The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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799 afleveringen, van nieuw naar oud
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Probabilistic Numeric CNNs with Roberto Bondesan - #482
10 mei 2021 · 41 min
Today we kick off our ICLR 2021 coverage joined by Roberto Bondesan, an AI Researcher at Qualcomm.
In our conversation with Roberto, we explore his paper Probabilistic Numeric Convolutional Neural Networks, which represents features as Gaussian processes, providing a probabilistic description of discretization error. We discuss some of the other work the team at Qualcomm presented at the conference, including a paper called Adaptive Neural Compression, as well as work on Guage Equvariant Mesh CNNs. Finally, we briefly discuss quantum deep learning, and what excites Roberto and his team about the future of their research in combinatorial optimization.
The complete show notes for this episode can be found at https://twimlai.com/go/482 Lees meer -
Building a Unified NLP Framework at LinkedIn with Huiji Gao - #481
6 mei 2021 · 35 min
Today we’re joined by Huiji Gao, a Senior Engineering Manager of Machine Learning and AI at LinkedIn.
In our conversation with Huiji, we dig into his interest in building NLP tools and systems, including a recent open-source project called DeText, a framework for generating models for ranking classification and language generation. We explore the motivation behind DeText, the landscape at LinkedIn before and after it was put into use broadly, and the various contexts it’s being used in at the company. We also discuss the relationship between BERT and DeText via LiBERT, a version of BERT that is trained and calibrated on LinkedIn data, the practical use of these tools from an engineering perspective, the approach they’ve taken to optimization, and much more!
The complete show notes for this episode can be found at https://twimlai.com/go/481. Lees meer -
Dask + Data Science Careers with Jacqueline Nolis - #480
3 mei 2021 · 35 min
Today we’re joined by Jacqueline Nolis, Head of Data Science at Saturn Cloud, and co-host of the Build a Career in Data Science Podcast.
You might remember Jacqueline from our Advancing Your Data Science Career During the Pandemic panel, where she shared her experience trying to navigate the suddenly hectic data science job market. Now, a year removed from that panel, we explore her book on data science careers, top insights for folks just getting into the field, ways that job seekers should be signaling that they have the required background, and how to approach and navigate failure as a data scientist.
We also spend quite a bit of time discussing Dask, an open-source library for parallel computing in Python, as well as use cases for the tool, the relationship between dask and Kubernetes and docker containers, where data scientists are in regards to the software development toolchain and much more!
The complete show notes for this episode can be found at https://twimlai.com/go/480. Lees meer -
Machine Learning for Equitable Healthcare Outcomes with Irene Chen - #479
29 april 2021 · 37 min
Today we’re joined by Irene Chen, a Ph.D. student at MIT.
Irene’s research is focused on developing new machine learning methods specifically for healthcare, through the lens of questions of equity and inclusion. In our conversation, we explore some of the various projects that Irene has worked on, including an early detection program for intimate partner violence.
We also discuss how she thinks about the long term implications of predictions in the healthcare domain, how she’s learned to communicate across the interface between the ML researcher and clinician, probabilistic approaches to machine learning for healthcare, and finally, key takeaways for those of you interested in this area of research.
The complete show notes for this episode can be found at https://twimlai.com/go/479. Lees meer -
AI Storytelling Systems with Mark Riedl - #478
26 april 2021 · 41 min
Today we’re joined by Mark Riedl, a Professor in the School of Interactive Computing at Georgia Tech. In our conversation with Mark, we explore his work building AI storytelling systems, mainly those that try and predict what listeners think will happen next in a story and how he brings together many different threads of ML/AI together to solve these problems. We discuss how the theory of mind is layered into his research, the use of large language models like GPT-3, and his push towards being able to generate suspenseful stories with these systems.
We also discuss the concept of intentional creativity and the lack of good theory on the subject, the adjacent areas in ML that he’s most excited about for their potential contribution to his research, his recent focus on model explainability, how he approaches problems of common sense, and much more!
The complete show notes for this episode can be found at https://twimlai.com/go/478. Lees meer -
Creating Robust Language Representations with Jamie Macbeth - #477
21 april 2021 · 40 min
Today we’re joined by Jamie Macbeth, an assistant professor in the department of computer science at Smith College.
In our conversation with Jamie, we explore his work at the intersection of cognitive systems and natural language understanding, and how to use AI as a vehicle for better understanding human intelligence. We discuss the tie that binds these domains together, if the tasks are the same as traditional NLU tasks, and what are the specific things he’s trying to gain deeper insights into.
One of the unique aspects of Jamie’s research is that he takes an “old-school AI” approach, and to that end, we discuss the models he handcrafts to generate language. Finally, we examine how he evaluates the performance of his representations if he’s not playing the SOTA “game,” what he bookmarks against, identifying deficiencies in deep learning systems, and the exciting directions for his upcoming research.
