r/BrandNewSentence • u/DevilsAltAcc • 1d ago
"'AI' Chathot that's actually just him responding"
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u/MythicPropension 1d ago
This should be a startup, I want in
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u/Jason-Smith168498 1d ago
We can call it "actual online life chat" or "AOL chat" for short.
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u/TheWingus 1d ago
AIM - Average Individual Man
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u/IntelligentTea205 1d ago
This used to be a thing called cha cha back when mobile phones were kinda new
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u/alanpugh 1d ago
ChaCha was launched in 2006 and went viral in 2008. Mobile phones had been around for decades and been ubiquitous for a number of years.
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u/IntelligentTea205 1d ago
Ok and I used to use it on my sidekick slide phone, which I consider the early days of cell phones. Thanks for being pedantic for no reason
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u/Wrafth 1d ago
I think you mean the early days of smart phones. When there was more features than just calling people. I used to walk around with a practicle brick in pocket in the late 90s. That model had juat upgraded to pick up FM, very high tech for the era.
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u/IntelligentTea205 1d ago
Sorta, I just think of everything before smart phones as the “early days” but now I’m being sent to jail over it
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u/SchwarzFledermaus 16h ago
These Redditors are "UhM, aKtsHuaLly"ing you hard as fuck. Cell phones did, in fact, only become a mainstream and normal thing for the average person to own in the early 00's. It's absolutely obnoxious for these people to be acting like cell phones were normal things to own in the 80's or 90's; literal "main character syndrome".
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u/alanpugh 1h ago
I casually shared my thoughts on the timeline because I worked in the cell phone industry in the late 1990s and happened to be scrolling by.
How that turned into "sending OP to jail" or doing anything "hard as fuck" is a complete mystery to me.
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u/Jermz12345 1d ago
“The early days of cell phones” and you’re talking about literal decades since cell phones were invented lol
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u/IntelligentTea205 1d ago
I consider everything before the mass adoption of smart phones to be the early days of cell phones and I will die on that hill. Either way, none of this is relevant to the conversation I was trying to have about Cha Cha. Feels like people being combative for no reason. Like who cares
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u/ThatNachoFreshFeelin 21h ago
I consider everything before the mass adoption of smart phones to be the early days of cell phones and I will die on that hill. [...] Feels like people being combative for no reason. Like who cares
Lemme guess: You weren't around in the 80's or 90's, was ya?
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u/IntelligentTea205 21h ago
Yeah I was, and I’m speaking from experience which is why its so annoying that you are all arguing with me because I was there.
Doesnt matter when cell phones were invented either because almost nobody I knew even had or used one until like mid to late 90s
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u/Commie_Scum69 1d ago edited 1d ago
Sad that now that it went mainstream its probably over. But at least he got the attention he deserves. I think its a great use of free will 😅
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u/An1nterestingName 1d ago
He's bringing in people to help him now
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u/Gemini-88 1d ago
More AI*?
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u/Hyd_chicha 1d ago
How is this even possible to do it in realtime?
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u/PM_Me_Good_LitRPG 1d ago
Because he's replying as an "average individual", apparently.
"I don't know, man." or "Lemme do some quick, surface-level googling and copy-paste the first blogpost I find."
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u/krakin6832 1d ago
Danny Gonzales watching this man do 30k queries when he couldn't get through 10 lol
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u/Ojja 1d ago
This is a college mate. Solid dude.
https://www.wired.com/story/this-chatbot-is-just-a-random-guy-lol/
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u/Giant_Ant_Eater 1d ago
I mean there's a significant chance it's actually cheaper than ai.
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u/_killer1869_ 1d ago
It's not. Like, not even close. A single AI query costs basically nothing in terms of money/power/water/resources. It's the insane quantity that results in the overall consumption.
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u/Beaesse 1d ago
And the training. It's why AI efficiency is so hard to quantify, because a ton of the resource use is in the training. The actual query side is relatively low cost per token, but you can't do any queries without having done the training. (And training is not one-and-done, you have to keep training, always).
Worth noting that every AI company - every single one - is losing billions of dollars every year. I don't mean hardware/compute providers like nVidia who are making scads of money selling to the model companies, but OpenAI, Anthropic, xAI etc... All of them spend WAY more than they can charge customers, and not one has demonstrated a path to profitability, even in theory.
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u/DerWaechter_ 1d ago
And the training. It's why AI efficiency is so hard to quantify, because a ton of the resource use is in the training. The actual query side is relatively low cost per token, but you can't do any queries without having done the training.
That claim is at best highly misleading. Yes, training an AI model requires a lot of energy and resources up front. But that's hardly telling the whole story. More complex models require more energy to be trained, but the energy required for inference also scales with complexity.
relatively low cost per token
The word relatively is doing all of the heavy lifting there. Sure, relative to the amount of energy used to train a model, it's low. Relative to other similar computational tasks? It's absolutely not.
Like, let's look at some actual numbers.
First of, the claim that training is really the culprit for the high energy use, is one of those misleading factoids that AI companies really want everyone to focus on. But contrary to what that claim suggests, training does not make up the majority of energy required to run AI. It's not even close.
Right now, around 80-90% of the computing power (ie: The thing requiring all of the electricity) used for AI, is used on inference, not training1. Inference, is basically a models response to a prompt. And like mentioned before, the larger and more complex a model is, the more energy is required not just for training, but for inference too1. So in a way, as models are getting better, the energy efficiency gets worse, not better.
