[https://futurism.com/artificial-intelligence/microsoft-satya-nadella-ai-slop](Didn’t Nadella beg people not to call it slop?)
mouthwashing_take_responsibility.gif
Then don’t invent the fucking torment nexus!
I keep shoving puppies into the shredder but all i get are shredded puppies!!
The problem is that they see people hating the torment nexus and then they assume it must be because they didn’t market it correctly.
Like "oh I guess they don’t like it because they can’t share it, let’s add a suffering multiplexer so they can enjoy it with friends and family*
*⠀for⠀a⠀small**⠀fee
**⠀might⠀not⠀be⠀small
The global nvestment in data centres for AI is a rouse, the GPUs will be repurposed for crypto based financial systems.
i (kind of) understand the crypto scam going on, and the AI center switch to crypto makes sense. but what’s the lie or angle companies make to sell the switch?
They don’t like when people use the AI trash they baked in their apps? Maybe they should get rid of it 🤔
Actions = Consequences
Oh, he’s the one running Linkedin, now it makes sense why that site, of all places, has anti-AI features now. I hope the shareholders will have mercy with his soul.
I got into this business inspired by the innovations Microsoft was exploring a decade ago. Microsoft led cloud convenience and digital platform synergy
ew
Sounds like the sort of guy who’s entire “job” is just saying things.
You need to leave!!!
I really think you should.
You don’t get to complain about the slop when you built the slop factory.
aparently these tech ceo shields thier own children from the brainrot/slop, they know its wrong its doing harm by placing them in expensive private schools away from the “brainrot”
And demanded everyone use the factory or lose their jobs.
He’s probably only complaining because it’s affecting him personally. If it was only destroying everyone else’s lives he would be happy to be an executioner. After all, he’s just following orders.
…And mandated their employees use it.
Now he’s crying they did what they were told
Remember, though: Microsoft invented the slop factory when they created Microsoft Office.
Sending useless documents back and forth via Outlook predates AI by decades.
I thought they admitted defeat, embracing the uselessness and futility of nearly all office work when they released SharePoint, but I guess they’re still just getting started 🤷
I’d give him the benefit of the doubt, because surely not everyone at microslop wants copilot everywhere, but he heads the department that put copilot into excel, so all my sympathies evaporated.
Congratulations on making me snort wine out of my nose!
Love it
most scenarios
That’s a strange way to spell “all”
Microsoft (and maybe all the AI companies) made at least few mistakes in the marketing of this technology. AI isn’t a replacement for human accountability. It still requires oversight and expertise. It is great for a first draft. It is terrible for a complete work product. Agents (with the right loops to verify accuracy) are reasonably complex - and most companies don’t have the people development infrastructure to train their teams with the right skills to build them. Honestly, AI is shining a light on how terribly businesses have been run over the last 30 years, and how lazy business leaders are.
It is terrible for a first draft if you’re aiming for something that reads like a human being’s actual thoughts. Don’t let an LLM think for you and create the first draft of “your” thoughts. At most, if you absolutely must, use it as a spell checker. But write your words yourself.
No one wants to know what ChatGPT thinks. We might want to know what you think… But only if it’s actually you doing the thinking.
Sorry but I don’t need my thoughts to write a cover letter lol
Nor do you need an LLM - someone makes a cover letter once and then you use it as a template.
It is great for a first draft
Only if the aim is towards mediocrity.
Do you aim for excellence in your first drafts? You may want to consider better effort allocation.
As my violin teacher used to say, “practice doesn’t make perfect, perfect practice makes perfect.”
If you’re not aiming for excellence every time you do something you’re practicing imperfection.
Sure man, but the vast majority of us do not work in the making beautiful sounds with violing business.
If some middle manager boss says to some minion to make a quick draft of a keynote of some random info that tangentially may make sense in one of his meetings, and the minion then goes on working on it on full attention for a day to make the beautifullest keynote of the word he did not do a draft and the boss is pissed because other shit did not get done. Having an llm quarter ass a keynote based on a prompt and two refinements is precisely the effort required for that job, any more than that is wasting time.
