As AI-first development redefines how software is built, “vibe coding” has emerged as a paradigm-shifting approach where developers simply say what they want, and an agent builds it. Coined by Andrej Karpathy, the term reflects a shift from code-heavy workflows to natural language-driven software prototyping. Here’s a list of reliable vibe coding tools that support […] The post Top 15 Vibe Coding Tools Transforming AI-Driven Software Development in 2025 appeared first on MarkTechPost. read more

In this tutorial, we’ll learn how to harness the power of Google’s Gemini models alongside the flexibility of Pandas. We will perform both straightforward and sophisticated data analyses on the classic Titanic dataset. By combining the ChatGoogleGenerativeAI client with LangChain’s experimental Pandas DataFrame agent, we’ll set up an interactive “agent” that can interpret natural-language queries. […] The post Build a Gemini-Powered DataFrame Agent for Natural Language Data Analysis with Pandas and LangChain appeared first on MarkTechPost. read more

Early large language models (LLMs) excelled at generating coherent text; however, they struggled with tasks that required precise operations, such as arithmetic calculations or real-time data lookups. The emergence of tool-augmented agents has bridged this gap by endowing LLMs with the ability to invoke external APIs and services, effectively combining the breadth of language understanding […] The post From Text to Action: How Tool-Augmented AI Agents Are Redefining Language Models with Reasoning, Memory, and Autonomy appeared first on MarkTechPost. read more

Bridging Perception and Action in Robotics Multimodal Large Language Models (MLLMs) hold promise for enabling machines, such as robotic arms and legged robots, to perceive their surroundings, interpret scenarios, and take meaningful actions. The integration of such intelligence into physical systems is advancing the field of robotics, pushing it toward autonomous machines that don’t just […] The post VeBrain: A Unified Multimodal AI Framework for Visual Reasoning and Real-World Robotic Control appeared first on MarkTechPost. read more

Despite the substantial progress in text-to-image (T2I) generation brought about by models such as DALL-E 3, Imagen 3, and Stable Diffusion 3, achieving consistent output quality — both in aesthetic and alignment terms — remains a persistent challenge. While large-scale pretraining provides general knowledge, it is insufficient to achieve high aesthetic quality and alignment. Supervised […] The post Yandex Releases Alchemist: A Compact Supervised Fine-Tuning Dataset for Enhancing Text-to-Image T2I Model Quality appeared first on MarkTechPost. read more

Large reasoning models, often powered by large language models, are increasingly used to solve high-level problems in mathematics, scientific analysis, and code generation. The central idea is to simulate two types of cognition: rapid responses for simpler reasoning and deliberate, slower thought for more complex problems. This dual-mode thinking reflects how humans transition from intuitive […] The post ALPHAONE: A Universal Test-Time Framework for Modulating Reasoning in AI Models appeared first on MarkTechPost. read more

In this tutorial, we’ll explore how to create smart, multi-agent workflows using the Mistral Agents API’s Handoffs feature. This lets different agents work together by passing tasks to each other, enabling complex problems to be solved in a modular and efficient way. We’ll build a system where agents collaborate to answer inflation-related questions—performing calculations, fetching […] The post How to Create Smart Multi-Agent Workflows Using the Mistral Agents API’s Handoffs Feature appeared first on MarkTechPost. read more

Large Language Models (LLMs) generate step-by-step responses known as Chain-of-Thoughts (CoTs), where each token contributes to a coherent and logical narrative. To improve the quality of reasoning, various reinforcement learning techniques have been employed. These methods allow the model to learn from feedback mechanisms by aligning generated outputs with correctness criteria. As LLMs grow in […] The post High-Entropy Token Selection in Reinforcement Learning with Verifiable Rewards (RLVR) Improves Accuracy and Reduces Training Cost for LLMs appeared first on MarkTechPost. read more

In this tutorial, we introduce the Gemini Agent Network Protocol, a powerful and flexible framework designed to enable intelligent collaboration among specialized AI agents. Leveraging Google’s Gemini models, the protocol facilitates dynamic communication between agents, each equipped with distinct roles: Analyzer, Researcher, Synthesizer, and Validator. Users will learn to set up and configure an asynchronous […] The post How to Build an Asynchronous AI Agent Network Using Gemini for Research, Analysis, and Validation Tasks appeared first on MarkTechPost. read more

Introduction: The Need for Dynamic AI Research Assistants Conversational AI has rapidly evolved beyond basic chatbot frameworks. However, most large language models (LLMs) still suffer from a critical limitation—they generate responses based only on static training data, lacking the ability to self-identify knowledge gaps or perform real-time information synthesis. As a result, these models often […] The post Google Introduces Open-Source Full-Stack AI Agent Stack Using Gemini 2.5 and LangGraph for Multi-Step Web Search, Reflection, and Synthesis appeared first on MarkTechPost. read more