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Just a reminder LLMs are incapable of even counting. They are a statistical model figuring out which tokens are most likely to appear next based on previous tokens.
Putting copilot in excel makes no sense whatsoever and MS must know people will use it and get completely wrong results.
…peak technology, gentlemen!
remember when Kirk had to outsmart ai using paradoxes? could have asked it about strawberries
That is different. It’s because you’re interacting with token-based models. There has been new research on giving byte level data to LLMs to solve this issue.
The numerical calculation aspect of LLMs and this are different.
It would be best to couple an LLM into a tool-calling system for rudimentary numeral calculations. Right now the only way to do that is to cook up a Python script with HF transformers and a finetuned model, I am not aware of any commercial model doing this. (And this is not what Microshit is doing)
Even better. They are incapable of discerning correlation vs causation, which is why they give completely illogical and irrelevant information.
Turns out pattern recognition means dogshit when you don’t know how anything works, and never will.
The only thing, beyond laughing at it being dumb or making silly pictures that I don’t really care about, that I’ve found as an actual useful use for this wave of AIs is basically “pretend you’re an expert in whatever field you’re being asked about, and that you’re talking to a moderately less experienced professional, and give a very brief description of the topic, focusing on what the user can lookup on their own instead”.
As an example, I asked it about designing some gears for a project. It told me I used a word wrong and the more precise term would give me better search results, defined a handful of terms I’d run into, and told me to buy a machinery handbook or get a design table since the parameters are all standardized.
The current approach isn’t going to replace thinking for yourself, but pattern recognition can do a good job seeing that questions about X often end up relating to A, B, and C.
Oh, and I also got Google’s to only respond as though it’s broken and it made it really fun to try to figure out the news through it’s cryptic gibberish. A solid hour of amusement, and definitely worth several billion dollars of other people’s money.
Somehow this reminds of a meme thread that just popped up wherein there are a lot of people proudly declaring their inability to study and claiming that the mere suggestion that one should read the manual as a first step to solving a problem is actually very offensive.
That’s not far off from reality, where normies laugh at you for suggesting they read the manual of the 21st century appliance (basically a computer) they spent hundreds/thousands purchasing.
Soon the ridicule will be replaced with offense, then “straight to jail” shortly after.
My only issue with RTFM is how often the manual is absolute dog shit, written by some engineer whom assumes knowledge only an engineer would already have.
It could, theoretically, be useful if they just made it a working manual for the software.
ie. “How do I connect these columns to a pivot table.”
But that doesn’t sell software like 'Replace your workers with AI!" (even though it can’t replace anything)
They seriously did this? FFS, they literally killed one of the few things MS still had going for it.
I disagree in that it’d be useful to find stuff in a limited set or automate some repetitive tasks. You can probably finagle some combination of a chatbot and a limited set of scripts into automating some common but complex tasks or at least helping you find out where the tools are or what they do.
That’s not how AI companions on spreadsheet software seem to work, though. They seem to have just plugged in the chatbot to the raw, unfiltered set of data and functionality, told the LLM to do its best to do what it’s told and called it a day. This goes for both MS and Google, for the record.
It’s pretty useless that way. I don’t know who convinced devs that the way to implement this was to go maximal and live with the failure rate instead of going narrow and keeping things under control, but it was a mistake.
Let’s jam a thing that is frequently wrong into absolutely everything!
it’s not only wrong, but also incredibly expensive to run wrong.
“The next version will be totally better bro, just trust me bro, it will all work out bro, gimme another billion dollars bro.”
i used to call it “investor scams” then they coined “vaporware”, 99% of AI advancement is pure investor scams.
Frequently is an undersell
I suppose I’m gonna have to be “that guy” again:
40 years ago, Microsoft did not “invent Excel”. They developed yet another spreadsheet application and called it “Excel”, presumably in a moment of coke-fueled hubris. (I mean, seriously, “Excel” as a product name? We don’t think about that much these days, because we have gotten used to that name, but if you didn’t already know about MS Excel, how high on your own supply do you need to be to call a software product that?)
The actual invention of the spreadsheet was done by other people. The earliest example was probably Visicalc for the Apple II, and a more prominent example predating Excel was Lotus 1-2-3.
Sorry to be so nitpicky, but urban legends like “Microsoft invented the spreadsheet”, “Microsoft invented word processors”, “MIcrosoft invented operating systems”, “Apple invented GUIs”, “Apple invented the computer mouse”, “Apple invented portable MP3 players”, “Apple invented smartphones” and the like form the base for some very distorted narratives about how our world works, and I don’t like it.
I’m a bit confused by your post. Who is actually making the claims you’re refuting? I don’t see anyone saying anything about the invention of spreadsheets at all
Separately, I always just assumed that “Excel” was a pun on the fact that it handles cells
Excel is an excellent name for the software and I have no idea why they dedicated so much of their rant to it. If you want to talk about high on your own supply, look at Apple’s…well, anything, but iwork in particularly.
Well, just so we’re clear, the competition included WordPerfect and Lotus Symphony.
Excel feels right in line with that.
It makes some sense. At the time computer stuff was office stuff. They named software suites the same way they named photocopiers and desk lamps. “Ah, yeah, here’s our LightMaster 2000 model. Really the best photons for your eyeball productivity. Please consider our Lightbulb Pro expansion as well”.
The 80s were wild, because you were out there playing some videogames and then suddenly stumbled upon a bunch of accessories and content clearly meant for a balding, extremely sexually frustrated man in their late 40s.
Don’t ask me if that was better or worse than living in a swamp of content intended exclusively for 12 year olds. I’m not ready for that question.
Why do you have to be that guy? Neither the OP nor any commenter has said that Microsoft invented spreadsheets, or even vaguely implied it. You’re arguing with the void.
40 years ago, Microsoft did not “invent Excel”.
Indeed. They invented Multiplan. Which they later renamed to Excel when they ported it to their system (it was a MacOS thing originally).
Old Excel team: Added a 3D racing game for no reason
New Excel team: Added spyware for no reason
Clippy: Just wanted to help
Item 2025 ($ millions) Non Cash Flow Expenses (81.3) Operating Profit (Loss) (121.3) Profit / (Loss) after Tax (70.6) Something that would look pretty believable in this spreadsheet if it had the label “Taxation Credit / (Charge)” (0.8) Net Debt (27.1) Switch to pandas
Just once I want to see a scenario where an LLM is the better tool for everyday computing. Maybe I’m just bad at technology, but ever task I’ve tried has been more effort for a worse result.
It’s pretty helpful for coding, when used responsibly
It’s probably going to cripple the industry though. Junior developers are just not getting brought on
Jesus Christ 🤦♂️
MS puts out an “LLMs suck at this” and y’all lose your mind.
i mean, if it sucks at this, why put it in lol
(rhetorical question, it’s to please investors, i know)
One of the absolute best uses for LLMs is to generate quick summaries for massive data. It is pretty much the only use case where, if the model doesn’t overflow and become incoherent immediately [1], it is extremely useful.
But nooooo, this is luddite.ml saying anything good about AI gets you burnt at the stake
Some of y’all would’ve lit the fire under Jan Hus if you lived in the 15th century
[1] This is more of a concern for local models with smaller parameter counts and running quantized. For premier models it’s not really much of a concern.
Because it’s good at other things like creating tables and fully utilizing all features that users typically aren’t informed or practice on. Being able to describe a table and how you want to layout data for the best results is helpful.
