Data Tells Us “What” and We Always Seek for “Why”

The Large Language Models (LLMs) in Artificial Intelligence (AI) are advancing text generation, translation, and summarization. Yet, limited access reduces comprehension, evaluation, and bias reduction. To address this, the Allen Institute for AI (AI2) introduces OLMo…

Introduction to Multi-modal Large Language Models (MLLMs) Multi-modal Large Language Models (MLLMs) have advanced significantly, evolving into multi-modal agents that assist humans in various tasks. However, when it comes to PC environments, these agents face unique…

Enhancing Problem-Solving with LLMs Large Language Models (LLMs) can significantly improve their problem-solving skills by thinking critically and using inference-time computation effectively. Various strategies have been researched, such as: Chain-of-thought reasoning Self-consistency Sequential revision with feedback…

The emergence of large language models like GPT, Claude, and Gemini has accelerated natural language processing (NLP) advances. Parameter-Efficient Sparsity Crafting (PESC) transforms dense models into sparse ones, enhancing instruction tuning’s efficacy for general tasks. The…

Practical Solutions and Value of Deep Learning in Healthcare Transforming Biomedical Data with Deep Learning Deep learning offers a transformative approach to process complex biomedical data, enabling end-to-end learning models that can extract meaningful insights directly…

California’s AI Safety Bill Sparks Controversy in Silicon Valley Practical Solutions and Value If you want to evolve your company with AI, stay competitive, use for your advantage California’s AI Safety Bill Sparks Controversy in Silicon…

In Collaboration with NVIDIA: Introducing Mistral NeMo In collaboration with NVIDIA, Mistral AI team has introduced Mistral NeMo, a groundbreaking 12-billion parameter model that sets new standards in artificial intelligence. Mistral NeMo is designed to be…

A privacy-focused browser extension called Lumos helps users efficiently manage and understand online content by performing all processing locally, addressing privacy concerns. It uses advanced language models to summarize and answer content questions, enabling users to…

Practical AI Solutions for Chart Understanding ChartGemma: A Breakthrough in Chart Understanding and Reasoning Charts are vital in various fields, but current models for chart understanding have limitations. They often rely on data tables rather than…

Introducing OLMES: Standardizing Language Model Evaluations Language model evaluation is crucial in AI research, helping to assess model performance and guide future development. However, the lack of a standardized evaluation framework leads to inconsistent results and…

Practical Solutions for Language Model Outputs Challenges in Language Model Outputs Language models often produce unstructured and inconsistent outputs, posing challenges in real-world applications. Extracting specific information, integrating with systems, and presenting data in preferred formats…

Recent advancements in human motion capture have made it possible to capture motion from RGB photos and films using affordable devices. This opens up opportunities for motion capture in various industries, including sports. However, there are…

Veriff is an identity verification platform partner for organizations in various industries. They use advanced technology, including AI-powered automation and human feedback, to verify user identities. Veriff standardized their model deployment workflow using Amazon SageMaker, reducing…

The TEXT2REWARD framework is introduced by researchers from several universities and Microsoft Research. It aims to create dense reward code for reinforcement learning (RL) based on goal descriptions. By using large language models, TEXT2REWARD generates symbolic…

Authorship Verification with AI: Enhancing Accuracy and Explainability Practical Solutions and Value Authorship Verification (AV) is crucial in natural language processing (NLP) for determining whether two texts share the same authorship. Traditional approaches relied on stylometric…

Revolutionizing Deep Model Fusion: Introducing Sparse Mixture of Low-rank Experts (SMILE) for Scalable Model Upscaling The training of large-scale deep models on broad datasets is becoming more and more costly in terms of resources and environmental…

Creating Intelligent Agents Made Easy Building intelligent agents has often been complicated and time-consuming, requiring technical skills and significant resources. Developers face challenges like API integration, environment setup, and dependency management. Simplifying these tasks is essential…

The development of FlexLLM addresses a critical bottleneck in deploying large language models by offering a more resource-efficient framework for their finetuning and inference tasks. This system enhances computational efficiency, promising to broaden the accessibility and…

The text provides solutions to fix the “Error Generating a Response” issue in ChatGPT. Users are advised to check the OpenAI server status, refresh the ChatGPT page or restart the browser, simplify prompts, run network speed…

Path planning, a method used to find the best route from one point to another within a map, is often done through search-based planning techniques like A* search. Recent studies highlight the benefits of data-driven path…