The complete show notes for this episode can be found at https://twimlai.com/go/477. Lees meer -
Reinforcement Learning for Industrial AI with Pieter Abbeel - #476
19 april 2021 · 58 min
Today we’re joined by Pieter Abbeel, a Professor at UC Berkeley, co-Director of the Berkeley AI Research Lab (BAIR), as well as Co-founder and Chief Scientist at Covariant.
In our conversation with Pieter, we cover a ton of ground, starting with the specific goals and tasks of his work at Covariant, the shift in needs for industrial AI application and robots, if his experience solving real-world problems has changed his opinion on end to end deep learning, and the scope for the three problem domains of the models he’s building.
We also explore his recent work at the intersection of unsupervised and reinforcement learning, goal-directed RL, his recent paper “Pretrained Transformers as Universal Computation Engines” and where that research thread is headed, and of course, his new podcast Robot Brains, which you can find on all streaming platforms today!
The complete show notes for this episode can be found at twimlai.com/go/476. Lees meer -
AutoML for Natural Language Processing with Abhishek Thakur - #475
15 april 2021 · 36 min
Today we’re joined by Abhishek Thakur, a machine learning engineer at Hugging Face, and the world’s first Quadruple Kaggle Grandmaster!
In our conversation with Abhishek, we explore his Kaggle journey, including how his approach to competitions has evolved over time, what resources he used to prepare for his transition to a full-time practitioner, and the most important lessons he’s learned along the way.
We also spend a great deal of time discussing his new role at HuggingFace, where he's building AutoNLP. We talk through the goals of the project, the primary problem domain, and how the results of AutoNLP compare with those from hand-crafted models. Finally, we discuss Abhishek’s book, Approaching (Almost) Any Machine Learning Problem.
The complete show notes for this episode can be found at https://twimlai.com/go/475. Lees meer -
Inclusive Design for Seeing AI with Saqib Shaikh - #474
12 april 2021 · 36 min
Today we’re joined by Saqib Shaikh, a Software Engineer at Microsoft, and the lead for the Seeing AI Project.
In our conversation with Saqib, we explore the Seeing AI app, an app “that narrates the world around you.” We discuss the various technologies and use cases for the app, and how it has evolved since the inception of the project, how the technology landscape supports projects like this one, and the technical challenges he faces when building out the app.
We also the relationship and trust between humans and robots, and how that translates to this app, what Saqib sees on the research horizon that will support his vision for the future of Seeing AI, and how the integration of tech like Apple’s upcoming “smart” glasses could change the way their app is used.
The complete show notes for this episode can be found at twimlai.com/go/474. Lees meer -
Theory of Computation with Jelani Nelson - #473
8 april 2021 · 34 min
Today we’re joined by Jelani Nelson, a professor in the Theory Group at UC Berkeley.
In our conversation with Jelani, we explore his research in computational theory, where he focuses on building streaming and sketching algorithms, random projections, and dimensionality reduction. We discuss how Jelani thinks about the balance between the innovation of new algorithms and the performance of existing ones, and some use cases where we’d see his work in action.
Finally, we talk through how his work ties into machine learning, what tools from the theorist’s toolbox he’d suggest all ML practitioners know, and his nonprofit AddisCoder, a 4 week summer program that introduces high-school students to programming and algorithms.
The complete show notes for this episode can be found at twimlai.com/go/473. Lees meer -
Human-Centered ML for High-Risk Behaviors with Stevie Chancellor - #472
5 april 2021 · 41 min
Today we’re joined by Stevie Chancellor, an Assistant Professor in the Department of Computer Science and Engineering at the University of Minnesota.
In our conversation with Stevie, we explore her work at the intersection of human-centered computing, machine learning, and high-risk mental illness behaviors. We discuss how her background in HCC helps shapes her perspective, how machine learning helps with understanding severity levels of mental illness, and some recent work where convolutional graph neural networks are applied to identify and discover new kinds of behaviors for people who struggle with opioid use disorder.
We also explore the role of computational linguistics and NLP in her research, issues in using social media data being used as a data source, and finally, how people who are interested in an introduction to human-centered computing can get started.
The complete show notes for this episode can be found at twimlai.com/go/472. Lees meer -
Operationalizing AI at Dataiku with Conor Jensen - #471
1 april 2021 · 24 min
In this episode, we’re joined by Dataiku’s Director of Data Science, Conor Jensen. In our conversation, we explore the panel he lead at TWIMLcon “AI Operationalization: Where the AI Rubber Hits the Road for the Enterprise,” discussing the ML journey of each panelist’s company, and where Dataiku fits in the equation.
The complete show notes for this episode can be found at https://twimlai.com/go/471. Lees meer -
ML Lifecycle Management at Algorithmia with Diego Oppenheimer - #470
1 april 2021 · 26 min
In this episode, we’re joined by Diego Oppenheimer, Founder and CEO of Algorithmia. In our conversation, we discuss Algorithmia’s involvement with TWIMLcon, as well as an exploration of the results of their recently conducted survey on the state of the AI market.
