13 Free AI Courses on AI Agents in 2025

Challenges in Visual Language Models (VLMs) Modern VLMs face difficulties with complex visual reasoning tasks, where simply understanding an image is not enough. Recent improvements in text-based reasoning have not been matched in the visual domain.…

Explore regularization methods to enhance Neural Network performance and avoid overfitting. Read more at Towards Data Science.

Innovative AI Framework: Phidata Revolutionizing Autonomous Assistants with Long-Term Memory and Actionable Capabilities In the modern world, artificial intelligence (AI), particularly large language models (LLMs), plays a crucial role in assisting businesses and individuals. However, traditional…

The Role of Synthetic Data in Improving LLMs’ Math Reasoning Capabilities Research Findings: Large language models (LLMs) face a challenge due to the scarcity of high-quality internet data. By 2026, researchers will need to rely on…

Learn how to create Clarifai Workflows using Python SDK and YAML configurations in this tutorial.

OpenAI’s o1 Models: Advancing AI Solutions The o1 Model Series: An Overview The o1 models are designed to be versatile and task-specific, excelling in natural language processing, data extraction, summarization, and code generation. They are optimized…

UC San Diego and New York University developed the V* algorithm, which outperforms GPT-4V in contextual understanding and precise targeting of specific visual elements in images. The algorithm employs a Visual Question Answering (VQA) LLM, SEAL,…

Understanding Recommender Systems Recommender systems (RS) provide personalized suggestions based on user preferences and past interactions. They help users find relevant content like movies, music, books, and products tailored to their interests. Major platforms like Netflix,…

Language models, powered by neural networks, have transformed machine comprehension and text generation. However, understanding their complex inner workings and ensuring alignment with human values presents challenges. Traditional methods to investigate large language models have limitations.…

Natural Language Processing (NLP) Solutions Transforming Multilingual NLP with Aya-23 Models Natural language processing (NLP) focuses on enabling computers to understand, interpret, and generate human language. This includes language translation, sentiment analysis, and text generation, aiming…

Artificial intelligence has made significant strides in 2023, particularly in the medical field. Some notable models include Med-PaLM 2, Bioformer, MedLM, RoseTTAFold, AlphaFold, and ChatGLM-6B. These models show promise in transforming medical processes, from providing high-quality…

This paper introduces weakly supervised pre-training of vision models on large-scale image-text data, reframing it as a classification task. This approach eliminates the need for pairwise similarity computations in contrastive loss, addressing computational challenges and achieving…

‘Large language models’ (LLMs) have gained prominence in the field of artificial intelligence and generative AI. This article discusses the collection methods and use cases of LLM data, projecting its significance in 2023. AIMultiple provides tools…

Transforming Natural Language Processing with Taipan Challenges with Current Architectures Transformer models have greatly improved natural language processing but struggle with long sequences. Their self-attention mechanism is computationally expensive, making it hard to manage long contexts…

Google has introduced Croissant, a new metadata format for machine learning (ML) datasets. Croissant aims to overcome the obstacles in ML data organization and make datasets more discoverable and reusable. It provides a consistent method for…

Significant strides have been made in natural language processing (NLP) using large language models (LLMs). However, LLMs struggle with structured information, leading to a need for new approaches. A team introduced StructLM, surpassing task-specific models on…

XGen-MM: A Series of Large Multimodal Models (LMMS) Developed by Salesforce AI Research If you want to evolve your company with AI, stay competitive, and use XGen-MM: A Series of Large Multimodal Models (LMMS) Developed by…

“`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…

Thank you for the list of useful links. I will make sure to include them in the summary. ITinAI.com recently published an article about researchers from UT Austin who have developed a framework called MUTEX. The…