Britton LaRoche
Britton LaRoche
  • Видео 38
  • Просмотров 21 711
Couchbase Vector Search
Learn how to connect to Couchbase Capella through the Confluent Cloud after calling a vector embedding service to automatically update the Couchbase Vector Search Indexes.
Просмотров: 17

Видео

Look at me, I am a monkey!
Просмотров 72Месяц назад
Lyrics by Britton LaRoche Music by Suno Video by Sora The lyrics are the only thing I can really claim as my own work. And quite frankly the lyrics are half baked, I just had fun with it. What blew me away as how beautiful Suno made the lyrics "Ah ah ah ooo ooo Eee eee eee eee" I was just typing the noises I thought a monkey would make. [Intro] Babab ababa boo eee I swing from tree to tree A mo...
Building a Real-Time Vector Database for RAG made easy with Confluent Cloud and MongoDB Atlas
Просмотров 4345 месяцев назад
Are you building a vector database with enterprise data for Retrieval-Augmented Generation (RAG) with an LLM? Learn how two of the hottest cloud native technologies have come together to make building a GenAI application with RAG a breeze. Watch an amazing demo (that you can easily replicate) showing how Confluent Cloud's Fully Managed Apache Kafka with FlinkSQL and MongoDB Atlas Vector Search ...
Poo Bear Rapping
Просмотров 66Год назад
Winnie the poo entered the public domain and because a rapper. Everything was done through artificial intelligence. Lyrics from ChatGPT-4 with AIPRM prompts. Melody and singer from uberduck.ai. Images generated with Midjourney V5, also with AIPRM prompts from ChatGPT-4. Videos generated from Pika Labs www.pika.art/ and runway runway.ai.
mERICA
Просмотров 34Год назад
A quick video inspired by our times. Set to rap music it highlights the value of liberty, responsibility and sacrifice.
Merica Song
Просмотров 75Год назад
Generated purely from AI. Its a new AI inspired national anthem for the United States of America
A Gen AI Franz Kafka Introduces ChatGPT-4 working with Confluent Cloud and Atlas Vector Search
Просмотров 590Год назад
An AI generated Franz Kafka introduces a demo on how to prompt ChatGPT-4 with real-time product Vector embeddings to assist customers in finding the right product. The demo Utilizes MongoDB Atlas Vector search working with the Confluent Cloud. MongoDB's product vector embeddings are continuously updated from multiple systems sending data to the Confluent Cloud allowing a Digital Assistant anima...
Franz Kafka Introduces ChatGPT4, MongoDB Vector Search, and Confluent Cloud
Просмотров 123Год назад
AI Generated Franz Kafka introduces a demo that show cases the synergy between Confluent Cloud, MongoDB Atlas Vector Search and ChatGPT-4.
Gen AI Charles Babbage Short intro of ChatGPT4 working with Confluent Cloud and Atlas Vector Search
Просмотров 225Год назад
Generative AI produced a reanimated version of Charles Babbage who introduces a Digital Assistant Demo integrating the Confluent Cloud and MongoDB Atlas vector search capabilities. These capabilities are used to prompt Chat GPT4 to provide near perfect product recommendations.
Gen AI Charles Babbage Short intro of ChatGPT4 working with Confluent Cloud and Atlas Vector Search
Просмотров 30Год назад
Generative AI produced a talking head of Charles Babbage who introduces a Digital Assistant Demo integrating the Confluent Cloud and MongoDB Atlas vector search capabilities. These capabilities are used to prompt Chat GPT4 to provide near perfect product recommendations. Fit for Halloween, Gen AI can be a bit creepy but it captures everyone's attention.
Gen AI Charles Babbage introduces Chat GPT4 working with Confluent Cloud and MongoDB Vector Search
Просмотров 59Год назад
Generative AI produced a digital twin of Charles Babbage who introduces a Digital Assistant Demo integrating the Confluent Cloud and MongoDB Atlas vector search capabilities. These capabilities are used to prompt Chat GPT4 to provide near perfect product recommendations. Edited to remove some of the built in delay from Chat GPT4.
