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Can anyone tell me what the value of GPT-3 actually is other than generating meaningless prose? What would a business use it for
by mrbukkake 5y ago
Can anyone tell me what the value of GPT-3 actually is other than generating meaningless prose? What would a business use it for
- crubier 5y agoHave you heard of GitHub copilot ? It’s based on GPT3 and I can tell you one thing: it does not generate meaningless prose (90% of the time)
- ghoomketu 5y agoYes I'm used it now but first time it started doing its thing, I wanted to stop and clap for how jaw dropping and amazing this technology is. I was a Jetbrains fan but this thing takes productivity to a whole new level. I really don't think I can go back to my normal programming without it anymore.
- amelius 5y agoHow many % of the time does it produce code that compiles?
- emteycz 5y agoThe overwhelming majority. Whatever used to take me an hour or two is now a 10-minute task.
- ilteris 5y agoI am so confused. Is there a tutorial explaining how you are using in the IDE whatever it is. I use vscode curious if it can be applied. Thanks
- crubier 5y agoIt works very well with VSCode. It has an integration. It shows differently than normal autocomplete, it shows just like gmail autocomplete (grayed out text sugggestion, and press tab to actually autocomplete). Sometimes the suggestion is just a couple tokens long, sometimes it’s an entire page of correct code. Nice trick: write a comment describing quickly what your code will do (“// order an item on click”) and enjoy the complete suggested implementation ! Other nice trick: write the code yourself, and then just before your code, start a comment saying “// this code” and let copilot finishe the sentence with a judgement about your code like “// this code does not work in case x is negative”. Pretty fun !
- icelancer 5y agoInteresting second use case; I use comments like this already as typical practice and I agree Copilot fills in the gaps quite well - never thought to do it in reverse... will give that a shot today.
- emteycz 5y agoI also like to do synthesis from example code (@example doccomment) and synthesis from tests.
- bidirectional 5y agoFrom my anecdotal experience, the vast majority of the time (90+%).
- crubier 5y agoIn my experience 95% of the time. And 80% of the time it output codes which is better than I would have done myself in a first approach (thinks of corner cases, adds meaningful comments etc.). It’s impressive.
- icelancer 5y agoI was exceptionally skeptical about it, but it's been very useful for me and I'm only using it for minor tasks, like automatically writing loops to pull out data from arrays, merge them, sort information, make cURL calls and process data, etc. Simply leading the horse to water is enough in something like PHP: // instantiate cURL event from API URL, POST vars to it using key as variable name, store output in JSON array and pretty print to screen Usually results in code that is 95-100% of the way done.
- inglor 5y agoThis - it is tremendously valuable to me and I use it all the time at work.
- skybrian 5y agoWhat do you use it for?
- inglor 5y agoCoding, I actually had to forbid it today in a course I teach because it solves all the exercises :) (given unit tests with titles students needed to fill those tests in)
- singlow 5y agoIsn't that just because others have stored solutions to these problems in GitHub?
- iamcurious 5y agoThat is my question too. Is it a fancier autocomplete? Or does it reason about code?
- robbedpeter 5y agoIt reasons over the semantic network between tokens, in a feedforward inference pass over the 2k(ish) words or tokens of the prompt. Sometimes that reasoning is superficial and amounts to probabilistic linear relationships, but it can go deeply abstract depending on training material, runtime/inference parameters, and context of the prompt.
- PeterisP 5y agoIn some sense you could think of as a fancy autocomplete which uses not only code but also comments as input, looks up previous solutions for the same problem but (mostly) appropriately replaces the variable names to those that you are using.
- nradov 5y agoThe fact that GPT3 works at all for coding indicates that our programming languages are too low level and force a lot of redundancy (low entropy). From a programmer productivity optimization perspective it should be impossible to reliably predict the next statement. Of course there might be trade offs. Some of that redundancy might be helping maintenance programmers to understand the code.
- hans1729 5y ago>From a programmer productivity optimization perspective it should be impossible to reliably predict the next statement Why? 99.9% of programming being done is composition of trivial logical propositions, in some semantic context. The things we implement are trivial, unless you're thinking about symbolic proofs etc
- tshaddox 5y agoI think that’s precisely the problem the parent commenter is describing.
- alephaleph 5y agoThat would only follow if we were trying to optimize code for brevity, and I have no clue why that would be your top priority.
- nradov 5y agoNot at all. Brevity (or verbosity) is largely orthogonal to level of entropy or redundancy. In principle it ought to be possible to code at a higher level of abstraction while still using understandable names and control flow constructs.
