Vladimir Dyachkov PhD

Introduction Embodied AI agents are becoming essential in interpreting complex instructions and acting effectively in dynamic environments. The ThinkAct framework, developed by researchers from Nvidia and National Taiwan University, represents a significant advancement in vision-language-action (VLA) reasoning. By introducing reinforced visual latent planning, ThinkAct effectively connects high-level reasoning with low-level robot control. The ThinkAct Framework […] ➡️➡️➡️

In recent years, large language models (LLMs) have transformed how we interact with technology. Many believe that allowing these models to “think longer” during inference can enhance their accuracy and robustness. Techniques such as chain-of-thought prompting and step-by-step explanations have become commonplace. However, a recent study led by Anthropic titled “Inverse Scaling in Test-Time Compute” […] ➡️➡️➡️

Understanding the Target Audience for a Coding Guide The primary audience for this tutorial includes software developers, data scientists, and business analysts. These professionals are keen on utilizing AI technologies to create scalable systems that enhance their workflows. Often working within enterprise environments, they seek to optimize processes through automation and intelligent systems. Pain Points […] ➡️➡️➡️

Understanding the Target Audience for FastVLM The introduction of FastVLM primarily targets AI researchers, machine learning practitioners, and business leaders keen on implementing and optimizing Vision Language Models (VLMs) in enterprise applications. This audience typically possesses a strong technical background and is engaged in fields such as AI development, data science, and product management. Pain […] ➡️➡️➡️

Startups today are navigating a rapidly changing landscape where speed and efficiency are paramount. With limited resources, many are turning to innovative solutions like Vibe Coding—AI-driven development environments that promise to streamline the coding process. These platforms can generate code from simple prompts, debug automatically, and execute tasks with minimal human intervention. However, the question […] ➡️➡️➡️

Understanding the Target Audience for MiroMind-M1 The MiroMind-M1 initiative is designed for a diverse group of professionals in the fields of mathematics, artificial intelligence (AI), and machine learning. This includes researchers, data scientists, and AI developers who are in search of reliable and transparent tools for mathematical reasoning. Common challenges faced by this audience include […] ➡️➡️➡️

In recent years, the field of artificial intelligence (AI) has seen significant advancements, particularly in training language models (LLMs). One of the most exciting developments is the Rubrics as Rewards (RaR) framework, which enhances reinforcement learning through structured, multi-criteria evaluation signals. This approach not only improves the quality of responses generated by LLMs but also […] ➡️➡️➡️

Building a Comprehensive AI Agent Evaluation Framework In today’s rapidly evolving tech landscape, ensuring the performance and reliability of AI agents is crucial for businesses. This article walks you through creating an advanced AI evaluation framework that assesses various metrics including performance, safety, and reliability. By implementing the AdvancedAIEvaluator class, we can leverage metrics like […] ➡️➡️➡️

Implementing Self-Refine Technique Using Large Language Models (LLMs) The Self-Refine technique is a transformative approach in utilizing Large Language Models (LLMs) for various tasks such as reasoning, code generation, and content creation. By allowing the model to evaluate its own output and provide feedback, we create a loop of continuous improvement. This process not only […] ➡️➡️➡️

Understanding the Value of AI “Wrappers” In the fast-paced world of artificial intelligence, a common misconception arises: that successful startups must create their own foundational technology. This belief is particularly evident among those developing what are known as “LLM wrappers” — businesses that utilize large language models (LLMs) like GPT or Claude to deliver solutions. […] ➡️➡️➡️

The Need for Safety in Agentic AI As agentic large language models (LLMs) evolve, they gain the ability to autonomously plan, reason, and act. This advancement brings significant risks, including: Content Moderation Failures: These can lead to harmful or biased outputs that may damage an organization’s reputation. Security Vulnerabilities: Issues such as prompt injections and […] ➡️➡️➡️

Introduction to Open Source Coding Tools The landscape of coding tools is rapidly evolving, especially with the rise of AI-powered solutions. In 2025, open-source alternatives are becoming increasingly competitive with commercial products like Cursor. These tools not only offer flexibility and privacy but also cater to a wide range of coding needs. Whether you are […] ➡️➡️➡️

Amazon has recently made strides in artificial intelligence by developing a new architecture that significantly reduces inference time by 30%. This innovation is particularly relevant for those in tech, marketing, and engineering fields who rely on AI for various applications. The key to this advancement lies in activating only the neurons that are relevant to […] ➡️➡️➡️

Microsoft has taken a bold step into the future of web browsing with the launch of Copilot Mode in Edge. This innovative feature signals a new era where browsers become intelligent partners in our online activities, blending advanced AI capabilities with everyday web tasks. What Is Copilot Mode? Copilot Mode is an experimental feature that […] ➡️➡️➡️

Creating a Knowledge Graph Using an LLM In the realm of artificial intelligence, one of the most interesting applications is the creation of Knowledge Graphs from unstructured data. This article will explore how to construct a Knowledge Graph from a medical log using a Large Language Model (LLM) like GPT-4o-mini. Unlike traditional Natural Language Processing […] ➡️➡️➡️

Introduction to GLM-4.5 and GLM-4.5-Air The artificial intelligence (AI) landscape is undergoing transformative changes, and one of the most notable developments in 2025 is Zhipu AI’s release of the GLM-4.5 series. Comprising two models, GLM-4.5 and GLM-4.5-Air, these systems aim to redefine open-source agentic AI by integrating hybrid reasoning capabilities. Designed to seamlessly connect reasoning, […] ➡️➡️➡️

Overview of the U.S. AI Playbook The U.S. White House has taken a bold step in the realm of technology with the release of the AI Playbook, formally known as “America’s AI Action Plan.” This strategic document sets forth the federal government’s unwavering commitment to artificial intelligence, aiming to enhance AI development across numerous sectors […] ➡️➡️➡️

Understanding the Target Audience The context-aware multi-agent AI system powered by Nomic embeddings and Gemini LLM has a diverse range of potential users. Primarily, it caters to: AI Researchers and Developers: These are individuals looking to push the boundaries of AI through innovative solutions. Business Professionals: This group is keen on leveraging AI for strategic […] ➡️➡️➡️

Understanding VLM2Vec-V2 VLM2Vec-V2 is a cutting-edge framework designed to enhance the way we process and analyze multimodal data, which includes images, videos, and visual documents. It aims to address the limitations of existing models that often struggle with diverse types of visual data. By unifying these modalities, VLM2Vec-V2 opens up new possibilities for AI applications […] ➡️➡️➡️

The Model Context Protocol (MCP) is reshaping how intelligent agents interact with backend services, applications, and data. For organizations looking to implement MCP, merely writing protocol-compliant code isn’t enough. A successful MCP project requires a structured approach that addresses architecture, security, user experience, and operational efficiency. Below, we delve into the key components that ensure […] ➡️➡️➡️