Thanks for the work, hope you gain 1 million subs🎉

seriously, you guys have no idea how much I've learned from this channel. The value is incalculable. Thank you so much!

You look like A.i generated model😅

Thank you for all your work 🙏 you are an inspiration 😊 I hope one day I can be as good as you

@@rameezalam1968 😂

Having programmed since 1963, it looks like a return to COBOL. Programming today is 90% getting things hooked up. 10% getting things done. 100% being clueless as to what's going on under the covers. Follow the bouncing ball programming.

A few months following their courses and their YT channel. I believe it's as useful (if not more) than my university degree, which took a lot of money and years.

I just completed their certification course in responsive web design and actually learned a lot from any other course and only in 40 days (300-350hours )and everything for free too

what, do you mean there is such thing as a paid course?? I am already 100% clueless. .

@@Jd-zd6bh I said it's free means it is free all courses on their website with certificate

She's an actor. There's tonnes of people behind the scene to write this content.

​@maciej2320 wow amazing me too from Ethiopia ❤

How do you know she's creating the content? You learned loads of stuff but is it making your more money?

ok simp

You're a lifesaver

Those skills are usefull for grad and research

Valid question

I believe this method is better than fine-tuning and significantly superior to using prompts, especially when you have a lot of information; the chat will provide much better answers.

I think this is more for AI to answer questions on your data..hence she downloaded data from hugging face . But this could also be your own data vectorized..stored in db and queried . I may be wrong but this what I infer.

Think its safe to assume if youre here that you know a bit of CS at least.

1 indicates an identical vector, or very close semantic meaning, or even identical text. (Note that it's the similarity of the vector's direction only, not scale.) 0 indicates an orthogonal relationship, ie, unrelated semantically. -1 in theory represents complete semantic opposition, but in practice, a perfect -1 is rare in natural language contexts.

Exactly my thought

With a lower score than expected

The model has seen misspellings before, and it knows they are related to the correct spelling more than other words.

Amazing. How could it know? @@technolus5742

You don't need to sign up for OpenAI Plus in order to create an API Key, they are billed separately. You also get a free 3-month API credit when you first create an account, the amount varies, I think they've decreased it now to about $5 (unfortunately I missed out on my credit, since I created my account last year and wasn't coding anything)

@@donaldoalmazan7338 thx for info

actually the 20$ for chatgpt is different from the api, for the api you can for example buy a 10$ credit and use it for as much as you would like, as long as it's used to finetune it will last long

passion to learn and explore

That is the simple Terminal. Later she uses Visual Studio Code

It is the linux terminal....curl is a linux command..but if u are on windows ..u may use wsl to use linux terminal on windows

In the beginning or early launch of gpt, open ai gave some free quota to dev account. probably that one has expired with the current email you are using

LangChain: "chaining" resulted in two answers for each prompt: "I don't know" and the headlines. The first answer came from OpenAI's LLM, the second answers (the headlines) came from the vector-DB (Astra/Cassandra) that she set up outside OpenAI. LangChain was the bridge between the two. It's a simple little example without much relevance, but it shows the bones. There is a lot more work to make something useful. For instance, you could use a pre-trained LLM to perform the organizational tasks and composition (the language parts) using current data from a real-time source. For instance, "what kind of activities would be good at Los Angeles beaches today?" The LLM could contextualize the meaning of the question using pre-trained data (an understanding of what constitutes beach sports and the condition necessary for each is something that won't much change over time), and then use an external source (weather channels, surf sites, diving data sites, sailing sites, etc.) to search for real-time conditions at LA Baches. The LLM - using the current real-time data - could then look for nearness matches based on how the conditions match up to certain sports. So instead of a generic pre-trained answer like, "people like to sunbathe, swim, dive and surf at beaches" you can get a specific answer such as, "The conditions at Redondo Beach suggest it's a good surf day, but rip tide warnings suggest it is a bad day for people to be swimming. There is a water quality alert for bacteria in Santa Monica Bay." The LLM used the external real-time data to give accurate point-in-time suggestions that it would otherwise never have using data from training months earlier. That's where LangChain can help - merging "new" or custom data into the pre-trained contextual LLM model. Hope this helped.

Yeh it seems to have moved location, open your table and on the right side under 'Database Details', 'Region' click the three dots and select download SCB :)

I was going to say, I cannot run the initial vector embedding program because of billing issues.

Google bard API

Context has two flavors, near and "not near". Joe is 38% near. Maybe Alice is 40% "not near", which would equate to a negative value (-.4). So context is more than "this one is like the other", it's also "but it's not like this other thing". If we just used a single dimension, then literally everything would be "like" everything else, which makes it a little difficult to differentiate. "The school bus is yellow. A banana is yellow. A bus is NOT LIKE a banana." Dimensions in dimensions.

Whats wrong of her explanation?

you can use a vscode terminal

@@chidiebere I'm using VS Code and I'm getting errors about the API key I created. Is there a way to validate a key?

how did you prepared a russian version?