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What is Agentic AI? Agentic AI represents a new phase in Artificial Intelligence, where machines can make decisions and solve problems independently. Unlike traditional generative AI, which focuses on creating content, agentic AI enables smart agents…

Elon Musk’s startup xAI will release its first AI products on November 4th to a select group. Musk claims that in “important respects,” xAI surpasses all existing AI. xAI aims to understand the true nature of…

Understanding Direct Q-Function Optimization (DQO) Aligning large language models (LLMs) with human preferences is crucial in AI research. Traditional reinforcement learning (RL) methods, like Proximal Policy Optimization (PPO), often require a lot of online sampling, leading…

Researchers have discovered 2.2 million new crystals, using GNoME, a deep learning tool that predicts material stability, accelerating discovery time equivalent to 800 years of research.

Vision-Language-Action Models (VLA) for Robotics VLA models combine large language models with vision encoders and are fine-tuned on robot datasets. This enables robots to understand new instructions and recognize unfamiliar objects. However, most robot datasets require…

A team from FAIR at Meta and collaborators from Georgia Tech and StabilityAI have advanced the refinement of large language models (LLMs) with Stepwise Outcome-based and Process-based Reward Models. This innovation significantly improves LLMs’ reasoning accuracy,…

Artificial intelligence and mathematical reasoning converge in a dynamic intersection, pushing the boundaries of problem-solving capabilities. Large Language Models (LLMs) exhibit promise in bridging linguistic nuances with mathematical logic, showcasing enhanced performance in handling diverse mathematical…

Privacy in machine learning models has become a critical concern due to Membership Inference Attacks (MIA). The new Relative Membership Inference Attack (RMIA) method, developed by researchers at the National University of Singapore, demonstrates its superiority…

Hermes-2-Theta-Llama-3-70B: Revolutionizing Text Generation and AI Applications Model Overview NousResearch introduces Hermes-2-Theta-Llama-3-70B, a powerful AI model merging NousResearch’s Hermes 2 Pro with Meta’s Llama-3 Instruct. This amalgamation creates a model that excels in generating coherent, contextually…

Advancing Vision-Language Reward Models: Practical Business Solutions Advancing Vision-Language Reward Models: Practical Business Solutions In the rapidly evolving field of artificial intelligence, process-supervised reward models (PRMs) present new opportunities for enhancing multimodal learning, particularly in vision-language…

Woodpecker is a new approach that aims to fix hallucinations in Multimodal Large Language Models (MLLM), such as GPT-4V. By connecting the MLLM to the internet, Woodpecker allows the model to validate its generated descriptions using…

Introducing DataGemma: Advancing AI Reliability Google’s DataGemma addresses the challenge of AI hallucinations by grounding large language models in real-world data from its Data Commons, offering practical solutions for accurate and reliable AI-generated content. Practical Solutions…

OpenAI-Altman saga continues with the firing of Sam Altman. Sources suggest that the reason behind his dismissal is an AI model known as Q*, which is believed to be powerful enough to threaten humanity. Q* combines…

Microsoft introduces Orca 2, an advanced reasoning model for smaller language models. Unlike traditional imitation learning, Orca instructs models in different reasoning techniques to improve their reasoning and comprehension skills. Orca 2 outperforms other models in…

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…

Introducing DataChain: Streamlining Unstructured Data Processing with AI Revolutionary Python Library for Data Scientists and Developers DVC.ai has unveiled DataChain, an open-source Python library that leverages advanced AI and machine learning to handle unstructured data at…

The paper “Improving k-Means Clustering with Disentangled Internal Representations” discusses the use of disentangled feature representations to enhance the quality of clustering algorithms. By maximizing disentanglement, the class memberships of data points can be preserved, resulting…

Researchers have developed a system called DEJAVU that predicts contextual sparsity in large language models (LLMs), enabling faster inference without compromising quality. DEJAVU achieves significant reduction in token generation latency without accuracy loss compared to existing…