The complete show notes for this episode can be found at twimlai.com/go/470. Lees meer -
End to End ML at Cloudera with Santiago Giraldo - #469 [TWIMLcon Sponsor Series]
29 maart 2021 · 22 min
In this episode, we’re joined by Santiago Giraldo, Director Of Product Marketing for Data Engineering & Machine Learning at Cloudera. In our conversation, we discuss Cloudera’s talks at TWIMLcon, as well as their various research efforts from their Fast Forward Labs arm.
The complete show notes for this episode can be found at twimlai.com/sponsorseries. Lees meer -
ML Platforms for Global Scale at Prosus with Paul van der Boor - #468 [TWIMLcon Sponsor Series]
29 maart 2021 · 22 min
In this episode, we’re joined by Paul van der Boor, Senior Director of Data Science at Prosus, to discuss his TWIMLcon experience and how they’re using ML platforms to manage machine learning at a global scale.
The complete show notes for this episode can be found at twimlai.com/sponsorseries. Lees meer -
Can Language Models Be Too Big? 🦜 with Emily Bender and Margaret Mitchell - #467
24 maart 2021 · 54 min
Today we’re joined by Emily M. Bender, Professor at the University of Washington, and AI Researcher, Margaret Mitchell.
Emily and Meg, as well as Timnit Gebru and Angelina McMillan-Major, are co-authors on the paper On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜. As most of you undoubtedly know by now, there has been much controversy surrounding, and fallout from, this paper. In this conversation, our main priority was to focus on the message of the paper itself. We spend some time discussing the historical context for the paper, then turn to the goals of the paper, discussing the many reasons why the ever-growing datasets and models are not necessarily the direction we should be going.
We explore the cost of these training datasets, both literal and environmental, as well as the bias implications of these models, and of course the perpetual debate about responsibility when building and deploying ML systems. Finally, we discuss the thin line between AI hype and useful AI systems, and the importance of doing pre-mortems to truly flesh out any issues you could potentially come across prior to building models, and much much more.
The complete show notes for this episode can be found at twimlai.com/go/467. Lees meer -
Applying RL to Real-World Robotics with Abhishek Gupta - #466
22 maart 2021 · 36 min
Today we’re joined by Abhishek Gupta, a PhD Student at UC Berkeley.
Abhishek, a member of the BAIR Lab, joined us to talk about his recent robotics and reinforcement learning research and interests, which focus on applying RL to real-world robotics applications. We explore the concept of reward supervision, and how to get robots to learn these reward functions from videos, and the rationale behind supervised experts in these experiments.
We also discuss the use of simulation for experiments, data collection, and the path to scalable robotic learning. Finally, we discuss gradient surgery vs gradient sledgehammering, and his ecological RL paper, which focuses on the “phenomena that exist in the real world” and how humans and robotics systems interface in those situations.
The complete show notes for this episode can be found at https://twimlai.com/go/466. Lees meer -
Accelerating Innovation with AI at Scale with David Carmona - #465
18 maart 2021 · 49 min
Today we’re joined by David Carmona, General Manager of Artificial Intelligence & Innovation at Microsoft.
In our conversation with David, we focus on his work on AI at Scale, an initiative focused on the change in the ways people are developing AI, driven in large part by the emergence of massive models. We explore David’s thoughts about the progression towards larger models, the focus on parameters and how it ties to the architecture of these models, and how we should assess how attention works in these models.
We also discuss the different families of models (generation & representation), the transition from CV to NLP tasks, and an interesting point of models “becoming a platform” via transfer learning.
The complete show notes for this episode can be found at twimlai.com/go/465. Lees meer -
Complexity and Intelligence with Melanie Mitchell - #464
15 maart 2021 · 33 min
Today we’re joined by Melanie Mitchell, Davis Professor at the Santa Fe Institute and author of Artificial Intelligence: A Guide for Thinking Humans.
While Melanie has had a long career with a myriad of research interests, we focus on a few, complex systems and the understanding of intelligence, complexity, and her recent work on getting AI systems to make analogies. We explore examples of social learning, and how it applies to AI contextually, and defining intelligence.
We discuss potential frameworks that would help machines understand analogies, established benchmarks for analogy, and if there is a social learning solution to help machines figure out analogy. Finally we talk through the overall state of AI systems, the progress we’ve made amid the limited concept of social learning, if we’re able to achieve intelligence with current approaches to AI, and much more!
The complete show notes for this episode can be found at twimlai.com/go/464. Lees meer -
Robust Visual Reasoning with Adriana Kovashka - #463
11 maart 2021 · 42 min
Today we’re joined by Adriana Kovashka, an Assistant Professor at the University of Pittsburgh.
