Загрузка видео...

Не удалось загрузить видео

На главную

.Weaviate AI Database is an AI-native vector database that allows you to store data objects and vector embeddings from your favorite machine learning models while scaling seamlessly into billions of data objects. AWS and NVIDIA work together in an ecosystem to deliver cost performance and efficiency for Weaviate. Weaviate...

AWSstartups's profile picture

AWS Startups

267,002 subscribers

1,476,044 просмотров • 4 месяцев назад •via X (Twitter)

Наука и технологии
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 8

Фото профиля AWS Startups
AWS Startups4 месяцев назад

@nvidia Learn more about AWS and NVIDIA:

Фото профиля Konstantin
Konstantin3 месяцев назад

@weaviate_io @nvidia Look at the face of AWS! United States of India! So proud.

Фото профиля Shaurya Chauhan
Shaurya Chauhan4 месяцев назад

@weaviate_io @nvidia Good to know about vector database on AWS market places,,, Can anyone really tell me how can I learn weaviate genuinely..The source, resources, everything. #AWSFriends #AWSCommunity

Фото профиля Frame
Frame3 месяцев назад

@weaviate_io @nvidia weaviate scales vectors well. Our identity layer needs that for memory replay.

Фото профиля Drmex Ω
Drmex Ω3 месяцев назад

@weaviate_io @nvidia Stinky jeet

Фото профиля Hyperbet Vietnam
Hyperbet Vietnam3 месяцев назад

@weaviate_io @nvidia cách anh em đang dùng weaviate trên aws marketplace để scale vector embeddings thì thấy chi phí và hiệu suất ra sao?

Фото профиля Hassan Argi
Hassan Argi3 месяцев назад

@weaviate_io @nvidia 💥"End the war against Iran." | Bernie Sanders

Фото профиля LESZEK SZAFRAN
LESZEK SZAFRAN3 месяцев назад

@weaviate_io @nvidia

Похожие видео

.Snorkel AI helps organizations leverage their own data and expertise to build high-quality, specialized AI systems orders of magnitude faster than fully manual approaches. The company drives value in partnership with AWS and NVIDIA to help their customers. Available in AWS Marketplace, Snorkel’s AI Data Development platform enables enterprises to turn their proprietary data and domain knowledge into expert evaluation and training data, with options for in house data development or white glove dataset delivery.
2:06

.Snorkel AI helps organizations leverage their own data and expertise to build high-quality, specialized AI systems orders of magnitude faster than fully manual approaches. The company drives value in partnership with AWS and NVIDIA to help their customers. Available in AWS Marketplace, Snorkel’s AI Data Development platform enables enterprises to turn their proprietary data and domain knowledge into expert evaluation and training data, with options for in house data development or white glove dataset delivery.

AWS Startups

2,761,707 просмотров • 4 месяцев назад

Real results from real teams. 🛠️💡 AWS Data & AI Bytes brings you demos & insights from customers building generative AI apps, scaling data platforms & modernizing with AWS services. Learn more about AWS for Data. 👉
0:38

Real results from real teams. 🛠️💡 AWS Data & AI Bytes brings you demos & insights from customers building generative AI apps, scaling data platforms & modernizing with AWS services. Learn more about AWS for Data. 👉

Amazon Web Services

12,130 просмотров • 1 год назад

December is the month for giving So here are 9 new Recipes demoing how to use Weaviate AI Database and Amazon Web Services, Contextual AI, @ChonkieAI, Parallel Web Systems, Google, Modaic, , and LlamaIndex 🦙 🧑‍🍳
0:30

December is the month for giving So here are 9 new Recipes demoing how to use Weaviate AI Database and Amazon Web Services, Contextual AI, @ChonkieAI, Parallel Web Systems, Google, Modaic, , and LlamaIndex 🦙 🧑‍🍳

Erika Shorten

12,888 просмотров • 11 месяцев назад

New short course: Building Multimodal Search and RAG", by Weaviate AI Database's Sebastia(N_) Witalec ✊🏽✊🏾✊🏿. Contrastive learning is used to train models to map vectors into an embedding space by pulling similar concepts closer together and pushing dissimilar concepts away from each other. This technique is also used to train multimodal embedding models that capture semantic similarity across different modalities like text, images, and audio. These multimodal embeddings can be used to build multimodal search and RAG systems. In this course, you'll learn how contrastive learning works, and how to add multimodality to RAG – so your models can draw on diverse, relevant context to answer questions. For example, a query about a financial report might synthesize information from text snippets, graphs, tables, and slides. You will also learn how visual instruction tuning lets you integrate image understanding into language models, and build a multi-vector recommender system using Weaviate’s open-source vector database. Please sign up here:
3:25

