AWS re:Invent 2022 – Keynote with Dr. Werner Vogels
Dr. Werner Vogels, Amazon.com VP and CTO, talks about the benefits of building asynchronous, loosely coupled systems and how event-driven architecture enables global scale. He then explains how the cloud is enabling customers to build more immersive experiences using 3D and how simulation is empowering customers to experiment and innovate in new ways.
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OpenAI’s New AI: Video Game Addict No More! 🤖
Two Minute Papers cover the paper “Efficient Training of Language Models to Fill in the Middle” in the following video.
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Guido van Rossum on Python 4.0
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Frank
- December 4, 2022
- AI
- ai clips
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- artificial intelligence
- artificial intelligence podcast
- Computer Science
- Consciousness
- Deep Learning
- einstein
- Elon Musk
- engineering
- friedman
- Guido van Rossum
- Joe Rogan
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- Lex Fridman
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Lex Fridman interviews Guido van Rossum, the creator of Python programming language.
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100+ JavaScript Concepts you Need to Know
The ultimate 10 minute JavaScript course that quickly breaks down over 100 key concepts every web developer should know. Learn the basics of JS and start building apps on the web, mobile, desktop, and more.
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Manu Parbhakar, AWS & Joel Jackson, Red Hat | AWS re:Invent 2022
Manu Parbhakar, Global Lead, Stategic Alliances at AWS & Joel Jackson, VP, Worldwide Technology Sales and GTM at Red Hat, join theCUBE at AWS re:Invent 2022 in Las Vegas, NV.
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Chuck Svoboda, Red Hat & Ted Stanton, AWS | AWS re:Invent 2022
Chuck Svoboda, Senior Director Cloud Services, GTM at Red Hat & Ted Stanton, Global Head of Sales, Red Hat & IBM, at AWS, join theCUBE at AWS re:Invent 2022 in Las Vegas, NV.
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Custom Training Question Answer Model Using Transformer BERT
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Frank
- December 4, 2022
- bert for question answering huggingface
- bert question answering github
- fine tune bert for question answering pytorch
- huggingface fine tune bert
- huggingface question answering tutorial
- krish naik deep learning
- krish naik machine learning
- question answering model using bert
- simple transformers question answering
- xlnet question answering github
The Simpletransformer library is based on the Transformers library by HuggingFace. Simple Transformers lets you quickly train and evaluate Transformer models. Only 3 lines of code are needed to initialize a model, train the model, and evaluate a model!
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Can the Same Net Fold into Two Shapes?
Stand up maths has some origami kind of fun.
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