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The ts_zip utility uses a Large Language Model to compress text files more efficiently than conventional tools. It requires a GPU and 4GB RAM, processing up to 1 MB/s on an RTX 4090. While supporting various languages and source code, it's optimized for English texts. Compression is measured in bits per byte (bpb). For instance, ts_zip compressed the 100MB "enwik8" file to 13.8MB (1.106 bpb), surpassing xz's 24.9MB...

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How-to Use AI to See Your Data in 3D

TrustGraph's Data Workbench 3D visualizer enhances data analysis with immersive, interactive 3D visualization. This tool helps uncover hidden relationships, provides intuitive navigation, and offers enhanced understanding of...

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How I run LLMs locally

A tech enthusiast describes their setup for running large language models locally on a high-end PC, covering hardware needs, software tools, model selection, and the advantages of local LLM use such as data control and reduced...

Can LLMs Accurately Recall the Bible

Large language models (LLMs) vary in their ability to accurately recall Bible verses. A benchmark test evaluated 11 different LLMs across six scenarios, from popular to obscure verses. Larger models like GPT-4 and Claude 3.5...

Building Life With Generative AI

Generative AI is being applied to life sciences, enabling precise protein engineering and antibody discovery. Flagship Pioneering's Geoff von Maltzahn explains how AI models can create improved antibodies for diseases like cancer...

QVQ: To See the World with Wisdom

The problem involves finding the derivative of a product function h(x) = f(x) * g(x) at x = 2, using given values for f(x), g(x), and their derivatives. Using the product rule for derivatives, h'(x) = f'(x)*g(x) + f(x)*g'(x). By...

The Structure of Neural Embeddings

Deep neural networks produce structured embeddings with hierarchical organization, linear feature representation, and superposition of concepts. These latent spaces exhibit properties like manifold structure, universality across...