This seems fundamentally unsuitable for its stated purpose, which is “understanding human behavior”.

While it may, as it says, produce “convincing interactions”, there is no basis at all peesented for believing it produces an accurate model of human behavior, so using it to “understand human behavior” is at best willful self-deception, and probably, with a little effort at tweaking inputs to produce the desired results, most often when used by someone who presents it as “enlightening productivity and business scenarios” it will be an engine for simply manufacturing support for a pre-selected option.

It is certainly easier and cheaper than exploring actual human interactions to understand human behavior, but then so is just using a magic 8-ball, which may be less convincing, but for all the evidence supporting this is just as accurate.

It looks like this defaults to GPT-4o: https://github.com/microsoft/TinyTroupe/blob/7ae16568ad1c4de...

If you're going to try this out I would strongly recommend running it against GPT-4o mini instead. Mini is 16x cheaper and I'm confident the results you'll get out of it won't be 1/16th as good for this kind of experiment.

Here's a quick way to start this running if you're using uv:

    cd /tmp
    git clone https://github.com/microsoft/tinytroupe
    cd tinytroupe
    OPENAI_API_KEY='your-key-here' uv run jupyter notebook

    OPENAI_API_KEY="$(jq -r '.openai' "$(dirname "$(llm logs path)")/keys.json")" \
      uv run jupyter notebook

I love jupyter notebooks. And, I'm amazed that a company like Microsoft would put a notebook front and center that starts off with a bunch of errors. Not a good look. I really think you can improve your AI marketing by a lot by creating compelling jupyter notebooks. Unsloth is a great example of the right way.

https://github.com/microsoft/TinyTroupe/blob/main/examples/a...

Here's the punchline from the Product Brainstorming example, imagining new AI-driven features to add to Microsoft Word:

> AI-driven context-aware assistant. Suggests writing styles or tones based on the document's purpose and user's past preferences, adapting to industry-specific jargon.

> Smart template system. Learns from user's editing patterns to offer real-time suggestions for document structure and content.

> Automatic formatting and structuring for documents. Learns from previous documents to suggest efficient layouts and ensure compliance with standards like architectural specifications.

> Medical checker AI. Ensures compliance with healthcare regulations and checks for medical accuracy, such as verifying drug dosages and interactions.

> AI for building codes and compliance checks. Flags potential issues and ensures document accuracy and confidentiality, particularly useful for architects.

> Design checker AI for sustainable architecture. Includes a database of materials for sustainable and cost-effective architecture choices.

Right, so what's missing in Word is an AI generated medical compliance check that tracks drug interactions for you and an AI architectural compliance and confidentiality... thing. Of course these are all followed by a note that says "drawbacks: None." Also, the penultimate line generated 7 examples but cut the output off at 6.

The intermediate output isn't much better, generally restating the same thing over and over and appending "in medicine" or "in architecture." They quickly drop any context this discussion relates to word processors in favor of discussing how a generic industrial AI could help them. (Drug interactions in Word, my word.)

Worth noting this is a Microsoft product generating ideas for a different Microsoft product. I hope they vetted this within their org.

As a proof of concept, this looks interesting! As a potentially useful business insight tool this seems far out. I suppose this might explain some of Microsoft's recent product decisions...

https://github.com/microsoft/TinyTroupe/blob/main/examples/p...

So fucking sad that the use of AI is for... manipulating more humans into clicking on ads

Go get a fucking life, do something for the climate and repairing our societies social fabric instead

Needs openai or azure APIs. I wonder if it's possible to just use any openapi-compatible local provider.

I envision a future where ads are llms targetized. Is this worst or better than what we have now?

This is really cool. I can see quite a number of potential applications.

Could this be applied to mass propaganda and disinformation campaigns on social networks?

Like not only generating and testing narratives but then even use it for agents to generate engagement.

We've seen massive bot networks unchecked on X to help tilt election results, so probably this could be deployed there too.

Actually Sburb.

How do I get the schizophrenic version of this

Hmm, now lets see if there is an effort anywhere to link it to a local llm.

Might help GRRM finish his books.

Written by George Hotz?