Gen AI Chat GPT4 - Confluent Cloud and MongoDB Vector Search
Просмотров 366Год назад
Digital Assistant Demo working with Confluent Cloud working and MongoDB vector search to prompt Chat GPT4 with near perfect product recommendations. Edited to remove some of the built in delay from Chat GPT4. Github here: github.com/brittonlaroche/GenAI-ChatGPT4-Confluent-MongoDB-Vector-Retail
Gen AI Chat GPT4 - Confluent Cloud and MongoDB Vector Search
Просмотров 325Год назад
Digital Assistant Demo working with Confluent Cloud working and MongoDB vector search to prompt Chat GPT4 with near perfect product recommendations. Github here: github.com/brittonlaroche/GenAI-ChatGPT4-Confluent-MongoDB-Vector-Retail
GenAI Kafcongo Update 2023-08-25
Просмотров 156Год назад
Kafcongo at Work... Our new digital assistant describes how Confluent Cloud, MongoDB Atlas and Chat GPT work together to update a LLM with realtime data. "Hello, my name is Jayne. I am your personal digital assistant. My insights are powered by real time event data streams from the Confluent Cloud for user clicks, purchases, returns, reviews and customer loyalty data. All of the events are sync...
GenAI MongoDB Vector Search working Confluent Cloud
Просмотров 917Год назад
Gen AI demo script running against a MongoDB product catalog in an Atlas database using a Vector Search against the products after an API call to Open AI Chat GPT 4 model. When the user clicks products this is put into Confluent Cloud through rest produce and synchronized to MongoDB through the connector architecture. Github behind the demo is here: github.com/brittonlaroche/GenAI-ChatGPT4-Conf...
Live Digital Agent Generative AI Chat GPT 4 demonstration with Confluent Kafka and MongoDB Atlas
Просмотров 153Год назад
Live Digital Agent Generative AI Chat GPT 4 demonstration with Confluent Kafka and MongoDB Atlas
Kafcongo Presentation
Просмотров 326Год назад
Kafcongo Presentation
Confluent Cloud Connect API with Postman
Просмотров 1,4 тыс.Год назад
Confluent Cloud Connect API with Postman
Connector Fixes Part 2
Просмотров 48Год назад
Connector Fixes Part 2
Confluent Cloud Connector Fixes Part 1
Просмотров 78Год назад
Confluent Cloud Connector Fixes Part 1
Processing new orders in real time from Oracle to MongoDB with the confluent Cloud!
Просмотров 112Год назад
Processing new orders in real time from Oracle to MongoDB with the confluent Cloud!
Create the fully managed MongoDB Atlas Sink Connector in the Confluent Cloud
Просмотров 758Год назад
Create the fully managed MongoDB Atlas Sink Connector in the Confluent Cloud
Create the fully managed Oracle Source JDBC Connector in the Confluent Cloud
Просмотров 441Год назад
Create the fully managed Oracle Source JDBC Connector in the Confluent Cloud
Creating a Confluent Cloud Cluster
Просмотров 508Год назад
Creating a Confluent Cloud Cluster
Creating a MongoDB Atlas Cluster
Просмотров 2,8 тыс.Год назад
Creating a MongoDB Atlas Cluster
Installing SQL Developer and Connecting to the New AWS RDS Oracle Instance
Просмотров 2,4 тыс.Год назад
Installing SQL Developer and Connecting to the New AWS RDS Oracle Instance
Creating an Oracle instance in AWS RDS
Просмотров 208Год назад
Creating an Oracle instance in AWS RDS
Charles on rope ladder
Просмотров 92 года назад
Charles on rope ladder
Realm Intro 2
Просмотров 374 года назад
Realm Intro 2
RealmIOT Intro Only
Просмотров 544 года назад
RealmIOT Intro Only

Комментарии

  • @jainc
    @jainc 3 месяца назад

    Hi Britton, am really interested in doing this walk-along, but the guide on github has been updated to use Amazon Bedrock instead of the openai api. I'm trying to use my openai api to follow along, but the syntax in the video no longer works and I don't see any alternatives to bedrock in your documentation. This feels like a really useful tutorial you've made. Any chance you can help me finish the demo using openai api?

