Kolmogorov-Arnold Networks (KANs) offer enhanced model accuracy and interpretability over Multi-Layer Perceptrons (MLPs) by applying activation functions on edges instead of nodes, based on the Kolmogorov-Arnold representation theorem. Read the paper and explore the documentation.
Better and Faster Large Language Models via Multi-Token Prediction
Training large language models like GPT and Llama with multi-token prediction enhances sample efficiency and improves downstream capabilities without increasing training time.
500 Byte Images: The Haiku Vector Icon Format (2016)
The Haiku Vector Icon Format (HVIF) is designed to create extremely small vector icon files, achieving sizes between 500 to 700 bytes, to efficiently store icons within an inode, reducing disk reads for faster folder display.
StoryDiffusion: Long-range image and video generation
StoryDiffusion introduces a novel approach to generate long-range images and videos, enhancing the storytelling aspect in digital content creation.
Alice's adventures in a differentiable wonderland
Simone Scardapane's book, Alice’s Adventures in a differentiable wonderland, serves as an intuitive primer on neural networks, emphasizing differentiable programming and the basics of function optimization through automatic differentiation. Differentiable programming
BASIC turns 60
BASIC, an interpreted programming language known for its simplicity and line-by-line execution, was created to democratize computing and has inspired generations since its inception at Dartmouth College in 1964.
Level of Gaussians: Real-Time View Synthesis for Millions of Square Meters
The Level of Gaussians (LoG) approach significantly enhances the real-time rendering of large-scale scenes by efficiently managing the detail levels of Gaussians based on the viewer's perspective.
The Landscape of Machine Learning on ArXiv
The ArXiv Machine Learning Landscape presents a visual data map showcasing the distribution and relationships of machine learning papers.
LLMs can't do probability
Large Language Models (LLMs) like GPT and Llama struggle with executing tasks that require a specific probability of outcomes, as demonstrated by an experiment where models overwhelmingly favored one choice over another despite instructions to vary responses.
Show HN: I'm 16 and building an AI based startup called Factful with friends
Factful introduces revolutionary capabilities like innovative fact-checking, AI-powered grammar suggestions, and advanced plagiarism detection, aiming to redefine information verification and communication.
Tour of CLIPS (2022)
CLIPS, a rule-based programming language developed by NASA in the mid-'80s, facilitates focusing on domain business logic over software execution mechanics, leveraging the Rete algorithm for efficient rule execution order and caching common calculations.
[R] KAN: Kolmogorov-Arnold Networks
Kolmogorov-Arnold Networks (KANs), inspired by the Kolmogorov-Arnold representation theorem, introduce learnable activation functions on edges instead of fixed ones on nodes, eliminating linear weights in favor of univariate functions parametrized as splines, aiming to outperform Multi-Layer Perceptrons (MLPs) in accuracy and interpretability. Read the paper
[R] CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments
CRISPR-GPT is an AI-powered tool designed to streamline the CRISPR-based gene editing experiment design, integrating LLMs with domain-specific knowledge and external tools for comprehensive support.
Claude Team plan and iOS app
Anthropic introduces a new Team plan for Claude, offering increased usage, access to the Claude 3 model family, and admin tools for $30 per user per month, aiming to enhance productivity across various industries.
Building a Large Japanese Web Corpus for Large Language Models
The newly built large Japanese web corpus significantly outperforms existing corpora in size and quality, with 312.1 billion characters from web pages between 2020 and 2023, aiming to enhance the training of Japanese large language models (LLMs).