In our conversation with Adriana, we explore her visual commonsense research, and how it intersects with her background in media studies. We discuss the idea of shortcuts, or faults in visual question answering data sets that appear in many SOTA results, as well as the concept of masking, a technique developed to assist in context prediction. Adriana then describes how these techniques fit into her broader goal of trying to understand the rhetoric of visual advertisements.
Finally, Adriana shares a bit about her work on robust visual reasoning, the parallels between this research and other work happening around explainability, and the vision for her work going forward.
The complete show notes for this episode can be found at twimlai.com/go/463. Lees meer -
Architectural and Organizational Patterns in Machine Learning with Nishan Subedi - #462
8 maart 2021 · 58 min
Today we’re joined by Nishan Subedi, VP of Algorithms at Overstock.com.
In our conversation with Nishan, we discuss his interesting path to MLOps and how ML/AI is used at Overstock, primarily for search/recommendations and marketing/advertisement use cases. We spend a great deal of time exploring machine learning architecture and architectural patterns, how he perceives the differences between architectural patterns and algorithms, and emergent architectural patterns that standards have not yet been set for.
Finally, we discuss how the idea of anti-patterns was innovative in early design pattern thinking and if those concepts are transferable to ML, if architectural patterns will bleed over into organizational patterns and culture, and Nishan introduces us to the concept of Squads within an organizational structure.
The complete show notes for this episode can be found at https://twimlai.com/go/462. Lees meer -
Common Sense Reasoning in NLP with Vered Shwartz - #461
4 maart 2021 · 37 min
Today we’re joined by Vered Shwartz, a Postdoctoral Researcher at both the Allen Institute for AI and the Paul G. Allen School of Computer Science & Engineering at the University of Washington.
In our conversation with Vered, we explore her NLP research, where she focuses on teaching machines common sense reasoning in natural language. We discuss training using GPT models and the potential use of multimodal reasoning and incorporating images to augment the reasoning capabilities.
Finally, we talk through some other noteworthy research in this field, how she deals with biases in the models, and Vered's future plans for incorporating some of the newer techniques into her future research.
The complete show notes for this episode can be found at https://twimlai.com/go/461. Lees meer -
How to Be Human in the Age of AI with Ayanna Howard - #460
1 maart 2021 · 36 min
Today we’re joined by returning guest and newly appointed Dean of the College of Engineering at The Ohio State University, Ayanna Howard.
Our conversation with Dr. Howard focuses on her recently released book, Sex, Race, and Robots: How to Be Human in the Age of AI, which is an extension of her research on the relationships between humans and robots. We continue to explore this relationship through the themes of socialization introduced in the book, like associating genders to AI and robotic systems and the “self-fulfilling prophecy” that has become search engines.
We also discuss a recurring conversation in the community around AI being biased because of data versus models and data, and the choices and responsibilities that come with the ethical aspects of building AI systems. Finally, we discuss Dr. Howard’s new role at OSU, how it will affect her research, and what the future holds for the applied AI field.
The complete show notes for this episode can be found at https://twimlai.com/go/460. Lees meer -
How to Be Human in the Age of AI with Ayanna Howard - #460
1 maart 2021 · 37 min
Today we’re joined by returning guest and newly appointed Dean of the College of Engineering at The Ohio State University, Ayanna Howard.
Our conversation with Dr. Howard focuses on her recently released book, Sex, Race, and Robots: How to Be Human in the Age of AI, which is an extension of her research on the relationships between humans and robots. We continue to explore this relationship through the themes of socialization introduced in the book, like associating genders to AI and robotic systems and the “self-fulfilling prophecy” that has become search engines.
We also discuss a recurring conversation in the community around AI being biased because of data versus models and data, and the choices and responsibilities that come with the ethical aspects of building AI systems. Finally, we discuss Dr. Howard’s new role at OSU, how it will affect her research, and what the future holds for the applied AI field.
The complete show notes for this episode can be found at https://twimlai.com/go/460. Lees meer -
Evolution and Intelligence with Penousal Machado - #459
25 februari 2021 · 57 min
Today we’re joined by Penousal Machado, Associate Professor and Head of the Computational Design and Visualization Lab in the Center for Informatics at the University of Coimbra.
In our conversation with Penousal, we explore his research in Evolutionary Computation, and how that work coincides with his passion for images and graphics. We also discuss the link between creativity and humanity, and have an interesting sidebar about the philosophy of Sci-Fi in popular culture.
Finally, we dig into Penousals evolutionary machine learning research, primarily in the context of the evolution of various animal species mating habits and practices.
The complete show notes for this episode can be found at twimlai.com/go/459. Lees meer -
Innovating Neural Machine Translation with Arul Menezes - #458
22 februari 2021 · 44 min
Today we’re joined by Arul Menezes, a Distinguished Engineer at Microsoft.
Arul, a 30 year veteran of Microsoft, manages the machine translation research and products in the Azure Cognitive Services group. In our conversation, we explore the historical evolution of machine translation like breakthroughs in seq2seq and the emergence of transformer models.