New short course: Building Multimodal Search and RAG", by Weaviate AI Database's Sebastia(N_) Witalec ✊🏽✊🏾✊🏿. Contrastive learning is used to train models to map vectors into an embedding space by pulling similar concepts closer together and pushing dissimilar concepts away from each other. This technique is also used to train multimodal embedding models that capture semantic similarity across different modalities like text, images, and audio. These multimodal embeddings can be used to build multimodal search and RAG systems. In this course, you'll learn how contrastive learning works, and how to add multimodality to RAG – so your models can draw on diverse, relevant context to answer questions. For example, a query about a financial report might synthesize information from text snippets, graphs, tables, and slides. You will also learn how visual instruction tuning lets you integrate image understanding into language models, and build a multi-vector recommender system using Weaviate’s open-source vector database. Please sign up here:

Andrew Ng

104,517 просмотров • 2 лет назад

$AMZN AWS launched Amazon Quick which is a desktop AI assistant that works across your apps and data to surface what matters and take action. This is agentic AI turning the inbox into an archive and becoming the layer that prioritizes and handles the busywork.
1:05

$AMZN AWS launched Amazon Quick which is a desktop AI assistant that works across your apps and data to surface what matters and take action. This is agentic AI turning the inbox into an archive and becoming the layer that prioritizes and handles the busywork.

Shay Boloor

44,667 просмотров • 6 месяцев назад

AWS Startups offers AI-powered migration planning and execution for startups moving from GCP, OpenAI, or Gemini to AWS. Generate a personalized migration plan in minutes that includes service mapping, cost estimates, architecture diagrams, Terraform templates, credit eligibility, and a step-by-step runbook. When you're ready to execute, choose the path that works for you. Use the AI Agent for guided migration, work hands-on with an AWS expert, or get matched with a certified AWS Partner.
1:15

AWS Startups offers AI-powered migration planning and execution for startups moving from GCP, OpenAI, or Gemini to AWS. Generate a personalized migration plan in minutes that includes service mapping, cost estimates, architecture diagrams, Terraform templates, credit eligibility, and a step-by-step runbook. When you're ready to execute, choose the path that works for you. Use the AI Agent for guided migration, work hands-on with an AWS expert, or get matched with a certified AWS Partner.

Amazon Web Services

5,548,117 просмотров • 3 месяцев назад

Build a RAG Application from Scratch 🐕 This video covers the architecture behind Verba 0.3.0! The design behind Verba is to have an explicit manager for each core component of RAG pipelines (Read, Chunk, Embed, Retrieve, Generate) 1. ReaderManager: Load in your data (GitHubReader, PDFReader, SimpleReader, etc.) 2. ChunkManager: Chunk up your data into smaller bits (avoids hitting the token limit and results in better retrieval) 3. EmbeddingManager: Convert your data into embeddings (use OpenAI, Cohere, SentenceTransformer, etc.) 4. RetrieverManager: Retrieve the relevant context from your query 5. GenerationManager: Generate an answer from the retrieved chunks Test out Verba on the Weaviate AI Database docs/blogs here: Verba repo:
4:36

Build a RAG Application from Scratch 🐕 This video covers the architecture behind Verba 0.3.0! The design behind Verba is to have an explicit manager for each core component of RAG pipelines (Read, Chunk, Embed, Retrieve, Generate) 1. ReaderManager: Load in your data (GitHubReader, PDFReader, SimpleReader, etc.) 2. ChunkManager: Chunk up your data into smaller bits (avoids hitting the token limit and results in better retrieval) 3. EmbeddingManager: Convert your data into embeddings (use OpenAI, Cohere, SentenceTransformer, etc.) 4. RetrieverManager: Retrieve the relevant context from your query 5. GenerationManager: Generate an answer from the retrieved chunks Test out Verba on the Weaviate AI Database docs/blogs here: Verba repo:

Erika Shorten

155,273 просмотров • 3 лет назад

Last week at NVIDIA GTC, the AWS 2026 AI Pitch Competition offered 6 early-stage AI companies the opportunity to compete for up to $25,000 in AWS credits, dedicated mentoring support from AWS and NVIDIA (through their Inception program), and exposure to senior leaders from AWS, NVIDIA, and top-tier VC firms. Startups Keyframe Labs, Kuvia, @NomadicML, Tynapse, Saptiva AI, and pitched to a panel of judges, presenting their technical and business models to the audience that gathered at the AWS booth. Nomadic took first place, followed by Kuvia in second and Bindwell in third. Each founder brought their A-game to the table, and we're excited to continue supporting them as they grow!
1:11

Last week at NVIDIA GTC, the AWS 2026 AI Pitch Competition offered 6 early-stage AI companies the opportunity to compete for up to $25,000 in AWS credits, dedicated mentoring support from AWS and NVIDIA (through their Inception program), and exposure to senior leaders from AWS, NVIDIA, and top-tier VC firms. Startups Keyframe Labs, Kuvia, @NomadicML, Tynapse, Saptiva AI, and pitched to a panel of judges, presenting their technical and business models to the audience that gathered at the AWS booth. Nomadic took first place, followed by Kuvia in second and Bindwell in third. Each founder brought their A-game to the table, and we're excited to continue supporting them as they grow!

