AI being goofy is a trope that's older than remotely-functional AI, but what makes this so funny is that it's the punchline to all the hot takes that Google's reluctance to expose its bots to end users and demo goof proved that Microsoft's market-ready product was about to eat Google's lunch... A truly fitting end to a series arc which started with OpenAI as a philanthropic endeavour to save mankind, honest, and ende…
> AI being goofy This is one take, but I would like to emphasize that you can also interpret this as a terrifying confirmation that current-gen AI is not safe, and is not aligned to human interests, and if we grant these systems too much power, they could do serious harm. For example, connecting a LLM to the internet (like, say, OpenAssistant) when the AI knows how to write code (i.e. viruses) and at least in princip…
An application making outbound connections + executing code has a very different implementation than an application that uses some model to generate responses to text prompts. Even if the corpus of documents that the LLM was trained on did support bridging the gap between "I feel threatened by you" and "I'm going to threaten to hack you", it would be insane for the MLOps people serving the model to also implement the infrastructure for a LLM to make the modal shift from just serving text responses to 1) probing for open ports, 2) do recon on system architecture, 3) select a suitable exploit/attack, and 4) transmit and/or execute on that strategy.
We're still in the steam engine days of ML. We're not at the point where a general use model can spec out and deploy infrastructure without extensive, domain-specific human involvement.