At @Supercomputing
? Drop by booth 3047 to:
– Discuss your model! Did you know 500+ models run on our #compiler?
– See dev tools like GroqFlow & GroqAPI, made for fine-grained control
– Discuss RealScale™, the technology that extends performance and #lowlatency from #chip to rack
TOOLS
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Groq Showcases Compiler, Developer Tools, and RealScale at Supercomputing
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Groq Team at Supercomputing Conference Booth 3047
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Last day of @Supercomputing
! Stop by booth 3047 to talk with the Groq team about advancing your #AI and #HPC systems with higher performance and #lowlatency. Folks like Victoria specialize in our #developer tool suite, time-to-production, and all things CX! #SC22 #HPCaccelerates -
AI in Project Management Interview with Ann Campea on AIToday Podcast
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In this @Cognilytica #AIToday #podcast 'AI in Project Management, Interview with Ann Campea, host of The Everyday PM Podcast' hosts @rschmelzer & @kath0134 interview @AnnCampea asking about #AI in #projectmanagement! Full episode: https://
cognilytica.com/2022/11/16/ai-
today-podcast-ai-in-project-management-interview-with-ann-campea-host-of-the-everyday-pm-podcast/?utm_source=dlvr.it&utm_medium=twitter
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#aiprojectmanagement #PM -
OpenCV Courses Launch with Free Trial and Black Friday Offers
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AI Enthusiasts -The official OpenCV Courses in AI are coming to you with incredible OFFERS!
But why wait? Take our 7-day FREE trial for OpenCV For Beginners! CLAIM IT NOW – http://
bit.ly/3UUD0lY #blackfriday #blackfridaysale #sale #blackfridaydeals #blackfridaysales #discount -
LLMs as Cognitive Engines Orchestrating Compute Infrastructure via Text
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Good post. A lot of interest atm in wiring up LLMs to a wider compute infrastructure via text I/O (e.g. calculator, python interpreter, google search, scratchpads, databases, …). The LLM becomes the "cognitive engine" orchestrating resources, its thought stack trace in raw text
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Groq Compiler: Fast ML/AI Model Compilation Without Kernel Libraries
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We run 100's of #ML/#AI models on Groq #Compiler, with no need for kernel libraries. We can tune your workload, with #software tools like GroqFlow and Groq #API. See for yourself–come by booth 3047 at @Supercomputing
, bring your model, and let's talk time-to-compile! #SC22 #HPC -
LangChain 0.0.14 Release with GitHub Actions and Vector DB Improvements
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🦜🔗LangChain version 0.0.14
— LangChain (@LangChain) 16 novembre 2022
🧹Improve GitHub Actions (@PredragGruevski)
🎉Improve env var handling (@deliprao)
🥗Improve coloring of logginghttps://t.co/LuIrkDkbzM
Also, here's an example of using the new vector DB question/answering chainhttps://t.co/hPFqkC1l2cLangChain version 0.0.14 Improve GitHub Actions (
@PredragGruevski
)
Improve env var handling (
@deliprao
)
Improve coloring of logging https://
github.com/hwchase17/lang
chain
… Also, here's an example of using the new vector DB question/answering chain -
TensorFlow and Keras Deep Learning Tutorial Without PhD Required
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TensorFlow, Keras, and deep learning, without a Ph.D. What you'll learn: • What is a neural network
• How to build one
• Learning rate schedules
• How to build convolutional neural networks
• How to use regularization
• What is overfitting https://
codelabs.developers.google.com/codelabs/cloud
-tensorflow-mnist/#0
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YOLOv6 Underwater Trash Detection Training Experiment
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Hundreds of aquatic species are being negatively impacted by the increased under water trash deposits. This is a real problem. We recently ran an underwater trash detection training experiment using YOLOv6.
— Satya Mallick (@LearnOpenCV) 16 novembre 2022
Head over to our https://t.co/tSVje68CSR for the full read.#yolov6 #ai pic.twitter.com/vS6Ug105WJHundreds of aquatic species are being negatively impacted by the increased under water trash deposits. This is a real problem. We recently ran an underwater trash detection training experiment using YOLOv6.
Head over to our https://
learnopencv.com/yolov6-custom-
dataset-training/
… for the full read. #yolov6 #ai -
GPT Training Framework with Dataset and Sampling Tools
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Prompt: "You are a GPT and you're in charge of training an even better GPT, congrats! You have a dataset here . You can train it on document chunks like this: and sample its current understanding like this: . And here's a calculator and a scratchpad . Begin:"