AI protein-prediction tool AlphaFold3 is now open source

AlphaFold3, a Nobel-prize-winning AI tool for modeling protein structures, is now open source and available for non-commercial use, allowing academic scientists to download and use the software code. This move comes after Google DeepMind initially withheld the code, sparking criticism from scientists, and now allows researchers to predict protein interactions, including those with potential drugs.

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OpenAI's new "Orion" model reportedly shows small gains over GPT-4

OpenAI's new "Orion" model reportedly shows small gains over its predecessor GPT-4, with improvements mainly in language capabilities and not consistently beating GPT-4 in areas like programming. This slowdown in large language model development affects the entire AI industry, with Google's Gemini 2.0 and Anthropic's Opus 3.5 also falling short of expectations.

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Qwen2.5-Coder Beats GPT-4o and Claude 3.5 Sonnet in Coding

Qwen2.5-Coder is a series of open-source code models that have achieved state-of-the-art (SOTA) performance in code generation, repair, and reasoning, with capabilities comparable to GPT-4o. The series includes six model sizes (0.5B, 1.5B, 3B, 7B, 14B, and 32B) to meet the needs of different developers and provide a platform for research.

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A stubborn computer scientist accidentally launched the deep learning boom

Prof. Fei-Fei Li's creation of the massive ImageNet dataset in the late 2000s, despite initial skepticism, ultimately led to the deep learning boom when a team from the University of Toronto used it to train a neural network that achieved unprecedented performance in image recognition. This breakthrough was made possible by the convergence of Li's dataset, Nvidia's CUDA platform, and the work of Geoffrey Hinton, who spent decades promoting neural networks despite widespread skepticism.

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PlayDialog: A voice model built for fluid, emotive conversations

PlayDialog beta is a powerful AI speech model that uses a conversation's historical context to deliver more natural sounding speech, setting new standards for matching human speech in real-life situations. It is complemented by PlayNote, a tool that lets users create conversational experiences from various media types, and is accessible through an API for large-scale content generation.

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Hunyuan-Large: An Open-Source Moe Model with 52B Activated Parameters

Hunyuan-Large, a 389 billion parameter open-source Transformer-based mixture of experts model, outperforms LLama3.1-70B and matches the performance of the larger LLama3.1-405B model across various benchmarks. The model's success is attributed to its large-scale synthetic data, mixed expert routing strategy, key-value cache compression technique, and expert-specific learning rate strategy.

ArXiv

Magnetic Field Evolution of Hot Exoplanets

Numerical simulations using the MESA model found that the magnetic field strength of gas giant planets depends on the convective energy flux from their interiors. The simulations showed that hot Jupiters' magnetic fields decrease over time, while hot Neptunes' fields die out after around 2 billion years, with factors like atmospheric mass and orbital separation also affecting the magnetic field strength.

ArXiv

One Born–Oppenheimer Theory to rule them all: hybrids pentaquarks and quarkonium

The Born-Oppenheimer effective field theory (BOEFT) is used to address the nature of XYZ exotic states in the hadronic sector, providing a unified description of hybrids, tetraquarks, pentaquarks, and other states. This approach incorporates nonadiabatic terms and predicts the emergence of exotics with molecular characteristics, such as the χc1(3872), through the phenomenon of avoided level crossing.

ArXiv

Qwen2.5-Coder Technical Report

The Qwen2.5-Coder series is a significant upgrade to its predecessor, consisting of six models that demonstrate impressive code generation capabilities while retaining general and math skills. These models have achieved state-of-the-art performance across over 10 benchmarks, outperforming larger models of the same size, and are expected to advance research in code intelligence and support wider adoption in real-world applications.

ArXiv

Combining Induction and Transduction for Abstract Reasoning

Researchers compared two approaches to learning from few examples: inferring a latent function and directly predicting outputs, using neural models on the ARC dataset. They found that inductive and transductive models, despite sharing the same architecture and training data, solved very different problems.

ArXiv

TinyTroupe, a new LLM-powered multiagent persona simulation Python library

TinyTroupe is a Python library that simulates people with specific personalities, interests, and goals, allowing for the investigation of convincing interactions and consumer types in customizable scenarios. It leverages Large Language Models (LLMs) to generate realistic behavior and can be applied to various fields such as advertisement, software testing, training, and product management.

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Show HN: I built a Claude AI chat interface to bypass platform limits

Claude UI is a modern chat interface for Anthropic's Claude AI models, built with Nuxt.js, offering features like conversation history management, multiple model support, and customizable behavior. The project uses a SQLite database with Drizzle ORM for data management and can be set up and run locally with Node.js and an Anthropic API key.

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A full-featured, open-source AI chatbot built by Vercel

The Next.js AI Chatbot is an open-source template built with Next.js and the AI SDK by Vercel, featuring advanced routing, server-side rendering, and support for multiple model providers. It can be easily deployed to Vercel with one click or run locally by setting up environment variables and installing dependencies.

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Linear Algebra for Data Science, Machine Learning, Signal Processing Book Demos

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CML: Continuous Machine Learning CI/CD for ML

Continuous Machine Learning (CML) is an open-source CLI tool for implementing continuous integration and delivery (CI/CD) with a focus on MLOps, allowing users to automate development workflows and generate visual reports with results and metrics on every pull request. CML integrates with GitLab, GitHub, or Bitbucket and can be used to train and evaluate models, compare ML experiments, and monitor changing datasets.

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