If the quick draft doesn’t justify the time and energy, the keynote certainly doesn’t. If the keynote is a waste of time, then the meeting is pointless. The best place for the LLM is to replace the jackass who called the pointless meeting in the first place.
I agree with you. Yet those jackasses will not be replaced any faster by us agreeing here.
If you are using a generator that combines everything (both bad and good) on the net, you will end right on the middle. If everyone that’s lazy uses the same method, your work becomes the definition of mediocre.
Nothing wrong with mediocre, I mean the corporate world is full of mediocrity and that’s what is expected in assignments.
That assumes that there is no effective way to filter good from bad. But there is - both automated heuristics and manual training does this.
LLMs absolutely produce mediocre output in some ways, but it’s not an inherent limitation caused by them “averaging” the internet. If that were the case there’d be a lot more typos, emojis and internet lingo by default. The fact that LLMs have these instantly recognisable stock ways of writing and stock phrases is a simple way of seeing that they don’t simply produce “average” output in that very naive sense.
The fact that they “average” their inputs is why there are comparatively few typos (different sources have different typos, so they average out), not too many emojis or internet lingo (again, different sources use different ones in different places, so they average away), and why they produce such tedious stock output (it’s an average of the inputs, so all the little quirks and idioms that make human communucation more vibrant have been blended away).
I’m sure there is some filtering on the inputs to try to remove the worst of it, but ultimately it’s still just taking the rest and building it’s probability tables from that, which leads to the homogenised outputs we see.
Mind you, having said there are fewer typos, the last time I bothered trying to get one to write some code, it managed to misspell a popular library name in multiple places, which gives some indication of how bad the inputs are, how bad the tokeniser is, or possibly both.
If “different typos” averaged out to “nearly no typos” the same logic would have different words average out to nearly no words. What actually happens is the model learns context, and can produce output which contains emojis in one context and not others. These contexts can be very far from the average context.
I’m afraid the upshot is you don’t understand how the models work. There is extensive filtering before training - they do not get “the entire internet” and average it. If you want to understand properly, there are a lot of resources that will let you, but I’m not going to try to do it here, so you’ll either have to believe me or be wrong, I’m afraid.
If “different typos” averaged out to “nearly no typos” the same logic would have different words average out to nearly no words.
No, because typos are irregular, so combining multiple sources does not reinforce them, whereas “words” (tokens would be a better term, because they’re not always full words) tend to be used in similar ways, reinforcing those patterns. As you say, context is relevant, an LLM isn’t just looking at the last token to decide the next, but at a much larger window. That does allow it to adjust to tone, as the probabilities of certain tokens, and so words, will depend on that tone, and the type of words used, and thus context, of a conversation. If emojis are used a lot in certain contexts, those patterns will tend to be reinforced in their training, and so produced more in their output.
As to filtering their input, at no point did I say they ingest “the entire internet”, so quoting it seems rather disingenuous. They scrape as much text as they can get, both online, and by OCRing books, as we’ve seen with the recent upset about the number they destroy. What the commercial models do with this afterwards is uncertain, as anything they say is likely to be misleading for commercial purposes. I think it’s a fair assumption that they want good quality data, however they define that, but filtering it all manually is obviously much too vast a project to do entirely manually, so it’s done heuristically, which has the obvious problem that it’ll let through low quality sources some of the time, lowering the quality of the overall data set. You only need to read the anodyne screed they produce to see how all of the little quirks and nuance that marks human communication tends to get left out, leaving LLM prose feeling rather vacuous and repetitive.
Do you even know what the word heuristic means? A heuristic is something that is just good enough. Not great, not perfect, just good enough to get the job done.
Heuristic algorithms were always going to result in LLMs that were only just good enough.
Heuristics are by definition imperfect, but they are not, generally, “just good enough”. In fact, heuristics may not be good enough for a given purpose.