We also discuss how they’re using multilingual transfer learning and combining what they’ve learned in translation with pre-trained language models like BERT. Finally, we explore what they’re doing to experience domain-specific improvements in their models, and what excites Arul about the translation architecture going forward.
The complete show notes for this series can be found at twimlai.com/go/458. Lees meer -
Building the Product Knowledge Graph at Amazon with Luna Dong - #457
18 februari 2021 · 44 min
Today we’re joined by Luna Dong, Sr. Principal Scientist at Amazon.
In our conversation with Luna, we explore Amazon’s expansive product knowledge graph, and the various roles that machine learning plays throughout it. We also talk through the differences and synergies between the media and retail product knowledge graph use cases and how ML comes into play in search and recommendation use cases. Finally, we explore the similarities to relational databases and efforts to standardize the product knowledge graphs across the company and broadly in the research community.
The complete show notes for this episode can be found at https://twimlai.com/go/457. Lees meer -
Towards a Systems-Level Approach to Fair ML with Sarah M. Brown - #456
15 februari 2021 · 38 min
Today we’re joined by Sarah Brown, an Assistant Professor of Computer Science at the University of Rhode Island.
In our conversation with Sarah, whose research focuses on Fairness in AI, we discuss why a “systems-level” approach is necessary when thinking about ethical and fairness issues in models and algorithms. We also explore Wiggum: a fairness forensics tool, which explores bias and allows for regular auditing of data, as well as her ongoing collaboration with a social psychologist to explore how people perceive ethics and fairness.
Finally, we talk through the role of tools in assessing fairness and bias, and the importance of understanding the decisions the tools are making.
The complete show notes can be found at twimlai.com/go/456. Lees meer -
AI for Digital Health Innovation with Andrew Trister - #455
11 februari 2021 · 42 min
Today we’re joined by Andrew Trister, Deputy Director for Digital Health Innovation at the Bill & Melinda Gates Foundation.
In our conversation with Andrew, we explore some of the AI use cases at the foundation, with the goal of bringing “community-based” healthcare to underserved populations in the global south. We focus on COVID-19 response and improving the accuracy of malaria testing with a bayesian framework and a few others, and the challenges like scaling these systems and building out infrastructure so that communities can begin to support themselves.
We also touch on Andrew's previous work at Apple, where he helped develop what is now known as Research Kit, their ML for health tools that are now seen in apple devices like phones and watches.
The complete show notes for this episode can be found at https://twimlai.com/go/455 Lees meer -
System Design for Autonomous Vehicles with Drago Anguelov - #454
8 februari 2021 · 51 min
Today we’re joined by Drago Anguelov, Distinguished Scientist and Head of Research at Waymo.
In our conversation, we explore the state of the autonomous vehicles space broadly and at Waymo, including how AV has improved in the last few years, their focus on level 4 driving, and Drago’s thoughts on the direction of the industry going forward. Drago breaks down their core ML use cases, Perception, Prediction, Planning, and Simulation, and how their work has lead to a fully autonomous vehicle being deployed in Phoenix.
We also discuss the socioeconomic and environmental impact of self-driving cars, a few research papers submitted to NeurIPS 2020, and if the sophistication of AV systems will lend themselves to the development of tomorrow’s enterprise machine learning systems.
The complete show notes for this episode can be found at twimlai.com/go/454. Lees meer -
Building, Adopting, and Maturing LinkedIn's Machine Learning Platform with Ya Xu - #453
4 februari 2021 · 49 min
Today we’re joined by Ya Xu, head of Data Science at LinkedIn, and TWIMLcon: AI Platforms 2021 Keynote Speaker.
We cover a ton of ground with Ya, starting with her experiences prior to becoming Head of DS, as one of the architects of the LinkedIn Platform. We discuss her “three phases” (building, adoption, and maturation) to keep in mind when building out a platform, how to avoid “hero syndrome” early in the process.
Finally, we dig into the various tools and platforms that give LinkedIn teams leverage, their organizational structure, as well as the emergence of differential privacy for security use cases and if it's ready for prime time.
The complete show notes for this episode can be found at https://twimlai.com/go/453. Lees meer -
Expressive Deep Learning with Magenta DDSP w/ Jesse Engel - #452
1 februari 2021 · 39 min
Today we’re joined by Jesse Engel, Staff Research Scientist at Google, working on the Magenta Project.
In our conversation with Jesse, we explore the current landscape of creativity AI, and the role Magenta plays in helping express creativity through ML and deep learning. We dig deep into their Differentiable Digital Signal Processing (DDSP) library, which “lets you combine the interpretable structure of classical DSP elements (such as filters, oscillators, reverberation, etc.) with the expressivity of deep learning.”
Finally, Jesse walks us through some of the other projects that the Magenta team undertakes, including NLP and language modeling, and what he wants to see come out of the work that he and others are doing in creative AI research.