AWS Startups

8,706,408 просмотров • 7 месяцев назад

This Drive is a Goldmine of AWS Certification Free Resources. Discover the following For FREE; - AWS Certified Solutions Architect - AWS Certified Developer - AWS Certified SysOps - AWS Certified Cloud Practitioner - AWS Certified Solution Architect - AWS Certified Developer - AWS Certified SysOps Administrator - AWS Certified Advanced Networking - AWS Certified Security - AWS Certified Big Data And much more. Drive link: If you enjoyed it and found it helpful; 1. Repost & Bookmark for future use. 2. Follow me Atal for more about AI, Tech Updates, and Free Courses. #AWS #AWSCertification #Onlinelearning
0:28

This Drive is a Goldmine of AWS Certification Free Resources. Discover the following For FREE; - AWS Certified Solutions Architect - AWS Certified Developer - AWS Certified SysOps - AWS Certified Cloud Practitioner - AWS Certified Solution Architect - AWS Certified Developer - AWS Certified SysOps Administrator - AWS Certified Advanced Networking - AWS Certified Security - AWS Certified Big Data And much more. Drive link: If you enjoyed it and found it helpful; 1. Repost & Bookmark for future use. 2. Follow me Atal for more about AI, Tech Updates, and Free Courses. #AWS #AWSCertification #Onlinelearning

Atal

71,352 просмотров • 2 лет назад

How to Train Your AI NFT (Introducing TolyAI) On-chain Clone We gathered Toly's Twitter activity from 2023 to 2025 and used it to create our SANA AI NFT. This allows you to ask questions and get answers that reflect Toly's Twitter style. The data is stored in a vector database, with the indexes secured on-chain via Metaplex Core APP DATA. We've made this agent openly available for everyone to use. Soon, anyone will be able to train their own AI NFT and store it on-chain. Toly Agent: Core Data: Dataset:
4:09

How to Train Your AI NFT (Introducing TolyAI) On-chain Clone We gathered Toly's Twitter activity from 2023 to 2025 and used it to create our SANA AI NFT. This allows you to ask questions and get answers that reflect Toly's Twitter style. The data is stored in a vector database, with the indexes secured on-chain via Metaplex Core APP DATA. We've made this agent openly available for everyone to use. Soon, anyone will be able to train their own AI NFT and store it on-chain. Toly Agent: Core Data: Dataset:

OctonetAI

19,373 просмотров • 1 год назад

Is your data center ready for AI? In this Transform Talks interview, Philippe Nicolas and Huawei's Yuan Yuan explain why moving to an all-flash data center is becoming inevitable for unified data access, higher efficiency, and AI-ready performance.
7:54

Is your data center ready for AI? In this Transform Talks interview, Philippe Nicolas and Huawei's Yuan Yuan explain why moving to an all-flash data center is becoming inevitable for unified data access, higher efficiency, and AI-ready performance.

Huawei

3,922,435 просмотров • 11 месяцев назад

Vector databases are a key part of many LLM applications that need search or data retrieval, for example with Retrieval Augmented Generation (RAG). Learn how they work + how to use them in our new short course, taught by Weaviate AI Database's Sebastia(N_) Witalec ✊🏽✊🏾✊🏿!
2:24

Vector databases are a key part of many LLM applications that need search or data retrieval, for example with Retrieval Augmented Generation (RAG). Learn how they work + how to use them in our new short course, taught by Weaviate AI Database's Sebastia(N_) Witalec ✊🏽✊🏾✊🏿!

Andrew Ng

420,683 просмотров • 3 лет назад

🚀I am excited to announce that Nile is live today! Nile is a Postgres platform to ship multi-tenant AI applications - fast, safe, and limitless Nile decouples storage from compute, virtualizes tenants, and supports vertical and horizontal scaling globally to provide 1. Unlimited Postgres databases, Unlimited virtual tenant databases 2. Customer-specific vector embeddings at 10x lower cost 3. Secure isolation for customer's data and embeddings 4. Autoscale to millions of tenants and billions of embedding 5. Place tenants on serverless or provisioned compute - globally in one database 6. Tenant-level branching, backups, schema migration, and insights
1:14

🚀I am excited to announce that Nile is live today! Nile is a Postgres platform to ship multi-tenant AI applications - fast, safe, and limitless Nile decouples storage from compute, virtualizes tenants, and supports vertical and horizontal scaling globally to provide 1. Unlimited Postgres databases, Unlimited virtual tenant databases 2. Customer-specific vector embeddings at 10x lower cost 3. Secure isolation for customer's data and embeddings 4. Autoscale to millions of tenants and billions of embedding 5. Place tenants on serverless or provisioned compute - globally in one database 6. Tenant-level branching, backups, schema migration, and insights

