , LinkedIn , X Daniel...
Oct 26, 2020•47 min•Ep. 110
Rajiv Shah teaches Daniel and Chris about data leakage, and its major impact upon machine learning models. It’s the kind of topic that we don’t often think about, but which can ruin our results. Raj discusses how to use activation maps and image embedding to find leakage, so that leaking information in our test set does not find its way into our training set. Join the discussion Changelog++ members get a bonus 1 minute at the end of this episode and zero ads. Join today! Sponsors: DigitalOcean –...
Oct 20, 2020•48 min•Ep. 109
Suju Rajan from LinkedIn joined us to talk about how they are operationalizing state-of-the-art AI at LinkedIn. She sheds light on how AI can and is being used in recruiting, and she weaves in some great explanations of how graph-structured data, personalization, and representation learning can be applied to LinkedIn’s candidate search problem. Suju is passionate about helping people deal with machine learning technical debt, and that gives this episode a good dose of practicality. Join the disc...
Oct 13, 2020•55 min•Ep. 108
We’re partnering with the upcoming R Conference , because the R Conference is well… amazing! Tons of great AI content, and they were nice enough to connect us to Daniel Chen for this episode. He discusses data science in Computational Biology and his perspective on data science project organization. Join the discussion Changelog++ members get a bonus 1 minute at the end of this episode and zero ads. Join today! Sponsors: DigitalOcean – DigitalOcean’s developer cloud makes it simple to launch in ...
Oct 06, 2020•54 min•Ep. 107
In anticipation of the upcoming NVIDIA GPU Technology Conference (GTC), Will Ramey joins Daniel and Chris to talk about education for artificial intelligence practitioners, and specifically the role that the NVIDIA Deep Learning Institute plays in the industry. Will’s insights from long experience are shaping how we all stay on top of AI, so don’t miss this ‘must learn’ episode. Join the discussion Changelog++ members get a bonus 2 minutes at the end of this episode and zero ads. Join today! Spo...
Sep 21, 2020•53 min•Ep. 106
So, you trained a great AI model and deployed it in your app? It’s smooth sailing from there right? Well, not in most people’s experience. Sometimes things goes wrong, and you need to know how to respond to a real life AI incident. In this episode, Andrew and Patrick from BNH.ai join us to discuss an AI incident response plan along with some general discussion of debugging models, discrimination, privacy, and security. Join the discussion Changelog++ members save 2 minutes on this episode becaus...
Sep 14, 2020•59 min•Ep. 105
Many people are excited about creating usable speech technology. However, most of the audio data used by large companies isn’t available to the majority of people, and that data is often biased in terms of language, accent, and gender. Jenny, Josh, and Remy from Mozilla join us to discuss how Mozilla is building an open-source voice database that anyone can use to make innovative apps for devices and the web (Common Voice). They also discuss efforts through Mozilla fellowship program to develop ...
Sep 09, 2020•59 min•Ep. 104
