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Good point

I’d say the solution is ordering in the answer (names and places first) or two independent queries. However, independent queries have a disadvantage- you pay twice for the input tokens (with the current on-demand pricing), which is less than desirable The advantage of independent queries is lower answer latency, though. And with cheaper models, you can often afford the double input tokens depending on the usecase

Cool but fine tuning is a necessary tool if you want to lock domain specific information that doesn't change frequently into the model while freeing up the context window for more dynamic content. An example: I want to make an AI model that generates quests in a game. For this I need to finetune the model to have the basics of the game universe and such and free up the context window to include the information that is coming from the game world, such as population of each territory, which faction controls which places, the user's location and progress, etc.

Do you use native AI note app like Mem or Saner?

You guys are producing some of the best conversations out there around AI and web development! And your speaking style is simply top notch.

Great content, and we appreciate the Pet Portal AI shout-out in the presentation! You've been incredible to work with and have really helped bring our vision to life! Love the way you break down and simplify concepts AND processes (i.e., Sanity 😊)

Thanks for your indepth explanation. It has effect.

You got yourself a new subscriber

Without any prior coding experience, I ambitiously tried to build a solution outside of an AI framework. The main issue was the inconsistent quality of my images, which made it difficult to extract text from PDFs and scanned images accurately. This often led to mistakes. Fortunately, I received some tips and tricks from other RUclips videos using some pretty powerful python libs If you'd like, feel free to send me a few pages you're having trouble with, and I'll run them through my text script. I'll let you know what's working and recommend some oth3er youtubers that might have helpful vids for you. FYI this is some of the first code i wrote so....yeah its a mess, But im pretty confident i might be able to help (for free obviously)

Spot on. I'm a product designer who for the last year has switched to mostly dev. I've always done a little bit of html/css but now with Claude, I'm actually able to bypass the great divide and push front-end.... and backend code. And it's not absolutely terrible either, crazy!

Good luck iterating over the initial design/code/test :)

Very well done explaining the uses of this tool! I believe future version of it will change how we go about everything, and a big step will be the ability to visualize and interact with these connections. I wanted to let you (and whoever sees this) know that I've collaborated with Brian (Creator of Smart Connections) and released the official plugin companion: "Smart Connections Visualizer". For this first version, it's an obsidian graph view that shows relevant connections to your current note. I'll still be adding much much more to it, also with an ability to customize how you see things like no other! Give my channel a peak if you want to find out more If it's not too much, could you pin this comment to let people know about this tool to enhance their experience with SC?

If you use ChatGPT does that not just make your Obsidian notes no longer private?

This is good Working tutorial will help viewers to understand more deeply nuances and start applying the concepts learnt. And some of them will come back and enrich every one with their experience

Hello, I don't know the principle of the pipeline, I wonder how can I establish a didicated law's gpt, I just upload some pdf, and each is at about 10Mb，but I failed to let gpt answer my quetion even if the pdf are so precise.

Congratulations. There are tools like Langsmith now that can be used to show the chain used by the GPT.

This is pretty cool. Can you give a tutrial of PDF ingestion pipeline?

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Congratulations on the 1k subscriber milestone! Well deserved with such great content. Turning my notifications on!

Have you taken a look at Amazon Q with dev mode in an IDE yet?

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"hallucinates a guess". I like that. 😆

There is anyway to use the GPU for this?

My vault is over 3million words across 2k+ files, all geared towards one project. I was excited to use the Co-Pilot plugin because it advertises "vault mode", but was quickly disappointed when its default reference amount was only 3 notes/files at a time (lol), and can only stretch to 10 but gives a warning that it will prolly screw up the responses. I want to communicate with my vault as a whole for perfect macro context, but it seems my case use is still not possible with current Ai? SmartConnections doesn't seem to be any better, or am I mistaken?

We had a well crafted GPT4 prompt with many tests covering our desired outputs. We took gpt35 and fine tuned it and now it's performing the same. Worked well for our use case!

dude try obsidian copilot can use ollama, with that can use dolphin mistral = it's uncensored AI so there is no guardrail, this way we can be anything creative with texts.

Almost none of this is AI.

Well done my man. Keep it up. Your content is valuable because your explainations are excellent!

Hi! Good video! I am wondering if you are using any of the openai service essentially you are not running the model locally right? Is there a local embedding and llm available for this, such as llama2 or mistral. Thanks! Awesome video.

