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Agentic AI
In our previous tutorial, we built an AI agent capable of answering queries by surfing the web. However, when building agents for longer-running tasks, two critical concepts come into play: ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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Top AI Coding Agents in 2025
AI-powered coding agents have significantly transformed software development in 2025, offering advanced features that enhance productivity and streamline workflows. Below is an overview of some of the ...
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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 ...