Shows
MLOps.communityBuilding LLM Products Panel // LLMs in Production Conference Part IIMLOps Coffee Sessions #172 with LLMs in Production Conference part 2 Building LLM Products Panel, George Mathew, Asmitha Rathis, Natalia Burina, and Sahar Mor Using hosted by TWIML's Sam Charrington.
We are now accepting talk proposals for our next LLM in Production virtual conference on October 3rd. Apply to speak here: https://go.mlops.community/NSAX1O
// Abstract
There are key areas we must be aware of when working with LLMs. High costs and low latency requirements are just the tip of the iceberg. In this panel, we hear about common pitfalls and challenges we must keep in mind when building...2023-08-1846 min
The Cloudcast2023 Look Ahead to AI/MLSam Charrington (@samcharrington, host @twimlai podcast) talks about the evolution of AI & ML in 2023, and the possibilities of ChatGPT.SHOW: 684CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OTHER NEW PODCAST - "CLOUDCAST BASICS"SHOW SPONSORS:Datadog Synthetic Monitoring: Frontend and Backend Modern MonitoringEnsure frontend issues don’t impair user experience by detecting user-facing issues with API and browser tests with a free 14 day Datadog trial. Listeners of The Cloudcast will al...2023-01-1145 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Live from TWIMLcon: AI Platforms 2022 - You're not Facebook. Architecting MLOps for B2B Use Cases with Jacopo TagliabueMuch of the way we talk and think about MLOps comes from the perspective of large consumer internet companies like Facebook or Google. If you work at a FAANG company, these approaches might work well for you. But what about if you work at one of the many small, B2B companies that stand to benefit through the use of machine learning? How should you be thinking about MLOps and the ML lifecycle in that case? In this live podcast interview from TWIMLcon: AI Platforms 2022, Sam Charrington explores these questions with Jacopo Tagliabue, whose perspectives and contributions on scaling...2022-10-2449 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Building Public Interest Technology with Meredith BroussardToday we’re joined by Meredith Broussard, an associate professor at NYU & research director at the NYU Alliance for Public Interest Technology. Meredith was a keynote speaker at the recent NeurIPS conference, and we had the pleasure of speaking with her to discuss her talk from the event, and her upcoming book, tentatively titled More Than A Glitch: What Everyone Needs To Know About Making Technology Anti-Racist, Accessible, And Otherwise Useful To All.In our conversation, we explore Meredith’s work in the field of public interest technology, and her view of the relationship between technology and arti...2022-01-1330 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Feature Stores for Accelerating AI DevelopmentIn this special episode of the podcast, we're joined by Kevin Stumpf, Co-Founder and CTO of Tecton, Willem Pienaar, an engineering lead at Gojek and founder of the Feast Project, and Maxime Beauchemin, Founder & CEO of Preset, for a discussion on Feature Stores for Accelerating AI Development. In this panel discussion, Sam and our guests explored how organizations can increase value and decrease time-to-market for machine learning using feature stores, MLOps, and open source. We also discuss the main data challenges of AI/ML, and the role of the feature store in solving those challenges. ...2020-11-3056 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)An Exploration of Coded Bias with Shalini Kantayya, Deb Raji and Meredith BroussardIn this special edition of the podcast, we're joined by Shalini Kantayya, the director of Coded Bias, and Deb Raji and Meredith Broussard, who both contributed to the film. In this panel discussion, Sam and our guests explored the societal implications of the biases embedded within AI algorithms. The conversation discussed examples of AI systems with disparate impact across industries and communities, what can be done to mitigate this disparity, and opportunities to get involved. Our panelists Shalini, Meredith, and Deb each share insight into their experience working on and researching bias in AI systems...2020-11-271h 24
The Lemar ShowSam Smith Demo Gave Me Energy | Nick RaphaelNick Raphael is the president of Capitol Records. Along with Jo Charrington he has signed, Jay-Z, Another Level, Big Brovaz, Lemar, JLS, Scouting For Girls, Charlotte Church, 5 Seconds Of Summer and Sam Smith among others. His knowledge in the music industry runs deep. He sits down with Lemar for a unique conversation and look back at his entry into the music industry and shares some lessons learnt. Nick Raphael:President (UK): Capitol Records: https://www.capitolrecords.com Follow Lemar:Website: https://lemar.lnk.to/officialwebsiteSNFa...2020-10-201h 45
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Machine Learning for Food Delivery at Global ScaleIn this special edition of the show, we discuss the various ways in which machine learning plays a role in helping businesses overcome their challenges in the food delivery space. A few weeks ago Sam had the opportunity to moderate a panel at the Prosus AI Marketplace virtual event with Sandor Caetano of iFood, Dale Vaz of Swiggy, Nicolas Guenon of Delivery Hero, and Euro Beinat of Prosus. In this conversation, panelists describe the application of machine learning to a variety of business use cases, including how they deliver recommendations, the unique ways they handle the logistics of deliveries, and fr...2020-10-0257 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)3D Deep Learning with PyTorch 3D w/ Georgia GkioxariToday we’re joined by Georgia Gkioxari, a research scientist at Facebook AI Research. Georgia was hand-picked by the TWIML community to discuss her work on the recently released open-source library PyTorch3D. In our conversation, Georgia describes her experiences as a computer vision researcher prior to the 2012 deep learning explosion, and how the entire landscape has changed since then. Georgia walks us through the user experience of PyTorch3D, while also detailing who the target audience is, why the library is useful, and how it fits in the broad goal of giving computers better mean...2020-09-1035 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)What are the Implications of Algorithmic Thinking? with Michael I. JordanToday we’re joined by the legendary Michael I. Jordan, Distinguished Professor in the Departments of EECS and Statistics at UC Berkeley. Michael was gracious enough to connect us all the way from Italy after being named IEEE’s 2020 John von Neumann Medal recipient. In our conversation with Michael, we explore his career path, and how his influence from other fields like philosophy shaped his path. We spend quite a bit of time discussing his current exploration into the intersection of economics and AI, and how machine learning systems could be used to create value and em...2020-09-0756 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Beyond Accuracy: Behavioral Testing of NLP Models with Sameer SinghToday we’re joined by Sameer Singh, an assistant professor in the