The complete show notes for this episode can be found at twimlai.com/go/452. Lees meer -
Semantic Folding for Natural Language Understanding with Francisco Weber - #451
29 januari 2021 · 55 min
Today we’re joined by return guest Francisco Webber, CEO & Co-founder of Cortical.io.
Francisco was originally a guest over 4 years and 400 episodes ago, where we discussed his company Cortical.io, and their unique approach to natural language processing. In this conversation, Francisco gives us an update on Cortical, including their applications and toolkit, including semantic extraction, classifier, and search use cases. We also discuss GPT-3, and how it compares to semantic folding, the unreasonable amount of data needed to train these models, and the difference between the GPT approach and semantic modeling for language understanding.
The complete show notes for this episode can be found at twimlai.com/go/451. Lees meer -
The Future of Autonomous Systems with Gurdeep Pall - #450
25 januari 2021 · 53 min
Today we’re joined by Gurdeep Pall, Corporate Vice President at Microsoft.
Gurdeep, who we had the pleasure of speaking with on his 31st anniversary at the company, has had a hand in creating quite a few influential projects, including Skype for business (and Teams) and being apart of the first team that shipped wifi as a part of a general-purpose operating system.
In our conversation with Gurdeep, we discuss Microsoft’s acquisition of Bonsai and how they fit in the toolchain for creating brains for autonomous systems with “machine teaching,” and other practical applications of machine teaching in autonomous systems. We also explore the challenges of simulation, and how they’ve evolved to make the problems that the physical world brings more tenable. Finally, Gurdeep shares concrete use cases for autonomous systems, and how to get the best ROI on those investments, and of course, what’s next in the very broad space of autonomous systems.
The complete show notes for this episode can be found at twimlai.com/go/450. Lees meer -
AI for Ecology and Ecosystem Preservation with Bryan Carstens - #449
21 januari 2021 · 36 min
Today we’re joined by Bryan Carstens, a professor in the Department of Evolution, Ecology, and Organismal Biology & Head of the Tetrapod Division in the Museum of Biological Diversity at The Ohio State University.
In our conversation with Bryan, who comes from a traditional biology background, we cover a ton of ground, including a foundational layer of understanding for the vast known unknowns in species and biodiversity, and how he came to apply machine learning to his lab’s research.
We explore a few of his lab’s projects, including applying ML to genetic data to understand the geographic and environmental structure of DNA, what factors keep machine learning from being used more frequently used in biology, and what’s next for his group.
The complete show notes for this episode can be found at twimlai.com/go/449. Lees meer -
Off-Line, Off-Policy RL for Real-World Decision Making at Facebook - #448
19 januari 2021 · 1 uur 2 min
Today we’re joined by Jason Gauci, a Software Engineering Manager at Facebook AI.
In our conversation with Jason, we explore their Reinforcement Learning platform, Re-Agent (Horizon). We discuss the role of decision making and game theory in the platform and the types of decisions they’re using Re-Agent to make, from ranking and recommendations to their eCommerce marketplace.
Jason also walks us through the differences between online/offline and on/off policy model training, and where Re-Agent sits in this spectrum. Finally, we discuss the concept of counterfactual causality, and how they ensure safety in the results of their models.
The complete show notes for this episode can be found at twimlai.com/go/448. Lees meer -
A Future of Work for the Invisible Workers in A.I. with Saiph Savage - #447
14 januari 2021 · 38 min
Today we’re joined by Saiph Savage, a Visiting professor at the Human-Computer Interaction Institute at CMU, director of the HCI Lab at WVU, and co-director of the Civic Innovation Lab at UNAM.
We caught up with Saiph during NeurIPS where she delivered an insightful invited talk “A Future of Work for the Invisible Workers in A.I.”. In our conversation with Saiph, we gain a better understanding of the “Invisible workers,” or the people doing the work of labeling for machine learning and AI systems, and some of the issues around lack of economic empowerment, emotional trauma, and other issues that arise with these jobs.
We discuss ways that we can empower these workers, and push the companies that are employing these workers to do the same. Finally, we discuss Saiph’s participatory design work with rural workers in the global south.
The complete show notes for this episode can be found at twimlai.com/go/447. Lees meer -
Trends in Graph Machine Learning with Michael Bronstein - #446
11 januari 2021 · 1 uur 14 min
Today we’re back with the final episode of AI Rewind joined by Michael Bronstein, a professor at Imperial College London and the Head of Graph Machine Learning at Twitter.
In our conversation with Michael, we touch on his thoughts about the year in Machine Learning overall, including GPT-3 and Implicit Neural Representations, but spend a major chunk of time on the sub-field of Graph Machine Learning.
We talk through the application of Graph ML across domains like physics and bioinformatics, and the tools to look out for. Finally, we discuss what Michael thinks is in store for 2021, including graph ml applied to molecule discovery and non-human communication translation. Lees meer -
Trends in Natural Language Processing with Sameer Singh - #445
7 januari 2021 · 1 uur 22 min
Today we continue the 2020 AI Rewind series, joined by friend of the show Sameer Singh, an Assistant Professor in the Department of Computer Science at UC Irvine.
