Humans& rethinks AI: from simple chatbots to coordination models

Humans& Rethinks AI: From Simple Chatbots to Coordination Models

In recent years, artificial intelligence (AI) has undergone impressive transformations, evolving from narrowly specialized systems to universal language models capable of dialogue at a level approaching human interaction. However, startup Humans&, founded by veterans from leading technology companies such as Anthropic, Meta, OpenAI, xAI, and Google DeepMind, believes that the current focus on chat interfaces is merely an intermediate stage. The company has announced the development of foundational models of a new type, where the key element is not the ability to conduct conversation, but coordination — the capability of systems to interact effectively with each other and with humans to solve complex, multifaceted problems.

The context of AI development shows that each new wave of innovation has brought with it a paradigm shift. While early AI systems were focused on specific tasks, the emergence of large language models (LLMs) ushered in an era of interactive, dialogue-based systems. ChatGPT and its analogues have demonstrated AI's potential as an assistant capable of answering questions, generating texts, and even writing code.

However, the founders of Humans& believe that the next major breakthrough will not be associated with improving the quality of individual interaction, but rather with the development of collective intelligence. They argue that the ability of AI systems to coordinate their actions, distribute tasks, and work in synergy with other agents and humans will become the foundation for solving truly large-scale problems.

A deeper dive into the concept proposed by Humans& reveals their vision of AI as infrastructure for complex automation. Rather than viewing AI as an autonomous agent or simple conversational partner, the startup aims to create systems that can serve as orchestrators. This means developing models capable of understanding user goals, breaking them down into subtasks, assigning these subtasks to appropriate AI agents or even humans, tracking execution, and integrating results. Such an approach requires not only advanced natural language understanding and generation skills, but also deep understanding of project management principles, distributed systems, and human-machine interaction. The Humans& team, with their experience working on cutting-edge AI models, strives to create the foundation for this new era.

The implications of such a paradigm shift could be quite significant. If AI systems can effectively coordinate their actions, this would open doors to automating processes that were previously considered too complex or required high levels of human involvement. Imagine scientific research where AI agents jointly analyze vast data sets, formulate hypotheses, and plan experiments; or complex supply chains where systems optimize routes and resources in real time, accounting for numerous variables.

This could also lead to a transformation of the workplace, where humans work in close collaboration with AI teams, focusing on creative and strategic aspects, while routine and coordination tasks are delegated to machines. Humans& aspires to be at the forefront of this transformation, offering tools and platforms that will enable businesses and researchers to harness the full potential of collective AI.

In conclusion, startup Humans& proposes an ambitious vision of the future of artificial intelligence that goes beyond current chatbots. By shifting the emphasis from individual dialogue to coordination and collective interaction, they aim to lay the foundation for a new generation of AI systems. These systems will be capable not only of answering questions but also of effectively managing complex tasks, orchestrating the work of numerous agents and humans. If Humans& manages to realize its ambitions, this could become the next major step in AI evolution, opening the path to unprecedented levels of automation and synergy across diverse areas of human activity.