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GAIN

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Posts tagged with GAIN

The Generative AI Tech Stack Featured Post

Beyond the Hype: A Pragmatic Technical Framework for Understanding and Building Enterprise-Ready Generative AI Systems

The Generative AI Tech Stack

Since the launch of ChatGPT, businesses and enterprises have been exploring ways to implement large language models into their organizations. However, for non-technical stakeholders, it can be challenging to grasp how all the components of generative AI fit together into a cohesive system.

To bridge this gap, this article introduces the Generative AI Tech Stack - a conceptual model for understanding the layers that comprise a complete generative AI solution. By structuring the stack into logical components, we aim to provide executives, managers, and other business leaders an accessible overview of how the parts interconnect.

The Generative AI Tech Stack

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What Are Large Language Model (LLM) Agents and Autonomous Agents Featured Post

Large language models are rapidly transcending their origins as text generators, evolving into autonomous, goal-driven agents with remarkable reasoning capacities. Welcome to the new frontier of LLM agents.

What Are Large Language Model (LLM) Agents and Autonomous Agents

Large language models (LLMs) like GPT-4 have demonstrated impressive capabilities in generating human-like text. Recent explorations go beyond text generation, framing LLMs as the core controller of agents and autonomous agents that can not just write but also reason, act, and learn.

LLMs have the potential to function as artificial general intelligence systems. They are rapidly transforming from passive language systems into active, goal-oriented agents capable of autonomous reasoning and task completion.

This development marks a seismic shift in artificial intelligence and promises to revolutionize how humans interact with machines.

What is a Large Language Model (LLM)

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Generative AI Networks (GAINs) Featured Post

GAIN is a Prompt Engineering technique to solve complex challenges beyond the capabilities of single agents.

Generative AI Networks (GAINs)

We introduced Generative AI Networks (GAINs) here as an early articulation of multi-agent AI: instead of one model working alone, a network of specialized agents coordinated to solve problems beyond any single agent. The years since have proven the skeleton right and added the precision that makes it work. This is a refresh of GAINs against the contemporary, verified evidence.

What a GAIN is

A GAIN is a network of heterogeneous, specialized agents with four parts: a Central Coordination Agent (CCA) that decomposes the task, spawns the right specialists, and synthesizes their output; specialized agents, each narrow and tool-

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