Thank You, Rick Jacobs. A timely and useful review. I have tried to use Pinecone in the past, but now I will give it a fresh effort !
@HomeDesign_Austin5 күн бұрын
great interview, i'd suggest improving the mics going forward, bit hard to hear
@satish10125 күн бұрын
One question What I understand is the plain text is send to LLM and LLM will return the summarized text . But if we are sending confidential info to LLM, then it would be a breach. In that case we can create our own LLM ?
@koliux117 күн бұрын
mmm booking "The Habitat Lombok" on Bali ... nice place I've been there. Dude learn some old school SQL databases and their engines and their indexes and at least then you can do better analogies to Pinecone arch. I really struggled to follow, and don't touch your face when you're presenting. Thanks for the workshop !
@Alice800022 күн бұрын
cool! What's your favorite use case where PC really shines?
@Elindorn_28 күн бұрын
Отлично 👍🏻
@shivanidwivedi1625Ай бұрын
this is 5 months old and many changes are there in methods , so i can i learn those?
@shivanidwivedi1625Ай бұрын
this environment we get from?
@anjanikumar8298Ай бұрын
not able to understand
@milindbebarta2226Ай бұрын
Can I get the slides from this presentation?
@redasaeed2180Ай бұрын
Great job mate!
@bkadduchАй бұрын
Does not show anything about getting started. Skipped many important steps useful for beginners
@JasonMelanconEsqАй бұрын
Providing a Fiverr like platform where we can find developers experienced with Langchain and Pinecone would be amazing!
@abhinavchhabra4947Ай бұрын
Does pinecone support hybrid search?
@seattlesonicАй бұрын
Excellent work! Very inspiring, and a good “domain” application of how to use PineCone.
@pelangosАй бұрын
Could be useful in a CRM application
@zackproserАй бұрын
Yep! Also across any kind of document / PDF search - not just legal!
@zuowang5185Ай бұрын
Do I have to use a vector database, how about using gpt to generate a ElasticSearch query and having the proprietary data in ES and then do the factual context padded gen model query @zackproser
@decryptifi22652 ай бұрын
Very nice explanation. Thanks Zack for sharing
@pinecone-ioАй бұрын
Glad you found it useful! 🙏
@aiwithgurinder2 ай бұрын
This is great. thanks for sharing. Request to put chapters for easy follow along. Thanks
@mateuszsmendowski26772 ай бұрын
Cool stuff :)
@pinecone-ioАй бұрын
Glad you liked, thanks!
@MaliciousCode-gw5tq2 ай бұрын
Hi how about Search Score What are your thoughts about it? will it represent the accuracy of the information taken from the DB which relates to the query?
@ChristianDesharnais2 ай бұрын
- 00:00: Discussion on transforming customer support with AI and language models - 00:16: Introduction to MyAsk AI founders and their focus on customer support - 01:04: Empowering customer support using AI chatbots and gathering feedback - 02:40: Insights into founders' background and transition to entrepreneurship - 04:44: Entrepreneurial journey from travel startup to AI-focused company - 04:52: Transition from tech interest to starting own business - 05:14: Challenges faced with Pluto travel startup and its closure - 06:01: Evolution towards AI with MK AI development - 09:28: AI Chat GPT customization and usability - 09:30: Focus on reducing support ticket volume - 09:42: Tailored content for users and customer support - 09:53: Differentiation from generic models for accuracy and customization - 14:12: AI Support Features Overview - 14:16: 75% resolution by AI, 25% to human - 14:32: Focus on quality answers through data - 15:10: Insights from conversations for better focus - 18:56: Discussion on key tools for rapid business development - 19:02: Usage of Bubble for no-code development in front and back end - 19:17: Importance of fast development cycles utilizing tools like Bubble and Carbon - 20:02: Integration of Portkey for AI model requests and fallback options - 23:41: Discussion on embedding models and chunking strategies - 24:02: Migration to new open AI embedding models - 24:24: Challenges in migrating embedding models - 24:46: Performance improvement with new OPI models - 28:25: Key points on data processing challenges and AI advancements - 28:37: Suggests focusing on customer use cases to streamline data handling - 29:05: Advises identifying poor-quality data sources to enhance outcomes - 29:29: Emphasizes the need for novel strategies in tackling data processing issues - 33:09: Challenges in deploying AI technologies and navigating distribution channels - 33:34: Differentiating services in a crowded market - 33:42: Demonstrating credibility and business stability - 34:25: Struggle to find repeatable distribution channels for AI products - 37:53: Discussion on managing system prompts and user feedback in LLMS production - 37:57: Challenges in ensuring obedience to system prompts - 38:07: Importance of patience and testing in LLMS production - 39:00: Handling user feedback signals and AI-human handover for improvement - 42:37: Discussion on handling unstructured data and updating content - 42:50: Scraping processes used for web content and PDFs - 42:58: Handling tabular data and structuring it - 44:20: Updating content in Pinecone index for customers
@garmanwu43502 ай бұрын
very pratical demo about multi modal
@MohamedHomaid2 ай бұрын
Great feature
@alishafii91413 ай бұрын
your explanation was great thanks. please keep go on.