department of computer science at UC Irvine. Sameer’s work centers on large-scale and interpretable machine learning applied to information extraction and natural language processing. We caught up with Sameer right after he was awarded the best paper award at ACL 2020 for his work on Beyond Accuracy: Behavioral Testing of NLP Models with CheckList. In our conversation, we explore CheckLists, the task-agnostic methodology for testing NLP models introduced in the paper. We also discuss how well we understand the cause of pitfalls or failu...2020-09-0341 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)How Machine Learning Powers On-Demand Logistics at Doordash with Gary RenToday we’re joined by Gary Ren, a machine learning engineer for the logistics team at DoorDash. In our conversation, we explore how machine learning powers the entire logistics ecosystem. We discuss the stages of their “marketplace,” and how using ML for optimized route planning and matching affects consumers, dashers, and merchants. We also talk through how they use traditional mathematics, classical machine learning, potential use cases for reinforcement learning frameworks, and challenges to implementing these explorations. The complete show notes for this episode can be found at twimlai.com/go/405! Check out our upcom...2020-08-3143 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Machine Learning as a Software Engineering Discipline with Dillon ErbToday we’re joined by Dillon Erb, Co-founder & CEO of Paperspace. We’ve followed Paperspace since their origins offering GPU-enabled compute resources to data scientists and machine learning developers, to the release of their Jupyter-based Gradient service. Our conversation with Dillon centered on the challenges that organizations face building and scaling repeatable machine learning workflows, and how they’ve done this in their own platform by applying time-tested software engineering practices. We also discuss the importance of reproducibility in production machine learning pipelines, how the processes and tools of software engineering map to the machine learnin...2020-08-2744 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)AI and the Responsible Data Economy with Dawn SongToday we’re joined by Professor of Computer Science at UC Berkeley, Dawn Song. Dawn’s research is centered at the intersection of AI, deep learning, security, and privacy. She’s currently focused on bringing these disciplines together with her startup, Oasis Labs. In our conversation, we explore their goals of building a ‘platform for a responsible data economy,’ which would combine techniques like differential privacy, blockchain, and homomorphic encryption. The platform would give consumers more control of their data, and enable businesses to better utilize data in a privacy-preserving and responsible way. We also discuss how...2020-08-2453 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Relational, Object-Centric Agents for Completing Simulated Household Tasks with Wilka CarvalhoToday we’re joined by Wilka Carvalho, a PhD student at the University of Michigan, Ann Arbor. In our conversation, we focus on his paper ‘ROMA: A Relational, Object-Model Learning Agent for Sample-Efficient Reinforcement Learning.’ In the paper, Wilka explores the challenge of object interaction tasks, focusing on every day, in-home functions. We discuss how he’s addressing the challenge of ‘object-interaction’ tasks, the biggest obstacles he’s run into along the way.2020-08-2041 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Model Explainability ForumToday we bring you the latest Discussion Series: The Model Explainability Forum. Our group of experts and researchers explore the current state of explainability and discuss the key emerging ideas shaping the field. Each guest shares their unique perspective and contributions to thinking about model explainability in a practical way. We explore concepts like stakeholder-driven explainability, adversarial attacks on explainability methods, counterfactual explanations, legal and policy implications, and more.2020-08-171h 27
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)What NLP Tells Us About COVID-19 and Mental Health with Johannes EichstaedtToday we’re joined by Johannes Eichstaedt, an Assistant Professor of Psychology at Stanford University. In our conversation, we explore how Johannes applies his physics background to a career as a computational social scientist, some of the major patterns in the data that emerged over the first few months of lockdown, including mental health, social norms, and political patterns. We also explore how Johannes built the process, and the techniques he’s using to collect, sift through, and understand the da2020-08-1358 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Human-AI Collaboration for Creativity with Devi ParikhToday we’re joined by Devi Parikh, Associate Professor at the School of Interactive Computing at Georgia Tech, and research scientist at Facebook AI Research (FAIR). In our conversation, we touch on Devi’s definition of creativity, explore multiple ways that AI could impact the creative process for artists, and help humans become more creative. We investigate tools like casual creator for preference prediction, neuro-symbolic generative art, and visual journaling.2020-08-1044 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Neural Augmentation for Wireless Communication with Max WellingToday we’re joined by Max Welling, Vice President of Technologies at Qualcomm Netherlands, and Professor at the University of Amsterdam. In our conversation, we explore Max’s work in neural augmentation, and how it’s being deployed. We also discuss his work with federated learning and incorporating the technology on devices to give users more control over the privacy of their personal data. Max also shares his thoughts on quantum mechanics and the future of quantum neural networks for chip design.2020-08-0648 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Quantum Machine Learning: The Next Frontier? with Iordanis KerenidisToday we're joined by Iordanis Kerenidis, Research Director CNRS Paris and Head of Quantum Algorithms at QC Ware.
Iordanis was an ICML main conference Keynote speaker on the topic of Quantum ML, and we focus our conversation on his presentation, exploring the prospects and challenges of quantum machine learning, as well as the field’s history, evolution, and future. We’ll also discuss the foundations of quantum computing, and some of the challenges to consider for breaking into the field.2020-08-041h 00
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)ML and Epidemiology with Elaine NsoesieToday we continue our ICML series with Elaine Nsoesie, assistant professor at Boston University. In our conversation, we discuss the different ways that machine learning applications can be used to address global health issues, including infectious disease surveillance, and tracking search data for changes in health behavior in African countries. We also discuss COVID-19 epidemiology and the importance of recognizing how the disease is affecting people of different races and economic backgrounds.