We last spoke with Sameer at our Natural Language Processing office hours back at TWIMLfest, and was the perfect person to help us break down 2020 in NLP. Sameer tackles the review in 4 main categories, Massive Language Modeling, Fundamental Problems with Language Models, Practical Vulnerabilities with Language Models, and Evaluation.
We also explore the impact of GPT-3 and Transformer models, the intersection of vision and language models, and the injection of causal thinking and modeling into language models, and much more.
The complete show notes for this episode can be found at twimlai.com/go/445. Lees meer -
Trends in Computer Vision with Pavan Turaga - #444
4 januari 2021 · 1 uur 9 min
AI Rewind continues today as we’re joined by Pavan Turaga, Associate Professor in both the Departments of Arts, Media, and Engineering & Electrical Engineering, and the Interim Director of the School of Arts, Media, and Engineering at Arizona State University.
Pavan, who joined us back in June to talk through his work from CVPR ‘20, Invariance, Geometry and Deep Neural Networks, is back to walk us through the trends he’s seen in Computer Vision last year. We explore the revival of physics-based thinking about scenes, differential rendering, the best papers, and where the field is going in the near future.
We want to hear from you! Send your thoughts on the year that was 2020 below in the comments, or via Twitter at @samcharrington or @twimlai.
The complete show notes for this episode can be found at twimlai.com/go/444 Lees meer -
Trends in Reinforcement Learning with Pablo Samuel Castro - #443
30 december 2020 · 1 uur 27 min
Today we kick off our annual AI Rewind series joined by friend of the show Pablo Samuel Castro, a Staff Research Software Developer at Google Brain.
Pablo joined us earlier this year for a discussion about Music & AI, and his Geometric Perspective on Reinforcement Learning, as well our RL office hours during the inaugural TWIMLfest. In today’s conversation, we explore some of the latest and greatest RL advancements coming out of the major conferences this year, broken down into a few major themes, Metrics/Representations, Understanding and Evaluating Deep Reinforcement Learning, and RL in the Real World.
This was a very fun conversation, and we encourage you to check out all the great papers and other resources available on the show notes page. Lees meer -
MOReL: Model-Based Offline Reinforcement Learning with Aravind Rajeswaran - #442
28 december 2020 · 38 min
Today we close out our NeurIPS series joined by Aravind Rajeswaran, a PhD Student in machine learning and robotics at the University of Washington.
At NeurIPS, Aravind presented his paper MOReL: Model-Based Offline Reinforcement Learning. In our conversation, we explore model-based reinforcement learning, and if models are a “prerequisite” to achieve something analogous to transfer learning. We also dig into MOReL and the recent progress in offline reinforcement learning, the differences in developing MOReL models and traditional RL models, and the theoretical results they’re seeing from this research.
The complete show notes for this episode can be found at twimlai.com/go/442 Lees meer -
Machine Learning as a Software Engineering Enterprise with Charles Isbell - #441
23 december 2020 · 46 min
As we continue our NeurIPS 2020 series, we’re joined by friend-of-the-show Charles Isbell, Dean, John P. Imlay, Jr. Chair, and professor at the Georgia Tech College of Computing.
This year Charles gave an Invited Talk at this year’s conference, You Can’t Escape Hyperparameters and Latent Variables: Machine Learning as a Software Engineering Enterprise. In our conversation, we explore the success of the Georgia Tech Online Masters program in CS, which now has over 11k students enrolled, and the importance of making the education accessible to as many people as possible. We spend quite a bit speaking about the impact machine learning is beginning to have on the world, and how we should move from thinking of ourselves as compiler hackers, and begin to see the possibilities and opportunities that have been ignored.
We also touch on the fallout from Timnit Gebru being “resignated” and the importance of having diverse voices and different perspectives “in the room,” and what the future holds for machine learning as a discipline.
The complete show notes for this episode can be found at twimlai.com/go/441. Lees meer -
Natural Graph Networks with Taco Cohen - #440
21 december 2020 · 58 min
Today we kick off our NeurIPS 2020 series joined by Taco Cohen, a Machine Learning Researcher at Qualcomm Technologies.
In our conversation with Taco, we discuss his current research in equivariant networks and video compression using generative models, as well as his paper “Natural Graph Networks,” which explores the concept of “naturality, a generalization of equivariance” which suggests that weaker constraints will allow for a “wider class of architectures.”
We also discuss some of Taco’s recent research on neural compression and a very interesting visual demo for equivariance CNNs that Taco and the Qualcomm team released during the conference.