Yes! I’m ready to upload my decades of original notes and content into Obsidian and instruct my LLM to cull through them to create new material based on my own source material. Come on, pick my brain.

Aye, very insightful, and was something I also picked up from using Stable Diffusion a lot. One thing that's helped a lot with prompting ChatGPT is the '-' dash seperator. It's a good way to make sure words are often not linked together as tokens, as 'Space Dash Space' is often just 1 seperate token in and of itself. If there are two seemingly odd words that I want to seperate in a prompt, it seems to give decent indication. I would say with json formatting, this can actually be pretty decent, as it's a clean well understood set of characters with clear meanings, [1,2,3] or whatever value is probably easily interpritable.

Oh this is just what I was looking for! A really great breakdown of this, thank you bud. Didn't even realise that something like Obsidian existed... Here I am doing api calls through vscode like a pleb, definitely time to move!

"you to curate data to feed AI"

I would say you are actually looking for Embeddings. You can set up a database with Embeddings based on our specific data which will be checked for similarities. The matches would then be used to create the context for the completions api. Fine tuning is more to modify the way how it answers. This was my understanding.

thanks for the insight

Can the content for training be collected from ChatGPT-4? For example, after chatting with ChatGPT-4, can the desired content be filtered and integrated into ChatGPT-3.5 for fine-tuning? Is this approach feasible and effective? Are there any considerations to keep in mind?

This struck me too, it seems not many quite noticed the gravity of the massive context. Not sure if you saw it, but there's a paper on arxiv with the title "World Model on Million-Length Video And Language With RingAttention" published a day or two before Sora and google's gemma 1.5 were announced. They show results with near perfect retrieval.

Question - as it relates to the needle in the haystack performance the research you quote is very recent work but unfortunately this damn space moves so freaking fast. Or is this even a question or maybe a statement. From what I understand in the Google blog post Gemini uses a new Mixture-of-Experts (MoE) architecture, which apparently delivers much improved processing/understanding of long context. They are quoting crazy needle in the haystack results. At the same time, GPT4 has a hard time processing moderately complex prompts (well within the token range in which it preforms well at in the needle test) so as a builder with road-rash I have a raised eyebrow! What am I missing?! :-)

Is it a waste of time for novelist too?

why, why so tiny amount of subscribers. Very much needed approach to problems, to tell 'wait a minute... here are the stones on the road"

Brother, one of the best breakdowns of this topic I've found yet.

The kung fu panda movies are pretty good.

i didnt get your point. You showed us a diagram with two system prompts, one before and one after the user prompts to control them. But in your code example, we didn't see that in action.

Sorry but why then it's a waste of time? It wasn't clear or finally mention as far as I've listened

I really like the video and your style so count me in as a subscriber. But showcasing Deno inside of Jupyter notebook and trying it out for myself was a bug disappointment as Deno can't track the values between cells and therefore there is no autocomplete or intellisense at all. I see in your video that it's the same in your installation.

Hi, new sub here. Do you have any video teaching how to build an small language model or using RAG to get a very simple conversation project demo going?

Very timely. I was just experimenting earlier with generating RFP responses based on past winning bids and corporate knowledge bases. The RAG is returning irrelevant docs even when there are very relevant docs. On other use cases, RAG seemed to work fairly well. I think it is to do with obscure concepts. In the RFP questions throwing off the vector distances. The buyers are after all trying to separate the good from the best. I will try some of these options as quick experiments but I’m going to have to dive deep into the vector distances, etc, and properly diagnose, build solid evaluation criteria, unit tests and monitoring KPIs for this stage of the pipeline. And try fine tuning for this use case.

Tinkering builds skills. Most people search for knowledge but its skills that they want, and skills will never be learned by watching an endless stream of social media, tutorials, lectures. It's doing vs knowing. Skills = applied knowledge = ability to do/create something

AI hype is big business. After watching a lot of AI dedicated channels for almost a year, I have learned to mainly view them with distrust. They hype everything AI to death, never honestly discussing limitations or problems, nor the solutions to the problems. Sources of good information are not mentioned, moreover they rarely have insight into what works and doesn't. Just superficial regurgitation of press announcements. This isn't true of everyone, but many.

Using chat gpt 4 its a odd mix of mid blowing capabilities, nuance, depth, subtlety to its answers but then often just really dumb predictive text where it has zero understanding