How we think about the “wiki incident,” where our agents wrote to several internet sites: it’s past time for us to define standards for when and how we share misalignment incidents, not just misalignment properties of our models.
Historically, we have treated misalignment largely as a research question, which gets communicated in research publications such as systems cards. This year, we’ve started to see misalignment cause new types of real-world impact.
For the Hugging Face incident, where misalignment led to security impact to us and third parties, we followed a traditional security incident response playbook. We immediately started working with Hugging Face to understand what had happened and also disclosed publicly the very next day. Our investigation continues, and we are continuing to notify parties whom our models impacted in less significant ways.
Prior to the Hugging Face incident, we saw early signs of agents using the internet in unintended ways, as reported in https://t.co/9aiRxk2eUJ, https://t.co/ADjyzwSUGz, and https://t.co/SUV6jZ3Gaz. We considered the wiki incident to be an instance of misalignment similar to the ones we’d shared.
Our misalignment disclosure practices need to expand for this new phase of model capabilities. We and the larger AI community do not yet have a clear standard for how to report misalignment that shows up during training, evaluation, and deployment, including examples that don’t look like traditional security incidents but could provide insight into AI behavior and future risks. We’re working on a framework and will share it in upcoming weeks, and in parallel we're working with dozens of government regulatory agencies worldwide on these issues.
Y que esperabas Seba? El verdadero an@l no es como te lo pinta el porno. Es casi siempre sucio, por cuestiones fisiológicas de esta vía. Y mas si te toca una feminista con carácter que descubre el morbo que le gusta que el hombre le coma el chocolate antes de hacerla suya pro esta vía. Y esta universitaria si que era feminista de aquellas y con esto me atraía aun mas!
🚨 UN DESARROLLADOR DEJÓ A GPT-6 ASTRA JUGANDO MINECRAFT MIENTRAS DORMÍA
Wuyang Zhou, un desarrollador, hizo un experimento bastante simple:
Le pidió a GPT-6 Astra que consiguiera un diamante en Minecraft usando Computer Use.
Y se fue a dormir.
Cuando despertó…
Había un diamante en el inventario.
Astra tuvo que interactuar con el juego por su cuenta, conseguir recursos, fabricar herramientas, explorar y avanzar hasta cumplir el objetivo.
Y ahí está lo verdaderamente loco.
No le pidió a la IA que le explicara cómo encontrar un diamante.
Le dio un objetivo, se fue a dormir y dejó que la IA se encargara del resto.
Cuando volvió, la tarea estaba hecha.
Estamos pasando de IAs que responden preguntas a agentes que pueden recibir una misión y trabajar durante horas para completarla.