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Comment by senordevnyc

10 days ago

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.

    • > fuzzy search

      > I do NOT want search to become any fuzzier than it already is.

      For a specialized shop site you may want it. Search term: "something 150", the client is looking for a 1.5m something, if you're doing an exact text search your search engine will give you a lot of noise. Or you'll have to fiddle with synonyms, dictionaries and how you index your products with a huge chance to break other types of search queries.

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    • I want both fuzzy search and exact search. Google still has the "I'm feeling lucky" button, so it can support multiple search buttons. It could default to fuzzy search and have an "I'm feeling unlucky" button for exact search.

    • I don't necessarily want search to become any fuzzier than it already is either, but what's happened has happened and I've already responded to the decline of traditional search engines. Nowadays I pretty much only search duckduckgo with site:(something), or else I ask perplexity the question and for some links. Traditional search engines now just give a thousand SEOed-to-death articles, probably generated by ai, from hundreds of pointless third party websites that just have the same basic milk.

      It might be that it's worth it to bifurcate soon. Search indexes and AI engines, doing different roles. The index would have to be sorted with AI though - to focus on original and first-party material and to downrank ad-driving slop.

  • 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.

    • With suitable safeguards or limits on what it can spend why not? On the one hand it might not fear repercussions as a human would, on the other hand it’s far less likely to embezzle funds to support its overly lavish lifestyle or gambling addiction.

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    • I don't know about you, but even as a senior engineer, my employer hasn't given me the ability to spend money :-) It's not something employers normally do.

      And as was pointed out, if you use something like MCP, you can control what it spends on. You can limit the amount, and limit to a whitelist. It may still occasionally buy the wrong thing, but the wrong thing will be something you preapproved.

  • 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!".

  • That doesn't seem like a #2 scenario, unless you're okay with your centered divs not being centered some of the time.

    • looking at most websites, regardless of how much money and human energy has been spent on them:

      yes I think we're okay with divs not being centered some of the time.

      many millions have been spilled to adjust pixels (while failing to handle loads of more common issues), but most humans just care if they can eventually get what they want to happen if they press the button harder next time.

      (I am not an LLM-optimist, but visual layout is absolutely somewhere that people aren't all that picky about edge cases, because the success rate is abysmally low already. it's like good translations: it can definitely help, and definitely be worth the money, but it is definitely not a hard requirement - as evidence I point to the vast majority of translated software.)

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    • I could imagine a vision-enabled transformer model being useful to create a customizable “reading mode”, that adjusts page layout based on things like user prefs, monitor/window size, ad recognition, visual detail of images, information density of the text, etc.

      Maybe in an alternate universe where every user-agent enabled browser had this type of thing enabled by default, most companies would skip site design all together and just publish raw ad copy, info, and images.

  • Are you describing coding html via LLM or actually using the llm as a rendering engine for ui

    • Neither. They're describing the philosophical similarities of:

        * "Has only been that way so far because that's how computers are" and
        * "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."
      

      Centering a div is seen as difficult because complexities that boil down to "that's just how computers are", and they find (imo rightful) frustration in that.

  • > 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.

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.

    • I think you miss my point. A 100% accurate llm would also be helpful, but is a different use case. Sometimes the tax guidance are incomplete or debatable. Sometimes reasonable, plausible, or acceptable is the target.

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.

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.

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]?"