Measuring AI progress has usually meant testing scientific knowledge or logical reasoning – but while the major benchmarks still focus on left-brain logic skills, there’s been a quiet push within AI companies to make models more emotionally intelligent. As foundation models compete on soft measures like user preference and “feeling the AGI,” having a good command of human emotions may be more important than hard analytic skills.
One sign of that focus came on Friday, when prominent open-source group LAION released a suite of open-source tools focused entirely on emotional intelligence. Called EmoNet, the release focuses on interpreting emotions from voice recordings or facial photography, a focus that reflects how the creators view emotional intelligence as a central challenge for the next generation of models.
“The ability to accurately estimate emotions is a critical first step,” the group wrote in its announcement. “The next frontier is to enable AI systems to reason about these emotions in context.”
For LAION founder Christoph Schumann, this release is less about shifting the industry’s focus to emotional intelligence and more about helping independent developers keep up with a change that’s already happened. “This technology is already there for the big labs,” Schumann tells TechCrunch. “What we want is to democratize it.”
The shift isn’t limited to open-source developers; it also shows up in public benchmarks like EQ-Bench, which aims to test AI models’ ability to understand complex emotions and social dynamics. Benchmark developer Sam Paech says OpenAI’s models have made significant progress in the last six months, and Google’s Gemini 2.5 Pro shows indications of post-training with a specific focus on emotional intelligence.
“The labs all competing for chatbot arena ranks may be fueling some of this, since emotional intelligence is likely a big factor in how humans vote on preference leaderboards,” Paech says, referring to the AI model comparison platform th …