Humans.ai Aims to Prove AI’s Next Frontier Is Coordination
▼ Summary
– Current AI chatbots are skilled at individual tasks but lack the design for managing complex, multi-user collaboration involving coordination and long-term team alignment.
– The startup Humans& aims to build a new foundation model architecture focused on social intelligence to act as a “central nervous system” for human-AI collaboration, not just information retrieval.
– Humans& raised a $480 million seed round based on its vision and the pedigree of its founding team, though it currently has no product and its exact form remains undefined, potentially targeting communication and collaboration platforms.
– The company plans to train its model using novel methods like long-horizon and multi-agent reinforcement learning to enable planning and coordination over time, rather than just generating one-off responses.
– Humans& faces significant competition from major AI companies enhancing collaboration on their platforms and risks like high funding needs, but believes its focus on social intelligence gives it a unique advantage.
While today’s AI chatbots excel at individual tasks like answering queries or summarizing text, they fall short when it comes to the complex, real-world challenge of coordinating groups. A new startup called Humans.ai, founded by veterans from leading AI labs, believes that solving this coordination problem is the next critical frontier for artificial intelligence. The company recently secured a substantial $48 million in seed funding to develop what it describes as a “central nervous system” for an economy where humans and AI work in tandem. Beyond the common narrative of AI as a human assistant, the firm’s core ambition is more groundbreaking: to construct a novel foundation model architecture engineered specifically for social intelligence.
The company argues that the industry is shifting from a first wave focused on smart, vertical question-answering models to a second wave where users seek practical applications for these tools. “People are trying to figure out what to do with all these things,” notes co-founder Andi Peng, a former Anthropic employee. Humans.ai positions itself as a guide into this new era, aiming to move beyond fears of job displacement. This timing is strategic, as businesses transition from simple chat interfaces to more autonomous AI agents. While models have grown competent, the workflows that integrate them remain clumsy, leaving a significant coordination gap that leaves many people feeling overwhelmed.
Despite being only a few months old, the startup attracted its impressive funding based on this vision and the pedigree of its team. A concrete product has not yet been released, and specifics remain under wraps. However, the team suggests its solution could eventually serve as a replacement for multi-user platforms like Slack for communication or Google Docs for collaboration, with potential applications for both enterprises and everyday consumers.
“We are building a product and a model that is centered on communication and collaboration,” explains CEO Eric Zelikman, formerly of xAI. The focus is on enhancing how people work together and communicate, both with each other and with AI tools. He illustrates the problem with a relatable example: the tedious process of getting a large group to agree on something like a company logo, which often requires herding everyone into a room to reconcile differing opinions.
The envisioned model would be trained to interact more naturally, asking questions in a manner that feels like a colleague trying to understand a situation, rather than a chatbot mechanically querying without context. Zelikman points out that current models are optimized for immediate user satisfaction and answer accuracy, not for the nuanced value of a question within a collaborative process. Part of the development challenge is that the product and the model are being designed in parallel. “We’re able to co-evolve the interface and the behaviors that the model is capable of into a product that makes sense,” co-founder Peng explains.
The startup’s clear intention is not to create another model that plugs into existing apps. Instead, Humans.ai aims to own the fundamental collaboration layer itself. This space is heating up, with other startups like AI note-taking app Granola raising significant funds for collaborative features. Prominent thinkers like LinkedIn founder Reid Hoffman also frame the next AI phase around coordination, arguing that real leverage comes from improving how teams share knowledge and conduct meetings, not from isolated automation projects. “AI lives at the workflow level,” Hoffman has stated, noting that those closest to the work best understand where the friction lies.
Humans.ai seeks to operate precisely in that realm. Its model would act as “connective tissue” for any organization, understanding individual skills and motivations to balance them for collective benefit. Achieving this requires a fundamental rethink of AI training methodologies. The company plans to train its model using innovative techniques like long-horizon and multi-agent reinforcement learning. These approaches teach a model to plan and act over extended periods and to operate effectively in environments with multiple AI or human participants, pushing beyond one-off responses toward coordinated, multi-step outcomes. “The model needs to remember things about itself, about you, and the better its memory, the better its user understanding,” says co-founder Yuchen He, a former OpenAI researcher.
The path forward is fraught with risk. The venture will require continuous, massive capital to train and scale a new foundation model, putting it in direct competition with tech giants for resources like computing power. More critically, Humans.ai isn’t just competing with collaboration tool companies; it’s challenging the dominant AI firms themselves. Companies like Anthropic, Google, and OpenAI are already weaving AI collaboration features into their existing platforms and workflows. None, however, appear focused on rebuilding a core model around social intelligence from the ground up. This could give Humans.ai a unique advantage or, alternatively, make it an attractive acquisition target for larger players constantly seeking top talent.
The founders, however, express a commitment to independence. They claim to have already declined acquisition interest. “We believe this is going to be a generational company,” Zelikman asserts, expressing confidence in the team’s ability to fundamentally reshape how people interact with AI models. Whether they can navigate the immense technical and competitive hurdles to realize their vision of an AI-powered coordination layer remains the central question for this ambitious new entrant.
(Source: TechCrunch)
