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Keymakr launches egocentric and robotics training data solutions for Physical AI systems

Keymakr launches egocentric and robotics training data solutions for Physical AI systems

Keymakr has officially launched a new suite of tools and services focused on egocentric data for Physical AI and robotics systems. It combines complex multimodal data collection "in the field" and the updated infrastructure of its own SaaS platform, Keylabs. This step confirms that the industry is now

Preventing LLM Hallucinations: Techniques & Best Practices 2026

Preventing LLM Hallucinations: Techniques & Best Practices 2026

One of the key challenges of modern large language models (LLMs) remains the phenomenon of hallucination - situations in which the model generates convincing but factually false or fabricated information. Despite significant progress in model quality in 2025-2026, this problem has not yet been fully eliminated, especially in open queries,

Key Metrics for Measuring LLM Performanc

Key Metrics for Measuring LLM Performanc

The performance evaluation of large language models extends far beyond simply checking whether answers are correct, because these systems operate in a space of subjectivity and probabilities. The main challenge is that a model can generate grammatically flawless and highly convincing text that, upon closer analysis, turns out to be

Transformer architecture explained

Transformer architecture explained

Before the advent of transformers, natural language processing systems struggled to handle long-term dependencies, preserve context, and scale to massively parallel learning. Traditional recurrent neural networks (RNNs) and long short-term memory (LSTM) networks processed language sequentially. The introduction of the transformer model replaced recursion with parallel attention-based

Continual Learning with LLMs: Adapting Models to New Information

Continual Learning with LLMs: Adapting Models to New Information

In a dynamic world where knowledge is constantly updated, there is a need for approaches that enable models to learn continuously without complete retraining. Continuous learning aims to overcome these limitations by allowing models to integrate new knowledge while preserving what they already have. One of the key problems in

Enterprise LLM Solutions: Custom AI Systems Guide

Enterprise LLM Solutions: Custom AI Systems Guide

A rapid transition toward multimodal systems and autonomous AI agents capable of executing complex sequences of actions in real-time is being observed. This technological wave promises the complete automation of intellectual labor; however, its implementation at the enterprise-scale faces barriers that cannot be overcome with mass consumer solutions.

The complete guide to LLM API integration

The complete guide to LLM API integration

Whether you're building a chatbot, automating workflows, or adding semantic search, API integration is the bridge between your product and AI capabilities. Below, we'll cover everything from REST API basics and model endpoints to SDK integration, embedding API usage, and architecture patterns. Quick Take * API integration