https://openai.com/blog/introducing-gpts?fbclid=IwAR1bc_tWeq8ejhleFn2qn-pPjY7Ch5tvWCvG1skwMrI_kNaUk4cgek4dcl0

https://github.com/mlfoundations/open_clip

https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/getting-the-most-from-cloud-services-and-containers?cid=soc-app&utm_content=buffer1e14a&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer

https://medium.com/@aakib2991/docker-part-3-docker-images-docker-file-and-port-expose-885d57d2e697

https://emotional-intelligence.github.io/?fbclid=IwAR0PggfJG_554P0PIECzj26xYKSvG0x_ttTMYwwUAZKIB0C3OTqcRcvNC2g

https://generativeai.pub/graph-of-thoughts-explained-f25b51afefab?gi=df0413646530

https://medium.com/neo4j/knowledge-graphs-llms-real-time-graph-analytics-89b392eaaa95

https://blog-streamlit-io.cdn.ampproject.org/c/s/blog.streamlit.io/langchain-streamlit/amp/

https://huggingface.co/datasets/JourneyDB/JourneyDB

https://huggingface.co/docs/transformers.js/index

https://towardsdatascience.com/how-i-coded-my-own-private-french-tutor-out-of-chatgpt-16b3e15007bb

https://omnimotion.github.io/

https://github.com/NielsRogge/Transformers-Tutorials

https://github.com/XingangPan/DragGAN

https://arxiv.org/abs/2306.07629

https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/what-runs-chatgpt-inside-microsoft-s-ai-supercomputer-featuring/ba-p/3830281?utm_content=buffer3d7e2&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer

https://artificialcorner.com/lamini-is-here-a-little-giant-llm-on-your-cpu-8af30ff5a7c2?gi=263024e685a2

https://amatriain.net/blog/transformer-models-an-introduction-and-catalog-2d1e9039f376/

https://hbr.org/2018/04/a-simple-tool-to-start-making-decisions-with-the-help-of-ai

https://arxiv.org/abs/2304.12210

https://github.com/h2oai/h2ogpt

https://www.infoq.com/news/2023/04/microsoft-visual-chatgpt/?utm_term=global&utm_content=buffer1c1e8&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer

https://huggingface.co/spaces/microsoft/HuggingGPT

https://github.com/jina-ai/gptdeploy

https://pub.towardsai.net/the-complete-guide-to-spiking-neural-networks-d0a85fa6a64

https://tcdi.github.io/plrust/plrust.html

https://github.com/mrsked/mrsk

https://github.com/facebookresearch/segment-anything

System Forecasting in Presence of Noise and Serial Correlation https://towardsdatascience.com/pca-for-multivariate-time-series-forecasting-dynamic-high-dimensional-data-ab050a19e8db

https://towardsdatascience.com/four-approaches-to-build-on-top-of-generative-ai-foundational-models-43c1a64cffd5 Four Approaches to build on top of Generative AI Foundational Models What works, the pros and cons, and example code for each approach towardsdatascience.com

https://arxiv.org/abs/2212.02691

https://crfm.stanford.edu/2023/03/13/alpaca.html

https://github.com/GoogleContainerTools/distroless

https://simonwillison.net/2023/Mar/17/beat-chatgpt-in-a-browser/

https://huggingface.co/spaces/onnx/export

Data science isn’t just Pandas, NumPy, and Scikit-learn anymore https://towardsdatascience.com/6-new-booming-data-science-libraries-you-must-learn-to-boost-your-skill-set-in-2023-106b318d9fa