  • @inoxide5454
    @inoxide5454 4 месяца назад

    ahhh that friggin' inbound rule eh? didn;'t see hta tin the manual !

  • @mariacunha8508
    @mariacunha8508 9 месяцев назад

    Thank you for this video, it was very informative and easy to follow :D

  • @aironmanDiver
    @aironmanDiver 11 месяцев назад

    It is an amazing demo, but how many customers want to lock with proprietary technology using their data, confluent cloud and an external LLM? to me it is the same problem with Cloudera Spark, Databricks, AWS, GCP and Azure. They are tremendously expensive services that very few companies can afford and on top of that these companies try to continue making money, but they see that they cannot because part of their technology is in the hands of these third-party services that become more important, necessary and expensive every year. They tie you down for life.

  • @dinkaman2160pukka
    @dinkaman2160pukka Год назад

    super cool dude! thx.

  • @tranhuudan6403
    @tranhuudan6403 Год назад

    CAN I ASK FOR SOURCE CODE?

  • @destocot1729
    @destocot1729 Год назад

    wow this is so cool, hope I can get up to this level, I just started with just just learning what create embedding is with openai and already feel overwhelmed and so behind

  • @KirkNesbitt
    @KirkNesbitt Год назад

    very cool

  • @AlexSimons-iy7lr
    @AlexSimons-iy7lr Год назад

    How awesome are MongoDB and Confluent?

  • @AlexSimons-iy7lr
    @AlexSimons-iy7lr Год назад

    This is so cool 😎🤙

  • @jefferyschmitz3009
    @jefferyschmitz3009 Год назад

    This is awesome work -

  • @derekkane4687
    @derekkane4687 Год назад

    This is so cool, Britton! Outstanding job.

  • @andrewjohnson3073
    @andrewjohnson3073 Год назад

    Nice job Britton!

  • @Duraiamuthan
    @Duraiamuthan Год назад

    Thanks it was helpful. To be precise deleting and re-adding the inbound rule did the magic for me.

  • @pankajwp
    @pankajwp Год назад

    Thank you so much, was always creating a new topic instead of using the one created by source

  • @clairromandia4035
    @clairromandia4035 Год назад

    *promosm*

  • @pavanbv25
    @pavanbv25 Год назад

    Thank you posting this awesome video. Can you please help me with videos to learn more about MongoDB Atlas sink connector. I am using it for first time in my project and i need to know more advance level. like if data is coming from CDC how this sink connector will work to push it to mongodb.

    • @scoobeedew
      @scoobeedew Год назад

      Slowly but surely... may do a deep dive on the MongoDB Atlas source and sink, but it will take some time.

  • @Me.C.K
    @Me.C.K 2 года назад

    Well done!

  • @papesaliouka
    @papesaliouka 3 года назад

    thank you

  • @programmingtechnology5510
    @programmingtechnology5510 3 года назад

    hello sir when i try to run realm-cli import --strategy=replace in ealm-master\inventoryDemo\export\backOffice> it throw error push failed: resource name can only contain ASCII letters, numbers, and underscores. what i should do please help me..

  • @karimdoublea5431
    @karimdoublea5431 4 года назад

    @Britton LaRoche looks nice and very promising.. is this also possible to do this with my existing MongoDB(4.X) on premise instead of Atlas?

  • @fidelventura957
    @fidelventura957 4 года назад

    Thank you, excellent demo.

  • @ThachNguyen-tx5yp
    @ThachNguyen-tx5yp 4 года назад

    This is so amazing!!! <3

  • @lyongreene8241
    @lyongreene8241 4 года назад

    w0w