marktechpost3d
Weaviate Researchers Introduce Function Calling for LLMs: Eliminating SQL Dependency to Improve Database Querying Accuracy and Efficiency
Databases are essential for storing and retrieving structured data supporting business intelligence, research, and enterprise applications. Querying databases typically requires SQL, which varies ...
marktechpost4d
Chain-of-Associated-Thoughts (CoAT): An AI Framework to Enhance LLM Reasoning
Large language models (LLMs) have revolutionized artificial intelligence by demonstrating remarkable capabilities in text generation and problem-solving. However, a critical limitation persists in ...
marktechpost3d
Princeton University Researchers Introduce Self-MoA and Self-MoA-Seq: Optimizing LLM Performance with Single-Model Ensembles
Large Language Models (LLMs) such as GPT, Gemini, and Claude utilize vast training datasets and complex architectures to generate high-quality responses. However, optimizing their inference-time ...
marktechpost4d
Ï€0 Released and Open Sourced: A General-Purpose Robotic Foundation Model that could be Fine-Tuned to a Diverse Range of Tasks
Robots are usually unsuitable for altering different tasks and environments. General-purpose models of robots are devised to circumvent this problem. They allow fine-tuning these general-purpose ...
marktechpost5d
4 Open-Source Alternatives to OpenAI’s $200/Month Deep Research AI Agent
Deep-Research is an iterative research agent that autonomously generates search queries, scrapes websites, and processes information using AI reasoning models. It aims to provide a structured approach ...
marktechpost4d
s1: A Simple Yet Powerful Test-Time Scaling Approach for LLMs
Language models (LMs) have significantly progressed through increased computational power during training, primarily through large-scale self-supervised pretraining. While this approach has yielded ...
marktechpost6d
ByteDance Proposes OmniHuman-1: An End-to-End Multimodality Framework Generating Human Videos based on a Single Human Image and Motion Signals
Despite progress in AI-driven human animation, existing models often face limitations in motion realism, adaptability, and scalability. Many models struggle to generate fluid body movements and rely ...
marktechpost6d
Zep AI Introduces a Smarter Memory Layer for AI Agents Outperforming the MemGPT in the Deep Memory Retrieval (DMR) Benchmark
The development of transformer-based large language models (LLMs) has significantly advanced AI-driven applications, particularly conversational agents. However, these models face inherent limitations ...
marktechpost6d
Meet Crossfire: An Elastic Defense Framework for Graph Neural Networks under Bit Flip Attacks
Graph Neural Networks (GNNs) have found applications in various domains, such as natural language processing, social network analysis, recommendation systems, etc. Due to its widespread usage, ...
marktechpost5d
Google DeepMind Achieves State-of-the-Art Data-Efficient Reinforcement Learning RL with Improved Transformer World Models
Reinforcement Learning RL trains agents to maximize rewards by interacting with an environment. Online RL alternates between taking actions, collecting observations and rewards, and updating policies ...
marktechpost6d
Meta AI Introduces VideoJAM: A Novel AI Framework that Enhances Motion Coherence in AI-Generated Videos
Despite recent advancements, generative video models still struggle to represent motion realistically. Many existing models focus primarily on pixel-level reconstruction, often leading to ...
marktechpost5d
Meta AI Introduces MILS: A Training-Free Multimodal AI Framework for Zero-Shot Image, Video, and Audio Understanding
Large Language Models (LLMs) are primarily designed for text-based tasks, limiting their ability to interpret and generate multimodal content such as images, videos, and audio. Conventionally, ...