http://sortbenchmark.org/ELSAR2022.pdf

https://www.intel.com/content/www/us/en/developer/partner/hugging-face.html

https://github.com/szheng3/rust-individual-project-2

https://github.com/amazon-science/mm-cot

https://github.com/nogibjj/rust-mlops-template/tree/static/OnnxDemo

Graph Forward-Forward (GFF) algorithm, an extension of the Forward-Forward procedure to graphs, able to handle features distributed over a graph’s nodes. This allows training graph neural networks with forward passes only, without backpropagation. https://arxiv.org/abs/2302.05282 Graph Neural Networks Go Forward-Forward We present the Graph Forward-Forward (GFF) algorithm, an extension of the Forward-Forward procedure to graphs, able…

https://huggingface.co/spaces/fffiloni/Pix2Pix-Video

https://aws.amazon.com/fr/blogs/opensource/sustainability-with-rust/

https://github.com/GokuMohandas/Made-With-ML

https://moez-62905.medium.com/decorating-your-python-code-a-beginners-guide-to-decorators-3bedb022cfe7

https://github.com/databricks/mlops-stack

https://github.com/cookiecutter/cookiecutter

https://www.width.ai/post/bart-text-summarization BART Text Summarization vs. GPT-3 vs. BERT: An In-Depth Comparison BART does a good job of producing a grammatically correct summary that covers both the focus areas — health and personality. It also removes all the spurious, unreadable text (like "@CAPS2"). www.width.ai

https://github.com/dair-ai/ML-Papers-Explained

https://towardsdatascience.com/adam-latest-trends-in-deep-learning-optimization-6be9a291375c

https://medium.com/@dita.niki03/a-summary-of-few-shot-learning-with-graph-neural-networks-c33b5d0d7a6f

https://medium.com/@RebelScience/deep-learning-is-not-just-inadequate-for-solving-agi-it-is-useless-2da6523ab107

This repository contains code to replicate our research described in "Cramming: Training a Language Model on a Single GPU in One Day". We experiment with language model pretraining a BERT-type model with limited compute, wondering "how bad can it really be"? https://github.com/JonasGeiping/cramming GitHub – JonasGeiping/cramming: Cramming the training of a (BERT-type) language model into limited…

https://blog.qooba.net/2022/10/25/speedup-mlflow-models-serving-with-rust/

https://github.com/Aeternalis-Ingenium/FastAPI-Backend-Template

DeepMind’s AlphaCode outperforms many human programmers in tricky software challenges https://www.science.org/content/article/ai-learns-write-computer-code-stunning-advance AI learns to write computer code in ‘stunning’ advance Software runs the world. It controls smartphones, nuclear weapons, and car engines. But there’s a global shortage of programmers. Wouldn’t it be nice if anyone could explain what they want a program to do, and…

Welcome to the 8th edition of our Top Python Libraries list! We are excited to present this year’s picks for the most innovative developments in the Python ecosystem. From this edition, we are expanding our list to include not only libraries per-se, but also tools that are built to belong in the Python ecosystem —…

https://medium.com/analytics-vidhya/quantum-artificial-intelligence-in-financial-crime-24a6671915e7

A quick overview of ChatGPT’s architecture… The AI Powering ChatGPT: A clever combination of the InstructGPT architecture with reinforcement learning models. "The main ideas behind ChatGPT were pioneered by another OpenAI’s , InstructGPT which was released earlier this year. InstructGPT fine tunes GPT to follow instructions which opens the door to a wider set of…

ChatGPT is like Google, StackOverflow and Readthedocs combined https://levelup.gitconnected.com/how-i-used-chatgpt-to-automate-these-6-tasks-in-my-data-science-role-52e8ddfc03cf

https://www.anyscale.com/blog/training-one-million-machine-learning-models-in-record-time-with-ray

https://www.photoroom.com/tech/switching-from-t4-to-a10/

https://m.youtube.com/watch?v=_BZGtifh_gw&feature=youtu.be

Meta AI recently introduced Data2vec 2.0, an AI processor that uses computer vision for multi-camera multi-person re-identification. Data2vec 2.0 is 16 times faster than the current leading self-supervised method in computer vision and is just as accurate. It is 11 times faster than wav2vec 2.0 on the LibriSpeech benchmark and just as accurate as RoBERTa…

https://huggingface.co/blog/rlhf

Faster big-data analysis workflows with an open-source library https://towardsdatascience.com/how-to-speed-up-data-processing-in-pandas-a272d3485b24