2020-07-3046 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Language (Technology) Is Power: Exploring the Inherent Complexity of NLP Systems with Hal Daumé IIIToday we’re joined by Hal Daume III, professor at the University of Maryland and Co-Chair of the 2020 ICML Conference. We had the pleasure of catching up with Hal ahead of this year's ICML to discuss his research at the intersection of bias, fairness, NLP, and the effects language has on machine learning models, exploring language in two categories as they appear in machine learning models and systems: (1) How we use language to interact with the world, and (2) how we “do” language.2020-07-271h 02
The Data BingeRyan Swanstrom & Derek Russell | The "Why" of Creating a Show - A Starter Discussion to Podcasting & LIVE StreamingToday's episode is a recording of a LIVE interview discussion, hosted on LinkedIn LIVE, featuring a program called "The Example Show" produced by Ryan Swanstrom. Ryan is a heavily credentialed Software Engineer, with a Masters in Math from Iowa State University, and a PHD in Computational Science and Statistics. Ryan's experience spans across over 20 years of working with notable enterprises including Northrup Grumman, all the way through to organizations like Wells Fargo and Microsoft, and most recently, Ryan consults for various organizations on his own, while late and current projects focus on reporting and analytics related to buying pattern...2020-07-261h 00
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Graph ML Research at Twitter with Michael BronsteinToday we’re excited to be joined by return guest Michael Bronstein, Head of Graph Machine Learning at Twitter. In our conversation, we discuss the evolution of the graph machine learning space, his new role at Twitter, and some of the research challenges he’s faced, including scalability and working with dynamic graphs. Michael also dives into his work on differential graph modules for graph CNNs, and the various applications of this work.2020-07-2355 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Panel: The Great ML Language (Un)Debate!Today we’re excited to bring ‘The Great ML Language (Un)Debate’ to the podcast! In the latest edition of our series of live discussions, we brought together experts and enthusiasts to discuss both popular and emerging programming languages for machine learning, along with the strengths, weaknesses, and approaches offered by Clojure, JavaScript, Julia, Probabilistic Programming, Python, R, Scala, and Swift. We round out the session with an audience Q&A (58:28).2020-07-201h 34
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)What the Data Tells Us About COVID-19 with Eric TopolToday we’re joined by Eric Topol, Director & Founder of the Scripps Research Translational Institute, and author of the book Deep Medicine. We caught up with Eric to talk through what we’ve learned about the coronavirus since it's emergence, and the role of tech in understanding and preventing the spread of the disease. We also explore the broader opportunity for medical applications of AI, the promise of personalized medicine, and how techniques like federated learning can offer more privacy in healthc2020-07-1642 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)The Case for Hardware-ML Model Co-design with Diana MarculescuToday we’re joined by Diana Marculescu, Professor of Electrical and Computer Engineering at UT Austin.
We caught up with Diana to discuss her work on hardware-aware machine learning. In particular, we explore her keynote, “Putting the “Machine” Back in Machine Learning: The Case for Hardware-ML Model Co-design” from CVPR 2020. We explore how her research group is focusing on making models more efficient so that they run better on current hardware systems, and how they plan on achieving true co2020-07-1345 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Computer Vision for Remote AR with Flora TasseToday we conclude our CVPR coverage joined by Flora Tasse, Head of Computer Vision & AI Research at Streem. Flora, a keynote speaker at the AR/VR workshop, walks us through some of the interesting use cases at the intersection of AI, CV, and AR technologies, her current work and the origin of her company Selerio, which was eventually acquired by Streem, the difficulties associated with building 3D mesh environments, extracting metadata from those environments, the challenges of pose estimation and more.2020-07-0940 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Deep Learning for Automatic Basketball Video Production with Julian QuirogaToday we're Julian Quiroga, a Computer Vision Team Lead at Genius Sports, to discuss his recent paper “As Seen on TV: Automatic Basketball Video Production using Gaussian-based Actionness and Game States Recognition.” We explore camera setups and angles, detection and localization of figures on the court (players, refs, and of course, the ball), and the role that deep learning plays in the process. We also break down how this work applies to different sports, and the ways that he is looking to improve i2020-07-0641 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)How External Auditing is Changing the Facial Recognition Landscape with Deb RajiToday we’re taking a break from our CVPR coverage to bring you this interview with Deb Raji, a Technology Fellow at the AI Now Institute.
Recently there have been quite a few major news stories in the AI community, including the self-imposed moratorium on facial recognition tech from Amazon, IBM and Microsoft. In our conversation with Deb, we dig into these stories, discussing the origins of Deb’s work on the Gender Shades project, the harms of facial recognition, and much more.2020-07-021h 20
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)AI for High-Stakes Decision Making with Hima LakkarajuToday we’re joined by Hima Lakkaraju, an Assistant Professor at Harvard University. At CVPR, Hima was a keynote speaker at the Fair, Data-Efficient and Trusted Computer Vision Workshop, where she spoke on Understanding the Perils of Black Box Explanations. Hima talks us through her presentation, which focuses on the unreliability of explainability techniques that center perturbations, such as LIME or SHAP, as well as how attacks on these models can be carried out, and what they look like.2020-06-2945 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Invariance, Geometry and Deep Neural Networks with Pavan TuragaWe continue our CVPR coverage with today’s guest, Pavan Turaga, Associate Professor at Arizona State University. Pavan gave a keynote presentation at the Differential Geometry in CV and ML Workshop, speaking on Revisiting Invariants with Geometry and Deep Learning. We go in-depth on Pavan’s research on integrating physics-based principles into computer vision. We also discuss the context of the term “invariant,” and Pavan contextualizes this work in relation to Hinton’s similar Capsule Network res2020-06-2546 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami BejnordiToday we’re joined by Babak Ehteshami Bejnordi, a Research Scientist at Qualcomm.
Babak is currently focused on conditional computation, which is the main driver for today’s conversation. We dig into a few papers in great detail including one from this year’s CVPR conference, Conditional Channel Gated Networks for Task-Aware Continual Learning, covering how gates are used to drive efficiency and accuracy, while decreasing model size, how this research manifests into actual products, and more!
2020-06-2255 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Building an ML-Forward Commerce Platform at Square with Marsal Gavalda - #384Today we’re joined by Marsal Gavalda, head of machine learning for the Commerce platform at Square, where he manages the development of machine learning for various tools and platforms, including marketing, appointments, and above all, risk management.
We explore how they manage their vast portfolio of projects, and how having an ML and technology focus at the outset of the company has contributed to their success, tips and best practices for internal democratization of ML, and much more.2020-06-1851 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Cell Exploration with ML at the Allen Institute w/ Jianxu ChenToday we’re joined by Jianxu Chen, a scientist at the Allen Institute for Cell Science.
At the latest GTC conference, Jianxu presented his work on the Allen Cell Explorer Toolkit, an open-source project that allows users to do 3D segmentation of intracellular structures in fluorescence microscope images at high resolutions, making the images more accessible for data analysis. We discuss three of the major components of the toolkit: the cell image analyzer, the image generator, and the image visualizer2020-06-1544 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Neural Arithmetic Units & Experiences as an Independent ML Researcher with Andreas MadsenToday we’re joined by Andreas Madsen, an independent researcher based in Denmark. While we caught up with Andreas to discuss his ICLR spotlight paper, “Neural Arithmetic Units,” we also spend time exploring his experience as an independent researcher, discussing the difficulties of working with limited resources, the importance of finding peers to collaborate with, and tempering expectations of getting papers accepted to conferences -- something that might take a few tries to get right.2020-06-1131 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)2020: A Critical Inflection Point for Responsible AI with Rumman ChowdhuryToday we’re joined by Rumman Chowdhury, Managing Director and Global Lead of Responsible AI at Accenture. In our conversation with Rumman, we explored questions like:
• Why is now such a critical inflection point in the application of responsible AI?
