The hottest ML Substack posts right now

And their main takeaways
Category
Top Technology Topics

7 Must-Have Features for Crafting Custom LLMs

Gradient Flow • 299 implied HN points • 21 Sep 23
🕹 Technology AI ML Generative AI Large Language Models Data
  1. Crafting custom large language models (LLMs) is essential for addressing concerns about intellectual property, data security, and privacy.
  2. Tools for building custom LLMs must include versatile tuning techniques, human-integrated customization, and data augmentation capabilities.
  3. Developing multiple custom LLMs requires features like experimentation facilitation with tools such as MLflow, the use of distributed computing accelerators, and documentation excellence for alignment, accuracy, and reliability.

The New Era of Efficient LLM Deployment

Gradient Flow • 299 implied HN points • 13 Jul 23
🕹 Technology AI ML Infrastructure Tools Computer Vision
  1. AI tools are becoming pervasive in tech with potential to increase productivity and contribute trillions annually to global productivity
  2. Efficient deployment of large language models (LLMs) is crucial for businesses to scale their AI initiatives and drive digital innovation
  3. Rethinking MLOps infrastructure is essential to accommodate the scale and complexity of LLMs, with a need for solutions addressing challenges in inference, serving, and deployment

Edge 373: Computationally Efficient LLM Reasoning with ReWOO

TheSequence • 413 implied HN points • 27 Feb 24
🕹 Technology AI ML Techniques
  1. ReWOO is a new reasoning technique optimized for information augmented LLMs, focusing on step-wise reasoning, tool-calls, and summarization as separate modules.
  2. RAG techniques impact the reasoning abilities of LLMs in generative AI applications, often requiring coordination between LLMs and external tools, which can increase computational demands.
  3. LLMFlows is introduced as a framework for building LLM applications, showcasing the importance of augmenting LLMs with external data like RAG to enhance their capabilities.
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🔥Building Plaid’s ML Fraud Detection Application—an apply() Fireside Chat

TheSequence • 441 implied HN points • 05 Feb 24
🕹 Technology ML Fraud Detection Fintech Data Management
  1. Learn how Plaid built the ML infrastructure powering Signal, their fraud detection app.
  2. Discover the technical solutions adopted by Plaid to overcome challenges like out-of-order transaction data.
  3. Understand the benefits of Plaid's new ML platform, including improved cost management and better access controls.

Deep Learning Weekly : Issue #309

Deep Learning Weekly • 216 implied HN points • 12 Jul 23
🕹 Technology AI ML MLOps Libraries Papers
  1. Deep Learning Weekly Issue #309 covers topics like Code Interpreter on ChatGPT Plus and ML system design with 200 case studies.
  2. Industry innovations include AI-generated chart captions and Nvidia's AI approach to carbon capture.
  3. Learning section highlights topics like Tiny Audio Diffusion and Swin Transformer for object recognition.

About my own interest in the current generative AI craze

Bojan’s Newsletter • 176 implied HN points • 27 Feb 23
🕹 Technology AI Future of work Creative work ML
  1. The author has not done fundamental work in generative AI, but has potential projects that may go in that direction.
  2. The author's interest in generative AI is linked to their long-term interest in the future of work, which directly affects their professional life.
  3. Generative AI tools have the potential to transform work dynamics significantly, especially in creative fields.

Dimension Hopper Part 1

General Robots • 395 HN points • 12 Jun 23
🕹 Technology AI Gaming Art ML Generative
  1. The project involves creating a 2D platformer where players design levels and AI generates visual representations.
  2. The journey to achieve this project involved experimenting with different techniques and models, such as adjusting depth images and adding more detail to improve visual outcomes.
  3. Using the right control images, supporting structures, and techniques like adding adjustable roughness, greatly improved the quality of the generated images.

Could Decision Trees Help With GenAI?

Bojan’s Newsletter • 137 implied HN points • 13 Mar 23
🕹 Technology AI ML GenAI
  1. Decision Trees are known for being accurate and robust in tabular data modeling.
  2. Generative AI systems can sometimes create inaccurate content, especially in domains where accuracy is crucial.
  3. Using tree-based ML models could potentially address issues of hallucination in Generative AI.