- crubier 5y agoI’m really not sure about that. By definition, high entropy means high information density (information per character). So with the same amount of information you would have less characters.
- pharmakom 5y agoCode is easier to write than read and maintain, so how useful is something that generates pages of 90% correct code?
- ALittleLight 5y agoIt's not useful if you use it to auto complete pages of code. It is useful to see it propose lines, read, and accept its proposals. Sometimes it just saves you a second of typing. Sometimes it makes a suggestion that causes you to update what you wanted to do. Sometimes it proposes useless stuff. On the whole, I really like it and think it's a boon to productivity.
- lysecret 5y agoHey for a long time i was also very sceptical. However i can refer you to this paper to a really cool applciaiton. https://www.youtube.com/watch?v=kP-dXK9JEhY https://www.youtube.com/watch?v=kP-dXK9JEhY. They baseically use clever GPT-3 prompting to create a dataset, you then train another model on. Besides, you can prompt these models to get (depending on the usecase) really good few shot performance. And finally, github copilot is another pretty neat application.
- warning26 5y agoGPT-3 is fairly effective at summarization, so that's one potential business use case: https://sdtimes.com/monitor/using-gpt-3-for-root-cause-incident-summarization-of-incidents/ https://sdtimes.com/monitor/using-gpt-3-for-root-cause-incid...
- Tijdreiziger 5y agohttps://replika.ai/ https://replika.ai/
- amelius 5y agoI hope that one day it will allow me to write down my thoughts in bullet-list form, and it will then produce beautiful prose from it. Of course this will be another blow for journalists, who rely on this skill for their income.
- DeathArrow 5y agoI played with GPT-3 giving it long news stories. It actually replied with more meaningful titles than the journalists themselves used.
- rm_-rf_slash 5y agoPerhaps GPT-3 was optimizing to deliver information while news sites these days optimize titles to get clicks.
- ailef 5y agoYou can prompt GPT-3 in ways that make it perform various tasks such as text classification, information extraction, etc... Basically you can force that "meaningless prose" into answers to your questions. You can use this instead of having to train a custom model for every specific task.
- jszymborski 5y agoWhile the generation is fun and even suitable for some use cases, I'm particularly interested in its ability to take in language and use it for downstream tasks. A good example is DALL-E[0]. Now, what's interesting to me is the emerging idea of "prompt engineering" where once you spend long enough with a model, you're able to ask it for some pretty specific results. This gives us a foothold in creating interfaces whereby you can query things using natural language. It's not going to replace things like SQL tomorrow (or maybe ever?) but it certainly is promising. [0] https://openai.com/blog/dall-e/ https://openai.com/blog/dall-e/
- 13415 5y agoAutomatic generation of positive fake customer reviews on Amazon, landing pages about topics that redirect to attack and ad sites, fake "journalism" with auto-generated articles mixed with genuine press releases and viral marketing content, generating fake user profiles and automated karma farming on social media sites, etc. etc.
- DeathArrow 5y agoThe state of the journalism is so poor, I'd rather take some AI generated articles instead.
- phone8675309 5y ago> fake "journalism" with auto-generated articles mixed with genuine press releases and viral marketing content How would you tell the difference from the real thing these days?
- mark_l_watson 5y agoYou can try it yourself - apply for a free API license from OpenAI. If you like to use Common Lisp or Clojure then I have examples in two of my books (you can download for free by setting the price to zero): https://leanpub.com/u/markwatson https://leanpub.com/u/markwatson
- moffkalast 5y agoI put in a request months ago, I think they're not approving people anymore.
- mark_l_watson 5y agoYou might try signing up directly for a paid non/free account, if that is possible to do. I was using a free account, then switched to paying them. Individual API calls are very inexpensive.
- pyb 5y agoI know of some credible developers who were struggling to get access, so YMMV
- mark_l_watson 5y agoIt took me over a month, so put in your request. Worth the effort!
- deleted 5y ago[deleted]
- phone8675309 5y agoIt's good for the university-industrial-business complex - people writing papers about a model they can't even run themselves. It practically prints money in journal articles, travel per diem, and conference honorariam, not even counting the per-API call rates.
- DeathArrow 5y ago>What would a business use it for If you think about business uses you can actually get advices from Jerome Powell, simulated by GPT-3. If someone use GPT-3 to simulate Warren Buffet, he can extract even more value. https://www.institutionalinvestor.com/article/b1tktmhcfdyqsk/An-Interview-With-a-Hyper-Realistic-AI-Powered-Simulation-of-Jerome-Powell https://www.institutionalinvestor.com/article/b1tktmhcfdyqsk...
