Proactive Agents for the Web with Devi Parikh - #756

Proactive Agents for the Web with Devi Parikh - #756

Today, we're joined by Devi Parikh, co-founder and co-CEO of Yutori, to discuss browser use models and a future where we interact with the web through proactive, autonomous agents. We explore the technical challenges of creating reliable web agents, the advantages of visually-grounded models that operate on screenshots rather than the browser’s more brittle document object model, or DOM, and why this counterintuitive choice has proven far more robust and generalizable for handling complex web interfaces. Devi also shares insights into Yutori’s training pipeline, which has evolved from supervised fine-tuning to include rejection sampling and reinforcement learning. Finally, we discuss how Yutori’s “Scouts” agents orchestrate multiple tools and sub-agents to handle complex queries, the importance of background, "ambient" operation for these systems, and what the path looks like from simple monitoring to full task automation on the web. The complete show notes for this episode can be found at https://twimlai.com/go/756.

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Empathy in AI with Rob Walker - TWiML Talk #248

Empathy in AI with Rob Walker - TWiML Talk #248

Today we’re joined by Rob Walker, Vice President of Decision Management at Pegasystems. Rob joined us back in episode 127 to discuss “Hyperpersonalizing the customer experience.” Today, he’s back for a discussion about the role of empathy in AI systems. In our conversation, we dig into the role empathy plays in consumer-facing human-AI interactions, the differences between empathy and ethics, and a few examples of ways empathy should be considered when enterprise AI systems.

5 Apr 201940min

Benchmarking Custom Computer Vision Services at Urban Outfitters with Tom Szumowski - TWiML Talk #247

Benchmarking Custom Computer Vision Services at Urban Outfitters with Tom Szumowski - TWiML Talk #247

Today we’re joined by Tom Szumowski, Data Scientist at URBN, parent company of Urban Outfitters and other consumer fashion brands. Tom and I caught up to discuss his project “Exploring Custom Vision Services for Automated Fashion Product Attribution.” We look at the process Tom and his team took to build custom attribution models, and the results of their evaluation of various custom vision APIs for this purpose, with a focus on the various roadblocks and lessons he and his team encountered along the

3 Apr 201950min

Pragmatic Quantum Machine Learning with Peter Wittek - TWiML Talk #245

Pragmatic Quantum Machine Learning with Peter Wittek - TWiML Talk #245

Today we’re joined by Peter Wittek, Assistant Professor at the University of Toronto working on quantum-enhanced machine learning and the application of high-performance learning algorithms. In our conversation, we discuss the current state of quantum computing, a look ahead to what the next 20 years of quantum computing might hold, and how current quantum computers are flawed. We then dive into our discussion on quantum machine learning, and Peter’s new course on the topic, which debuted in Februar

1 Apr 20191h 5min

*Bonus Episode* A Quantum Machine Learning Algorithm Takedown with Ewin Tang - TWiML Talk #246

*Bonus Episode* A Quantum Machine Learning Algorithm Takedown with Ewin Tang - TWiML Talk #246

In this special bonus episode of the podcast, I’m joined by Ewin Tang, a PhD student in the Theoretical Computer Science group at the University of Washington. In our conversation, Ewin and I dig into her paper “A quantum-inspired classical algorithm for recommendation systems,” which took the quantum computing community by storm last summer. We haven’t called out a Nerd-Alert interview in a long time, but this interview inspired us to dust off that designation, so get your notepad ready!

1 Apr 201940min

Supporting TensorFlow at Airbnb with Alfredo Luque - TWiML Talk #244

Supporting TensorFlow at Airbnb with Alfredo Luque - TWiML Talk #244

Today we're joined by Alfredo Luque, a software engineer on the machine infrastructure team at Airbnb. If you’re interested in AI Platforms and ML infrastructure, you probably remember my interview with Airbnb’s Atul Kale, in which we discussed their Bighead platform. In my conversation with Alfredo, we dig a bit deeper into Bighead’s support for TensorFlow, discuss a recent image categorization challenge they solved with the framework, and explore what the new 2.0 release means for their users.

28 Mars 201940min

Mining the Vatican Secret Archives with TensorFlow w/ Elena Nieddu - TWiML Talk #243

Mining the Vatican Secret Archives with TensorFlow w/ Elena Nieddu - TWiML Talk #243

Today we’re joined by Elena Nieddu, Phd Student at Roma Tre University, who presented on her project “In Codice Ratio” at the TF Dev Summit. In our conversation, Elena provides an overview of the project, which aims to annotate and transcribe Vatican secret archive documents via machine learning. We discuss the many challenges associated with transcribing this vast archive of handwritten documents, including overcoming the high cost of data annotation.

27 Mars 201943min

Exploring TensorFlow 2.0 with Paige Bailey - TWiML Talk #242

Exploring TensorFlow 2.0 with Paige Bailey - TWiML Talk #242

Today we're joined by Paige Bailey, TensorFlow developer advocate at Google, to discuss the TensorFlow 2.0 alpha release. Paige and I talk through the latest TensorFlow updates, including the evolution of the TensorFlow APIs and the role of eager mode, tf.keras and tf.function, the evolution of TensorFlow for Swift and its inclusion in the new fast.ai course, new updates to TFX (or TensorFlow Extended), Google’s end-to-end ML platform, the emphasis on community collaboration with TF 2.0, and more.

25 Mars 201939min

Privacy-Preserving Decentralized Data Science with Andrew Trask - TWiML Talk #241

Privacy-Preserving Decentralized Data Science with Andrew Trask - TWiML Talk #241

Today we’re joined by Andrew Trask, PhD student at the University of Oxford and Leader of the OpenMined Project, an open-source community focused on researching, developing, and promoting tools for secure, privacy-preserving, value-aligned artificial intelligence. We dig into why OpenMined is important, exploring some of the basic research and technologies supporting Private, Decentralized Data Science, including ideas such as Differential Privacy,and Secure Multi-Party Computation.

21 Mars 201933min

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