The hottest AI/ML Substack posts right now

And their main takeaways
Category
Top Technology Topics
Tech Talks Weekly 79 implied HN points 30 Aug 24
  1. This week features new talks from 11 conferences, including GopherCon UK 2024 and PyCon US 2024. It's a great way to catch up on the latest in tech from experts in the field.
  2. The Tech Talks Weekly newsletter provides a convenient way to stay updated without the clutter of platforms like YouTube. You can watch talks at your own pace and reduce FOMO.
  3. Readers are encouraged to share the newsletter and provide feedback through a form. This helps improve the content and build a better community around technology discussions.
Deep (Learning) Focus 609 implied HN points 08 May 23
  1. LLMs can solve complex problems by breaking them into smaller parts or steps using CoT prompting.
  2. Automatic prompt engineering techniques, like gradient-based search, provide a way to optimize language model prompts based on data.
  3. Simple techniques like self-consistency and generated knowledge can be powerful for improving LLM performance in reasoning tasks.
Tribal Knowledge 11 HN points 17 Jul 24
  1. RAG provides context to an LLM by fetching data from various sources, not just vector databases. It can use any data store to enhance the language model's predictions.
  2. Context for an LLM can include system prompts, chat history, RAG, fine-tuning, and more. Any way to turn information into text can improve LLM performance.
  3. RAG can work with vectors, but it's not limited to them. By enabling the LLM to call functions, it can fetch data from a variety of sources beyond vectors, like relational or graph databases.
Dubverse Black 98 implied HN points 09 Aug 23
  1. Self Supervised Learning (SSL) is a way to train models using synthetic labels generated from the data itself.
  2. SSL can be applied in different domains like NLP, Speech, Vision using techniques like MLM, LM, VicReg, Autoencoders, and VAE.
  3. SSL enables models to learn powerful data representations inexpensively which can be utilized for various tasks like transfer learning and fine-tuning.
TheSequence 77 implied HN points 18 Feb 24
  1. Last week saw the release of five major foundation models in the generative AI space, each from a different tech giant, showcasing innovative advancements in various areas like text-to-video generation and multilingual support.
  2. These new models are not only significant for the future of generative AI applications but also highlight the unique innovations and contributions made by different companies in the AI field.
  3. The continuous evolution and release of these super models are driving progress and setting new standards in the field of generative AI, pushing boundaries and inspiring further advancements.
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MLOps Newsletter 78 implied HN points 05 Aug 23
  1. ClimaX is a deep learning model designed for weather and climate tasks like forecasting temperature and predicting extreme weather events.
  2. XGen is a 7B LLM trained on up to 8K sequence length, achieving state-of-the-art results in tasks like MMLU, QA, and HumanEval.
  3. GPT-4 API from OpenAI provides easy access to a powerful language model capable of generating text, translating languages, and answering questions.
VuTrinh. 19 implied HN points 19 Mar 24
  1. Balancing your data infrastructure is key for efficiency and reliability. Companies like Uber face challenges in maintaining this balance as they scale up their data needs.
  2. Figma's database team has successfully handled a massive growth in data since 2020, showing that scaling can lead to new technical challenges but also growth opportunities.
  3. Optimizing data pipelines can save significant costs. Techniques to reduce data shuffling in processes like Apache Spark can help make data handling more efficient.
Tech Talks Weekly 0 implied HN points 04 Jun 24
  1. QCon talks cover a wide range of software engineering topics, including backend, frontend, AI, and DevOps. These talks are great for anyone looking to learn more about tech trends.
  2. A curated list of 35 must-watch talks from QCon London and San Francisco includes interesting topics like how Netflix uses Java and scaling with Amazon DynamoDB. These videos can help you understand real-world applications of technology.
  3. If you subscribe, you'll get a weekly email with new talks from over 100 conferences. This is an easy way to stay updated on tech without the clutter of YouTube.
Tom’s Substack 0 implied HN points 11 Nov 23
  1. Evaluation of models should focus on selecting the best performing model, giving confidence in AI outputs, identifying safety and ethical issues, and providing actionable insights for improvement.
  2. Standard evaluation approaches face challenges like broad performance metrics, data leakage from benchmarks, and lack of contextual understanding.
  3. To improve evaluations, embrace human-centered evaluation methods and red-teaming to understand user perceptions, uncover vulnerabilities, and ensure models are safe and effective.
m3 | music, medicine, machine learning 0 implied HN points 17 Aug 23
  1. Providing a wider range of examples to ChatGPT helps in generating more natural-sounding outputs.
  2. Using a local plugin for ChatGPT allows for accessing and providing context from local files for better collaboration.
  3. Example-driven development with LLMs is useful for identifying relevant context, mimicking input characteristics, and making connections between different types of files.
Exponential Industry 0 implied HN points 28 Jan 24
  1. AI partnerships are advancing industrial automation by improving quality, throughput, and worker safety.
  2. Businesses are investing in new technologies like sensors, robotics, 3D printing, and AI to enhance manufacturing processes.
  3. Government initiatives like Made Smarter are driving tech investments in SMEs for industry growth and sustainability.
Sector 6 | The Newsletter of AIM 0 implied HN points 03 Jun 24
  1. The Data Engineering Summit in Bengaluru was a huge success, with over 1,000 attendees and more than 50 speakers from the AI and analytics community.
  2. Key topics of discussion included software deployment architectures and frameworks for using data in business, highlighting the importance of these technologies.
  3. Attendees showed lots of enthusiasm for the discussions and innovative ideas that were shared at the event, demonstrating a vibrant interest in data engineering.