Thanks, "hire"-->"higher" typo fixed.

Indeed. Major quality change from prior models.

Had a nice chat with GPT-4.5 the other day about fat metabolism and related topics. Then I asked it for an optimal nutrition an exercise plan for a hypothetical person matching either I or my wife's age, height, weight, gender, and overall distribution of body fat. It came back detailed plans, very different for each of us, and very different from anything I've seen in a published source, but which extremely closely matches the sets of disparate diets, eating routines, exercise routines, and supplements we'd stumbled upon as "things that seem to make us feel better when we do them" over the course of about 7 years of self-experimentation. There were also a few simple additional suggestions for me that I'd never thought could really matter that it turned out, when I tried them, do. 

On one hand I didn't learn anything "new" except some implementation details (timing and dosage of supplements and pairings of foods, for example) and the value of combining all the pieces instead of trying them one at a time. On the other hand, it found and validated and gave good citations for a bunch of things I'm confident were not explicit or implicit in my prompts and which do not match advice I'd ever received from any "expert" source.

If you do it right, being willing to ask questions of those higher up, like said CEO, is how you get noticed, on their radar, as someone potentially worth watching and investing in and promoting in the future. A secure CEO in a healthy culture is likely to take it as a good sign that employees are aware, intelligent, and paying attention enough to ask clear, well-formed questions.

But if you ask a question in a way that offends that particular individual in whatever way, or makes your direct boss look bad to his direct boss (in either of their perceptions), then that can lead to any of those individuals retaliating in various ways, if their personality or position in the hierarchy makes them feel insecure or like that would make them look or feel better.  Asking makes you and them socially vulnerable, and being willing to do so shows you're secure in your understanding of how people will react as well as in your own position/role/status.

Since this was a Zoom meeting, the fact that you asked verbally is also in some sense a status claim, that you felt empowered to ask a question in a way that commanded everyone's attention and interrupted the CEO's talk track. It's a power move, or can be seen as such. If you'd written in a public chat channel, you'd have left it up to others when and how to respond. If you'd back-channel messaged someone higher up in your organization, you'd have given them the option to either ignore it, message you back, or ask the question in the style and at the moment they deemed most appropriate.

Or, and this is what I think happened at the math conference example, if your question is insufficiently well-formed, then a large public meeting is the wrong forum in which to ask it, because the answer may (in the opinion of those better informed) be a waste of everyone's time. Now of course a great speaker will try to hear that kind of question, figure out the source of the confusion, consider whether similar confusions are likely to be prominent among the audience, and either address that source, or gently let you know there are other factors you're missing that sidestep the question, or else point you in the direction of the info that will resolve your confusion (aka "Come ask me after, and I'll list some papers and textbooks you might want to check out on that.") But a less comfortable and capable speaker won't know to or know how to do that, and might shut you down, or get flustered.

Two other examples:

Some forums have a cultural expectation that the option to ask questions is in some sense not real, or not intended to be used, even when it looks like it should be. A colleague of mine was once asked to be on an expert panel in Korea, and asked a fellow panelist a detailed question; he was later told that was a major faux pas, because panels in that context are scripted and no one asks real questions in real time. He got a pass because he was an American and no one had thought to tell him that expectation, but it did interfere with his ability to network at that event and he didn't get invited back.

In a small upper-level college or grad school class, you're supposed to ask detailed questions. If you don't, or can't, you're probably not paying enough attention. But in an intro class of 800 students in a big lecture hall, the lecturer is often going to be pressed for time, and they'd never get through everything if students all felt free to raise questions; the proper time to do that is in office hours or a recitation with the professor or a TA. If the question is important or a lot of people ask something similar, it's their job to filter it up to mention in a future lecture.

Without a currently-implausible level of trust in a whole bunch of models, people, and companies to understand how and when to use privileged information and be able to execute it, removing the New Chat button would be a de factor ban on LLM use in some businesses, including mine (consulting). The fact that Chemical Company A asked a question about X last month is very important information that I'm not allowed to use when answering Chemical Company B's new question about the future of X, and also I'm not allowed to tell the model where either question came from or why I asked them and I have to remember every piece of information that I need to tell it not to use. Also, at least at current capability levels, "Open five chat windows and try different versions of a prompt" is actually a useful strategy for me that disappears if companies make that interface change.

There's an important reason to keep some of us around. This is also an important point.

Consequentialism tells us that the thing to do is the thing with the best results. But, this is a ridiculously high standard, that nobody can actually live up to. Thus, consequentialism tells us that everybody is bad, and we should all condemn everybody and all feel guilty. 

In these scenarios I like point out that the other party is using an appeal to consequences as the justification for rejecting consequentialism.

