Artificial Intelligence in Analytics

DeepCoder-14B-Preview: A Breakthrough in Code Reasoning DeepCoder-14B-Preview: A Breakthrough in Code Reasoning Introduction The increasing complexity of software and the demand for enhanced developer productivity have led to a significant need for intelligent code generation and…

Google DeepMind’s Imagen 2 is a cutting-edge text-to-image diffusion model, producing realistic, detailed images based on text prompts. It offers inpainting and outpainting features, enabling flexible image manipulation. With a focus on precision and user satisfaction,…

Practical Solutions and Value of KITA: A Programmable AI Framework Addressing Issues with Large Language Models (LLMs) Large Language Models (LLMs) often produce unjustified responses, known as hallucinations. KITA offers a solution by providing reliable and…

Graph Attention Inference for Network Topology Discovery in Multi-Agent Systems (MAS) Practical Solutions and Value The study presents a unique Machine Learning (ML) strategy to understand and manage multi-agent systems (MAS) by identifying their underlying graph…

Enhancing AI with SynPO Aligning AI with Human Preferences Recent advancements in Large Language Models (LLMs) have focused on producing honest, safe, and useful responses. This alignment helps models understand what humans find important in their…

This article explores the use of LangChain, an open-source framework, and the Azure OpenAI gpt-35-turbo model to query SQL databases using natural language. It demonstrates how to use LangChain to convert user input into appropriate SQL…

In today’s rapidly evolving generative AI world, deepsense.ai aims to establish new solutions by combining Advanced Retrieval-Augmented Generation (RAG) with Small Language Models (SLMs). SLMs are compact versions of Language Models with fewer parameters, offering benefits…

Researchers used neural networks to analyze satellite and radar images and found that a large portion of the world’s fishing and energy vessels operate as “dark vessels,” not publicly sharing their location. They developed deep learning…

Transforming Language Model Training with Critique Fine-Tuning Limitations of Traditional Training Methods Traditional training for language models often relies on imitating correct answers. While this works for simple tasks, it limits the model’s ability to think…

Introduction to NVIDIA’s Innovations in Physical AI NVIDIA recently made waves at SIGGRAPH 2025 with groundbreaking announcements that promise to redefine the landscape of physical AI applications. Their new suite of Cosmos world models, simulation libraries,…

Understanding the Challenges of Vision Transformers Vision Transformers (ViTs) have shown great success in tasks like image classification and generation. However, they struggle with complex tasks that involve understanding relationships between objects. A major issue is…

Recent studies show that policy depiction strongly influences learning performance. Carnegie Mellon University and Peking University researchers propose using differentiable trajectory optimization for deep reinforcement and imitation learning. Their approach, DiffTOP, outperforms previous methods in both…

Researchers from the University of Wisconsin–Madison and Amazon Web Services studied improving Large Language Models of code (Code-LLMs) to detect potential bugs. They introduced the task of buggy-code completion (bCC), evaluated on datasets buggy-HumanEval and buggy-FixEval.…

Modeling Collaborator introduces a user-in-the-loop framework to transform visual concepts into vision models, addressing the need for user-centric training. By leveraging human cognitive processes and advancements in language and vision models, it simplifies the definition and…

Understanding AmbiGraph-Eval and Its Impact on Graph Query Generation The introduction of AmbiGraph-Eval marks a significant step forward for professionals who rely on graph databases and natural language processing (NLP). The target audience includes researchers, data…

This week’s AI news roundup highlights various topics. There are discussions on AI’s potential control over humans, the EU AI Act, and improvements in AI technology like Humane’s “AI Pin” and Nvidia’s H100 and H200 chips.…

The text explores a numerical optimization technique and emphasizes its geometric interpretation. (14 words)

Understanding and Mitigating Hallucinations in Vision-Language Models Understanding and addressing hallucinations in vision-language models (VLVMs) is crucial for ensuring accurate and reliable outputs, especially in critical applications like medical diagnostics and autonomous driving. Challenges and Solutions…

Practical Solutions and Value of Compositional GSM in Assessing AI Reasoning Capabilities Overview: Natural Language Processing (NLP) has evolved with large language models (LLMs) tackling challenging problems like mathematical reasoning. However, assessing their true reasoning abilities…