- vitus 5y agoSomehow I don't think that this is quite how Jerome Powell would respond in an interview: > Interviewer: How do you think a global pandemic would impact the financial system? > Mr. Powell: A pandemic will have impact on the economy. It will have an impact on the financial system. > Interviewer: What would the impact be? > Mr. Powell: If a major pandemic occurred, the economy would be affected, and the financial system would be affected. Yes, GPT-3 can provide a convincing chatbot, but it shouldn't be confused for domain expertise.
- robbedpeter 5y agoThis is a bad example. Here's an output from gpt-j-6b by EleutherAI: Prompt( Jerome Powell was interviewed about the impact of a pandemic on the economy. > > Interviewer: What would the impact be? > Mr. Powell: If a major pandemic occurred) Output( it could be very disruptive. > > Interviewer: How disruptive? > Mr. Powell: Well, it could be disruptive in a number of ways. > > Interviewer: How so? > Mr. Powell: Well, one of the first things that would be disrupted would be the supply chain. ) Using prompts well makes a huge difference. If you parse the generated output, classify it, then develop a decision tree that uses further prompts to refine the response, you can get more sophisticated, valuable responses. The output in the parent is comparable to an off-the-cuff interview response. If you emulate a deeper thought process, you can get more meaningful output, and if you use the right prompts, you can access the semantic networks in the model related to your domain of interest.
- notahacker 5y agoI think the "bad example" is actually the good one, because it's a reminder that actually you're not getting business advice from someone with Warren Buffet or Jerome Powell's understanding of the economy, you're getting text generated by analysing patterns in other not-necessarily-applicable text. If you start forcing it in very specific directions you start getting text that summarises the commentary in the corpus, but most of that commentary doesn't come from Warren Buffet or Jerome Powell and isn't applicable to the future you're asking it about...
- DeathArrow 5y agoChat bots are an usage. I think you might use it for customer support. One example of GPT-3 powered chat bot: https://www.quickchat.ai/emerson https://www.quickchat.ai/emerson
- micro_cam 5y agoActually using this class (larger transformer based language models) of models to generate text is to me the least interesting use case. They can also all be adapted and fine tuned for other tasks in content classification, search, discovery etc. Think facnial recognition for topics. Want to mine a whole social network for anywhere people are talking about _______ even indirectly with very low false negative rate? You want to fine tune a transformer model. Bert tends to get used for this more because it is freely available, established and not too expensive to fine tune but i suspect this is what microsoft licensing gpt-3 is all about.
- hubraumhugo 5y agoAt https://reviewr.ai https://reviewr.ai we're using GPT-3 to summarize product reviews into simple bullet-point lists. Here's an example with backpack reviews: https://baqpa.com https://baqpa.com
- staticautomatic 5y agoDid you test it against extractive summarizers?
- hubraumhugo 5y agoWe experimented with BERT summarization, but the results weren't too good. Do you have any resources or experiences in this area?
- moffkalast 5y agoThat sounds like BERT alright.
- cma 5y agoHow do you avoid libel?
- kingcharles 5y agoAre you confusing libel with something else? Can you extrapolate what you mean here? Are you saying that they will be liable for libel (!) if they publish a negative summary of a product?
- cma 5y agoIf they mischaracterize a positive review into a negative summary based on factual mistakes they know the system makes at a high rate, I would think they would be liable for libel right?
- 5y ago
- supperburg 5y agoThat’s like if an alien took Mozart as a specimen and then disregarded the human race because this human, while making interesting sounds, does nothing of value. You have to look at the bigger picture.
- akelly 5y agohttps://copy.ai/ https://copy.ai/
- teaearlgraycold 5y agoHey, I work there! To be honest it's still very much a prototype. We have big plans for the next few months.
- CamperBob2 5y agoGPT-3 and similar ML/AI projects may have many interesting and valuable commercial applications, not all of which are readily apparent at this stage of the game. For instance, it could be used to insert advertisements for herbal Viagra at https://www.geth3r3a1N0W.com https://www.geth3r3a1N0W.com into otherwise-apropros comments on message boards, preferably near the end once it's too late to stop reading. Life online is about to become very annoying.
- teaearlgraycold 5y agoI work for a company that re-sells GPT-3 to small business owners. We help them generate product descriptions in bulk, Google ads, Facebook ads, Instagram captions, etc.