This, to me, gestures at a set of questions with potentially different answers.

1. If I've been living as a sexual person of any kind, should I choose to make myself ace, given the choice?
2. If I've been living as an asexual person, should I choose to change that, given the option? If so, to what sexuality?
3. If I am in something like Rawls' original position and can choose my sexuality for my upcoming life, what should I pick?
4. If I am in something like Rawls' original position and can choose everyone's sexualities for their upcoming lives, what should I pick?

(1) and (2) are individual choices where I can't think of any universally compelling reason to say yes or no for anyone else. Some choices will be more or less convenient in different societal contexts, and more or less appealing in different personal contexts.

For (3), I could see arguments to be made for either ace or bi or pan, moreso than straight or gay or anything else.

For (4) choosing ace or gay is likely to result in very low fertility rates, unless you are able to get very fine grained as to what kind of asexuality people end up with or get to tweak other drives as well. This probably leads to population collapse unless the technology level is substantially beyond ours. Straight, bi, or pan, all potentially lead to worlds that I can imagine going well.

Some of both, more of the former, but I think that is largely an artifact of how we have historically defined tasks. None of us have ever managed an infinite army of untrained interns before, which is how I think of LLM use (over the past two years they've roughly gone from high school student interns to grad student interns), so we've never refactored tasks into appropriate chunks for that context. 

I've been leading my company's team working on figuring out how to best integrate LLMs into our workflow, and frankly, they're changing so fast with new releases that it's not worth attempting end-to-end replacement in most tasks right now. At least, not for a small company. 80/20 rule applies on steroids, we're going to have new and better tools and strategies next week/month/quarter anyway. Like, I literally had a training session planned for this morning, woke up to see the Gemini 2.5 announcement, and had to work it in as "Expect additional guidance soon, please provide feedback if you try it out." We do have a longer term plan for end-to-end automation of specific tasks, as well, where it is worthwhile. I half-joke that Sam Altman tweets a new feature and we have to adapt our plans to it.

Current LLMs can reduce the time required to get up-to-speed on publicly available info in a space by 50-90%. They can act as a very efficient initial thought partner for sanity checking ideas/hypotheses/conclusions, and teacher for overcoming mundane skill issues of various sorts ("How do I format this formula in Excel?"). They reduce the time required to find and contact people you need to actually talk to by much less, maybe 30%, but that will go way down if and when there's an agent I can trust to read my Outlook history and log into my LinkedIn and Hunter.io and ZoomInfo and Salesforce accounts and draft outreach emails. Tools like NotebookLM make it much more efficient to transfer knowledge across the team. AI notetakers help ensure we catch key points made in passing in meetings and provide a baseline for record keeping. We gradually spend more time on the things AI can't yet do well, hopefully adding more value and/or completing more projects in the process.

These are very reasonable questions that I learned about the hard way camping in the desert two years ago. I do not recommend boondocking in central Wyoming in August. 

First, because when you live in an aluminum box with 1" thick R7 walls you need more air conditioning in summer than that much solar can provide. It doesn't help that RV air conditioners are designed to be small and light and cheap (most people only use them a handful of days a year), so they're much less efficient than home air conditioners, even window units. I have 2x 15k BTU/hr AC units, and can only run one at a time on my inverter (they use 1400-1800W each). On very hot days (>90-95F) I need both at least some of the time.

Second, because the conversion efficiency of silicon PV falls at high temperatures, so hot and sunny summer days are actually not my days of peak production.

Third, my batteries and inverter are unfortunately but unavoidably placed in a closed compartment with limited airflow covered in black painted aluminum. And consumer grade inverters are not great, there's something like 15-20% loss (heat generation). That means on hot days it's sometimes challenging to keep these from overheating, and running the generator to give the inverter a break while the batteries recharge can be helpful.

Fourth, in addition to low solar production in winter, electricity consumption in an RV is higher than you might expect in cold weather. The propane furnace draws electric power for the fan. Since the plumbing is exposed to air, you need electric tank and line heaters for the fresh water tank, waste water tanks, and water lines to avoid freezing. I also use electric tank warmers for my propane tanks, since when the weather drops below freezing a partially-empty 20 lb tank can't supply the steady 30k BTU/hr the furnace needs (it normally relies on ambient heat to boil off liquid propane, and at low T in a small tank that doesn't happen fast enough, which can cut supply and even freeze the regulator). On a cold winter day, I'm probably drawing an average of 300-600 watts just to keep the plumbing and furnace working well. Granted, not many people winter in an RV in Massachusetts, I'm an unusual case. I wouldn't have this problem in most of the Southwest or Florida where other RVers go.