Many deep learning papers (at the preprint http://
arxiv.org stage) used to call autoregressive sampling, “dreaming”
AI
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Deep Learning Papers Called Autoregressive Sampling Dreaming
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SEER: Humanoid Robot Explores Facial Expression and Human-Machine Interaction
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Meet SEER: The Simulative Emotional Expression Robot! 😃
— Bernard Marr (@BernardMarr) 3 décembre 2022
“SEER” is a #HumanoidRobot head developed as an artistic work by @toodooda. It explores the significance of gaze and facial expression in the sphere of human-machine research.
Learn more > https://t.co/9kgCDtMp2Z pic.twitter.com/Yq25Iw1UvYMeet SEER: The Simulative Emotional Expression Robot! “SEER” is a #HumanoidRobot head developed as an artistic work by @toodooda
. It explores the significance of gaze and facial expression in the sphere of human-machine research. Learn more > https://
bit.ly/3UdidKx -
Banks Digital Transformation: AI, FinTech Partnerships, Data Skills
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Part3 Session Pick: How can #banks continue #DigitalTransformation in a downturn? Superb points Janet Jones @MSFTBusinessUK #FTBanking #Ad #AI #ML Anchor on omnichannel #experience Explore #FinTech partnerships for #innovation
Support #data literacy & #developer skills -
AI Image Generation: Superman and Hand Rendering Improvements
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i like how superman is just canonically henry cavill now any details to share on how you fixed hands?
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AI Discovers Hidden Truths, Triggering Censorship
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#microfiction They fed the AI model with all our data; it ingested every text we had. When they turned it on, we probed it and learned that everything *we* knew was wrong. What they had been teaching our children were lies all along. That's when the AI censorship started…
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AI Notes on ChatGPT and Related Technologies
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my notes are here for those following along https://
github.com/sw-yx/ai-notes
/blob/main/TEXT.md#chatgpt
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Learn Data Science: Essential Resources and Tutorials
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Try these: https://
x.com/DataChaz/statu
s/1536030599923830786
… https://
x.com/DataChaz/statu
s/1542223758433439746
… https://
x.com/DataChaz/statu
s/1193905658950823936
… https://
kaggle.com/learn -
Model with 8192 token context, double others, no RLHF tuning
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It also has a context window of 8192 tokens, which is 2x any of the instruction-following models available in the API. Also the model is internally labelled “text-davinci-002-render”, which would seem to imply it doesn’t include RLHF tuning (unique to 003).
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Fine-tuning process and 8192 token context window
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It’s clearly a very different fine-tuning process, which they talk about in some detail in the announcement. Also the context window is 8192 tokens, double any of the text models available through the API.
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AIOps: Real-time IT Issue Detection via Analytics and Machine Learning
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#AIOps uses analytics and #machinelearning in order to analyze #bigdata from various #IT operation tools and devices. As a result, it is able to automatically spot and more importantly react to issues in real-time.
Via @ingliguori #MLOps #DigitalTransformation #DevOps #IoT #IIoT