OpenAI’s Sora for video, Gemini 1.5's infinite context, and a secret Mistral model

Democratizing Automation • 221 implied HN points • 16 Feb 24
🕹 Technology AI Models ML Video Innovation
  1. OpenAI introduced Sora, an impressive video generation model blending Vision Transformer and diffusion model techniques
  2. Google unveiled Gemini 1.5 Pro with nearly infinite context length, advancing the performance and efficiency using the Mixture of Expert as the base architecture
  3. The emergence of Mistral-Next model in the ChatBot Arena hints at an upcoming release, showing promising test results and setting expectations as a potential competitor to GPT4

Why Job Displacement Predictions are Wrong: Explanations of Cognitive Automation

Scaling Knowledge • 117 implied HN points • 30 May 23
🕹 Technology AI Automation Cognition ML Economics
  1. Predictions about job displacement due to large language models are often wrong because they lack explanations of how LLMs and human intelligence differ.
  2. Jobs are more likely to be augmented than automated by technologies like LLMs, as human creativity and autonomy are essential in many fields like software engineering, medicine, law, and media production.
  3. Regulations on AI and cognitive automation may hinder progress and knowledge creation, leading to unforeseen consequences and limiting the potential benefits of such technologies.

How to cultivate a high-signal AI feed

Democratizing Automation • 166 implied HN points • 28 Feb 24
🕹 Technology AI ML Data Research Communication
  1. Be intentional about your media diet in the ML space, curate and focus your energy to save time and avoid misleading content.
  2. When evaluating ML content, focus on model access, credibility, and demos; choosing between depth or breadth in your feed; and checking for reproducibility and verifiability.
  3. Ensure to socialize your information, build relationships in the community, and consider different sources and content types for a well-rounded perspective.

A minimal viable product for alignment

Musings on the Alignment Problem • 399 implied HN points • 29 Mar 22
🕹 Technology AI Research Automation Alignment ML
  1. Progress in AI can expand the range of problems humanity can solve, addressing the limitation of human capabilities.
  2. Automating alignment research using AI systems can accelerate progress by overcoming talent bottlenecks and enabling faster evaluation and generation of solutions.
  3. An alignment MVP approach is less ambitious than solving all alignment problems but can still lead to solutions by leveraging automation and AI capabilities.

Pinterest improves their Closeup Recommendation System through foundational changes

MLOps Newsletter • 98 implied HN points • 07 Oct 23
🕹 Technology AI Data ML Models Libraries
  1. Pinterest improved their Closeup Recommendation System with foundational changes like hybrid data logging and sampling.
  2. Pinterest uses a model refreshing framework to keep their Closeup Recommendation model up-to-date and adaptable.
  3. Distilling step-by-step can help train smaller, more efficient, and interpretable language models like LLMs.

Market Map & Analysis: AI Synthetic Data Companies

The Strategy Deck • 78 implied HN points • 06 Jul 23
🕹 Technology AI Data ML Synthetic Data Computer Vision
  1. Synthetic data is crucial for ML by replacing real-world data, protecting sensitive information, and validating AI applications.
  2. Synthetic data is used in computer vision for autonomous vehicles and is expanding to other data types like text and tabular data.
  3. There are specialized and general-purpose synthetic data platforms developing innovative solutions for various industries and use cases.

📌 ML Engineering Event: Mastering AI and ML at Production Scale at apply()

TheSequence • 84 implied HN points • 19 Feb 24
🕹 Technology AI ML
  1. The event offers real-world insights from engineering leaders on ML model deployment and best practices.
  2. Participants can engage in sponsor-free knowledge sharing sessions with peers, focusing on in-depth discussions.
  3. Attendees have the opportunity to network with a diverse group of AI and ML engineers, including industry veterans and emerging leaders.

LLM agents and integration dead-ends

Democratizing Automation • 146 implied HN points • 12 Jul 23
🕹 Technology AI Integration ML Generative AI Language Models
  1. The biggest immediate roadblock in generative AI unlocking economic value is the barrier of enabling direct integration of language models
  2. Many are exploring the use of large language models (LLMs) for various business tasks through LLM agents, which are facing challenges of integration and broad scope
  3. The successful commercial viability of LLM agents depends on trust, reliability, management of failure modes, and understanding of feedback dynamics

Gig Economy, AI, and LLM: Friends or Foes?

Gad’s Newsletter • 47 implied HN points • 05 Feb 24
🕹 Technology AI ML Gig Economy Artificial Intelligence Large Language Models
  1. The gig economy connects freelancers with businesses through digital platforms for flexible, temporary work.
  2. Advancements in AI, particularly LLM and ML, are empowering gig workers by automating tasks, providing data-driven insights, and improving service quality.
  3. Challenges in the gig economy arise from the potential job displacement due to automation and AI advancements, along with ethical concerns about bias and privacy.