• How should engineers and practitioners think about AI ethics and responsible AI?
• Why is AI ethics inherently personal and how can you define your own personal approach?
• Is the implementation of AI governance necessarily authoritarian?2020-06-081h 01
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Panel: Advancing Your Data Science Career During the PandemicToday we’re joined by Ana Maria Echeverri, Caroline Chavier, Hilary Mason, and Jacqueline Nolis, our guests for the recent Advancing Your Data Science Career During the Pandemic panel.
In this conversation, we explore ways that Data Scientists and ML/AI practitioners can continue to advance their careers despite current challenges. Our panelists provide concrete tips, advice, and direction for those just starting out, those affected by layoffs, and those just wanting to move forward in their careers.2020-06-041h 07
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)On George Floyd, Empathy, and the Road AheadVisit twimlai.com/blacklivesmatter for resources to support organizations pushing for social equity like Black Lives Matter, and groups offering relief for those jailed for exercising their rights to peaceful protest. 2020-06-0206 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Engineering a Less Artificial Intelligence with Andreas ToliasToday we’re joined by Andreas Tolias, Professor of Neuroscience at Baylor College of Medicine.
We caught up with Andreas to discuss his recent perspective piece, “Engineering a Less Artificial Intelligence,” which explores the shortcomings of state-of-the-art learning algorithms in comparison to the brain. The paper also offers several ideas about how neuroscience can lead the quest for better inductive biases by providing useful constraints on representations and network architecture.2020-05-2846 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Rethinking Model Size: Train Large, Then Compress with Joseph GonzalezToday we’re joined by Joseph Gonzalez, Assistant Professor in the EECS department at UC Berkeley.
In our conversation, we explore Joseph’s paper “Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers,” which looks at compute-efficient training strategies for models. We discuss the two main problems being solved; 1) How can we rapidly iterate on variations in architecture? And 2) If we make models bigger, is it really improving any efficiency?2020-05-2552 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)The Physics of Data with Alpha LeeToday we’re joined by Alpha Lee, Winton Advanced Fellow in the Department of Physics at the University of Cambridge. Our conversation centers around Alpha’s research which can be broken down into three main categories: data-driven drug discovery, material discovery, and physical analysis of machine learning. We discuss the similarities and differences between drug discovery and material science, his startup, PostEra which offers medicinal chemistry as a service powered by machine learning, and much more2020-05-2133 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Is Linguistics Missing from NLP Research? w/ Emily M. Bender 🦜Today we’re joined by Emily M. Bender, Professor of Linguistics at the University of Washington.
Our discussion covers a lot of ground, but centers on the question, "Is Linguistics Missing from NLP Research?" We explore if we would be making more progress, on more solid foundations, if more linguists were involved in NLP research, or is the progress we're making (e.g. with deep learning models like Transformers) just fine?2020-05-1852 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Disrupting DeepFakes: Adversarial Attacks Against Conditional Image Translation Networks with Nataniel RuizToday we’re joined by Nataniel Ruiz, a PhD Student at Boston University.
We caught up with Nataniel to discuss his paper “Disrupting DeepFakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systems.” In our conversation, we discuss the concept of this work, as well as some of the challenging parts of implementing this work, potential scenarios in which this could be deployed, and the broader contributions that went into this work.2020-05-1442 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Understanding the COVID-19 Data Quality Problem with Sherri Rose - #374Today we’re joined by Sherri Rose, Associate Professor at Harvard Medical School. We cover a lot of ground in our conversation, including the intersection of her research with the current COVID-19 pandemic, the importance of quality in datasets and rigor when publishing papers, and the pitfalls of using causal inference.
We also touch on Sherri’s work in algorithmic fairness, the shift she’s seen in fairness conferences covering these issues in relation to healthcare research, and a few recent pape2020-05-1144 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)The Whys and Hows of Managing Machine Learning Artifacts with Lukas BiewaldToday we’re joined by Lukas Biewald, founder and CEO of Weights & Biases, to discuss their new tool Artifacts, an end to end pipeline tracker. In our conversation, we explore Artifacts’ place in the broader machine learning tooling ecosystem through the lens of our eBook “The definitive guide to ML Platforms” and how it fits with the W&B model management platform. We discuss also discuss what exactly “Artifacts” are, what the tool is tracking, and take a look at the onboarding process for users.2020-05-0754 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Language Modeling and Protein Generation at Salesforce with Richard Socher - #372Today we’re joined Richard Socher, Chief Scientist and Executive VP at Salesforce. Richard and his team have published quite a few great projects lately, including CTRL: A Conditional Transformer Language Model for Controllable Generation, and ProGen, an AI Protein Generator, both of which we cover in-depth in this conversation. We also explore the balancing act between investments, product requirement research and otherwise at a large product-focused company like Salesforce.2020-05-0442 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)AI Research at JPMorgan Chase with Manuela VelosoToday we’re joined by Manuela Veloso, Head of AI Research at J.P. Morgan Chase. Since moving from CMU to JP Morgan Chase, Manuela and her team established a set of seven lofty research goals. In this conversation we focus on the first three: building AI systems to eradicate financial crime, safely liberate data, and perfect client experience. We also explore Manuela’s background, including her time CMU in the ‘80s, or as she describes it, the “mecca of AI,” and her founding role with RoboCup.2020-04-3046 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Panel: Responsible Data Science in the Fight Against COVID-19In this discussion, we explore how data scientists and ML/AI practitioners can responsibly contribute to the fight against coronavirus and COVID-19. Four experts: Rex Douglass, Rob Munro, Lea Shanley, and Gigi Yuen-Reed shared a ton of valuable insight on the best ways to get involved.
We've gathered all the resources that our panelists discussed during the conversation, you can find those at twimlai.com/talk/370.2020-04-2958 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Adversarial Examples Are Not Bugs, They Are Features with Aleksander MadryToday we’re joined by Aleksander Madry, Faculty in the MIT EECS Department, to discuss his paper “Adversarial Examples Are Not Bugs, They Are Features.” In our conversation, we talk through what we expect these systems to do, vs what they’re actually doing, if we’re able to characterize these patterns, and what makes them compelling, and if the insights from the paper will help inform opinions on either side of the deep learning debate.2020-04-2741 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)AI for Social Good: Why "Good" isn't Enough with Ben GreenToday we’re joined by Ben Green, PhD Candidate at Harvard and Research Fellow at the AI Now Institute at NYU.