@davidmiller6263 ай бұрын
OUTDATED
@TBARBL3 ай бұрын
I am watching the stream in 2024.
@AhmedKorany3 ай бұрын
I really enjoyed your explanation of what is the vector DB is and it’s role in LLM world.
@pinecone-io3 ай бұрын
Thanks so much!
@xwyangjshb23 ай бұрын
good job!
@anangrajsinghtomar32793 ай бұрын
very useful for someone starting with pinecone like me !!
@AlanDeikman4 ай бұрын
I ended up with the flu sorry I was in no shape. Thanks for the recording.
@BTFranklin4 ай бұрын
I was traveling when the stream happened, so I couldn't attend live. I very much appreciate that you posted this recording. Excellent information and analysis here.
@MatijaGrcic4 ай бұрын
Great workshop!
@micjays68874 ай бұрын
Hi, i'm ecuadorian, Can you provide me with this Notebook
@thelateknights5 ай бұрын
One question -- it seems to me like each embedding / vector would contain a different number of dimensions. Trying to establish a master-type vector template with every single conceivable dimension represented would involve mainly blank space and be a computational nightmare (hence PCA and other dimensional reduction techniques). So if something complex like "the US Constitution" has thousands of dimensions and something like "grass" has hundreds of dimensions, how can they be compared, seeing as they reside in spaces with different numbers of dimensions? Like, you can't find the distance between an object that resides in 7 dimensional space and an object that resides in 11 dimensional space, right?
@JeffreyMyersII5 ай бұрын
What? Since when did English become an ambiguous language? From my understanding, it's the opposite. Ambiguous languages are those like Semitic languages. Just the fact you can use a different English word to clarify an ambiguous English word is unambiguous.
@djpete2009Ай бұрын
In terms of machine learning, English is ambiguous. We communicate mostly contextually. If you give one set of prompts to two or three different LLMs, the output will be wildly different. Especially in Image generation and the likes.
@JeffreyMyersIIАй бұрын
@@djpete2009 True, but I wouldn't call English an ambiguous language. Sure, ambiguity exists, but compared to other natural languages, it's rather unambiguous.
@djpete2009Ай бұрын
@@JeffreyMyersII English is spoken differently in England, NI, Wales and Scotland. The regional differences alone is so variegated its not even the same language. But it is. Intrinsically.
@Gabriel-wl9yy5 ай бұрын
Is this the official channel?
@pinecone-ioАй бұрын
It is, yes!
@user-wj7fm4xk7o5 ай бұрын
I would love to have the same tutorial but for free tier as well, since Serverless and Pods indexes are not supported without paid plan
@pinecone-io4 ай бұрын
The free plan now runs serverless indexes.
@ytprodata5 ай бұрын
The baked-in subtitles are SO distracting. Really spoils an otherwise good presentation
@tedk-4221 күн бұрын
You can turn them off by closing your eyes
@donovanh78785 ай бұрын
Unwatchable with the baked-in closed captions. You are also subverting assistive technologies when not using proper closed captions.
@maqknight5 ай бұрын
what about using javascript imstead of python cause i am doing a project and pinecone is suppoused to retireve the data from aws s3 and open a chat where the user chats with their pdf
@harshadnaidu42946 ай бұрын
what an excellent explanation
@pinecone-ioАй бұрын
So glad it was helpful!
@davidtindell9506 ай бұрын
Thank You. Yes! This was / is useful !!
@zenfoil6 ай бұрын
Very great video explaining a complex concept
@JanVansteenlandt6 ай бұрын
Thanks for the upload, as other people here I subscribed but missed the actual live webinar, it's not that easy to make some time.
@user-te8rb7ki8z6 ай бұрын
Please stop using jupyter notebooks they have 0 real world application
@lixpiai6 ай бұрын
Thanks! But please don't use the on-screen text, it's horrible! Can't watch the video because of it, soooo annoying!!!!
@pinecone-ioАй бұрын
Understood, thanks for the feedback!
@amo60026 ай бұрын
I'm a guy who just wants to use the tools to get the work done. I jumped to serverless, got halfway across and then saw that langchain which I was using (and I think many others) is broke when it comes to Pinecone.from_documents(). Loading a premade dataset to pinecone.dataset does not help me as I don't need to work with a play dataset. Things are moving fast on this I know, but the transitions should be a little more coordinated. I would love to move forward but I needed some handholding which just wasn't there. Other youtube videos with Mr Briggs are tremendous BTW.
@user-he3sn8qt6m6 ай бұрын
This was a great session. Thanks!
@saliexplore30946 ай бұрын
Your explanation of embedding spaces was on point! Thanks for sharing.
@pinecone-io6 ай бұрын
Thanks so much for the feedback, and glad it was useful!