tedmiston

That's why I clarified that the current clinical guidance is probably too aggressive. Severity of symptoms, length of time on the drug, etc seem to be important factors but still the side effects are very personal.

I think it is more about tapering at a tolerable rate than any particular extended duration.

It will be interesting to see how the guidelines change once they're updated.

Did you read the post at all?

Their definition is clearly stated in the first paragraph:

    Using data compiled by the federal government’s Bureau of Labor Statistics, the True Rate of Unemployment tracks the percentage of the U.S. labor force that does not have a full-time job (35+ hours a week) but wants one, has no job, or does not earn a living wage, conservatively pegged at $26,000 (in 2025 dollars) annually before taxes.

No, the strategy in Wordle of solving hard mode by guessing the target word vs in Not Wordle preserving along as possible in Not Wordle by not guessing the target word are not the same thing at all.

Huh?!

FWIW quitting any SSRI cold turkey is highly disrecommended vs gradual tapering over ~2–6 weeks but even that current guidance is probably too aggressive.

Something like one step down every 2–4 weeks or ideally hyperbolic tapering is better for neurobiology but that's also a PITA.

https://www.outro.com/blog/stopping-antidepressants-what-is-...

By playing Wordle well, you are essentially eliminating as much unknown words as possible each turn, e.g., SALET alone takes 12974 words down to 34 here today.

But this is like Wordle hard mode with the forced letters, so the optimal strategy is probably to invert and eliminate as little words as possible each turn.

I got pretty far here using weird words, but PIZZA turned out to be a terrible first guess for Don't Wordle (eliminating ~75% of the words):

    *      12974
    PIZZA   3169
    AQUAS    290
    SAWED     17
    MEASE      7
    LEASH      0

*browser extensions' job

Is this an AI generated comment?

What do any of these words have to do with a person disassembling a camera in a surveillance dragnet?

The post is overloaded with false generalizations like this.

The post is just full of half-baked conjectures masquerading as facts... combined with "things they read" by unspecified authors and sources... the author seems to prefer engaging in AI doomerism as opposing to actually understanding.

> Diseconomies of Scale. Every new technology I can think of thrived, in part, due to economies of scale, where the larger the industry grew, the more efficient it got. AI is going in the opposite direction, where every new AI model consumes more resources than its predecessors. This may turn out to be the fatal flaw – the bigger the industry gets, the more its operating costs increase.

[Agreed] Newer gens of models are more power-efficient per task, not less.

This is a low quality post full of basic errors.

this is a bizarre timeline of reality where an ME degree gets you waitlisted for an electrician apprenticeship

> Had this been a < thing it was not > we'd be seeing people going to jail over this.

"If my grandmother had wheels, she would have been a bike."

> Betteridge's law of headlines is an adage that states: "Any headline that ends in a question mark can be answered by the word no." It is based on the assumption that if the publishers were confident that the answer was yes, they would have presented it as an assertion; by presenting it as a question, they are not accountable for whether it is correct or not.

https://en.wikipedia.org/wiki/Betteridge%27s_law_of_headline...

> you are constantly not finishing today's tasks. it lives to see another day. if you can fix it, bound it to the workflow, you will be a billionaire

dual dishwashers

Allergy immunotherapy (shots) work by gradually desensitizing the immune system for your specific allergens over several years, so yes. Some people can get to the point where they no longer need a daily antihistamine, but it's all very personalized and individual.

In any case, it's worth doing the skin prick allergy shot testing so you can have some idea of what common allergens affect you and the intensity of each.

the creative inputs to the whole process and judgment aspects of telling it how to refine and edit

Definitely. One of my fav techniques is to ask an LLM to simplify something by 90% or 99% if it looks overly complicated. Or asking the output to be critically reviewed by another agent too.

pretty big leap of faith there

likewise

The adoption curve across companies and industries is highly variable right now. Tech moves fast but plenty of boring industries need software but don't move on the bleeding edge of tech / LLMs / etc.

Even in the discourse here, you can see people getting variable quality of results and variable skepticism, some of which is valid, but a lot of it reads more like not having spent time really understanding prompt engineering.

What does a random bug in one LLM's frontend app have to do with learning how to do prompt engineering well?

> What are you writing that Claude is actually writing all of it? Every time I get past the green field stage, I just end up throwing out what it writes half the time since its trash.

For the current state of frontier models, you need to break the steps down so that the LLM understands a process like what you might go through as you expect it (which is often different for everyone).

i.e., get it to agree to a spec, then get it to agree to a build plan, agree on unit test signatures, UI etc as needed, then let it build, ...

"Prompt engineering"

> LLMs (at least today’s) don’t build simple solutions ...

... by default.

> One area where I feel safe saying they are “wrong”, rather than just going with a different assumption that was left unsaid, would be when it makes up API endpoints. It sees the general pattern in an API, then makes up an endpoint that sounds good, follows the pattern, but isn’t actually implemented.

I remember seeing this maybe 6+ months ago, but using paid plans, RAG, and a high thinking mode has eliminated a ton (almost all) of those kinds of hallucinations. Open models and free tiers are not there yet though.

> I’ve also seen a lot of issues with co-workers using an LLM to write their readme files. I look at the readme for what return values I should get, go to use them, and get an error. I check the code, and sure enough, none of the variables in the readme exist. The LLM just through they sounded good. Things like this I would say are pretty objectively wrong.

LLMs don't co-sign the quality of PRs though — your coworkers do. It's not unusual for docs to get oudated and not be maintained enough in small codebases, but that's not an LLM specific problem.

They work in that they induce taking more breaks (20/20/20 rule) but they're also annoying in that they interrupt deep focus. If the latter can become a bit smoother about not interrupting deep focus context, then they'll be more helpful.

Time Out is okay but extremely annoying in that it always seems to pop up and take over the screen at the worst possible times even with configuration to make it less interruptive. I stopped using it in favor of just closing my laptop for a bit with that.

It could be a lot better if it understood the focus context better, but it doesn't do that today. Hopefully LookAway is better at that.

> I work with one guy who's just completely lost the ability consensus-build ideas with human beings. When he reaches consensus with his AI assistants on a design, analysis, plan of action, etc., he's extremely resistant to considering any other options or accepting any other input. When people do push back, he ...

To me this reads like a personal resistance to feedback / resistance to behavior change or a very jr eng more than agent related. Code isn't sacred — LLMs often easily generate absurdly overcomplicated garbage spaghetti code, but this appears to be getting better, and they are "steerable" towards better outputs with a few rounds of revisions, and some light process around a light spec, TDD, etc.

Well that's a Silicon Valley level pivot

you can do the period trick:

> . http://example.com .

https://www.idownloadblog.com/2024/03/15/how-to-send-links-w...

I generalized the statement from one cloud to big public clouds categorically to show by hyperbole that ... what difference does it make?! [One can find analogous critiques of Azure, GCP, etc.]

Last year, AWS did ≥ $100B in revenue across millions of customers. But where do you draw the line exactly? "Everyone who uses < thing > is < problematic >" feels extreme.