The hottest AI/ML Substack posts right now

And their main takeaways
Top Technology Topics
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.
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.
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.
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.
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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.