A survey of more than 2,000 smartphone users by second-hand smartphone marketplace SellCell found that 73% of iPhone users and a whopping 87% of Samsung Galaxy users felt that AI adds little to no value to their smartphone experience.
SellCell only surveyed users with an AI-enabled phone – thats an iPhone 15 Pro or newer or a Galaxy S22 or newer. The survey doesn’t give an exact sample size, but more than 1,000 iPhone users and more than 1,000 Galaxy users were involved.
Further findings show that most users of either platform would not pay for an AI subscription: 86.5% of iPhone users and 94.5% of Galaxy users would refuse to pay for continued access to AI features.
From the data listed so far, it seems that people just aren’t using AI. In the case of both iPhone and Galaxy users about two-fifths of those surveyed have tried AI features – 41.6% for iPhone and 46.9% for Galaxy.
So, that’s a majority of users not even bothering with AI in the first place and a general disinterest in AI features from the user base overall, despite both Apple and Samsung making such a big deal out of AI.
Again: What is the percent “accurate” of an SEO infested blog about why ivermectin will cure all your problems? What is the percent “accurate” of some kid on gamefaqs insisting that you totally can see Lara’s tatas if you do this 90 button command? Or even the people who insist that Jimi was talking about wanting to kiss some dude in Purple Haze.
Everyone is hellbent on insisting that AI hallucinates and… it does. You know who else hallucinates? Dumbfucks. And the internet is chock full of them. And guess what LLMs are training on? Its the same reason I always laugh when people talk about how AI can’t do feet or hands and ignore the existence of Rob Liefeld or WHY so many cartoon characters only have four fingers.
Like I said: I don’t like the AI Assistants that won’t tell me where they got information from and it is why I pay for Kagi (they are also AI infested but they put that at higher tiers so I get a better search experience at the tier I pay for). But I 100% use stuff like chatgpt to sift through the ninety bazillion blogs to find me a snippet of a helm chart that I can then deep dive on whether a given function even exists.
But the reality is that people are still benchmarking LLMs against a reality that has never existed. The question shouldn’t be “we need this to be 100% accurate and never hallucinate” and instead be “What web pages or resources were used to create this answer” and then doing what we should always be doing: Checking the sources to see if they at least seem trustworthy.
I don’t think that’s a good comparison in context. If Forbes replaced all their bloggers with ChatGPT, that might very well be a net gain. But that’s not the use case we’re talking about. Nobody goes to Forbes as their first step for information anyway (I mean…I sure hope not…).
Correct.
If we’re talking about an AI search summarizer, then the accuracy lies not in how correct the information is in regard to my query, but in how closely the AI summary matches the cited source material. Kagi does this pretty well. Last I checked, Bing and Google did it very badly. Not sure about Samsung.
On top of that, the UX is critically important. In a traditional search engine, the source comes before the content. I can implicitly ignore any results from Forbes blogs. Even Kagi shunts the sources into footnotes. That’s not a great UX because it elevates unvetted information above its source. In this context, I think it’s fair to consider the quality of the source material as part of the “accuracy”, the same way I would when reading Wikipedia. If Wikipedia replaced their editors with ChatGPT, it would most certainly NOT be a net gain.
You know, I was happy to dig through 9yo StackOverflow posts and adapt answers to my needs, because at least those examples did work for somebody. LLMs for me are just glorified autocorrect functions, and I treat them as such.
A colleague of mine had a recent experience with Copilot hallucinating a few Python functions that looked legit, ran without issue and did fuck all. We figured it out on testing, but boy was that a wake up call (colleague in question has what you might call an early adopter mindset).