The Good A.I. We’re Not Talking About

The Digital Anthropologist • 19 implied HN points • 04 Jan 24
🕹 Technology AI ML NLP Deep Learning
  1. Artificial Intelligence (AI) is not just about Generative AI (GAI) like ChatGPT. There are various other proven AI tools like Machine Learning (ML), Deep Learning, Natural Language Processing (NLP), and Expert Systems being successfully used in industries such as healthcare, manufacturing, and more.
  2. AI tools have been around for decades and have shown significant positive impacts on society. Despite the hype around GAI, it remains a small part of the broader AI landscape.
  3. Beyond the flashy headlines, many AI applications are working behind the scenes in specialized industries, quietly making a positive difference. While GAI is getting attention, the real-world impact of other AI tools continues to be substantial.

📌 ML Engineering Event: Lineup for apply() 2024 is Now Live!

TheSequence • 42 implied HN points • 08 Mar 24
🕹 Technology AI ML Events
  1. The lineup for the apply() 2024 ML Engineering Event, featuring industry leaders from LangChain, Meta, and Visa, is now live.
  2. The agenda includes keynote sessions on LangChain, semi-supervised learning, and uplift modeling by experts from the respective fields.
  3. Attendees can look forward to gaining insights and actionable tips for mastering AI and ML at the event.

Hot Topics #21 (Mar. 17, 2023)

The Merge • 19 implied HN points • 17 Mar 23
🕹 Technology AI ML Optimization Speech Synthesis Robotics
  1. GPT-4 is a new large-scale model by OpenAI that can accept image and text inputs to produce text outputs.
  2. PaLM-E is an embodied multimodal language model that incorporates real-world sensor data into language tasks.
  3. Meta-black-box optimization can discover effective update rules for evolution strategies through meta-learning.

📌 Exciting news! The speaker lineup for apply() 2024 is now live

TheSequence • 21 implied HN points • 15 Mar 24
🕹 Technology AI ML Data science Events
  1. The speaker lineup for apply() 2024 event is now live, featuring industry leaders from companies like LangChain, Meta, Visa, and more.
  2. The event offers actionable insights to master AI and ML in production, with sessions on topics like LangChain Keynote, Semi-Supervised Learning, and Uplift Modeling.
  3. Attendees can register for free to join the event live on April 3rd, with the option to receive on-demand videos as well.

🙄 The AI is coming for my UX job

Counting Stuff • 54 implied HN points • 13 Apr 23
🕹 Technology AI UX ML Translation Market Impact
  1. A startup is using AI to create fake personas for product testing, but it misses the point of user testing.
  2. Usability studies run by project managers may be biased without proper training, focusing on understanding user motivations rather than specific actions.
  3. Like machine translation disrupted the translation market, AI in UX may provide some value for simple tasks but human experts are still needed for complex nuances.

Meta's Inside the lab & Nvidia's GTC Spring

Sector 6 | The Newsletter of AIM • 39 implied HN points • 27 Feb 22
🕹 Technology AI ML Metaverse Conferences Virtual Events
  1. Meta hosted a virtual event called 'Inside the Lab', focusing on their advancements in the metaverse. It aimed to share updates after their rebranding from Facebook.
  2. Nvidia's GTC Spring also featured important news in AI and machine learning. This event is known for showcasing the latest technology developments.
  3. These events highlight the growing interest and progress in virtual realities and AI technologies in the industry. People are excited about the future possibilities.

Local Llama and much more!

ScaleDown • 11 implied HN points • 15 Aug 23
🕹 Technology AI ML Deployment Open Source
  1. The newsletter focuses on deploying LLMs locally, offering tips and expert answers.
  2. It includes a comprehensive guide on local deployment of LLMs, combining reliable methods with innovation.
  3. The newsletter addresses top LLM questions, covering topics like overfitting, customization, and linguistic diversity.

LLM Chronicles #5: GPT For Ecommerce Search Engine With Pinecone

Pratik’s Pakodas 🍿 • 8 implied HN points • 09 May 23
🕹 Technology ML Search Engine GPT Ecommerce Data science
  1. In certain scenarios, companies use 2 types of hybrid search: weighted scoring and filter and rerank, especially prevalent in e-commerce.
  2. GPT can be leveraged for query understanding to parse out complex queries and populate Elasticsearch/Solr with detected entities.
  3. Although using GPT-4 for this purpose may be costly and slow, training an open-source model like MPT-7B can be a more viable option.