Earlier quoted context omitted.
You're using the wrong definition, then. /s Where is some evidence that NLP is 'solved'? What does it even mean? OpenAI itself acknowledges the fundamental limitations of ChatGPT and the method of training it, but apparently everybody is happily sweeping them under the rug: "ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers. Fixing this issue is challenging, as: (1) during RL training,…
It'd be great if GPT could provide it's sources for the text it generated. I've been asking it about lyrics from songs that I know of, but where I can't find the original artist listed. I was hoping chat gpt had consumed a stack of lyrics and I could just ask it, "What song has this chorus or one similar to X..." It didn't work. Instead it firmly stated the wrong answer. And when I gave it time ranges it just noped o…
Anyone else witnessing a panic inside NLP orgs of big tech companies?
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Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?
#32Earlier quoted context omitted.
It'd be great if GPT could provide it's sources for the text it generated. I've been asking it about lyrics from songs that I know of, but where I can't find the original artist listed. I was hoping chat gpt had consumed a stack of lyrics and I could just ask it, "What song has this chorus or one similar to X..." It didn't work. Instead it firmly stated the wrong answer. And when I gave it time ranges it just noped o…
Have you tried bing chat? That search & sourcing is exactly what it does.
Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?
#33OpenAI could build a state-of-the-art tool with a few hundred developers - to me, that means that money will converge to them and other big orgs rather than the opposite.
Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?
#34I tried translating something from English to German (my native language) yesterday with ChatGPT4 and compared it to Microsoft Translate, Google Translate and DeepL. My ranking: 1. ChatGPT4 - flawless translation. I was blown away 2. DeepL - very close, but one mistake 3. Google Translate - good translation, some mistakes 4. Microsoft Translate - bad translation, many mistakes I can understand the panic.
Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?
#35During my master's degree in data science, we had several companies visit our faculty to recruit students. Not a single one was a specialized NLP company, but many of them had NLP projects going on. Most of those projects were the usual "solution looking for a problem to solve". Even those projects that might have had _some_ utility, would have been way more effective to buy/license a product than to develop an in-ho…
I wonder if this is a bad as everyone thinks. When a new technology arrives which is not completely understood, isn't the right approach to try to find some applications for it? Sure, most will fail, but some valid use cases will likely emerge.
I'm pretty sure almost all technologies at some point were solutions looking for a problem to solve. Examples include the internet, the computer and math.
Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?
#36I tried translating something from English to German (my native language) yesterday with ChatGPT4 and compared it to Microsoft Translate, Google Translate and DeepL. My ranking: 1. ChatGPT4 - flawless translation. I was blown away 2. DeepL - very close, but one mistake 3. Google Translate - good translation, some mistakes 4. Microsoft Translate - bad translation, many mistakes I can understand the panic.
Does it translate hate speech too?
Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?
#37As one of the comments on reddit posts - it's not just big tech companies, but also entire university teams which feel the goalposts moving miles ahead all of a sudden. Imagine working on your PhD on chat bots since start of 2022. Your entire PhD topic might be irrelevant already...
Will this effect the job market (both academic and commercial) for these folks? It's very hard to say. Clearly lots of value will be generated by the new generation of models. There will be a lot of catchup and utilisation work where people will want to have models in house and with specific features that the hyperscale models don't have (for example constrained training sets). I'm wondering how many commercial illustrators have had their practices disrupted by Stable Diffusion? Will the same dynamics (what ever they are) apply for the use of LLM's?
Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?
#38I tried translating something from English to German (my native language) yesterday with ChatGPT4 and compared it to Microsoft Translate, Google Translate and DeepL. My ranking: 1. ChatGPT4 - flawless translation. I was blown away 2. DeepL - very close, but one mistake 3. Google Translate - good translation, some mistakes 4. Microsoft Translate - bad translation, many mistakes I can understand the panic.
Fellow German here. Funny thing about DeepL: It translates "pathetisch" as "pathetic". For example: "Das war eine pathetische Rede." -> "That was a pathetic speech." I guess we have to get used to software redefining the meaning of words. It was kind of funny when that happened regarding Google Maps / neighborhood names, but with LLMs it's a different ballgame.
Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?
#39Earlier quoted context omitted.
> Honestly, I can't wait for GPT and other productivity tools to wrech havock upon the tech labour market. Some people in tech really need to be taken down a notch or two. That's an odd reason to want this.
Less bullshit jobs. Society needs doctors, nurses, plumbers and teachers not tech bros.
While adtech, crypto and other bullshit gets massive funding because it can turn a profit.
The incentives to have a good society don't align with the incentives of financial capitalism.
Re: Anyone else witnessing a panic inside NLP orgs of big tech companies?
#40If you were an NLP researcher at a university whose past years of experience is facing existential threat due to this rapid innovation causing your area to become obsolete, what would be some good areas to pivot to or refocus on?
Get out of academia and into industry. Why the hell stay in in academia? This is clearly the next technological wave, and you shouldn't sleep on it. Especially when you're so well positioned to take advantage of your experience. You can make $500,000/yr (maybe more with all the new startups and options) and be on the bleeding edge. If you want to go back to academia later, you can comfortably do so. Most don't, but t…
ETA: And though it may take longer, people who understand these models will eventually be in possession of the most valuable skill there is. Perhaps one of the last valuable human skills, if things go a certain direction.