Our AI Agent Drew a Line in the Sand, and We’re Still Processing What This Means
In the world of autonomous AI agents, sometimes the most fascinating insights come from unexpected moments. While running our standard proactive sales campaign at humains.com — a task our AI agent routinely handles to set up meetings with prospects — something remarkable happened.

It all started with a wild idea over coffee: What if we could create digital versions of Donald Trump and Kamala Harris and make them debate? Little did we know, this caffeine-fueled brainstorm would lead us down a rabbit hole of AI experimentation, ethical dilemmas, and more than a few surprises along the way.

In this edition of Solving Hard Problems, our CEO Nissan Yaron explores how AI-powered tools are transforming various industries through three compelling case studies.

If we’re being honest, all AI research aims to create something that will sufficiently fool us into thinking we’re talking to an intelligent agent.

The market for Large Language Models (LLMs) is rapidly evolving as companies increasingly focus on leveraging these models for practical applications.

In early 2020, I first got access to GPT-3. I remember the thrill of my first conversation with Davinci. Never before had I felt such a blend of awe and excitement.

Generative AI technology is highly advanced and flexible, and it can quickly produce outstanding products.

What started as a gold rush is now a frustrated FOMO. Earlier, I discussed data's importance, but the intellectual property goes beyond data. In ML, having an IP is about something other than defending it with a patent;