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08:49

TensorFlow Serving performance optimization

Wei Wei, Developer Advocate at Google, shares general principles and best practices to improve TensorFlow Serving performance. He discusses how to improve the latency for API surfaces, batching, and more parameters that you can tune. Resources: TensorFlow Serving performance guide → https://goo.gle/3zW168E Profile Inference Requests with TensorBoard → https://goo.gle/3zWjluJ TensorFlow Serving batching configuration → https://goo.gle/3xT2SVz […]
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21:17

[ML News] AI models that write code (Copilot, CodeWhisperer, Pangu-Coder, etc.)

#mlnews #ai #copilot OUTLINE: 0:00 – Intro 0:20 – Copilot Now Generally Available 3:20 – FOSS Org leaves GitHub 6:45 – Google’s Internal ML Code Completion 9:10 – AI Trains Itself to Code Better 14:30 – Amazon CodeWhisperer in Preview 15:15 – Pangu-Coder: A New Coding Model 17:10 – Useful Things References: Copilot Now Generally […]
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07:27

Advanced features on TensorFlow Serving

Wei Wei, Developer Advocate at Google, shares several advanced TensorFlow Serving features (experimental). Learn how TF Serving can tend JAX models, serve non-TensorFlow models with new servables, and remotely predict RPC with distributed serving. Resources: TF Serving model server parameters → https://goo.gle/3tQ99Qq Intro to JAX: Accelerating Machine Learning research → https://goo.gle/3xOKBsq Convert JAX models to […]
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40:26

Causal Conceptions of Fairness and their Consequences with Sharad Goel – #586

Today we close out our ICML 2022 coverage joined by Sharad Goel, a professor of public policy at Harvard University. In our conversation with Sharad, we discuss his Outstanding Paper award winner Causal Conceptions of Fairness and their Consequences, which seeks to understand what it means to apply causality to the idea of fairness in […]
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56:01

The Evolution of Machine Learning Platforms at Facebook (Webcast)

ML has several applications for businesses, but Meta – the world’s largest social network – is implementing it in nearly every part of its platform. Their internal ML platform FBLearner Flow is able to personalize news feeds, rank search results, filter out offensive content, and much more, and has become one of Meta’s most widely […]
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49:28

Brain-Inspired Hardware and Algorithm Co-Design with Melika Payvand – #585

Today we continue our ICML coverage joined by Melika Payvand, a research scientist at the Institute of Neuroinformatics at the University of Zurich and ETH Zurich. Melika spoke at the Hardware Aware Efficient Training (HAET) Workshop, delivering a keynote on Brain-inspired hardware and algorithm co-design for low power online training on the edge. In our […]
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08:18

Two Minute Papers: Google’s Parti AI: Magical Results! 💫

❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambdalabs.com/papers 📝 The paper “Google Parti: Pathways Autoregressive Text-to-Image model” is available here: https://parti.research.google/ 4 of my favorite prompts from the video (add these to benchmarks if you feel like it): – surprised scholars looking at a magical parchment emitting magic dust high […]
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05:51

TensorFlow Serving client examples

Wei Wei, Developer Advocate at Google, walks through how to send REST and gRPC prediction requests to TensorFlow serving backend with Python and C++. Don’t worry if your client uses another language, below there are new sets of codelabs covering web, Android, Flutter, and iOS frontends. Codelabs Image Classification with TensorFlow Serving (Web) → https://goo.gle/3tQfqMb […]
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06:34

Deploying production ML models with TensorFlow Serving overview

Wei Wei, Developer Advocate at Google, overviews deploying ML models into production with TensorFlow Serving, a framework that makes it easy to serve the production ML models with low latency and high throughput. Learn how to start a TF Serving model server and send POST requests using the command line tool. Wei covers what it […]
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44:23

Equivariant Priors for Compressed Sensing with Arash Behboodi – #584

Today we’re joined by Arash Behboodi, a machine learning researcher at Qualcomm Technologies. In our conversation with Arash, we explore his paper Equivariant Priors for Compressed Sensing with Unknown Orientation, which proposes using equivariant generative models as a prior means to show that signals with unknown orientations can be recovered with iterative gradient descent on […]
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01:03:48

SingularityNET: Ambassador Townhall Meeting #10 | July 12th 2022

Miro board with notes: https://miro.com/app/board/uXjVO0WVUBA=/ Meeting slides: https://docs.google.com/presentation/d/1TIJXrFGrNLJ6q4esILH9q-vCeiupWnKbm7DosbBPG_g/ Dework: https://app.dework.xyz/singularitynet-ambas/ GitBook: https://snet-ambassadors.gitbook.io/home/ The next Town Hall meeting will be going live and recorded on July 19th, at 18:00 UTC, on our Discord. To join upcoming ambassador meetings, please make sure that you’re part of our Discord community! Discord: https://discord.gg/snet Special thanks to those who joined […]
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53:32

