OpenAI Codex: Just Say What You Want! 🤖
Two Minutes Papers examines the paper “Evaluating Large Language Models Trained on Code” in the following video.
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First look at OpenAI Codex
In this video, Ania Kubow shares her insights into OpenAI Codex beta version, and how she built an entire website using only 152 spoken words.
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Data Science with OpenAI Codex
This video has no audio, but it will leave you speechless as OpenAI Codex converts natural language into code. Data Science may never be the same. No tags,
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Do Neural Networks Think Like Our Brain?
Two Minute Papers examines the paper “Multimodal Neurons in Artificial Neural Networks.”
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How to Accelerate Innovation with AI at Scale
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Frank
- November 24, 2020
- AI model
- Azure
- Azure AI
- Azure HPC
- Chris Berner
- Cloud
- edge containers
- gpt-3
- High Performance Computing
- hybrid
- in depth artificial intelligence system
- inferencing
- intelligent cloud
- Intelligent edge
- Machine Learning
- Microsoft
- model training
- next gen ai systems
- Nidhi Chappell
- NLP
- OpenAI
- Scale
Did you ever wonder how much further AI can scale? In this session, Nidhi Chappell (Head of Product, Specialized Azure Compute at Microsoft) and Christopher Berner (Head of Compute at OpenAI) share their perspectives and insight about how the Microsoft-OpenAI partnership is taking significant steps to eliminate the barriers of scale to AI processes. Of […]
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GPT-3 vs Human Brain
GPT-3 has 175 billion parameters/synapses and produces astonishing results. Human brain has 100 trillion synapses. How much will it cost to train a language model the size of the human brain? Lex Fridman works through the math.
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14 Cool Apps Built on OpenAI’s GPT-3 API
Bakz T. Future shows off 14 Cool applications built on top of OpenAI’s GPT-3 (general purpose transformer) API (currently in private beta).
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GPT-3: Language Models are Few-Shot Learners
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Frank
- June 2, 2020
- AI
- artificial intelligence
- Arxiv
- attention
- autoregressive
- Bert
- boolq
- common crawl
- context
- corpus
- deep language
- Deep Learning
- explained
- Few Shot
- glue
- GPT-2
- gpt-3
- gpt2
- gpt3
- heads
- language model
- Machine Learning
- Math
- Microsoft
- mlm
- Natural Language Processing
- natural questions
- Neural Networks
- news
- NLP
- OpenAI
- Paper
- preplexity
- question answering
- sota
- strings
- superglue
- training data
- Transformers
- turing
- Wikipedia
- zero shot
How far can you go with ONLY language modeling? Can a large enough language model perform NLP task out of the box? OpenAI take on these and other questions by training a transformer that is an order of magnitude larger than anything that has ever been built before and the results are astounding. Yannic Kilcher […]
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OpenAI Model Generates Python Code
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Frank
- June 1, 2020
- AI
- arguments
- artificial intelligence
- Arxiv
- Build
- Code
- code completion
- completion
- Dataset
- Deep Learning
- docstring
- explained
- function body
- generate
- GitHub
- gpt2
- Intellicode
- intellisense
- interpolate
- language model
- Machine Learning
- Microsoft
- msbuild
- name
- Neural Networks
- OpenAI
- Paper
- programmer
- Python
- smart
- stackoverflow
- vscode
OpenAI demonstrated what happens when you learn a language model on thousands of GitHub Python repositories Yannic Kilcher talks about this code completion engine which can write an entire function from just the name. Source Clip: https://youtu.be/fZSFNUT6iY8 Full Video: https://www.pscp.tv/Microsoft/1OyKAYWPRrWKb
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Deep Learning New Frontiers
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Frank
- March 29, 2020
- 6.s191
- 6s191
- adversarial attacks
- AI
- Alexander Amini
- amini
- artificial intelligence
- AutoML
- ava soleimany
- bayesian deep learning
- Computer Vision
- deep evidential regression
- Deep Learning
- deep learning basics
- deep learning python
- Deep Mind
- deeplearning
- evidential deep learning
- generalization
- graph neural networks
- Introduction
- lecture 2
- Machine Learning
- MIT
- mit deep learning
- Neural Networks
- OpenAI
- soleimany
- TensorFlow
- tensorflow tutorial
- what is deep learning
MIT Introduction to Deep Learning 6.S191: Lecture 6 with Ava Soleimany. Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!! Lecture Outline 0:00 – Introduction 0:58 – Course logistics 3:59 – Upcoming guest lectures 5:35 – Deep learning and expressivity […]
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