I Built an OpenAI-Style Swarm That Runs Entirely on My Laptop. Here’s How.

Author(s): Vatsal Saglani

Originally published on Towards AI.

A developer’s journey into creating a privacy-focused, cost-effective multi-agent system using Python and open-source LLMs.

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You know how in sci-fi movies, AI systems seamlessly collaborate to solve complex problems? This always used to fascinate me as a kid. When I started learning about machine learning and deep learning in my pre-final year of undergrad in 2017–18, I was amazed by the potential of these models. It was fascinating how these models could learn to differentiate between dog breeds, predict the price of a house, classify tweet sentiments, and even play games like chess and Go.

Attention, Tokenization, Transformers, and GPT were the new buzzwords, and I was fascinated by how these models could be used to add intelligence to applications. After graduating, when I started working as a data scientist, I gained first-hand experience training, fine-tuning, and deploying models for a wide range of applications. Those days we used to train/fine-tune models for individual tasks or features. We used to discuss how meta-learning, few-shot learning, and few-shot prompting could help us build more intelligent models. But we didn’t exactly know how could we build a system that could learn to do multiple tasks without being explicitly told how to do so.

Then in 2020,… Read the full blog for free on Medium.

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Published via Towards AI