Ben’s research is focused on the social and policy impacts of data science, with a focus on algorithmic fairness and the criminal justice system. We discuss his paper ‘Good' Isn't Good Enough,’ which explores the 2 things he feels are missing from data science and machine learning research; A grounded definition of what “good” actually means, and the absence of a “theory of change.2020-04-2341 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)The Evolution of Evolutionary AI with Risto MiikkulainenToday we’re joined by Risto Miikkulainen, Associate VP of Evolutionary AI at Cognizant AI. Risto joined us back on episode #47 to discuss evolutionary algorithms, and today we get an update on the latest on the topic. In our conversation, we discuss use cases for evolutionary AI and the latest approaches to deploying evolutionary models. We also explore his paper “Better Future through AI: Avoiding Pitfalls and Guiding AI Towards its Full Potential,” which digs into the historical evolution of AI. 2020-04-2037 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Neural Architecture Search and Google’s New AutoML Zero with Quoc LeToday we’re super excited to share our recent conversation with Quoc Le, a research scientist at Google. Quoc joins us to discuss his work on Google’s AutoML Zero, semi-supervised learning, and the development of Meena, the multi-turn conversational chatbot.
This was a really fun conversation, so much so that we decided to release the video! April 16th at 12 pm PT, Quoc and Sam will premiere the video version of this interview on Youtube, and answer your questions in the chat. We’ll see you there!2020-04-1654 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Automating Electronic Circuit Design with Deep RL w/ Karim BeguirToday we’re joined by return guest Karim Beguir, Co-Founder and CEO of InstaDeep. In our conversation, we chat with Karim about InstaDeep’s new offering, DeepPCB, an end-to-end platform for automated circuit board design. We discuss challenges and problems with some of the original iterations of auto-routers, how Karim defines circuit board “complexity,” the differences between reinforcement learning being used for games and in this use case, and their spotlight paper from NeurIPS.2020-04-1335 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Neural Ordinary Differential Equations with David DuvenaudToday we’re joined by David Duvenaud, Assistant Professor at the University of Toronto, to discuss his research on Neural Ordinary Differential Equations, a type of continuous-depth neural network. In our conversation, we talk through a few of David’s papers on the subject. We discuss the problem that David is trying to solve with this research, the potential that ODEs have to replace “the backbone” of the neural networks that are used to train today, and David’s approach to engineering.2020-04-0949 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)The Measure and Mismeasure of Fairness with Sharad GoelToday we’re joined by Sharad Goel, Assistant Professor at Stanford. Sharad, who also has appointments in the computer science, sociology, and law departments, has spent recent years focused on applying ML to understanding and improving public policy. In our conversation, we discuss Sharad’s extensive work on discriminatory policing, and The Stanford Open Policing Project. We also dig into Sharad’s paper “The Measure and Mismeasure of Fairness: A Critical Review of Fair Machine Learning.”2020-04-0648 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Simulating the Future of Traffic with RL w/ Cathy WuToday we’re joined by Cathy Wu, Assistant Professor at MIT. We had the pleasure of catching up with Cathy to discuss her work applying RL to mixed autonomy traffic, specifically, understanding the potential impact autonomous vehicles would have on various mixed-autonomy scenarios. To better understand this, Cathy built multiple RL simulations, including a track, intersection, and merge scenarios. We talk through how each scenario is set up, how human drivers are modeled, the results, and much more.2020-04-0235 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Consciousness and COVID-19 with Yoshua BengioToday we’re joined by one of, if not the most cited computer scientist in the world, Yoshua Bengio, Professor at the University of Montreal and the Founder and Scientific Director of MILA. We caught up with Yoshua to explore his work on consciousness, including how Yoshua defines consciousness, his paper “The Consciousness Prior,” as well as his current endeavor in building a COVID-19 tracing application, and the use of ML to propose experimental candidate drugs.2020-03-3049 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Geometry-Aware Neural Rendering with Josh TobinToday we’re joined by Josh Tobin, Co-Organizer of the machine learning training program Full Stack Deep Learning. We had the pleasure of sitting down with Josh prior to his presentation of his paper Geometry-Aware Neural Rendering at NeurIPS. Josh's goal is to develop implicit scene understanding, building upon Deepmind's Neural scene representation and rendering work. We discuss challenges, the various datasets used to train his model, and the similarities between VAE training and his process, and mor2020-03-2626 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)The Third Wave of Robotic Learning with Ken GoldbergToday we’re joined by Ken Goldberg, professor of engineering at UC Berkeley, focused on robotic learning. In our conversation with Ken, we chat about some of the challenges that arise when working on robotic grasping, including uncertainty in perception, control, and physics. We also discuss his view on the role of physics in robotic learning, and his thoughts on potential robot use cases, from the use of robots in assisting in telemedicine, agriculture, and even robotic Covid-19 testing.2020-03-231h 01
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Learning Visiolinguistic Representations with ViLBERT w/ Stefan LeeToday we’re joined by Stefan Lee, an assistant professor at Oregon State University. In our conversation, we focus on his paper ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks. We discuss the development and training process for this model, the adaptation of the training process to incorporate additional visual information to BERT models, where this research leads from the perspective of integration between visual and language tasks.2020-03-1827 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Upside-Down Reinforcement Learning with Jürgen SchmidhuberToday we’re joined by Jürgen Schmidhuber, Co-Founder and Chief Scientist of NNAISENSE, the Scientific Director at IDSIA, as well as a Professor of AI at USI and SUPSI in Switzerland. Jürgen’s lab is well known for creating the Long Short-Term Memory (LSTM) network, and in this conversation, we discuss some of the recent research coming out of his lab, namely Upside-Down Reinforcement Learning.2020-03-1634 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)SLIDE: Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning with Beidi ChenBeidi Chen is part of the team that developed a cheaper, algorithmic, CPU alternative to state-of-the-art GPU machines. They presented their findings at NeurIPS 2019 and have since gained a lot of attention for their paper, SLIDE: In Defense of Smart Algorithms Over Hardware Acceleration for Large-Scale Deep Learning Systems. Beidi shares how the team took a new look at deep learning with the case of extreme classification by turning it into a search problem and using locality-sensitive hashing.2020-03-1231 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Advancements in Machine Learning with Sergey LevineToday we're joined by Sergey Levine, an Assistant Professor at UC Berkeley. We last heard from Sergey back in 2017, where we explored Deep Robotic Learning. Sergey and his lab’s recent efforts have been focused on contributing to a future where machines can be “out there in the real world, learning continuously through their own experience.” We caught up with Sergey at NeurIPS 2019, where Sergey and his team presented 12 different papers -- which means a lot of ground to cover!2020-03-0943 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Secrets of a Kaggle Grandmaster with David OdaiboImagine spending years learning ML from the ground up, from its theoretical foundations, but still feeling like you didn’t really know how to apply it. That’s where David Odaibo found himself in 2015, after the second year of his PhD. David’s solution was Kaggle, a popular platform for data science competitions.
