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Showing posts from January, 2022

COVID19: Exponential Growth, Under Control, Going Down

  https://nitter.grimneko.de/chriswithers13/status/1399419862057984004 Source code to generate the graph: https://github.com/mountainMath/xkcd_exponential  

The Rise of Open Source Challengers

 https://rajko-rad.medium.com/the-rise-of-open-source-challengers-4a3d93932425   A look at how OSS takes over the application layer + the potential end of closed source software categories The Open Source Challenger Landscape 2021 Reach out to discuss any thoughts, comments, suggestions or if you would just like to chat on the future of open source software or follow me at @rajko_rad on twitter for more content on data, OSS and infra! Note: the above landscape is certainly not a comprehensive overview of all top open source companies today (a list of ~200–300 top OSS companies is separately maintained, and NEA has partnered with many of them). Instead, I am highlighting the emergence of open source companies that directly challenge existing and well known incumbents in categories that have traditionally been closed source vs. open source . Quick recap: how did we get here? Much has been said and written about the history of open source software (OSS) and companies with open s

Computer Science courses with video lectures

  https://github.com/Developer-Y/cs-video-courses   Introduction to Computer Science Data Structures and Algorithms Systems Programming Database Systems Software Engineering Artificial Intelligence Machine Learning Web Programming and Internet Technologies Computer Networks Math for Computer Scientist Theoretical CS and Programming Languages Embedded Systems Real time system evaluation Computer Organization and Architecture Security Computer Graphics Image Processing and Computer Vision Computational Biology Quantum Computing Robotics Computational Finance Blockchain Development Misc  

How a False Love for AI/ML is Destroying our Engineering Colleges

  https://www.linkedin.com/pulse/how-false-love-aiml-destroying-our-engineering-colleges-sarangi/   Just go to a CSE or EE department in any engineering college in India (other than the major IITs), you will find 90% of the faculty and students working on what they refer to as "machine learning". In fact, I will not be surprised if it is 100%. I recently sat in a few faculty selection committees where all 30/30 candidates were in AI/ML (also called soft computing in India) !!! You will almost never find anybody working on hardware, theory, networking, databases, or computer graphics in a CSE department or on devices, control theory, communication theory, or VLSI in an Electronics department. Even if someone has done her Ph.D in theory, she just works on her version of AI/ML, and theses from B.Tech to Ph.D are produced at an industrial scale. I recently was made aware of a university that has close to 500 faculty in CS, 480+ work in ML !!!

What do language models know about your city

 

Bitcoin Crypto Policy

  In 2021, Congress Has Introduced 35 Bills Focused On U.S. Crypto Policy   Congress Introduces A Game-Changing Crypto Bill As The Price Of Bitcoin, Ethereum, BNB, Solana, Cardano, XRP Sinks Congress Announces Hearing on Bitcoin's Energy Use Bitcoin POlicy INstitute   Fact Checking Climate Organizations' Crypto Letter Key Facts on Bitcoin & the Environment    

Deploy GPT-J 6B for inference using Hugging Face Transformers and Amazon SageMaker

  https://huggingface.co/blog/gptj-sagemaker   Almost 6 months ago to the day, EleutherAI released GPT-J 6B , an open-source alternative to OpenAIs GPT-3 . GPT-J 6B is the 6 billion parameter successor to EleutherAIs GPT-NEO family, a family of transformer-based language models based on the GPT architecture for text generation. EleutherAI 's primary goal is to train a model that is equivalent in size to GPT⁠-⁠3 and make it available to the public under an open license. Over the last 6 months, GPT-J gained a lot of interest from Researchers, Data Scientists, and even Software Developers, but it remained very challenging to deploy GPT-J into production for real-world use cases and products. There are some hosted solutions to use GPT-J for production workloads, like the Hugging Face Inference API , or for experimenting using EleutherAIs 6b playground , but fewer examples on how to easily deploy it into your own environment. In this blog post, you will learn how to easi