Building Next-Gen AI Agents: A Deep Dive into NinjaTech AI’s Multi-Agent Personal AI Assistant

NinjaTech AI Launches MyNinja.ai: The World’s First Multi-Agent Personal AI Assistant

NinjaTech AI, a leading artificial intelligence (AI) company, has recently unveiled MyNinja.ai, a groundbreaking multi-agent personal AI assistant designed to revolutionize productivity. The team at NinjaTech AI, including Arash Sadrieh, Tahir Azim, and Tengfui Xue, have worked tirelessly to create a platform that can handle time-consuming complex tasks with ease.

MyNinja.ai is powered by specialized agents that excel at tasks such as scheduling meetings, conducting deep research, generating code, and assisting with writing. These agents are capable of breaking down intricate, multi-step tasks into manageable solutions, all while learning from past experiences and dynamically evaluating generated solutions. The best part? MyNinja.ai operates autonomously and asynchronously, allowing users to focus on their day while Ninja takes care of the heavy lifting in the background.

To achieve the level of accuracy and efficiency required for MyNinja.ai, NinjaTech AI leveraged multiple large language models (LLMs) optimized for specific tasks. By fine-tuning these models for various downstream tasks and personas, the team was able to ensure that each agent was tailored to excel in its designated area.

One of the key components of building MyNinja.ai was the use of AWS Trainium chips for training the models. By utilizing a cluster of Trainium instances, NinjaTech AI was able to efficiently parallelize the training process, resulting in quick iteration times and low costs. This approach allowed the team to fine-tune and test their models rapidly, ultimately saving significant resources compared to traditional training methods.

The results speak for themselves, with MyNinja.ai’s enhanced Llama 3 RAG model achieving impressive accuracies on benchmark datasets such as HotPotQA and Natural Questions (NQ) Open. These results demonstrate the effectiveness of NinjaTech AI’s approach to building cutting-edge AI agents.

Looking ahead, NinjaTech AI has ambitious plans to further enhance their models and user experience. By incorporating ORPO for fine-tuning and building a custom ensemble model from their existing agents, the team aims to continue pushing the boundaries of AI technology.

To learn more about NinjaTech AI’s innovative approach to building multi-agent personal AI assistants, you can read their whitepaper or try out MyNinja.ai for free. With a team of experts like Arash Sadrieh, Tahir Azim, and Tengfei Xue leading the charge, the future of AI productivity tools looks brighter than ever.