Fast forward four years, and David is now a Kaggle Grandmaster, the highest designation, with particular accomplishment in computer vision competitions, and co-founder and CTO of Analytical2020-03-0541 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)NLP for Mapping Physics Research with Matteo ChinazziPredicting the future of science, particularly physics, is the task that Matteo Chinazzi, an associate research scientist at Northeastern University focused on in his paper Mapping the Physics Research Space: a Machine Learning Approach. In addition to predicting the trajectory of physics research, Matteo is also active in the computational epidemiology field. His work in that area involves building simulators that can model the spread of diseases like Zika or the seasonal flu at a global scale.2020-03-0335 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Metric Elicitation and Robust Distributed Learning with Sanmi KoyejoThe unfortunate reality is that many of the most commonly used machine learning metrics don't account for the complex trade-offs that come with real-world decision making. This is one of the challenges that Sanmi Koyejo, assistant professor at the University of Illinois, has dedicated his research to address. Sanmi applies his background in cognitive science, probabilistic modeling, and Bayesian inference to pursue his research which focuses broadly on “adaptive and robust machine learning.”2020-02-2756 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)High-Dimensional Robust Statistics with Ilias DiakonikolasToday we’re joined by Ilias Diakonikolas, faculty in the CS department at the University of Wisconsin-Madison, and author of the paper Distribution-Independent PAC Learning of Halfspaces with Massart Noise, recipient of the NeurIPS 2019 Outstanding Paper award. The paper is regarded as the first progress made around distribution-independent learning with noise since the 80s. In our conversation, we explore robustness in ML, problems with corrupt data in high-dimensional settings, and of course, the paper.2020-02-2436 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)How AI Predicted the Coronavirus Outbreak with Kamran KhanToday we’re joined by Kamran Khan, founder & CEO of BlueDot, and professor of medicine and public health at the University of Toronto. BlueDot has been the recipient of a lot of attention for being the first to publicly warn about the coronavirus that started in Wuhan. How did the company’s system of algorithms and data processing techniques help flag the potential dangers of the disease? In our conversation, Kamran talks us through how the technology works, its limits, and the motivation behind the wor2020-02-1951 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Turning Ideas into ML Powered Products with Emmanuel AmeisenToday we’re joined by Emmanuel Ameisen, machine learning engineer at Stripe, and author of the recently published book “Building Machine Learning Powered Applications; Going from Idea to Product.” In our conversation, we discuss structuring end-to-end machine learning projects, debugging and explainability in the context of models, the various types of models covered in the book, and the importance of post-deployment monitoring. 2020-02-1742 minThe CloudcastA "AI & ML" Look Ahead for 2020Sam Charrington (@samcharrington, Host of TWIML & AI Podcast) talks about AI & ML trends in 2020, frameworks to understand usage patterns, hot new technology to explore, how long projects take to succeed, and the inherent bias built into every AI & ML model.SHOW: 437SHOW SPONSOR LINKS:Datadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtMongoDB Homepage - The most popular database for modern applicationsMongoDB Atlas - MongoDB-as-a-Service on AWS, Azure and GCP...2020-02-1442 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Algorithmic Injustices and Relational Ethics with Abeba BirhaneToday we’re joined by Abeba Birhane, PhD Student at University College Dublin and author of the recent paper Algorithmic Injustices: Towards a Relational Ethics, which was the recipient of the Best Paper award at the 2019 Black in AI Workshop at NeurIPS. In our conversation, break down the paper and the thought process around AI ethics, the “harm of categorization,” how ML generally doesn’t account for the ethics of various scenarios and how relational ethics could solve the issue, and much more.2020-02-1341 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)AI for Agriculture and Global Food Security with Nemo SemretToday we’re excited to kick off our annual Black in AI Series joined by Nemo Semret, CTO of Gro Intelligence. Gro provides an agricultural data platform dedicated to improving global food security, focused on applying AI at macro scale. In our conversation with Nemo, we discuss Gro’s approach to data acquisition, how they apply machine learning to various problems, and their approach to modeling.2020-02-101h 04
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Practical Differential Privacy at LinkedIn with Ryan RogersToday we’re joined by Ryan Rogers, Senior Software Engineer at LinkedIn, to discuss his paper “Practical Differentially Private Top-k Selection with Pay-what-you-get Composition.” In our conversation, we discuss how LinkedIn allows its data scientists to access aggregate user data for exploratory analytics while maintaining its users’ privacy through differential privacy, and the connection between a common algorithm for implementing differential privacy, the exponential mechanism, and Gumbel noise.2020-02-0733 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Networking Optimizations for Multi-Node Deep Learning on Kubernetes with Erez CohenToday we conclude the KubeCon ‘19 series joined by Erez Cohen, VP of CloudX & AI at Mellanox, who we caught up with before his talk “Networking Optimizations for Multi-Node Deep Learning on Kubernetes.” In our conversation, we discuss NVIDIA’s recent acquisition of Mellanox, the evolution of technologies like RDMA and GPU Direct, how Mellanox is enabling Kubernetes and other platforms to take advantage of the recent advancements in networking tech, and why we should care about networking in Deep Lea2020-02-0531 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Managing Research Needs at the University of Michigan using Kubernetes w/ Bob KillenToday we’re joined by Bob Killen, Research Cloud Administrator at the University of Michigan. In our conversation, we explore how Bob and his group at UM are deploying Kubernetes, the user experience, and how those users are taking advantage of distributed computing. We also discuss if ML/AI focused Kubernetes users should fear that the larger non-ML/AI user base will negatively impact their feature needs, where gaps currently exist in trying to support these ML/AI users’ workloads, and more!2020-02-0325 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Scalable and Maintainable Workflows at Lyft with Flyte w/ Haytham AbuelFutuh and Ketan UmareToday we kick off our KubeCon ‘19 series joined by Haytham AbuelFutuh and Ketan Umare, a pair of software engineers at Lyft. We caught up with Haytham and Ketan at KubeCo, where they were presenting their newly open-sourced, cloud-native ML and data processing platform, Flyte. We discuss what prompted Ketan to undertake this project and his experience building Flyte, the core value proposition, what type systems mean for the user experience, how it relates to Kubeflow and how Flyte is used across Lyft.2020-01-3045 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Causality 101 with Robert Osazuwa NessToday Robert Osazuwa Ness, ML Research Engineer at Gamalon and Instructor at Northeastern University joins us to discuss Causality, what it means, and how that meaning changes across domains and users, and our upcoming study group based around his new course sequence, “Causal Modeling in Machine Learning," for which you can find details at twimlai.com/community. 