What are Large Language Models (LLMs)?
ฝัง
- เผยแพร่เมื่อ 27 มิ.ย. 2024
- Learn about Large Language Models (LLMs), a powerful neural network that enables computers to process and generate language better than ever before. Dale and Nikita share how LLMs work and how you can interact with them via prompts.
Resources:
Try out Bard → goo.gle/420KQhw
What is a Transformer? → goo.gle/3VABlDw
Subscribe to Google Developers → goo.gle/developers
#MachineLearning #MLmodels #LLMs #GenerativeAI - วิทยาศาสตร์และเทคโนโลยี
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❤❤ Dear Developers,
It's Okay ❤❤
@@mizanursbestreview Deep Learning and GPT-4 are fake intelligence. For example, It struggles with fingers, and with drinking beer. LLM are a dead-end for AGI because they do not [understand]! the implications of their outputs! Also, GPT-4 is designed by the Wealthy to serve their needs!
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Douglas Lenat wrestled with creating the true AI . AI lost a giant.
He was not correct about some AI-things but he opened my mind about great many more things about AI.
RIP Douglas Lenat, 1950-2023
Thanks for diving in! What a great explanation.
Very good video! These llms are much clearer now!
Your insights are like gems that light up every conversation.
Wow, amazing video, everything was well explained! I really learn a lot from your videos, thank you so much 🤗🤗
In brief (GPT4):
In this video, the speakers discuss the power of Large Language Models (LLMs) in understanding and generating human language. LLMs are based on the transformer architecture invented by Google and are trained on massive text datasets. Their ability to be used for a variety of tasks, such as chat, copywriting, translation, summarization, and code generation, makes them incredibly powerful and efficient.
LLMs can be utilized without being a machine learning expert, as they function like sophisticated autocomplete systems. Users can input text and receive output text based on the patterns and language learned by the LLM. The input text is called a prompt, and prompt design is crucial for getting the desired output from the LLM.
There are two main approaches for prompt design: zero-shot learning, which involves using a single command, and few-shot learning, which includes providing examples. However, there's no optimal way to write model prompts since the results are highly dependent on the underlying model, and small changes in wording or word order can have a significant impact.
Users can try out LLMs like Google Bard and experiment with different prompt structures and formats to find what works best for their specific use case.
You are not using BARD? :P
GPT-4 is fake intelligence. For example, It struggles with fingers, and with drinking beer. LLM are a dead-end for AGI because they do not [understand]! the implications of their outputs!
Also, GPT-4 is designed by the Wealthy to serve their needs!
I found more understanding with this video vs one 12 times longer due to the extremely positively beneficial way this was presented in an extremely easy to learn visual manner so thank you very much indeed ❤️
I use bard everyday and it helped my workflow increase significantly
Can't wait to see what Google has up their sleeves with A.I
Excellent detailed information, Highly recommend everyone
Very good video about LLM and prompt engineering
Thanks for your explanations.
Very simple and rich video
Thank you!
Excellent intuitive video about prompt engineering for starters, thank you.
Thanks for this overview!
The first AI transformer model, known as "Transformer," was introduced by researchers at Google in the paper titled "Attention is All You Need," published by Vaswani et al. in 2017.
well explained..Thank you so much
So clearly,thank you very much
Amazing video gilrs! Thank you!
Nailed the "silence, brand" vibe.
Thank you! this has helped me learn more about this
It's our pleasure! Glad you enjoyed the video 😎
Thanks ❤
Really helpful. Thank you for explaining it so well!
Thanks for shring
"and definitely let us know what you are building"
being google, I'm pretty sure you already know that
ChatGPT is the elephant in the room. I didnt even know you can talk to Google Bard at the moment
Like Google bard ...................
🇨🇴👋🙋♂👍🤝 Saludos desde la ciudad de Bogotá D.C.
Pretty sophisticated stuff is going on with AI. How is PALM different to BARD ?
Bard isn’t currently supported in your country. Stay tuned! - that's all about G approach
I'm with you
Great video. You guys are very sympathetic and explained the concept of an LLM in a simple but understandable way!
Cool.
When i finally I get GenAIs to respond with what i wanted (often this will take multiple prompts, corrections), i ask it a simple question:
> "Please give the prompt which would have generated the last output"
I'm really with a question.
So, waiting for the next video to learn, what do you think isn't it a hard job?
