#ml
Schmidhuber J. Deep Learning: Our Miraculous Year 1990-1991. In: arXiv.org [Internet]. 12 May 2020 [cited 7 Jul 2024]. Available: https://arxiv.org/abs/2005.05744
Schmidhuber J. Deep Learning: Our Miraculous Year 1990-1991. In: arXiv.org [Internet]. 12 May 2020 [cited 7 Jul 2024]. Available: https://arxiv.org/abs/2005.05744
arXiv.org
Deep Learning: Our Miraculous Year 1990-1991
The Deep Learning Artificial Neural Networks (NNs) of our team have revolutionised Machine Learning & AI. Many of the basic ideas behind this revolution were published within the 12 months of our...
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#ml
I was searching for a tool to visualize computational graphs and ran into this preprint. The hierarchical visualization idea is quite nice.
https://arxiv.org/abs/2212.10774
I was searching for a tool to visualize computational graphs and ran into this preprint. The hierarchical visualization idea is quite nice.
https://arxiv.org/abs/2212.10774
arXiv.org
Towards Efficient Visual Simplification of Computational Graphs in...
A computational graph in a deep neural network (DNN) denotes a specific data flow diagram (DFD) composed of many tensors and operators. Existing toolkits for visualizing computational graphs are...
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#fun
Not sure how they draw that conclusion though.
https://www.reddit.com/r/dataengineering/s/xw5XAu5JQ4
Not sure how they draw that conclusion though.
https://www.reddit.com/r/dataengineering/s/xw5XAu5JQ4
Reddit
From the dataengineering community on Reddit
Explore this post and more from the dataengineering community
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#misc
A podcast episode about the random bill thief.
https://open.spotify.com/episode/5M4ghNl16ZA3Cnx41KWQRy?si=DJKtuwXfTL6c37BuyCfNbQ
This is the story:
https://www.nytimes.com/2019/03/25/business/facebook-google-wire-fraud.html
A podcast episode about the random bill thief.
https://open.spotify.com/episode/5M4ghNl16ZA3Cnx41KWQRy?si=DJKtuwXfTL6c37BuyCfNbQ
This is the story:
https://www.nytimes.com/2019/03/25/business/facebook-google-wire-fraud.html
NY Times
He Tried to Bilk Google and Facebook Out of $100 Million With Fake Invoices (Published 2019)
A Lithuanian man pleaded guilty last week to wire fraud and said he was part of a scheme to imitate vendors and fraudulently invoice corporations.
#dl
There is this new lib called scale. One could compile CUDA code to use it on AMD GPU.
https://docs.scale-lang.com/manual/how-to-use/
I don't know who is more pissed off, NVidia or AMD.
There is this new lib called scale. One could compile CUDA code to use it on AMD GPU.
https://docs.scale-lang.com/manual/how-to-use/
I don't know who is more pissed off, NVidia or AMD.
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#ai
RAG is evolving so fast.
Gao, Yunfan, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, Meng Wang, and Haofen Wang. 2023. “Retrieval-Augmented Generation for Large Language Models: A Survey.” arXiv [Cs.CL]. arXiv. http://arxiv.org/abs/2312.10997.
RAG is evolving so fast.
Gao, Yunfan, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, Meng Wang, and Haofen Wang. 2023. “Retrieval-Augmented Generation for Large Language Models: A Survey.” arXiv [Cs.CL]. arXiv. http://arxiv.org/abs/2312.10997.
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#ai
Deep learning model quantization:
A Visual Guide to Quantization - by Maarten Grootendorst
https://newsletter.maartengrootendorst.com/p/a-visual-guide-to-quantization#%C2%A7symmetric-quantization
Deep learning model quantization:
A Visual Guide to Quantization - by Maarten Grootendorst
https://newsletter.maartengrootendorst.com/p/a-visual-guide-to-quantization#%C2%A7symmetric-quantization
Maartengrootendorst
A Visual Guide to Quantization
Exploring memory-efficient techniques for LLMs
#ml
Meta's second version of segment anything.
https://github.com/facebookresearch/segment-anything-2
They have a nice demo:
https://sam2.metademolab.com/
Meta's second version of segment anything.
https://github.com/facebookresearch/segment-anything-2
They have a nice demo:
https://sam2.metademolab.com/
GitHub
GitHub - facebookresearch/sam2: The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM…
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th...
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#math
‘Sensational breakthrough’ marks step toward revealing hidden structure of prime numbers | Science | AAAS
https://www.science.org/content/article/sensational-breakthrough-marks-step-toward-revealing-hidden-structure-prime-numbers
‘Sensational breakthrough’ marks step toward revealing hidden structure of prime numbers | Science | AAAS
https://www.science.org/content/article/sensational-breakthrough-marks-step-toward-revealing-hidden-structure-prime-numbers
Science
‘Sensational breakthrough’ marks step toward revealing hidden structure of prime numbers
Proof provides fresh tools to attack famed Riemann hypothesis, math’s biggest unsolved problem
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#tools
Looks like github is providing foundation models soon.
Marketplace
https://github.com/marketplace/models
Looks like github is providing foundation models soon.
Marketplace
https://github.com/marketplace/models
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#ai
Looks like we don't need "Pydantic is all you need" anymore. It's easier to built actionable models/workflows with this new update.
https://openai.com/index/introducing-structured-outputs-in-the-api/
Looks like we don't need "Pydantic is all you need" anymore. It's easier to built actionable models/workflows with this new update.
https://openai.com/index/introducing-structured-outputs-in-the-api/
OpenAI
Introducing Structured Outputs in the API
We are introducing Structured Outputs in the API—model outputs now reliably adhere to developer-supplied JSON Schemas.
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