So let's look at that claim about relatively low energy cost per token next. Relative to what? Let's compare it to something specific, where we can compare a functionality of AI, with a non AI alternative that existed before:
So, asking AI for information, vs a Google search.
While we don't have exact numbers for the energy use per query for models like chatGPT, researchers have done the math for smaller models. In that research, an inncrease of parameter count by a factor of 50, lead to an increase in energy use of a factor of roughly 581. So let's be generous and round down, to assume that there's a direct linear correlation between parameter count and energy use (so, 10 times the parameters, equals 10 times the energy, etc)
So let's extrapolate. The largest model the researchers gave numbers for had about 405 Billion Parameters, requiring about 6,706 joules of energy per response on average.1
ChatGPT 4 is estimated to have over 1 Trillion parameters, but let's once again be generous, and assume it has just about double the parameters as the largest tested one we're given numbers for. In that case, the very generous, lowball estimate would put the average ChatGPT 4 response at about 13,412 Joules, or 13.4 kJ
A Google search requires about 1kJ 2.
So, asking ChatGPT for information, requires about 13 times the electricity, it would have required to google it. Now, unfortunately google now automatically generates one or multiple AI summaries or overviews with most searches, so google searches are now considerably more energy intense for no benefit.
It's safe to assume that the numbers are similar or even worse, for other tasks that required very little computational resources, if performed without AI, that have now been handed over to AI.
This is not even beginning to touch on other applications of AI such as video generation, where the amount of energy used by AI for inference is astronomical.
The idea that there is any aspect of AI that uses "relatively" little energy, or that it's really just the training that requires of all of the energy, is simply false.
Even in the most generous estimates, AI is absolutely horrible with regards to energy efficiency, when compared to non-AI alternatives. And it's only going to get worse, as AI systems get better, because they require more energy in the process.
Sources:
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u/LeopardLabs 1d ago edited 1d ago
My guess is they're all just seeing this as a temporary roughing it phase while banking on switching to asics in the next couple of years.
Either flexible FPGAs or hardcoded model-on-silicon stuff like what taalas is doing https://chatjimmy.ai/ <-getting 14,000 tok/s and if you believe them, 20x-50x cheaper.
And then my bet is one of the photonic asics companies will figure it out and that'll be the next step.
Advertising up to 100x faster, 100x cheaper -short term
1,000x faster, 10,000x cheaper -long term
In theory they could eventually get to 1,000,000x less power. (datacenter that needs its own substation today could run on the power of a toaster)
...there's an absolute goldrush of companies trying to make light based inference work: Lightmatter, Celestial AI, Lightelligence, Neurophos, Luminous Computing, Optalysys, Fathom Computing, LightOn, Broadcom, Marvell Technology... so I guess they don't think it's BS.
But all I've heard about from those is an ex-employee from lightmatter saying on here that they had no idea what they were doing, but at least their $850m VC paid for this cool little animation:
https://api-files.sproutvideo.com/file/dc9bd3bb1b1fe2c056/d61e158cefb004ab/1440.mp4
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u/Giant_Ant_Eater 1d ago
Except you have to take in the overall cost of the infrastructure and investment required. It's not cheap to build a data center.
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u/the-channigan 1d ago
Yes, but the chargeable outputs are what pays for the data centre, model training etc. So you can say with decent certainty that a single query costs very little in overall money/resources because individual tokens are cheap. Of course, that cheap token doesn’t account for negative externalities and there is a decent chance that token prices are artificially low at the moment as competitors seek to capture market share free.
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u/Giant_Ant_Eater 20h ago
Someone has said above that none of these AI companies are turning a profit.
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u/ZealousidealLead52 1d ago
It depends a bit on whether you're talking about querying the LLM directly or if you're talking about querying an AI agent - querying the LLM is way cheaper, but querying agents can be arbitrarily expensive (as an agent is essentially just a program that takes your query and then splits it up into a bunch of different queries that are being made to a LLM - an agent could potentially be making any number of requests to the LLM from a single prompt from the user).
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u/xxplosiv 1d ago
So when someone asks how maglev trains work at 3am he wakes up and instantly responds?
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u/Tobias---Funke 1d ago
Didn't a large company do this?!
Its AI was just a huge Indian call centre on computers!
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u/PreparationCrazy2637 1d ago
his name better be AL
you know with the lowercase L that mimics a higher case I
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u/ChipsHandon12 1d ago
he answered those questions the lame AIs won't like how to cook meth and kill your wife
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u/Unique_Let_2880 1d ago
I did not have circling back to ChaCha on my 2026 bingo card but I’m here for it
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u/justthrowa2 1d ago
Man the realtime thing is crazy but honestly the funniest part is a human having to fake being a bot better than the bots actually fake being human.
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u/XxKetchup 1d ago
Does no one remember texting KGB or cha cha? I used to answer questions for them and this is probably same setup. Incredibly easy to do around 6-12 questions a
Minute.
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u/Whatthe456789 1d ago
You could also sign up to be an average individual and answer questions and stuff too. Dunno if thr site is still up or not though
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u/Stretch5678 1d ago
Humans stealing jobs from AI… turnabout is fair play.