161–170 of 284 posts
> All suggestions are welcome. Monetize it! Evil answer: Partner with an advertiser and sell https://api.opencagedata.com/geocode/v1/json as an ad space. This may be the first opportunity for an application/json-encoded advertisement. Nice answer: Partner with an actual phone lookup platform and respond with a 301 Moved Permanently at the endpoint.
The biggest takeaway for me was that it was getting info from YouTube videos. Is it actually watching and learning from the videos or where links to GitHub just included in the comments?
I think this is just an incorrect assumption on the part of the blog authors.
Screenshots https://imgur.com/a/sNR87c7 You can see the OpenCage logo on the bottom right of the images. We wrote a separate blog post about that about a year ago, we felt today's blog post would be too long if we added those screenshots, too.
Because ChatGPT is so new, we are in this weird period where people haven't learned that is just as incorrect as the rest of us. I am hoping that in a year from now people will be more skeptical of what they hear from conversational AI. But perhaps that is optimistic of me.
Even if it’s wrong, dangerous, misleading, fundamentally flawed as a concept whatever. Big tech and money will find ways to keep putting it in front of us.
I'm curious -- does anyone know of ML directions that could add any kind of factual confidence level to ChatGPT and similar? We all know now that ChatGPT is just autocomplete on steroids. It produces plausibly convincing patterns of speech. But from the way it's built and trained, it's not like there's even any kind of factual confidence level you could threshold, or anything. The concept of factuality doesn't exist…
By definition, an LLM doesn't have a semantic world model or ontology. Even the most "dumb" (and I use that in quotes because they really aren't) animal is able to reason about uncertain concepts and understands risk and uncertainty. Yann Lecun has posted a lot recently about this but basically LLMs are a "useful offramp on the road to AGI".
In fact many propose that when you train an LLM, in order to be able to predict the next word with enough accuracy, it must internally build a world model.
Yann Lecun is very salty about chatgpt, I wouldn't take his word seriously.
> All suggestions are welcome. Monetize it! Evil answer: Partner with an advertiser and sell https://api.opencagedata.com/geocode/v1/json as an ad space. This may be the first opportunity for an application/json-encoded advertisement. Nice answer: Partner with an actual phone lookup platform and respond with a 301 Moved Permanently at the endpoint.
> actual phone lookup platform uh, you mean stalker / scammer platform? This would be a major privacy violation.
Because ChatGPT is so new, we are in this weird period where people haven't learned that is just as incorrect as the rest of us. I am hoping that in a year from now people will be more skeptical of what they hear from conversational AI. But perhaps that is optimistic of me.
It is quite interesting really. I took AI in school but I have not dived deep at all in ChatGPT but isn't chatGpt just learning from the internet? Could someone push "wrong" opinion heavily online to sway the opinion of AI? I can only imagine a bot that learned from 4chan.
Dreams can come true…
Earlier quoted context omitted.
I think this is just an incorrect assumption on the part of the blog authors.
Cofounder here. We traced it back to two youtube videos where a developer is coding a phone tracking solution. The map then shows the geographical center of India and it's claimed that was the correct location. Then other users starting putting the code on github, then forked, then people created libraries and now AI tools pick that up. We already tried contacting the youtube authors, we left comments on the github r…
The claim in the blog post that "ChatGPT has picked up that content" is false.
I'm waiting for people to start calling me to ask questions about something ChatGPT said, and I'll tell them it's wrong. Then they'll start arguing with me and saying if ChatGPT said it, it must be right, and I must be wrong. And then I'll need to waste time proving that this idiotic chat bot that is spewing out garbage is, in fact, spewing out garbage.
I'm curious -- does anyone know of ML directions that could add any kind of factual confidence level to ChatGPT and similar? We all know now that ChatGPT is just autocomplete on steroids. It produces plausibly convincing patterns of speech. But from the way it's built and trained, it's not like there's even any kind of factual confidence level you could threshold, or anything. The concept of factuality doesn't exist…
That's basically what the new Bing is. It's a large language model that can run searches, and then use what comes back from those searches to generate answers to questions. Whether or not the information that comes back from those searches is reliable is a whole other question. I would love to learn what the latest research is into "factual correctness" detection. Presumably there are teams out there trying to solve…