Five things you need to know about the EU’s new AI Act

Researchers from the College of Computer Science, Sichuan University, and the Engineering Research Center of Machine Learning and Industry Intelligence, Ministry of Education Chengdu, China, have introduced DREditor, a time-efficient method for adapting dense retrieval models…

Artificial intelligence has come a long way, evolving from basic language models to sophisticated systems known as Large Reasoning Models (LRMs). These advanced tools aim to mimic human-like thinking by generating intermediate reasoning steps before arriving…

Reinforcement Learning in Language Model Training Reinforcement learning (RL) is essential for training large language models (LLMs) to enhance their reasoning capabilities, especially in mathematical problem-solving. However, the training process often suffers from inefficiencies, such as…

Mark Zuckerberg showcased a new avatar technology on the Lex Fridman podcast, using lifelike avatars created through Meta’s Quest 3 headsets and noise-canceling headphones. The demonstration received admiration and respect, marking a shift in perception of…

Practical AI Solutions for Document Processing Efficiently Handle Unstructured Data with DocETL As unstructured data volumes rise in sectors like healthcare, legal, and finance, the demand for accurate processing solutions grows. Traditional methods struggle with the…

Autonomous Robot Navigation and Efficient Data Collection: Human-Agent Joint Learning and Reinforcement-Based Autonomous Navigation Human-Agent Joint Learning for Robot Manipulation Skill Acquisition The system integrates human operators and robots in a joint learning process to enhance…

Researchers from the University of Michigan propose new benchmarks and evaluation protocols to assess the Theory of Mind capability of Large Language Models (LLMs). They advocate for a holistic evaluation approach that categorizes machine ToM into…

Understanding AI Hallucinations and Practical Solutions A Cautionary Note “Don’t believe everything you get from ChatGPT“ – Abraham Lincoln. AI can sometimes generate information that seems accurate but is actually false. This issue, known as hallucinations,…

Real AI has been chosen to build Europe’s first-ever Human-Centered LLM on the LEONARDO AI Computer Cluster. LEONARDO is the fourth largest AI cluster in the world and Real AI aims to provide responsible AI development…

NVIDIA AI Introduces Eagle 2: A Transparent Vision-Language Model Vision-Language Models (VLMs) have enhanced AI’s capability to process different types of information. However, they face challenges like transparency and adaptability. Proprietary models, such as GPT-4V and…

Model Predictive Control (MPC) is widely used in fields such as power systems and robotics. A recent study from Carnegie Mellon University focused on the convergence characteristics of a sampling-based MPC technique called Model Predictive Path…

Transforming Natural Language Processing with SmolLM2 Recent advancements in large language models (LLMs) like GPT-4 and Meta’s LLaMA have changed how we handle natural language tasks. However, these large models have some drawbacks, especially regarding their…

The tutorial discusses efficient dataset sampling techniques in Python. It compares three methods: uniform, random, and Latin Hypercube Sampling (LHS). Uniform sampling is simple but scales poorly with dimensions. Random sampling is straightforward, better for large…

AIWaves Inc. has developed Weaver, a family of Large Language Models (LLMs) designed specifically for creative and professional writing. Weaver utilizes innovative training methodologies, including a unique approach to data synthesis and advanced techniques such as…

Theory of Mind Meets LLMs: Hypothetical Minds for Advanced Multi-Agent Tasks Practical Solutions and Value In the field of artificial intelligence, the Hypothetical Minds model introduces a novel approach to address the challenges of multi-agent reinforcement…

Scientists from universities in Victoria and Copenhagen applied AI to the Free Ocean Wave Dataset, successfully predicting rogue waves using a neural network. Employing symbolic regression, they derived an equation revealing the causal factors of these…