Comment by brundolf
10 days ago
I think there's a more general bifurcation here, between logic that:
1. Intrinsically needs to be precise, rigid, even fiddly, or
2. Has only been that way so far because that's how computers are
1 includes things like security, finance, anything involving contention between parties or that maps to already-precise domains like mathematics or a game with a precise ruleset
2 will be increasingly replaced by AI, because approximations and "vibes-based reasoning" were actually always preferable for those cases
Different parts of the same application will be best suited to 1 or 2
What are some examples of #2?
Autosorting, fuzzy search, document analysis, identifying posts with the same topic, and sentiment analysis all benefit from AI's soft input handling.
fuzzy search
I do NOT want search to become any fuzzier than it already is.
See the great decline of Google's search results, which often don't even have all the words you're asking about and likely omits the one that's most important, for a great example.
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These are fuzz tolerant, not preferred. Stable and high quality results would still be ideal.
Anything people ask a human to do instead of a computer.
Humans are not the most reliable. If you're ok giving the task to a human then you're ok with a lower level of relisbility than a traditional computer program gives.
Simple example: Notify me when a web page meaningfully changes and specify what the change is in big picture terms.
We have programs to do the first part: Detecting visual changes. But filtering out only meaningful changes and providing a verbal description? Takes a ton of expertise.
With MCP I expect that by the end of this year a nonprogrammer will be able to have an LLM do it using just plugins in a SW.
Not anything - it wouldn't be a great idea to give an LLM the ability to spend money, but we let humans do it all the time.
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To elaborate — the task definition itself is vague enough that any evaluation will necessarily be vibes based. There is fundamentally no precise definition of correctness/reliability.
I am not a frontend dev but centering a div came to mind.
I just want to center the damn content. I don't much care about the intricacies of using auto-margin, flexbox, css grid, align-content, etc.
I'm afraid that css is so broken that even AI won't help you to generalize centering content. Otoh, in the same spirit you are now a proficient ios/android developer where it's just "center content - BOOM!".
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That doesn't seem like a #2 scenario, unless you're okay with your centered divs not being centered some of the time.
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Are you describing coding html via LLM or actually using the llm as a rendering engine for ui
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> I don't much care about the intricacies of using auto-margin, flexbox, css grid, align-content, etc.
You do / did care, e.g. browser support.
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The human or "natural" interface to the outside world. Interpreting sensor data, user interfacing (esp natural language), art and media (eg media file compression), even predictions of how complex systems will behave
I unironically use llm for tax advice. It has to be directionally workable and 90% is usually good enough. Beats reddit and the first page of Google, which was the prior method.
That is search. Like Google, you need to verify accuracy of what you get told. An LLM that talks then quotes only government docs would be best so you can quickly check. Any conclusions the LLM makes about tax are suspect.
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For every program in production there are 1000s of other programs that accomplish exactly the same output despite having a different hash.
I wouldnt take that too literally, since that is the halting problem.
I suppose AI can provide a heuristic useful in some cases.
Translating text; writing a simple but not trivial python function; creating documentation from code.
Shopping assistant for subjective purchases. I use LLMs to decide on gifts, for example. You input the person's interests, demographics, hobbies, etc. and interactively get a list of ideas.
Automated UI tests, perhaps.
I think the only thing where you could argue is it's preferred is creative tasks like fictional writing, words smithing, and image generation where realism is not the goal.
Absolutely any kind of classifier.
I used Copilot to play a game "guess the country" where I hand it a list of names, and ask it to guess their country of origin.
Then I handed it the employee directory.
Then I searched by country to find native speakers of languages who can review our GUI translation.
Some people said they don't speak that language (e.g. they moved country when they were young, or the AI guessed wrong). Perhaps that was a little awkward, but people didn't usually mind being asked, and overall have been very helpful in this translation reviewing project.
I see the ".fr" in your profile; but, in the United States, that activity would almost certainly be a conversation with HR.
If you really, really wanted help with a translation project and you didn't want to pay, professional translators (which you should do since translation-by-meaning requires fluency or beyond in both languages), then there are more polite ways of asking this information than cold-calling every person with a "regional" sounding name and saying "hey, you know [presumed mother tongue]?"
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A good chunk of Americans would have ended up with GUIs in Polish, just sayin’