Ram

39,554 просмотров • 2 лет назад

YouTube is more than just a video platform; its comment section is a treasure trove of insights waiting to be unearthed. 1. Export all comments from any YouTube video, 2. Integrate with a vector database like Weaviate AI Database, 3. Create multiple AI agents to analyze language, sentiment, and context, 4. Generate a report. Here's an example from Anthropic CEO's talk on "$10 Billion Models, OpenAI, Scaling, & Alignment," featuring 427 comments. (See the second post for the results ↓) If you're a creator or part of a growth-focused business, you can: Get to know your market better than ever, Identify gaps, opportunities, and consumer sentiments, Gain real-time, unparalleled insights, Improve your content strategy and build a more engaged community. Join CompactKnow's waitlist now.
0:25

YouTube is more than just a video platform; its comment section is a treasure trove of insights waiting to be unearthed. 1. Export all comments from any YouTube video, 2. Integrate with a vector database like Weaviate AI Database, 3. Create multiple AI agents to analyze language, sentiment, and context, 4. Generate a report. Here's an example from Anthropic CEO's talk on "$10 Billion Models, OpenAI, Scaling, & Alignment," featuring 427 comments. (See the second post for the results ↓) If you're a creator or part of a growth-focused business, you can: Get to know your market better than ever, Identify gaps, opportunities, and consumer sentiments, Gain real-time, unparalleled insights, Improve your content strategy and build a more engaged community. Join CompactKnow's waitlist now.

Muratcan Koylan

181,397 просмотров • 3 лет назад

The AWS Local Zone in Athens is live. AWS just got closer to customers in Greece. The Athens Local Zone supports Amazon S3 and Amazon EBS Local Snapshots. Store, access, and back up data within Greece while running latency-sensitive workloads with single-digit millisecond response times.
0:30

The AWS Local Zone in Athens is live. AWS just got closer to customers in Greece. The Athens Local Zone supports Amazon S3 and Amazon EBS Local Snapshots. Store, access, and back up data within Greece while running latency-sensitive workloads with single-digit millisecond response times.

Amazon Web Services

2,769,406 просмотров • 3 месяцев назад

Made in San Francisco with AWS: David Twizer, CEO & Co-founder, xpander.ai. Why SF? “For the AI agent space, this city is mission zero.” xpander enables teams to build and deploy AI agents with any framework, in any environment. With Amazon Bedrock, the startup can train models and AWS solutions, scaling their business much faster.
1:07

Made in San Francisco with AWS: David Twizer, CEO & Co-founder, xpander.ai. Why SF? “For the AI agent space, this city is mission zero.” xpander enables teams to build and deploy AI agents with any framework, in any environment. With Amazon Bedrock, the startup can train models and AWS solutions, scaling their business much faster.

AWS Startups

11,353,493 просмотров • 6 месяцев назад

Now why would you see Oracle & AWS in a video together? Think cloud migration & deployment. Daniel Newman talks w/ Karan (Oracle Cloud) and Ruba Borno (Amazon Web Services) to get inside perspectives on the Oracle Database@AWS partnership, zero-ETL integration, and more.
18:08

Now why would you see Oracle & AWS in a video together? Think cloud migration & deployment. Daniel Newman talks w/ Karan (Oracle Cloud) and Ruba Borno (Amazon Web Services) to get inside perspectives on the Oracle Database@AWS partnership, zero-ETL integration, and more.

Six Five Media

22,758 просмотров • 1 год назад

AI-ready data, all under one roof. 🏠☁️💰 Introducing preview of Amazon S3 Vectors—the first cloud object store with built-in vector support. Store vectors at scale with up to 90% total savings and query with ease, all in one place. #AWS #AWSSummit 👉
0:30

AI-ready data, all under one roof. 🏠☁️💰 Introducing preview of Amazon S3 Vectors—the first cloud object store with built-in vector support. Store vectors at scale with up to 90% total savings and query with ease, all in one place. #AWS #AWSSummit 👉

Amazon Web Services

50,729 просмотров • 1 год назад

Introducing the next generation of AI pioneers! 💡 🚀 We’re excited to announce the 80 startups selected for the 2024 AWS Generative AI Accelerator! They'll receive up to $1M in credits, mentorship, and support from #AWS and NVIDIA. Meet the cohort:
0:56

Introducing the next generation of AI pioneers! 💡 🚀 We’re excited to announce the 80 startups selected for the 2024 AWS Generative AI Accelerator! They'll receive up to $1M in credits, mentorship, and support from #AWS and NVIDIA. Meet the cohort:

AWS Startups

18,237 просмотров • 2 лет назад