Google AI Introduces Croissant: A Metadata Format for Machine Learning-Ready Datasets
When building machine learning (ML) models using preexisting datasets, experts in the field must first familiarize themselves with the data, decipher its structure, and determine which subset to use as…
Automation Anywhere delivers a record fourth quarter performance
Continued Profitability, Quarterly Growth and Strong Momentum Heading into next fiscal year Automation Anywhere, the leader in intelligent automation that puts AI to work across organizations, today announced it delivered record…
01.AI launches Top-Performing Vector Database “Descartes” for LLM
01.AI, a Beijing-based generative AI unicorn founded by global AI thought leader Dr. Kai-Fu Lee, announced the successful development of a new type of vector database based on a fully navigatable graph.…
This Machine Learning Research from Tel Aviv University Reveals a Significant Link between Mamba and Self-Attention Layers
Recent studies have highlighted the efficacy of Selective State Space Layers, also known as Mamba models, across various domains, such as language and image processing, medical imaging, and data analysis.…
Meet Apollo: Open-Sourced Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People
Medical artificial intelligence (AI) is rapidly evolving, aiming to harness the vast potential of large language models (LLMs) to revolutionize healthcare delivery. These technological advancements promise to enhance diagnosis accuracy,…
Training Value Functions via Classification for Scalable Deep Reinforcement Learning: Study by Google DeepMind Researchers and Others
Value functions are a core component of deep reinforcement learning (RL). Value functions, implemented with neural networks, undergo training via mean squared error regression to align with bootstrapped target values.…
This AI Paper from UCSD and ByteDance Proposes a Novel Machine Learning Framework for Filtering Image-Text Data by Leveraging Fine-Tuned Multimodal Language Models (MLMs)
In artificial intelligence, the synergy between visual and textual data plays a pivotal role in evolving models capable of understanding and generating content that bridges the gap between these two…
Enhancing Tool Usage in Large Language Models: The Path to Precision with Simulated Trial and Error
Developing large language models (LLMs) in artificial intelligence, such as OpenAI’s GPT series, marks a transformative era, bringing profound impacts across various sectors. These sophisticated models have become cornerstones for…
INSTRUCTIR: A Novel Machine Learning Benchmark for Evaluating Instruction Following in Information Retrieval
Large Language Models (LLMs) have increasingly been fine-tuned to align with user preferences and instructions across various generative tasks. This alignment is crucial for information retrieval systems to cater to…
This AI Paper from Microsoft Proposes a Machine Learning Benchmark to Compare Various Input Designs and Study the Structural Understanding Capabilities of LLMs on Tables
The ability of Large Language Models (LLMs) to solve tasks related to Natural Language Processing (NLP) and Natural Language Generation (NLG) using few-shot reasoning has led to an increase in…