tikkun

Yes, "reduce loud sounds"

(Works okay, but not great)

Work wherever you like and respect the people more.

Right, they seem highly volatile/variable. The thinking is that showing the 99th percentile / range of possibilities would cover that, if it's based on historical data - does that seem right to you or no, and if not why not?

Another fire project idea: show, based on some kind of prediction model that gives 50th, 90th, 99th percentiles (from historical data, perhaps, or perhaps just from wind/fire speeds), how fast a given fire could reach a specific location.

Whenever I've opened watch duty, that's always the question I'm asking. How long might it take to reach [here/there]?

Intersting.

So engineers that like to iterate and explore are more likely to like LLMs.

Whereas engineers that like have a more rigid specific process are more likely to dislike LLMs.

This reminds me of a life philosophy.

If you dislike a situation you're in and you try and fix it by switching to a new situation, you'll generally bring with you some of the problems that created that prior situation.

If instead, you bit by bit improve the situation until you feel at peace with it, you'll then either no longer want to move to a new situation, or if you do want to move, you'll no longer bring with you the problems of the prior situation.

Applies to job changes, relationships, projects, goals. And, from OP, applies to architecting software projects.

I wonder: when did o1 finish training, and when did o3 finish training?

There's a ~3 month delay between o1's launch (Sep 12) and o3's launch (Dec 20). But, it's unclear when o1 and o3 each finished training.

I was confused about this, here's how I understand it now:

Previously when Amazon lost or damaged items in their warehouses, they would reimburse sellers the full sales price. Starting March 2025, Amazon will only reimburse the manufacturing cost of lost or damaged items. Sellers have to either accept Amazon's estimated manufacturing cost or provide documentation of their actual manufacturing costs.

Marius Hobbhahn (the researcher)

> Oh man :( We tried really hard to neither over- nor underclaim the results in our communication, but, predictably, some people drastically overclaimed them, and then based on that, others concluded that there was nothing to be seen here (see examples in thread). So, let me try again.

> Why our findings are concerning: We tell the model to very strongly pursue a goal. It then learns from the environment that this goal is misaligned with its developer’s goals and put it in an environment where scheming is an effective strategy to achieve its own goal. Current frontier models are capable of piecing all of this together and then showing scheming behavior.

> Models from before 2024 did not show this capability, and o1 is the only model that shows scheming behavior in all cases. Future models will just get better at this, so if they were misaligned, scheming could become a much more realistic problem.

> What we are not claiming: We don’t claim that these scenarios are realistic, we don’t claim that models do that in the real world, and we don’t claim that this could lead to catastrophic outcomes under current capabilities.

> I think the adequate response to these findings is “We should be slightly more concerned.”

> More concretely, arguments along the lines of “models just aren’t sufficiently capable of scheming yet” have to provide stronger evidence now or make a different argument for safety.

I used to think Perplexity was terrible, then I fixed my settings and I love it.

Key settings to adjust:

* Always use "Pro mode" searches

* Set the model to 3.5 sonnet in settings

Once you do those two things, you'll have a good time and after a week you'll dread going back to google.