Claude for Desktop

Claude is an AI partner available for desktop and mobile devices, designed for deep work and focused tasks. It can be downloaded for macOS, Windows, and Windows (arm64) on its website, or accessed through the Apple App Store and Google Play.

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Show HN: TikTok Influencers Database with Analyzed Audio

The provided text appears to be a list of various social media profiles, likely on platforms like Instagram or TikTok, categorized by niche or topic. The list includes profiles related to business and entrepreneurship, finance, education, career development, lifestyle, and more, each with a unique set of interests and affiliations.

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Show HN: Shimmer – ADHD-adapted body doubling

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Nearly 90% of our AI crawler traffic is from ByteDance

Nearly 90% of HAProxy's AI crawler traffic comes from Bytespider, a web scraper owned by Bytedance, the parent company of TikTok. This is based on analytics from HAProxy Edge, a global network used to serve traffic for haproxy.com.

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Support for Claude Sonnet 3.5, OpenAI O1 and Gemini 1.5 Pro

Qodo has announced support for four advanced AI models, including Anthropic's Claude Sonnet 3.5, OpenAI's o1 and o1-mini, and Google's Gemini 1.5 Pro, to enhance its AI-driven software development platform. These models offer improved code understanding, problem reasoning, and natural language understanding, enabling developers to tackle complex coding tasks and automate workflows more efficiently.

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Tokenformer: Rethinking transformer scaling with tokenized model parameters

Researchers have introduced TokenFormer, a scalable architecture that overcomes the high computational costs associated with scaling Transformers by leveraging the attention mechanism for interactions between tokens and model parameters. This allows for progressive and efficient scaling without requiring retraining from scratch, enabling models to grow from 124M to 1.4B parameters while maintaining comparable performance.

ArXiv

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

The last decade has seen significant advancements in data science and machine learning, particularly with deep learning methods, which have made previously intractable tasks feasible. This text aims to unify the principles behind successful neural network architectures through geometric principles, providing a common framework and a way to incorporate prior physical knowledge into neural architectures.

ArXiv

Revisiting Reliability in Large-Scale Machine Learning Research Clusters

The paper presents a study on managing large-scale machine learning (ML) clusters, analyzing 11 months of data from two environments with over 150 million GPU hours and 4 million jobs. The study reveals that smaller jobs are more numerous but large jobs are more vulnerable to failures, and proposes methods to estimate reliability metrics and gauge the efficacy of potential software mitigations.

ArXiv

DAWN: Designing Distributed Agents in a Worldwide Network

Large Language Models (LLMs) have evolved into sophisticated entities capable of complex reasoning and decision-making, leading to the development of specialized LLM-based agents for diverse tasks. Distributed Agents in a Worldwide Network (DAWN) is a framework that integrates these agents with traditional software systems, enabling global communication and collaboration while ensuring safety and security.

ArXiv

Neuromorphic Programming: Emerging Directions for Brain-Inspired Hardware

Neuromorphic computers require a new approach to programming that differs from conventional methods, necessitating a paradigm shift in how we think about programming. This paper proposes a framework for neuromorphic programming that aligns with the physical intricacies of these systems, challenging conventional paradigms and advocating for underutilized techniques.

ArXiv

Show HN: Cerebellum – Open-Source Browser Control with Claude 3.5 Computer Use

Cerebellum is a lightweight browser automation tool that uses a Large Language Model (LLM) to accomplish user-defined goals on webpages by navigating a directed graph of webpages and executing keyboard and mouse actions. It simplifies web browsing to navigating a graph of nodes, where each node represents a webpage, and edges represent user actions.

Repo

Show HN: IdentityRAG – customer identity resolution for LLM applications

IdentityRAG is a retrieval-augmented generation system that integrates identity resolution capabilities to provide accurate, context-aware responses about specific customers by retrieving unified customer data across disparate sources and generating LLM responses. It offers key features such as unifying data from various sources, searching and retrieving relevant customer data, consolidating data into a golden record, disambiguating conflicts, and deduplicating redundant information.

Repo

venvstacks: Virtual Environment Stacks for Python

Here's a summary of the text in a couple of sentences:

venvstacks is a tool that allows packaging Python applications and their dependencies into a portable, deterministic format, without requiring multiple copies of large dependencies like PyTorch or CUDA. It achieves this by using a layered approach of virtual environments, including runtime, framework, and application layers, which can be archived and published separately while maintaining dependency locking.

Repo

Show HN: Lumen – Free AI GitHub commit summarizer. Supports fuzzy-search

Lumen is a free CLI tool that uses AI to summarize Git commits without requiring an API key. It supports three AI providers: Groq, OpenAI, and Phind, and can be installed using Homebrew or Cargo.

Repo

Spelled out implementation of LLM parallelisms in pure C

The current projects involve implementing machine learning algorithms in pure C, including parallelizing multi-layer perceptron (MLP) training using OpenMPI and developing a TF/IDF implementation. Other projects include random math and plotting utilities with SDL2.

Repo