AlphaGeometry: AI’s landmark achievement in geometry

The article discusses the process of fine-tuning a base LLama2 LLM to output SQL code using Parameter Efficient Fine-Tuning techniques. It covers the hardware requirements, optimization methods, and the actual fine-tuning process. The workflow for fine-tuning…

This paper introduces the groundbreaking Infini-gram, which modernizes traditional n-gram language models by leveraging trillion-token training data. It challenges historical constraints on n, introducing the concept of an ∞-gram LM and demonstrating its potential to complement…

Atom is a new low-bit quantisation technique developed by researchers to increase the serving throughput of Large Language Models (LLMs). By using low-bit operators and quantisation, Atom reduces memory usage without sacrificing precision, resulting in improved…

Practical AI Solutions for Your Company Discover the Value of TIGER-Lab’s MMLU-Pro Dataset If you want to evolve your company with AI, stay competitive, and leverage the latest advancements in AI technology, TIGER-Lab’s MMLU-Pro Dataset is…

AI’s advancement in planning complex tasks necessitates innovative strategies. Large language models exhibit potential for multi-step problem-solving, leveraging a framework with a solution generator, discriminator, and planning method. Research highlights the critical role of discriminator accuracy…

Embedding-Based Retrieval: Enhancing Search Efficiency Understanding the Concept Embedding-based retrieval aims to create a shared semantic space where both queries and items are represented as dense vectors. This allows for matching based on meaning rather than…

The text discusses the problem of class imbalance in machine learning and explores the use of resampling methods, specifically random oversampling, to solve it. It explains the concept of class imbalance, the impact it has on…

Dendritic Neural Networks: A Step Closer to Brain-Like AI Artificial Neural Networks (ANNs) are inspired by the way biological neural networks work. They are effective but have some drawbacks, such as high energy consumption and a…

Transforming Speech Synthesis with Visatronic Speech synthesis is evolving to create more natural audio outputs by combining text, video, and audio data. This approach enhances human-like communication. Recent advancements in machine learning, especially with transformer models,…

“`html Introduction to LADDER Framework Large Language Models (LLMs) can significantly enhance their performance through reinforcement learning techniques. However, training these models effectively is still a challenge due to the need for vast datasets and human…

Understanding CyberGym and Its Importance The world of cybersecurity is evolving rapidly, and with it, the methods we use to evaluate artificial intelligence (AI) agents in this field must also advance. CyberGym, developed by UC Berkeley,…

The UK government has released a report on the capabilities and risks of frontier AI models, which will be discussed at the upcoming AI Safety Summit. The report acknowledges the potential benefits of AI but also…

Microsoft has recently unveiled Code Researcher, an innovative deep research agent designed to tackle the complexities of debugging large-scale systems code. This tool is particularly beneficial for software developers, system architects, and IT managers who often…

Practical Solutions for Terminal-Based UI Development Challenges of Terminal-Based UI Development Developing complex, interactive applications for the terminal can be challenging. Traditional tools often lack the necessary features for creating sophisticated user interfaces. Introducing Textual: A…

Challenges in Internal Data Research Modern businesses encounter numerous obstacles in internal data research. Data is often dispersed across various sources such as spreadsheets, databases, PDFs, and online platforms, complicating the extraction of coherent insights. Organizations…

LEO is a generalized agent developed by researchers at the Beijing Institute for General Artificial Intelligence, CMU, Peking University, and Tsinghua University. It is trained in an LLM-based architecture and is capable of perceiving, reasoning, planning,…

Reinforcement Learning: Addressing Sample Inefficiency Challenges in Real-World Applications Reinforcement learning (RL) is crucial for developing intelligent systems, but sample inefficiency limits its practical application in real-world scenarios. This hinders deployment in environments where obtaining samples…

Understanding LLMs and Their Role in Planning Large Language Models (LLMs) are becoming increasingly important as various industries explore artificial intelligence for better planning and decision-making. These models, particularly generative and foundational ones, are essential for…

Slovakian startup CulturePulse is working with the UN to use AI to gain a better understanding of the Israeli-Palestinian conflict. The company uses large datasets and machine learning to build digital twins of audiences and believes…