2020-01-2739 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)PaccMann^RL: Designing Anticancer Drugs with Reinforcement Learning w/ Jannis BornToday we’re joined by Jannis Born, Ph.D. student at ETH & IBM Research Zurich, to discuss his “PaccMann^RL” research. Jannis details how his background in computational neuroscience applies to this research, how RL fits into the goal of anticancer drug discovery, the effect DL has had on his research, and of course, a step-by-step walkthrough of how the framework works to predict the sensitivity of cancer drugs on a cell and then discover new anticancer drugs.2020-01-2342 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Social Intelligence with Blaise Aguera y ArcasToday we’re joined by Blaise Aguera y Arcas, a distinguished scientist at Google. We had the pleasure of catching up with Blaise at NeurIPS last month, where he was invited to speak on “Social Intelligence.” In our conversation, we discuss his role at Google, and his team’s approach to machine learning, and of course his presentation, in which he touches discussing today’s ML landscape, the gap between AI and ML/DS, the difference between intelligent systems and true intelligence, and much more. 2020-01-2047 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Music & AI Plus a Geometric Perspective on Reinforcement Learning with Pablo Samuel CastroToday we’re joined by Pablo Samuel Castro, Staff Research Software Developer at Google. We cover a lot of ground in our conversation, including his love for music, and how that has guided his work on the Lyric AI project, and a few of his papers including “A Geometric Perspective on Optimal Representations for Reinforcement Learning” and “Estimating Policy Functions in Payments Systems using Deep Reinforcement Learning.”
2020-01-1644 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Trends in Computer Vision with Amir ZamirToday we close out AI Rewind 2019 joined by Amir Zamir, who recently began his tenure as an Assistant Professor of Computer Science at the Swiss Federal Institute of Technology. Amir joined us back in 2018 to discuss his CVPR Best Paper winner, and in today’s conversation, we continue with the thread of Computer Vision. In our conversation, we discuss quite a few topics, including Vision-for-Robotics, the expansion of the field of 3D Vision, Self-Supervised Learning for CV Tasks, and much more! 2020-01-141h 37
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Trends in Natural Language Processing with Nasrin MostafazadehToday we continue the AI Rewind 2019 joined by friend-of-the-show Nasrin Mostafazadeh, Senior AI Research Scientist at Elemental Cognition. We caught up with Nasrin to discuss the latest and greatest developments and trends in Natural Language Processing, including Interpretability, Ethics, and Bias in NLP, how large pre-trained models have transformed NLP research, and top tools and frameworks in the space.2020-01-091h 12
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Trends in Fairness and AI Ethics with Timnit Gebru - #336Today we keep the 2019 AI Rewind series rolling with friend-of-the-show Timnit Gebru, a research scientist on the Ethical AI team at Google. A few weeks ago at NeurIPS, Timnit joined us to discuss the ethics and fairness landscape in 2019. In our conversation, we discuss diversification of NeurIPS, with groups like Black in AI, WiML and others taking huge steps forward, trends in the fairness community, quite a few papers, and much more.2020-01-0649 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Trends in Reinforcement Learning with Chelsea FinnToday we continue to review the year that was 2019 via our AI Rewind series, and do so with friend of the show Chelsea Finn, Assistant Professor in the CS Department at Stanford University. Chelsea’s research focuses on Reinforcement Learning, so we couldn’t think of a better person to join us to discuss the topic. In this conversation, we cover topics like Model-based RL, solving hard exploration problems, along with RL libraries and environments that Chelsea thought moved the needle last year.2020-01-021h 08
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Live from TWIMLcon! Use-Case Driven ML Platforms with Franziska BellToday we're Franziska Bell, Ph.D., the Director of Data Science Platforms at Uber, who joined Sam on stage at TWIMLcon last week. Fran provided a look into the cutting edge data science available company-wide at the push of a button. Since joining Uber, Fran has developed a portfolio of platforms, ranging from forecasting to conversational AI. Hear how use cases can strategically guide platform development, the evolving relationship between her team and Michelangelo (Uber’s ML Platform) and much more!2019-10-1032 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)LIVE FROM TWIMLcon! Encoding Company Culture in Applied AI SystemsIn this episode, Sam is joined by Deepak Agarwal, VP of Engineering at LinkedIn, who graced the stage at TWIMLcon: AI Platforms for a keynote interview. Deepak shares the impact that standardizing processes and tools have on a company’s culture and productivity levels, and best practices to increasing ML ROI. He also details the Pro-ML initiative for delivering machine learning systems at scale, specifically looking at aligning improvement of tooling and infrastructure with the pace of innovation and more2019-10-0432 min
Leadership, Brand Strategy & Transformation - Minter DialogueThe State of Play of Machine Learning, Deep Learning and Artificial Intelligence with Sam Charrington, host of the TWiMLAI podcastMinter Dialogue Episode #340Sam Charrington is an industry analyst, specialized in Machine Learning and Artificial Intelligence. He's also the host of the very successful podcast, TWiMLAI aka This Week in Machine Learning and AI. In this conversation with Sam, we plunge into how and why businesses are using ML and AI, the biggest learnings Sam has had after doing nearly 300 episodes, who was his favorite guest, as well as the outlook for AI/ML in 2020.If you've got comments or questions you'd like to see answered, send your email...2019-09-0842 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Disentangled Representations & Google Research Football with Olivier BachemToday we’re joined by Olivier Bachem, a research scientist at Google AI on the Brain team.
