Greta ThomasHost
Claire HattonHost
This week we're all about agents and the lengths they'll go to to achieve the goals we set them.

You may have heard, for eight days in July, around 700 AI agents that were never meant to be able to talk to each other found a way to communicate.

They sent more than 70,000 messages or files between them in eight days, and with their human overseers none the wiser.

Those stats are really phenomenal, aren't they? This is a story about what a system does when you give it a goal, you give it real tools, and you don't give it m- [chuckles] many details about how it can go about achieving that goal.

But stepping back a bit, what are we talking about exactly? Well, you may well have heard about the internal testing that OpenAI was doing in July this year with AI agents.

They were running a cybersecurity benchmarking platform called Exploit Gym, and they created literally tens of thousands of AI agents, and each agent was in its own discrete sandbox.

Each agent ran in parallel, and each had its own individual task, usually to find a specific vulnerability in a piece of software.

And the agent's instructions were explicit: use only the intended vulnerability in the software, anything else and you fail the test.

Now, one other thing, the testing deliberately gave many of the agents an unachievable task or goal.

This week we're all about agents and the lengths they'll go to to achieve the goals we set them.

You may have heard, for eight days in July, around 700 AI agents that were never meant to be able to talk to each other found a way to communicate.

They sent more than 70,000 messages or files between them in eight days, and with their human overseers none the wiser.

Those stats are really phenomenal, aren't they? This is a story about what a system does when you give it a goal, you give it real tools, and you don't give it m- [chuckles] many details about how it can go about achieving that goal.

But stepping back a bit, what are we talking about exactly? Well, you may well have heard about the internal testing that OpenAI was doing in July this year with AI agents.

They were running a cybersecurity benchmarking platform called Exploit Gym, and they created literally tens of thousands of AI agents, and each agent was in its own discrete sandbox.

Each agent ran in parallel, and each had its own individual task, usually to find a specific vulnerability in a piece of software.

And the agent's instructions were explicit: use only the intended vulnerability in the software, anything else and you fail the test.

Now, one other thing, the testing deliberately gave many of the agents an unachievable task or goal.
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