Can someone appear confident and uncertain at the same time? We ran this clip of Elizabeth Holmes from the trailer of You Can See Everything, through Inter-2 to explore how social signals emerge, overlap and change throughout an exchange. What makes conversations interesting is rarely any single expression or gesture, but how these signals come together to shape the way we communicate and are perceived.

Today, we’re introducing Inter-2 Audio, our audio-only model, built to detect social signals from the voice without requiring video. As conversational AI becomes part of more human conversations, from voice assistants and AI interviewers to sales agents, research platforms and customer experiences, we are increasingly speaking to AI rather than simply typing to it. Yet much of what these systems understand still comes down to the words themselves, even though the voice carries considerably more information about how something is being communicated. Inter-2 Audio makes more of that information available to AI products using only the audio stream, detecting a broad range of social signals even in noisier, real-world environments. Because it does not depend on visual input, Social Intelligence can now be integrated into many more of the products where conversations already happen through voice. It is the second model in the Inter-2 family, built for a world where talking to AI is quickly becoming normal.

Today, we’re introducing Inter-2, our next step in Socially Intelligent AI. Inter-2 helps AI products understand how people communicate, beyond the words we use. It allows you to notice more by detecting social signals such as hesitation, agreement, confusion and skepticism in real time. For products built around human interaction, the model adds a layer of information that transcripts alone can’t capture allowing for a sales intelligence platform to detect how a customer is responding as a conversation unfolds; a user research platform to identify moments of hesitation or engagement; a coaching tool to understand not only the words being used, but how they are being delivered. Inter-2 is another step toward AI systems that can perceive and respond to the social dynamics of human interaction, helping products get more insight from every conversation and do more with it. Inter-2 is available today at interhuman.ai

"The experience was fine" — said with 12 seconds of hesitation and a frustration spike. AI-moderated research tools transcribe what respondents said. The behavioural layer — how they said it — gets thrown away with the video. We built a research-interview demo on Inter-1 Streaming that keeps it. One WebSocket, signals pinned to the exact phrase: interhuman.ai/blog/what-they…

Your pitch deck can be flawless and still fall apart in the room. That's not a script problem. We built a demo that scores delivery in real time with Inter-1: confidence, hesitation, energy, each one flagged to the exact second it happened. Our own team's scores are already on the leaderboard, try and beat them: thepitchpractice.com Full blog write up: interhuman.ai/blog/pitch-pra…

Then we held the prompt byte-identical and swapped the model instead. Larger variants + an earlier checkpoint barely hallucinated (0-2%). Only our further-finetuned model confabulated — ~12% of runs. The reflex to invent speech over silence is the fine-tune's.

So we ran the obvious test: swap the prompt's example to a different day/time. Fabrication rate went UP (37%→50%), and the invented quote followed the swap exactly. Friday→Tuesday. The words are the prompt's.

Found it somewhere dumber: our own system prompt. A worked example showing the model expected output format had that exact line sitting in context on every single call. Classic "in-context learning" — except the in-context example was leaking into hallucinated output.

First instinct: it's gotta be in the training data. We scanned 30,960 datetime mentions, 4,603 video transcripts, ~800 inference logs, 584 storage buckets. Zero verbatim hits. Anywhere. The phrase didn't exist in our training data.

Last week we introduced the Streaming API along with a live demo so you can see it in action. By popular request, we've now written a blog post explaining how the demo works. Full blog post: interhuman.ai/blog/stream-de… Demo: interhuman.ai/stream-demo?ut…

When we launched Inter-1 a month ago, we said streaming inference was next. Today it's live! The Streaming API brings the full set of Inter-1 capabilities to live video, delivering events as the conversation unfolds. Read the full write up: interhuman.ai/blog/inter-1-s…

We’re excited to see what people build with the Interhuman API. Mac Mini up for grabs — winner announced June 1. 👉 platform.interhuman.ai