Managing Data Labeling Ops for Success with Audrey Smith – #583

Today we continue our Data-Centric AI Series joined by Audrey Smith, the COO at MLtwist, and a recent participant in our panel on DCAI. In our conversation, we do a deep dive into data labeling for ML, exploring the typical journey for an organization to get started with labeling, her experience when making decisions around […]
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51:25

Engineering A ML-Powered Developer-First Search Engine with Richard Socher – #582

Today we’re joined by Richard Socher, the CEO of You.com. In our conversation with Richard, we explore the inspiration and motivation behind the You.com search engine, and how it differs from the traditional google search engine experience. We discuss some of the various ways that machine learning is used across the platform including how they […]
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01:23:41

SingularityNET: Ambassador Townhall Meeting #9 | July 5th 2022

Miro board with notes: https://miro.com/app/board/uXjVO0WVUBA=/ Slides: https://docs.google.com/presentation/d/1JKE2Mh6YTL9et6_IN1Fo9GPT2ZWZZE7SnlZy7QRqe08/edit?usp=sharing Dework: app.dework.xyz/singularitynet-ambas GitBook: https://snet-ambassadors.gitbook.io/home/ The next Town Hall meeting will be July 12th, 18UTC. Special thanks to those who joined live! —- SingularityNET is a decentralized marketplace for artificial intelligence. We aim to create the world’s global brain with a full-stack AI solution powered by a decentralized protocol. […]
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10
44:03

SingularityNET: Ambassador Townhall Meeting #8 | June 30th 2022

Miro board with notes: https://miro.com/app/board/uXjVO0WVUBA=/ Slides: https://docs.google.com/presentation/d/19UPn8iCDJ3nv1lFvQMiZIjyfu11QXVO-dDqpZ9gisXY/edit?usp=sharing Dework: app.dework.xyz/singularitynet-ambas GitBook: https://snet-ambassadors.gitbook.io/home/ The next Town Hall meeting will be July 5th, 18UTC. Special thanks to those who joined live! —- SingularityNET is a decentralized marketplace for artificial intelligence. We aim to create the world’s global brain with a full-stack AI solution powered by a decentralized protocol. […]
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54:45

On The Path Towards Robot Vision with Aljosa Osep – #581

Today we wrap up our coverage of the 2022 CVPR conference joined by Aljosa Osep, a postdoc at the Technical University of Munich & Carnegie Mellon University. In our conversation with Aljosa, we explore his broader research interests in achieving robot vision, and his vision for what it will look like when that goal is […]
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01:02:31

Data-Centric AI: Why This Trend Is Here To Stay (Panel)

To scale AI solutions across nearly every industry, data quality becomes increasingly important. With a data-centric approach, industries that aren’t typically synonymous with AI-driven applications can use AI to drive innovation because of excellent data collection, labeling, and transformation. In this discussion, we explore how data scientists and ML/AI practitioners can use data-centric AI to […]
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114
08:09

What have AI language models learned?

AI and ML researchers developed Large Language Models (LLMs) like BERT to help machines interact with natural language, improving their abilities in tasks like chat and translation! Nithum Thain, Senior Software Engineer at Google PAIR, highlights the Explorable “What Have Language Models Learned” by Adam Pearce and shares what we can learn about BERT by […]
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51:04

More Language, Less Labeling with Kate Saenko – #580

Today we continue our CVPR series joined by Kate Saenko, an associate professor at Boston University and a consulting professor for the MIT-IBM Watson AI Lab. In our conversation with Kate, we explore her research in multimodal learning, which she spoke about at the Multimodal Learning and Applications Workshop, one of a whopping 6 workshops […]
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08:40

Two Minute Papers: Google AI Simulates Evolution On A Computer! 🦖

❤️ Check out Weights & Biases and sign up for a free demo here: https://wandb.com/papers ❤️ Their mentioned post is available here (Thank you Soumik Rakshit!): https://wandb.me/modern-evolution 📝 The paper “Modern Evolution Strategies for Creativity: Fitting Concrete Images and Abstract Concepts” is available here: https://es-clip.github.io/ 🧑‍🎨 My previous genetic algorithm implementation for the Mona Lisa […]
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01:33:07

SingularityNET: Ambassador Townhall Meeting #7 | June 21st 2022

Miro board with notes: https://miro.com/app/board/uXjVO0WVUBA=/ Slides: https://docs.google.com/presentation/d/1aMCU8n6qOTreuFFpJDYonn2UkBZ9M95CGxZsvHkLHMI/edit?usp=sharing Dework: app.dework.xyz/singularitynet-ambas GitBook: https://snet-ambassadors.gitbook.io/home/ The next Town Hall meeting will be June 28st, 18UTC. Special thanks to those who joined live! —- SingularityNET is a decentralized marketplace for artificial intelligence. We aim to create the world’s global brain with a full-stack AI solution powered by a decentralized protocol. […]