ineedasername

Yes, not everyone will be able to launch a swarm of agents and a few billion tokens, but scientific research has always had areas where the most advanced tools were beyond the reach of every scientist who might like to have access.

It also shows the same reasoning error mode many criticisms of a precautionary initiative or intervention to a problem:

Assuming that a problem whose trajectory was at a certain place when the initiative began has failed simply because it isn't solved on their own wished for timeline or standard of success, or that it wasn't meaningfully changed from what itnwod otherwise have been.

What happened to realizing there are hard problems, that different things may need to be tried, or that those things tried were partial but not complete solutions?

Perhaps that shouldn't be seen as failure when delivering even what they have done in a short period of time has required AI capable of causing these problems? Imagine if they were even more effective with more consistent results?

"They've failed" in the context of interpreting their actions w. calls for regulation as a purely cynical result of models increased capabilities has a little too much contradiction in it to my thinking. I won't venture a guess on where purely retreats back and some legitimate concern on their part fills in the gap but it's difficult not to see some. And in Anthropic's case it's also a little more consistent with what they've always said- as well as how they've acted at times, which is how they've ended up on the US blacklist of suppliers.

To be clear, I did not create the course itself. I had discretion on the specific material and approach to the course so long as it fit appropriate catalogue requirements: a multidisciplinary offering on the use of language to manipulate & persuade.

My own implementation had 3 pillars, with a central, loose thesis: Fundamentally, propaganda consists of poor arguments made in some way incomplete, incorrect, or insincerely, and simply learning to recognize their hallmarks is a 1st line defense against it. The first pillar used an excellent book, Logical Self Defense, as the foundation and I tried to entertain as best I could while hammering home its tenets on logical fallacies, premises, sufficient claim support, etc. The second pillar was a little light psychology and cognitive science. Influence techniques, psychological studies, cognitive blind spots, Benjamin Libet's readiness & awareness experiments, eye tracking saccades, even a live demonstration on the ease of implanting false memories through word choice. The message being that the human mind isn't perfect, it takes shortcuts, and care & awareness of that fact are the minimum requirements to avoiding some of it. The third pillar was simply case studies in propaganda. Readings, movies, news stories, as long as it didn't derail conversation I changed things to whatever was most topical at the time.

Ruthless pruning is unneeded with an LLM and it can take me twice the time to say half as many words.

And, early in the ‘GPT era, I hadn’t unchecked the “allow your chats to be used in future training etc” box, and definitionally they are longer and denser than others’ prompts in such raw scrapings of training materials…

Sorry.

This seems an incorrect assumption, or at least a conclusion built on incomplete information and consideration of additional factors. The first one that comes to mind is that these customers will on average be the heaviest users. That doesn’t make them less valuable, that makes them the exact ones most like to be willing to refer others to your product and the most able to do so with specifics on their recommendations and, hopefully, a positive endorsement of the service received, not just the product features.

This implies another aspect as well: even if good support weren’t to get you wider positive awareness, poor customer service and even average service that nonetheless has more negative recommendations to other can lose you business, and that too can have a compounding effect.

In general there’s also no getting around the fact that a smaller number of people will (or should) have disproportionate support requests, unless you’ve got a very homogeneous user base with homogenized use patterns. Or your products &/or documentation are of poor quality.

It’s probably not a bad idea also to take most support requests that aren’t inherently specific to a customer and require intervention as an opportunity & need to review your documentation, perhaps auto surface the most relevant bits it when a person submits a request with a an option “if this answered your question click here and we’ll mark your message as resolved, otherwise we have it, and will be in contact with”.

There’s no getting around the need to provide support and it’s possible for some businesses there could be an ideal global min/max that provides least effort & service cost for then elasticity of price & quality and customer tolerance, but I think if you find yourself in the mindset of “what’s the worst I can get away with” instead of “most I can afford to optimize long term contentment and good will referrals, you could be looking at things wrong. I’m not sure what “relationship” should mean in any case, if not something like what I’ve described.

Those poor battlefields. How rarely it is that anyone thinks of their needs.

So... Bullet anthropomorphizing is also a thing.