OpenAI’s Sarcastic Chat Bot [GPT-3 API Beta]
Key Takeaways
The video discusses OpenAI's GPT-3 API Beta, a generative pre-trained transformer 3 model that can be fine-tuned for various tasks, and explores its capabilities through the OpenAI playground, including text generation, translation, and conversation, with a focus on the Marv sarcastic chatbot example.
Full Transcript
we all have probably dreamt of an ai that can literally do anything in one request like writing codes for us translating for us designing for us or even making memes for us and actually as of last year these useful applications are already slowly becoming a reality these are all products from language models called gpt3 which is short for generative pre-trained transformer 3. it was published by openai along with a paper called language models or few shot learners and the main takeaway is that it is trained with a lot of data like literally the whole internet and with a lot of parameters a historical large number of it in the ai model the few shot in title basically means when evaluating the ai you provide a few demonstrations of what you wanted to do first this is to basically fine tune it to your task then it will learn and imitate the topic of your demonstrations for things you ask it to do this is because in a nutshell gpt 3 is just an auto text completion on steroids without you demonstrating how it should exactly run it'll just be spitting out endless loops of text so every application that you saw has already been fine-tuned to do exactly what it was shown but the flexibility and precision is mind-blowingly on point so i'll give it that the codes and the pre-trained models weren't released initially but i think they are not planning to release it in the future either however they do have an api for gpg3 models on their official website where you can sign up for and this is also the reason why i was late to the party as i was waiting to get my hands onto their beta access so i could test out what gpt3 could really do so basically for every free personal beta access we get 300k tokens which is like one word per token to use running through the model this includes your input and generated output while each playground for the text evaluation and generation is capped to 2056 tokens so it is actually a pretty kind amount for people that just want to play with it and after my three hours session of playing with it it only took around 50k tokens and that's it to start off we can basically head to their playground and reproduce all the examples from their papers and receive even more information by adjusting various parameters for model evaluation at the side if we don't know how to utilize the ai we can just head to the example section where it provides examples of how to fine tune gpt 3 and obtain results acting like those functions in the playground this is basically the few shot learning slash fine tuning steps i mentioned previously so the ai can do what you have demonstrated it to do there are notably three examples they gave that caught my attention summarize for a second grader movie to emoji and marv the sarcastic chatbot the summarize for a second grader function is basically structured in a narrative way and designed to look like a story this is rather fascinating because it feels like the fine tuning process is to create a context instead of creating a function so the consistency will be more difficult to maintain since no specific structure and operation is specified absolutely so if the ai does not understand your instructions then you are doomed movie to emoji is actually a surprise for me though they may not actually be that accurate but they can definitely find some information based on the movie title or even anime title in some cases to generate the right emojis since movies are pretty easy to match i tested on some animes to see how cultured gpt3 is and it turns out that it can list out animes really easily while not going off to standard movies and it even knew some of the plots to pair with the right emojis which i did not expect marv the sarcastic chatbot is an exciting idea but the execution is really just like an e for effort in the title it was toned down so much that it wasn't really sarcasm anymore but instead a chatbot that is just reluctant to answer your questions so to be more accurate i got clickbaiter first then you guys got clickbait onto my video so ultimately is openi's fault for clickbaiting of us but honestly this is understandable because it's to prevent the potential abuse like people who might get gpg theory and say dumb or offensive stuff like they even have a dedicated user agreement section for social media usage like i cannot discreetly show unsafe generations and they are basically not responsible for what i bait the ai to say so every time the ai generates something potentially offensive in the playground you will be greeted either with an orange highlight or a red highlight to indicate it is actually a little problematic but keep in mind that all these are learned from the internet so really blame the growth environment not the kid so i forcefully changed the prompt myself after testing the reluctant bot but still got roughly the same results what is cool though is that the ai really understands the content within the fine tuning because it stopped answering my questions once my fine tuning mentioned that it will not answer the same question again or change the way that it answers my question what i struggle the most is to get the ai to answer questions as sarcastic or funny as the examples in the provided fine-tuning i only end up with a few semi-successful ones while i was hoping for something along the lines of the t is for trying to ask better questions in the future which would have been amazing anyways aside from these three functions i decided to talk about today the playground also offers a wide range of applications for you to use as well as coming up with your own fine-tuning method to design a function that you wanted to perform you want a personal tutor that teaches you how to use pytorch here it'll literally explain anything for you you want a translator because google translate is not accurate enough here it'll literally be accurate if the ai is in the mood for some translations do you want a friend to recommend you an anime to watch well this is definitely hell of a degenerate ai than what i expected but here so after some pretty deep conversations with my friend over here i would say that its potential is basically limitless and we also have come to an agreement that this open ai beta is hella cool since openai's beta api is upgradeable for business purposes with today's sponsor 27 stars you can make your cool fine-tuned gpt3 function into any web page or app right now 27 stars is a london-based development company that creates custom tailored web and mobile applications for businesses of all sizes with their expertise they can hook up the api with any services you currently have or planning to create easily other than that they are capable of web developments while also offering an exclusive 10 discount for all my viewers who are utilizing their services all you have to do is to include my name in the initial email to receive the discount and by working with them you are also indirectly supporting my channel too which allows me to make more content in the future shout out to connie md and many other patreons that support my work through patreon and if you want to play around in the beta playground you can sign up here now if you want to share your results feel free to join my discord and share with our amazing community follow my twitter if you haven't and i'll see you all in the next one
Original Description
Today's Sponsor is 27 Stars,
Develop your own AI software right now!
Check it out here: https://27stars.co.uk/bycloud
Include "bycloud" in the initial email to receive a 10% discount for all your purchases.
THIS VIDEO IS NOT SPONSORED BY OpenAI.
It's just incredible how GPT-3 is so flexible yet accurate. I would love to see what OpenAI will do with this funding from their API Beta. But not gonna lie, I am pretty late to this GPT-3 news, but hope this little fun demo can explain to you more what GPT-3 can or cannot do.
GPT-3: Language Models are Few-Shot Learners
[Paper] https://arxiv.org/abs/2005.14165
[API Beta] https://beta.openai.com/
[GPT-3 Paper Explained by Yannic Kilcher] https://youtu.be/SY5PvZrJhLE
This video is supported by the kind Patrons:
🙏Emdy, Conny Cancun, Mazen Alotaibi, Sascha Henrichs, Jake Disco, Demilson Quintao, Martin Schmitt, Zeldus Zumbain
Support me on Patreon if you hope to see more:
https://www.patreon.com/bycloud
or by becoming a member instead (same perks!):
https://www.youtube.com/channel/UCgfe2ooZD3VJPB6aJAnuQng/join
[Discord] https://discord.gg/NhJZGtH
[Twitter] https://twitter.com/bycloudai
[Patreon] https://www.patreon.com/bycloud
[Music] steaminwaffles - aquarium boy
[Profile Art] https://twitter.com/pygm7
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