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LoRA's Limitations: Head-to-Head with Full RL

Low-Rank Adaptation (LoRA) has recently gained popularity due to its significantly lower computational cost compared to full-model post-training, while still achieving comparable performance on supervised fine tuning workloads. However, our experiments indicate that LoRA is less effective in reinfor

Applying RL: Open Source SLM Trained for MCP

MCP is quickly becoming the open standard for AI agents, and for good reason! It’s well designed and easy to use — however, MCP implementations are limited since: 1. The best models are large and closed-source (3.7 Sonnet, Gemini 2.5 Pro) 2. It introduces tool sprawl (numerous MCP clients, MCP serve

Responsive Software

Software has changed a lot since its infancy in the 1950s. However – from early mainframes and monolithic architectures to modern unstructured databases and distributed architectures – the fundamental pattern has remained the same: moving data to a central location for processing. The technology has

Teach AI Agents How to Learn in Real-Time