marktechpost5d
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 ...
marktechpost6d
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 ...
marktechpost4d
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 ...
marktechpost6d
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 ...
marktechpost5d
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 ...
marktechpost1d
Machine Learning
Protecting user data while enabling advanced analytics and machine learning is a critical challenge. Organizations must process and analyze data without compromising privacy, but existing solutions ...
marktechpost13d
Creating An AI Agent-Based System with LangGraph: A Beginner’s Guide
For example, when a user asks a question, the LLM analyzes the input and decides whether it can answer directly or if additional steps (like a web search) are needed.
marktechpost5d
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 ...
marktechpost7d
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 ...
marktechpost7d
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 ...
marktechpost4d
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 ...
marktechpost7d
Fine-Tuning Llama 3.2 3B Instruct for Python Code: A Comprehensive Guide with Unsloth
In this tutorial, we’ll walk through how to set up and perform fine-tuning on the Llama 3.2 3B Instruct model using a specially curated Python code dataset. By the end of this guide, you’ll have a ...