This article showcases a bench project featuring a Seeed Studio XIAO-ESP32-C3 microcontroller board and a 1.28-inch circular TFT display. The XIAO-ESP32-C3, known for its small size and energy efficiency, is packed with the TFT display on a prototyping board. The uncommitted pins are wired to pin sockets, creating a small bench setup.
This is a hands-on guide with Python example code that walks through the deployment of an ML-based search API using a simple 3-step approach. The article provides a deployment strategy applicable to most machine learning solutions, and the example code is available on GitHub.
WVIK's Chris Hicks reviews The House of Blue Leaves at Playcrafters Barn Theatre, a production directed by Kathy Graham. The play, set in 1965 New York City, follows the story of Artie Shaughnessy, a zookeeper who dreams of fame in Hollywood, and his troubled family.
This article provides a step-by-step guide on building a generative search engine for local files using Qdrant, NVidia NIM API, or Llama 3. It includes system design, indexing local files, and creating a user interface.
Microsoft has deployed GPT-4, a large language model, in an isolated, air-gapped Azure Government Top Secret cloud for use by the Department of Defense. Once accredited, Pentagon officials will be able to use the technology in a secure environment. The tool is expected to help DOD officials deal with vast amounts of data and simplify information sorting. Microsoft is a major investor in OpenAI, the maker of GPT-4 and the popular ChatGPT.
"A fast AI notes app designed to organize and unlock users' best ideas. Key features include Mem Chat for answering questions, related notes suggestions, smart search, AI-powered collections..."
A post discussing preventative maintenance concerns for a 2016 Honda HR-V that is about to hit 100,000 miles.
The highlighted articles cover a variety of topics, including algorithmic thinking for data scientists, outlier detection in time-series data, route optimization for visiting NFL teams, minimum vertex coloring problem solution, high-cardinality features, multilingual RAG (Rapidly-explainable AI) system development, fine-tuning smaller transformer models, long-form visual understanding, multimodal image-text models, the theoretical underpinnings of learning, data science stress management, and reinforcement learning.
Last week, Anthropic announced a significant breakthrough in our understanding of how large language models work. The research focused on Claude 3 Sonnet, the mid-sized version of Anthropic’s latest frontier model. Anthropic showed that it could transform Claude's otherwise inscrutable numeric representation of words into a combination of ‘features’, many of which can be understood by human beings. The vectors Claude uses to represent words can be understood as the sum of ‘features’—vectors that represent a variety of abstract concepts from immunology to coding errors to the Golden Gate Bridge. This research could prove useful for Anthropic and the broader industry, potentially leading to new tools to detect model misbehavior or prevent it altogether.
