Comment on WATER!
lemming741@lemmy.world 1 day agoMuch like Amazon has an incentive to not show you the specific thing it knows you’re searching for, people theorize that these interfaces are designed to burn through your tokens.
Comment on WATER!
lemming741@lemmy.world 1 day agoMuch like Amazon has an incentive to not show you the specific thing it knows you’re searching for, people theorize that these interfaces are designed to burn through your tokens.
AmbitiousProcess@piefed.social 1 day ago
I doubt that's the case, currently.
Right now, there's a lot of genuine competition in the AI space, so they're actually trying to out compete one another for market share. It's only once users are locked into using a particular service that they begin deliberate enshittification with the purpose of getting more money, either from paying for tokens, or like Google did when it deliberately made search quality worse so people would see more ads ("What are you gonna do, go to Bing?")
By contrast, if ChatGPT sucks, you can locally host a model, use one from Anthropic, Perplexity, any number of interfaces for open source (or at least, source-available) models like Deepseek, Llama, or Qwen, etc.
It's only once industry consolidation really starts taking place that we'll see things like deliberate measures to make people either spend more on tokens, or make money from things like injecting ads into responses.
brucethemoose@lemmy.world 1 day ago
Most people don’t know anything beyond ChatGPT and Copilot.
If we are talking programmers, maybe include claude, gemini, deepseek and perplexity search, though this is not always true.
…Point being, OpenAI does have a short term ‘default’ and known brand advantage, unfortunately.
That being said, there’s absolutely manipulation of LLMs, though not what OP is thinking persay. I see more of:
Benchmaxxing with a huge sycophancy bias (which works particularly well in LM Arena).
Benchmaxxing with massive thinking blocks, which is what OP is getting at. I’ve found Qwen is particularly prone to this, and it does drive up costs.
Token laziness from some of OpenAI’s older models, as if they were trained to give short responses to save GPU time.
“Deep Frying” models for narrow tasks (coding, GPQA style trivia, math, things like that) but making them worse outside of that, especially at long context.
…Straight up cheating by training on benchmark test sets.
Safety training to a ridiculous extent with stuff like Microsoft Phi, OpenAI, Claude, and such, for political reasons and to avoid bad PR.
In addition, ‘free’ chat UIs are geared for gathering data they can use to train on.
You’re right that there isn’t much like ad injection or deliberate token padding yet, but still.
lemming741@lemmy.world 1 day ago
I think it’s more about extracting money from normies, not someone savvy enough to run a model locally. And I don’t know if they do or don’t, I was just trying to explain the comic.