Michael Abramov

Traditional power grids, built for one-way power flow, are now suffering from the variability of solar and wind power, peak usage spikes, and aging infrastructure. Modern infrastructure requires real-time decision-making based on AI models trained on labeled operational data. These systems analyze weather conditions, consumer behavior, and equipment performance to

Centralized systems that collect raw user data have become a liability and regulatory risk. New laws like GDPR and California’s CCPA have forced organizations to change how they handle sensitive information. Enter a privacy-first alternative that changes how AI models gain intelligence. Rather than pooling datasets in a single

Fine-tuning large language models (LLMs) on proprietary enterprise data has become essential for achieving domain-specific performance, especially in regulated or knowledge-heavy industries. General-purpose LLMs often fall short when dealing with specialized terminology, internal procedures, or compliance requirements. The tuning process typically begins with selecting a base model and applying quantization

It is well known that most errors in AI systems arise from poor data preparation. This highlights a critical gap that is often overlooked: rigorous labeling processes adapted for modern neural networks. In this section, we explore how rigorous workflows improve machine learning results. We examine how raw input data

Keymakr has officially launched the Research Alliance Program — a social initiative designed to support scientists, academic institutions, and research teams in the development of AI models. A Vision for open science Access to high-quality data remains one of the biggest challenges in scientific discovery across robotics, medicine, automotive, and other

As autonomous drones become increasingly integrated into commercial, industrial, and defense operations, their ability to navigate complex airspace safely hinges on the quality of data used to train their systems. Data annotation and labeling key elements within aerial imagery, sensor data, and environmental recordings are essential. From identifying power lines