Top Tweets for #matraix
Glad to be invited to speak at two events at AGI House last weekend and share our work on Personal Agents! π
@MatrAIx2026 @YuexingHao
#MatrAIx #PersonalAgents #Agents #AI
At OpenAI to chat about Personal Agents! And just in time for the Halloween festivities! π
@OpenAI @MatrAIx2026 @YuexingHao
#MatrAIx #OpenAI #Agent #PersonalAgent #Halloween
Excited to be invited by @Alibaba_Qwen team to give a talk about PersonalAgentEval (https://t.co/yctrXG7EMw)! Had great discussions about eval and training for Personal Agents.
@MatrAIx2026 @YuexingHao
#MatrAIx #PersonalAgents #Agents #Qwen #Alibaba #MetaMuse #OpenAIDots #ClaudeDuet #GrokBot #Hark #Instinct
πππ Great honor! Nobel prize winner, Prof. Vernon L. Smith, just joined MatrAIx as a senior advisor!!!
@MatrAIx2026
#MatrAIx #NobelPrize #Agents #PersonalAgents #AI #LLM #Google #OpenAI #Meta #Anthropic #xAI #Microsoft #Hark
What if your marketing, sales and product teams could test ideas on thousands of different customers before going to the real market?
Meet #MatrAIx from researchers at #Harvard #MIT.
They built a population of 8.3 billion persona records with 1,290 attributes.
The interesting part isn't the number.
It's the architecture:
Persona β AI Agent β Environment β Actions β Evaluation
A persona can represent different backgrounds, preferences, capabilities and behaviours.
The AI agent then acts as that persona inside a survey, chatbot, website or app.
Now think about what this could mean for GTM:
Marketing
β Test different offers and messages
β Compare concepts and landing pages
β See how different customer segments respond
Sales
β Simulate different buyer profiles
β Test sales conversations
β Discover possible objections
β Compare different value propositions
BD
β Test partnership propositions
β Explore different stakeholder reactions
β Identify potential objections before the real meeting
Product
β Test UX and features
β Find where users get stuck
β Discover problems across different user segments
And this isn't just a persona prompt.
The system can capture the actual interaction trajectory and evaluate the outcome.
That creates an interesting new loop:
Design β Simulate β Find problems β Fix β Simulate again β Real-world test
They've also released a 1M persona dataset and the code.
Synthetic users won't replace real customers.
But using them as a large-scale testing layer before real-world experiments could be a very powerful idea.
This is where AI personas get really interesting.
https://t.co/im2wVvOG0g
https://t.co/1an2CEcgGH
https://t.co/TaD9fO4F11
ΒΏUn gemelo digital de toda la humanidad? EstΓ‘ siendo muy comentada la creaciΓ³n por parte de Harvard y del MIT de #MatrAIx...pero no siempre del todo bien divulgada por algunos tuiteros.
Realmente, se trata de un simulador (uno enorme eso sΓ) formado por 8.300 millones de agentes sintΓ©ticos, definidos por 1.290 atributos de personalidad y contexto, que pueden responder encuestas, conversar con chatbots, navegar por webs o utilizar aplicaciones. Pero no son realmente personas digitalizadas, ni tampoco una muestra perfectamente representativa del planeta. De hecho, el comportamiento puede cambiar muchΓsimo segΓΊn el LLM que interprete la misma persona.
AΓΊn asΓ, es un proyecto realmente interesante, innovador y open source. Β‘AsΓ que no nos hemos podido resistir a probarlo! Hemos hecho algunas pruebas (limitadas) con preguntas sobre IA y educaciΓ³n...y otra algo mΓ‘s controvertidas.+
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