One of the simplest ways online applications share data is through the use of webhooks, a one-way communication format for moving data from one application to another. However, webhooks aren’t the only method for data transfer between networked applications. As an engineer, it is very important to use the right tool for the right problem,…

https://machinelearning.apple.com/research/stable-diffusion-coreml-apple-silicon

https://datasetsearch.research.google.com/

https://www.binance.com/en/blog/all/using-mlops-to-build-a-realtime-endtoend-machine-learning-pipeline-3820048062346322706

Games have long been a proving ground for new AI advancements — from Deep Blue’s victory over chess grandmaster Garry Kasparov, to AlphaGo’s mastery of Go, to Pluribus out-bluffing the best humans in poker. But truly useful, versatile agents will need to go beyond just moving pieces on a board. Can we build more effective…

Magic3D is a new text-to-3D content creation tool that creates 3D mesh models with unprecedented quality. Together with image conditioning techniques as well as prompt-based editing approach, we provide users with new ways to control 3D synthesis, opening up new avenues to various creative applications. https://deepimagination.cc/Magic3D/

Demo for using CLIPSeg, a CLIP-based model for zero- and one-shot image segmentation. This model can be used to segment things in an image based on text. This way, one can use it to provide a binary mask for Stable Diffusion, which the latter needs to inpaint. To use it, simply upload an image and…

https://learnk8s.io/troubleshooting-deployments

https://gto76.github.io/python-cheatsheet/

Getting the most out of limited resources allows advances in natural language processing (NLP) research and practice while being conservative with resources. Those resources may be data, time, storage, or energy. Recent work in NLP has yielded interesting results from scaling; however, using only scale to improve results means that resource consumption also scales. That…

Galactica was supposed to help scientists. Instead, it mindlessly spat out biased and incorrect nonsense. https://www-technologyreview-com.cdn.ampproject.org/c/s/www.technologyreview.com/2022/11/18/1063487/meta-large-language-model-ai-only-survived-three-days-gpt-3-science/amp/

Azure Container Apps is a fully managed serverless container service for building and deploying modern apps at scale. Today, we’re introducing new preview features to make it even easier to build and deploy container apps: A new GitHub action to build and deploy container apps A new Azure Pipelines task to build and deploy container…

An energy-efficient chip called NeuRRAM fixes an old design flaw to run large-scale AI algorithms on smaller devices, reaching the same accuracy as wasteful digital computers. https://www.quantamagazine.org/a-brain-inspired-chip-can-run-ai-with-far-less-energy-20221110/

GALACTICA is a general-purpose scientific language model. It is trained on a large corpus of scientific text and data. It can perform scientific NLP tasks at a high level, as well as tasks such as citation prediction, mathematical reasoning, molecular property prediction and protein annotation. A demo is available at galactica.org. https://github.com/paperswithcode/galai

Understanding the various feature engineering techniques can be handy for an ML practitioner. After all, features are one of the most determining factors about how machine learning and deep learning models perform in real-time. https://towardsdatascience.com/which-feature-engineering-techniques-improve-machine-learning-predictions-227d732068f5 Which Feature Engineering Techniques improve Machine Learning Predictions? | by Suhas Maddali | Nov, 2022 | Towards Data Science Photo…

Python libraries and frameworks data scientists must know for time series analysis in 2022 https://moez-62905.medium.com/top-python-libraries-for-time-series-analysis-in-2022-eebe95913085

How we designed a multimodal deep learning framework for quick product development, and how the Room Type Classification models built upon it helped us better understand the homes on our platform. https://medium.com/airbnb-engineering/widetext-a-multimodal-deep-learning-framework-31ce2565880c