Would be nice to have diffusers models that can run on mobile. Diffusers is so powerful
Can a subsequent SFT and RTHF with different, additional or lesser contents change the character, improve, or degrade a GPT model?
gosh they are beautiful
I still don't understand how do you go from a language model which predicts the next word to a question answering system.
Same
Because it's impossible to predict undefined input.
They don't per se. It just happens to be that in common text an answer frequently follows a question, so the next predicted words happen to be those starting the answer. They never actually leave next word prediction.
@@zvxcvxcz I see but those systems seem to form an answer using the related documents. Let's say neural nets somehow determine which paragraphs are similar to the question asked. Do neural nets also form the answer text or there is some other algorithm that forms the answer text?
nice explaination
Please stop saying they understand. They don't, and saying it over and over are giving normal people a very warped view of what these models are capable of. And yes, the bigger they get and the more info they're fed, the tougher it becomes to demonstrate that they don't understand because the outputs between the traines model and someone with actual understanding become closer together, but it really is actually the case that these models as they work today most certainly do not understand anything.
🎯 Key Takeaways for quick navigation:
00:00 🤖 Introduction to Large Language Models (LLMs)
01:26 🧠 How LLMs Work
03:19 📝 Prompt Design for LLMs
04:43 🤯 Challenges in Writing Model Prompts
05:13 🌟 Conclusion and Applications
Made with HARPA AI
Looks like a dead heat in a zeppelin race 👀
Is LLM part of NLP? Is an LLM always an NLP model? Or can an LLM be another kind of model?
Also, BERT is Transformer but not an LLM, right? Transformer can be LLM or not, right?
Waiting to see Bard Open-sourced😎
what is a mud kiln?
Unless you have been living under a rock, you would know about a thing called reversible computation.
Watson developed by IBM more than 10 years was very good in language understanding. What model was behind Watson?
According to the knowledge available on public internet, watson is not built on a particular ML mdel. A bunch of algorithm and technologies is used to implement it. For more reference you can visit given link.
I like that the video starts with an insult.
❤❤
Can you open source your models?
lol
France is to Paris , Japan is to .......????
So you mean to say there is a sentence in word corpus that is very close to above sentence. So my question is i doubt that above sentence is there in word corpus then how will it predict Tokyo. Is there any other technique also used?
Where is the math? Where is the compilable code? How much is a language model? What would be the hardware requirements?
I still can’t access Bard. Something about permission setting blah blah
The words chat and conversation imply spoken communication. However, neither Google Bard nor OpenAI chat GPT are capable of speaking or understanding spoken words. It's strictly text, which gets tedious pretty quickly. These reviews never seem to reflect that. Plus, my view so far is that it's like the Wizard of Oz: just someone behind the curtain trying madly to keep up the illusion.
Thanks, great infos, and very friendly girls. Take care
The output of LLM is always probabilistic and never deterministic.
So deep
Chapter: fuchsia learning
it seams i've been living under a rock jhajhajha ::/
2.2k+...Thanks
Advance AI
yeah guys like google bard
What you are saying is AlG recording of your digital alpha rhythm .
This video demonstrates what's wrong with google lately..
Everyone heard about this because of ChatGPT which they try to not mention because it's a Microsoft thing.
Microsoft has licensed use, but it is not a Microsoft thing, it is from OpenAI.
Entrepreneurship is dirty bro you gotta do anything to just sustain. No other option
Google had created the first Ai chat bot 2 years earlier than open ai... But launch it because of its harmful effect on people
Google developed most of base tech that were later used by OpenAI, tech like from word embedding algorithms to Transformer architecture, and they gave them away for free, but Google are not arrogant enough to use the word "Open";😅
I need LLM
In my experience Bard has been totally unreliable.
Ask bard how many about football results and it gets it wrong.
AIG is in effect your creator of matrix Pandora's box 🎁
Wow. LLM is a black box you can not do it. We can train it for all tasks. What a waste! :(
One can get a pre-trained free model to build own vector DB with own data and search them.
Mention ChatGPT without mentioning ChatGPT
You are now AlG artificial intelligence video chat
Deneme yorum
I"m sempel
So you guys are pushing prompt engineering as a real job?
There won't be dedicated "prompt engineers", instead prompt engineering is simply a skill that developers now need to have.
😢I 😢
Therefore you do not exist
Aweful audio quality