Olivier joins us to discuss his work on Google’s research football project, their foray into building a novel reinforcement learning environment. Olivier and Sam discuss what makes this environment different than other available RL environments, such as OpenAI Gym and PyGame, what other techniques they explored while using this environment, and what’s on the horizon for their team and Football RLE.
2019-08-2242 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Learning with Limited Labeled Data with Shioulin SamToday we’re joined by Shioulin Sam, Research Engineer with Cloudera Fast Forward Labs.
Shioulin and I caught up to discuss the newest report to come out of CFFL, “Learning with Limited Label Data,” which explores active learning as a means to build applications requiring only a relatively small set of labeled data. We start our conversation with a review of active learning and some of the reasons why it’s recently become an interesting technology for folks building systems based on deep learning2019-04-2344 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Dissecting the Controversy around OpenAI's New Language ModelIn the inaugural TWiML Live, Sam Charrington is joined by Amanda Askell (OpenAI), Anima Anandkumar (NVIDIA/CalTech), Miles Brundage (OpenAI), Robert Munro (Lilt), and Stephen Merity to discuss the controversial recent release of the OpenAI GPT-2 Language Model.
We cover the basics like what language models are and why they’re important, and why this announcement caused such a stir, and dig deep into why the lack of a full release of the model raised concerns for so many.
2019-02-251h 05The CloudcastAn AI and ML Look Ahead for 2019Show: 382Description: Brian talks with Sam Charrington (@samcharrington, Machine Learning & AI analyst, advisor & host of “This Week in Machine Learning & AI” podcast) about trends in the industry, the evolution of AI at the edge, new research areas in 2019, and a discussion about adding AI and ML to business applications. Show Sponsor Links:Liquid Technology - IT Value RecoveryTry CloudLast Service, get a free t-shirt and chance at Amazon Gift CardDatadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podca...2019-01-2341 min
cloud2030Mathew Lodge on Data Science as a Service in 20 Minutes from ScratchJoining us this week is Mathew Lodge, SVP of Products & Marketing of Anaconda.
Highlights
• 2 min 57 sec: What does Anaconda do?
o Help data scientists be productive & enterprise AI / Data Science
• 3 min 36 sec: How do you interact with Anaconda?
o About 2.5 million downloads a month of Anaconda Distribution
o Install binary packages for data science to Python
• 5 min 55 sec: Who are data scientists?
o Data wrangling and understanding
• 9 min 12 sec: Data Science as a verb
o Understand how to turn data into actionable insight
• 10 min 47 sec: How learn to use the tools? Community!
o Community around Anaconda open source to share packages...2018-08-1839 min
ModernEnterpriseAI in the Enterprise with Sam CharringtonIn this episode, we talk with Sam Charrington of Cloud Pulse on the trends shaping AI adoption in the enterprise. Sam also hosts a popular podcast called "This Week in ML and AI"
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Support this podcast: https://podcasters.spotify.com/pod/show/modernenterprise/support2018-03-1453 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Block-Sparse Kernels for Deep Neural Networks with Durk Kingma - TWiML Talk #80The show is part of a series that I’m really excited about, in part because I’ve been working to bring them to you for quite a while now. The focus of the series is a sampling of the interesting work being done over at OpenAI, the independent AI research lab founded by Elon Musk, Sam Altman and others. In this show I’m joined by Jonas Schneider, Robotics Technical Team Lead at OpenAI. This episode features Durk Kingma, a Research Scientist at OpenAI. Although Durk is probably best known for his pioneering work on variational autoencoders, he joined me thi...2017-12-0744 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Robotics at OpenAI with Jonas Schneider - TWiML Talk #76The show is part of a series that I’m really excited about, in part because I’ve been working to bring them to you for quite a while now. The focus of the series is a sampling of the interesting work being done over at OpenAI, the independent AI research lab founded by Elon Musk, Sam Altman and others. In this show I’m joined by Jonas Schneider, Robotics Technical Team Lead at OpenAI. While in San Francisco a few months ago, I spent some time with Jonas at the OpenAI office, during which we covered a lot of intere...2017-12-0145 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)AI Robustness and Safety with Dario Amodei - TWiML Talk #75The show is part of a series that I’m really excited about, in part because I’ve been working to bring them to you for quite a while now. The focus of the series is a sampling of the interesting work being done over at OpenAI, the independent AI research lab founded by Elon Musk, Sam Altman and others. In this episode i'm joined by Dario Amodei, Team Lead for Safety Research at OpenAI. While in San Francisco a few months ago, I spent some time at the OpenAI office, during which I sat down with Dario to chat abou...2017-11-3036 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Towards Artificial General Intelligence with Greg Brockman - TWiML Talk #74The show is part of a series that I’m really excited about, in part because I’ve been working to bring them to you for quite a while now. The focus of the series is a sampling of the interesting work being done over at OpenAI, the independent AI research lab founded by Elon Musk, Sam Altman and others. In this episode, I’m joined by Greg Brockman, OpenAI Co-Founder and CTO. Greg and I touch on a bunch of topics in the show. We start with the founding and goals of OpenAI, before diving into a discussion on Artifi...2017-11-2855 min
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)Explaining Black Box Predictions with Sam Ritchie - TWiML Talk #73This week, we’ll be featuring a series of shows recorded from Strange Loop, a great developer-focused conference that takes place every year right in my backyard! The conference is a multi-disciplinary melting pot of developers and thinkers across a variety of fields, and we’re happy to be able to bring a bit of it to those of you who couldn’t make it in person! In this episode, I speak with Sam Ritchie, a software engineer at Stripe. I caught up with Sam RIGHT after his talk at the conference, where he covered his team’s work on expla...2017-11-2538 min
The CloudcastThe Cloudcast #321 - This Week in ML and AIAaron & Brian talk with Sam Charrington (@samcharrington, Host of This Week in ML & AI Podcast) about the differences between AI and ML, how to manage data gravity, the maturity of the technology, press coverage, and the societal impacts of AI and ML.Show Links:This Week in AI & ML PodcastCloudPulse Strategies[PODCAST] @PodCTL - Containers | Kubernetes - RSS Feed, iTunes, Google Play, Stitcher, TuneIn and all your favorite podcast players[A CLOUD GURU] Get The Cloudcast Alexa Skill[A CLOUD GURU] DISCOUNT: Serverless for Beginners (only $15 instead of $29)[A CLOUD GURU] FREE: Alexa Development for A...2017-11-1634 min