The field of data science is always getting better, both in terms of the tools that are already available and those that are being developed every day. Even though no tool is flawless and comprehensive, having the right tools on your side can make a big difference in productivity and execution. https://moez-62905.medium.com/data-scientists-starter-toolkit-for-end-to-end-machine-learning-life-cycle-in-2022-2d2420bda22c

https://vickiboykis.com/2022/11/10/how-i-learn-machine-learning/

An awesome list of references for MLOps – Machine Learning Operations https://github.com/visenger/awesome-mlops

https://karpathy.medium.com/software-2-0-a64152b37c35

MLflow is an open-source framework that’s designed to manage the complete machine learning lifecycle. Its ability to train and serve models on different platforms allows you to use a consistent set of tools regardless of where your experiments are running: locally on your computer, on a remote compute target, on a virtual machine, or on…

Learn the foundations of machine learning through intuitive explanations, clean code and visualizations. Learn how to combine machine learning with software engineering to build production-grade applications. https://github.com/GokuMohandas/Made-With-ML GokuMohandas/Made-With-ML: Learn how to responsibly develop, deploy and maintain production machine learning applications. – GitHub Mission. ML is not a separate industry, instead, it’s a powerful way of…

Building a scalable and real-time recommendation system is vital for many businesses driven by time-sensitive customer feedback, such as short-videos ranking or online ads. Despite the ubiquitous adoption of production-scale deep learning frameworks like TensorFlow or PyTorch, these general-purpose frameworks fall short of business demands in recommendation scenarios for various reasons: on one hand, tweaking…

Reinforcement learning (RL) is an area of machine learning that focuses on training intelligent agents using related experiences so they can learn to solve decision making tasks, such as playing video games, flying stratospheric balloons, and designing hardware chips. Due to the generality of RL, the prevalent trend in RL research is to develop agents…

Tabular data is among the oldest and most ubiquitous forms of data. However, the generation of synthetic samples with the original data’s characteristics still remains a significant challenge for tabular data. While many generative models from the computer vision domain, such as autoencoders or generative adversarial networks, have been adapted for tabular data generation, less…

https://techcommunity.microsoft.com/t5/apps-on-azure-blog/code-to-cloud-with-azure-kubernetes-service-aks/ba-p/3669916?utm_content=buffere4c0d&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer

https://blog.streamlit.io/make-a-video-content-analyzer-app-with-streamlit-and-assemblyai/

https://dev.to/docker/9-docker-extensions-every-developer-must-try-1no2

With neural search seeing rapid adoption, more people are looking at using it for indexing and searching through their unstructured data. I know several folks already building PDF search engines powered by AI, so I figured I’d give it a stab too. How hard could it possibly be? https://jina.ai/news/search-pdfs-with-ai-and-python-part-1/ Search PDFs with AI and Python:…

The success of today’s AI applications requires not only model training (Model- centric) but also data engineering (Data-centric). In data-centric AI, active learning (AL) plays a vital role, but current AL tools can not perform AL tasks efficiently. To this end, this paper presents an efficient MLOps system for AL, named ALaaS (Active-Learning-as-a-Service). Specifically, ALaaS…

Active Learning as a Service (ALaaS) is a fast and scalable framework for automatically selecting a subset to be labeled from a full dataset so to reduce labeling cost. It provides a out-of-the-box and standalone experience for users to quickly utilize active learning. https://github.com/MLSysOps/Active-Learning-as-a-Service MLSysOps/Active-Learning-as-a-Service: A scalable & efficient active learning/data selection system for everyone.…

This post is the first installment of the series of introductions to the RAPIDS ecosystem. The series explores and discusses various aspects of RAPIDS that allow its users solve ETL (Extract, Transform, Load) problems, build ML (Machine Learning) and DL (Deep Learning) models, explore expansive graphs, process geospatial, signal, and system log data, or use…