The complete show notes for this episode can be found at twimlai.com/go/440. Lees meer -
Productionizing Time-Series Workloads at Siemens Energy with Edgar Bahilo Rodriguez - #439
18 december 2020 · 41 min
Today we close out our re:Invent series joined by Edgar Bahilo Rodriguez, Lead Data Scientist in the industrial applications division of Siemens Energy.
Edgar spoke at this year's re:Invent conference about Productionizing R Workloads, and the resurrection of R for machine learning and productionalization. In our conversation with Edgar, we explore the fundamentals of building a strong machine learning infrastructure, and how they’re breaking down applications and using mixed technologies to build models.
We also discuss their industrial applications, including wind, power production management, managing systems intent on decreasing the environmental impact of pre-existing installations, and their extensive use of time-series forecasting across these use cases.
The complete show notes can be found at twimlai.com/go/439. Lees meer -
ML Feature Store at Intuit with Srivathsan Canchi - #438
16 december 2020 · 41 min
Today we continue our re:Invent series with Srivathsan Canchi, Head of Engineering for the Machine Learning Platform team at Intuit.
As we teased earlier this week, one of the major announcements coming from AWS at re:Invent was the release of the SageMaker Feature Store. To our pleasant surprise, we came to learn that our friends at Intuit are the original architects of this offering and partnered with AWS to productize it at a much broader scale. In our conversation with Srivathsan, we explore the focus areas that are supported by the Intuit machine learning platform across various teams, including QuickBooks and Mint, Turbotax, and Credit Karma, and his thoughts on why companies should be investing in feature stores.
We also discuss why the concept of “feature store” has seemingly exploded in the last year, and how you know when your organization is ready to deploy one. Finally, we dig into the specifics of the feature store, including the popularity of graphQL and why they chose to include it in their pipelines, the similarities (and differences) between the two versions of the store, and much more!
The complete show notes for this episode can be found at twimlai.com/go/438. Lees meer -
re:Invent Roundup 2020 with Swami Sivasubramanian - #437
14 december 2020 · 49 min
Today we’re kicking off our annual re:invent series joined by Swami Sivasubramanian, VP of Artificial Intelligence, at AWS.
During re:Invent last week, Amazon made a ton of announcements on the machine learning front, including quite a few advancements to SageMaker. In this roundup conversation, we discuss the motivation for hosting the first-ever machine learning keynote at the conference, a bunch of details surrounding tools like Pipelines for workflow management, Clarify for bias detection, and JumpStart for easy to use algorithms and notebooks, and many more.
We also discuss the emphasis placed on DevOps and MLOps tools in these announcements, and how the tools are all interconnected. Finally, we briefly touch on the announcement of the AWS feature store, but be sure to check back later this week for a more in-depth discussion on that particular release!
The complete show notes for this episode can be found at twimlai.com/go/437. Lees meer -
Predictive Disease Risk Modeling at 23andMe with Subarna Sinha - #436
11 december 2020 · 40 min
Today we’re joined by Subarna Sinha, Machine Learning Engineering Leader at 23andMe.
23andMe handles a massive amount of genomic data every year from its core ancestry business but also uses that data for disease prediction, which is the core use case we discuss in our conversation.
Subarna talks us through an initial use case of creating an evaluation of polygenic scores, and how that led them to build an ML pipeline and platform. We talk through the tools and tech stack used for the operationalization of their platform, the use of synthetic data, the internal pushback that came along with the changes that were being made, and what’s next for her team and the platform.
The complete show notes for this episode can be found at twimlai.com/go/436. Lees meer -
Scaling Video AI at RTL with Daan Odijk - #435
9 december 2020 · 40 min
Today we’re joined by Daan Odijk, Data Science Manager at RTL.
In our conversation with Daan, we explore the RTL MLOps journey, and their need to put platform infrastructure in place for ad optimization and forecasting, personalization, and content understanding use cases. Daan walks us through some of the challenges on both the modeling and engineering sides of building the platform, as well as the inherent challenges of video applications.
Finally, we discuss the current state of their platform, and the benefits they’ve seen from having this infrastructure in place, and why using building a custom platform was worth the investment.
The complete show notes for this episode can be found at twimlai.com/go/435. Lees meer -
Benchmarking ML with MLCommons w/ Peter Mattson - #434
7 december 2020 · 46 min
Today we’re joined by Peter Mattson, General Chair at MLPerf, a Staff Engineer at Google, and President of MLCommons.
In our conversation with Peter, we discuss MLCommons and MLPerf, the former an open engineering group with the goal of accelerating machine learning innovation, and the latter a set of standardized Machine Learning speed benchmarks used to measure things like model training speed, throughput speed for inference.
We explore the target user for the MLPerf benchmarks, the need for benchmarks in the ethics, bias, fairness space, and how they’re approaching this through the "People’s Speech" datasets. We also walk through the MLCommons best practices of getting a model into production, why it's so difficult, and how MLCube can make the process easier for researchers and developers.
The complete show notes page for this episode can be found at twimlai.com/go/434. Lees meer