Am I right that you’re not actually disagreeing with my comment?
Heuristics that aren’t good enough aren’t used for that purpose… what kind of rebuttal is this even?
It still requires oversight and expertise
Perhaps some people who don’t mind the ethics of gen AI work very hard to produce good work. But I believe that when you give people an easy, low-effort path, a great many of them will take it (regardless of the quality of the results). Training notwithstanding, a vast number of people cannot resist the lure of doing as little as possible.
Yeah I get the feeling lazy people love it, and people who work hard know it doesn’t produce very good results in most circumstances.
Unfortunately it seems a lot of managers are in the lazy group. So they assume that when employees tell them it doesn’t work very well, they think it’s because they have a “bad attitude” or something like that.
First draft of what? The AI* doesn’t know what you’re trying to make, so to use it, you first need to write a prompt to convey to it what you’re trying to convey. If what you’re trying to make takes the form of prose, there’s your first draft already; there’s nothing the AI can add other than padding and replacing your voice with a psychopath’s. But to begin with, if you have the skill to turn a first draft into a final product, it’s almost always going to be faster to just use that skill to create the first draft yourself instead of trying to convey to an AI what it’s supposed to be like. If it isn’t, it’s something that’s so easy to describe that there’s either no value in making it or those few words are already the perfect way to convey it.
Also, this just completely undermines the whole thing:
It still requires oversight and expertise.
The sole virtue AI arguably has, is its accessibility; anyone who can read and write a supported natural language, can make use of it. But the moment it starts requiring expertise, that accessibility becomes worthless. To anyone who is even somewhat serious about what they’re trying to do, that natural language interface just offers far too little control for their purposes.
*) For the purposes of this comment, “AI” refers to the kinds of natural language-driven generative AI heavily marketed by companies like Microsoft, not the general concept of artificial intelligence or even the underlying technology of those products.
This is an incredibly stupid take, can’t believe people upvoted this shit, lol
Have you not used AI agents anytime in the past 6 months?
They can pull in information that you don’t write down, it can create Powerpoint slides, it can create mermaid diagrams from your description.
Those are not things you just do manually because you can? At that point why not code in Notepad instead of relying on the stupid machine assisted IDEs?
And it is usually half right, its really a mess, unless you give it a really good rough draft outline.
I find writing the code is the easy part. The difficult part is figuring out what the requirements are, fitting together all of the data relationships, figuring out the security so the correct people and systems have access to the data. To do these things I need very specific knowledge of the systems I’m working on, knowledge the AI doesn’t have.
I could see it could give you a simple interface that’s similar to something it’s been trained on. But it’s capabilities are very limited in terms of doing anything novel. It can’t actually understand a problem, it can only give some code similar to problems that exist in it’s training data. Sometimes that’s useful, since at times I do have to solve problems that’s been solved by others. But most of the time the AI can’t understand what I’m trying to do and it’s easier to write the code than it is to try to explain to an LLM how to write the code I want it to write.
Maybe you are doing some exotic stuff, but for me it’s more than capable of writing code, coding is mostly about applying existing patterns to solve known problems, very few programmers deal with novel problems.
Design Patterns book has been out for what? 2 decades, and it’s not outdated.
For good team interoperability you want to have code that’s standardized, that’s also where LLMs excel at.
It’s a nice productivity tool, just like an IDE is a nice productivity tool
Attention driven economy. All enterprises now behave like they had a field week at used cars salesmen retreat. You can’t sell unless the value proposition is grotesquely inflated.
I have a niece working for the gov on AI… 6 months ago she was all in on it, excited about the potential… yesterday she told me she is looking for a placement in a different area because she sees zero future in these projects
Tell her to practice her cursive. Young people and machines can’t read it. That’ll come in handy in the coming forever everywhere war for humanity
Talking from experience, if you write cursively whilst having bad enough handwriting, it can become a reasonably effective form of encryption in general.
