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13:26

EAGER IN PRODUCTION | MICHAEL SUO

With TorchScript, PyTorch provides ease-of-use and flexibility in eager mode, while seamlessly transitioning to graph mode for speed, optimization, and functionality in C++ runtime environments. In this talk, Michael Suo (Software Engineer, Meta AI) covers our journey enabling PyTorch eager mode execution in production at Meta. He’ll also discuss the technical challenges involved in packaging, […]
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11:20

RADIOLOGY AI @MARS VETERINARY HEALTH | MICHAEL FITZKE

The global veterinary imaging market size was valued at 2.01 billion in 2018 and increase in utilization for veterinary diagnostics is expected to be driven largely by rising demand for pet insurance and growing animal healthcare expenditure, increasing companion animal population, and growth in the number of veterinary practitioners globally. Currently, while medical imaging use […]
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16:15

SingularityNET: About the Intricacy of Tasks – AGI-21 Conference Contributed Talks

—- 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. We gathered the leading minds in machine learning and blockchain to democratize access to AI technology. Now anyone can take advantage of a global network of AI algorithms, […]
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05:09

SingularityNET: Pathform – The 🔟th installment in the SingularityNET Ecosystem update series

Blog: https://blog.singularitynet.io/trueagi-singularitynet-ecosystem-roadmap-end-of-year-review-series-10-5ed9251839bb Newsletter Website: http://pathform.io/pathform Pathform aims to uplift human consciousness globally by developing and mapping Precision Consciousness – targeted, personalized micro-interventions – and from that space, facilitating collaboratively co-created understanding and solutions to the most pressing global issues. The Pathform app is being designed to utilize SingularityNET AI services, increasing platform API calls, and […]
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05:01

SingularityNET: Catalyst Fund7 Proposal | Ethical AI

Ethical AI, Catalyst Fund7 Proposal – Problem Statement: AI and Machine Learning systems have well-know problems stemming from hidden biases and prejudices. How to address these ethical problems? Solution: We will deploy data sets for machine learning, neural nets and Bayesian nets that (1) identify biases and (2) teach ethical standards. Cardano Full Proposal: https://cardano.ideascale.com/a/dtd/Ethical-AI-for-Singularity-Cardano/382631-48088 […]
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04:29

SingularityNET: 2021 Year End Update – Blockchain and Smart Contract Team, Sridhar Kolapalli

Blog: https://blog.singularitynet.io/part-1-singularitynet-2021-year-end-update-and-a-sneak-peak-at-q1-2022-72110777b757 SingularityNET’s outstanding blockchain team creates secure and efficient smart contracts for the SingularityNET ecosystem (Platform, Marketplace, and Spin-Off Project blockchain interactions). The team designs contracts that minimize friction and maximize blockchain capability. This team’s function is growing increasingly important and complex as SingularityNET becomes truly multi-chain. —- SingularityNET is a decentralized marketplace for […]
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24:19

A friendly introduction to distributed training (ML Tech Talks)

Google Cloud Developer Advocate Nikita Namjoshi introduces how distributed training models can dramatically reduce machine learning training times, explains how to make use of multiple GPUs with Data Parallelism vs Model Parallelism, and explores Synchronous vs Asynchronous Data Parallelism. Mesh TensorFlow → https://goo.gle/3sFPrHw Distributed Training with Keras tutorial → https://goo.gle/3FE6QEa GCP Reduction Server Blog → […]
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29:30

SingularityNET: AI Future by Vladimir Smolin – AGI-21 Conference Contributed Talks

—- 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. We gathered the leading minds in machine learning and blockchain to democratize access to AI technology. Now anyone can take advantage of a global network of AI algorithms, […]
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54:42

TWiML & AI x Fast.ai Machine Learning Study Group – Session 3 – October 21, 2018

**SUBSCRIBE AND TURN ON NOTIFICATIONS** **twimlai.com** This video is a recap of our Fast.ai x TWiML Online Machine Learning Study Group. In this session, we review Lesson 3, Performance, Validation and Model Interpretation. It’s not too late to join the study group. Just follow these simple steps: 1. Sign up for the TWiML Online Meetup, […]
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05:22

SingularityNET: Catalyst Fund7 Proposal | MUSEVERSE: AI bridge to Metaverse

MUSEVERSE: AI bridge to Metaverse, Catalyst Fund7 Proposal – Problem Statement: There is no existing Music platform combining AI and the Metaverse worlds powered by SingularityNET and Cardano blockchains. Solution: We are building a decentralised Music platform on Cardano by using the interactive power of the Metaverse integrated on AI & SingularityNet. Cardano Full Proposal: […]
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09:12

Self-Driving Cars – Lecture 11.4 (Object Tracking: Holistic Scene Understanding)

Lecture: Self-Driving Cars (Prof. Andreas Geiger, University of Tübingen) Course Website with Slides, Lecture Notes, Problems and Solutions: https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/autonomous-vision/lectures/self-driving-cars/ Source of this “Tübingen Machine Learning” AI Video
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26:44

How to Code RL Agents Like DeepMind

DeepMind is known for leading the way in deep reinforcement learning research. Creating novel agents to conquer the most advanced environments requires the use of some sophisticated infrastructure. Fortunately for us mere mortals, they’ve open sourced their framework for designing deep reinforcement learning agents: ACME. In ACME, you’ll find everything from deep Q learning all […]
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05:11

SingularityNET: Catalyst Fund7 Proposal | NuNet: Decentralized SPO Computing

NuNet: Decentralized SPO Computing, Catalyst Fund7 Proposal – Problem Statement: How to increase the decentralization & resilience of the Cardano network and reduce reliance on big tech cloud on the hardware level? Solution: NuNet will enable SPOs to run computing workflows on community provisioned hardware, increasing resilience and aiding decentralization. Cardano Full Proposal: https://cardano.ideascale.com/a/dtd/NuNet-Decentralized-SPO-Computing/383862-48088 Additional […]
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33:20

Self-Driving Cars – Lecture 11.2 (Object Tracking: Filtering)

Lecture: Self-Driving Cars (Prof. Andreas Geiger, University of Tübingen) Course Website with Slides, Lecture Notes, Problems and Solutions: https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/autonomous-vision/lectures/self-driving-cars/ Source of this “Tübingen Machine Learning” AI Video
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01:51:49

SingularityNET: OpenNARS for Applications Overview & Hands on and Demonstration – Peter lsaev & Patrick Hammer

The AGI Society has organised its 13th Artificial General Intelligence Conference this year online. The AGI conference series is the only major conference series devoted wholly and specifically to the creation of AI systems possessing general intelligence at the human level and ultimately beyond. By gathering together active researchers in the field, for presentation of […]
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27:45

Self-Driving Cars – Lecture 9.3 (Reconstruction and Motion: Optical Flow)

Lecture: Self-Driving Cars (Prof. Andreas Geiger, University of Tübingen) Course Website with Slides, Lecture Notes, Problems and Solutions: https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/autonomous-vision/lectures/self-driving-cars/ Source of this “Tübingen Machine Learning” AI Video
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09:20

Self-Driving Cars – Lecture 10.2 (Object Detection: Performance Evaluation)

Lecture: Self-Driving Cars (Prof. Andreas Geiger, University of Tübingen) Course Website with Slides, Lecture Notes, Problems and Solutions: https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/autonomous-vision/lectures/self-driving-cars/ Source of this “Tübingen Machine Learning” AI Video