Name: Introduction to Astra: Cassandra-as-a-Service on Google Cloud
Start: 2021-02-18T19:00:00Z
End: 2021-02-18T19:00:36.000Z
Location: BrightTALK
Rating: 5

We provide the real-time vector data tools that Gen AI apps need, with seamless integration with developers’ stacks of choice (RAG, Langchain, LlamaIndex, OpenAI, GCP, AWS, Azure, etc).


Join us to explore the future of humans and machines in a dynamic discussion. Discover how AI reshapes job markets, the importance of human qualities, and the path to continuous learning and collaborative optimism.

The Future of Humans + Machines: Co-Creating with AI

Explore the transformative journey Rakuten Card is driving by integrating generative AI into business-critical operations.

Moving Gen AI from Concept to Business Critical

Join experts delving into enterprise AI governance models, ethics, risk, cross-sector collaboration, policy and privacy:
- Every developer building generative applications needs to be aware of their company governance processes
- The ethical implications are wide-ranging and intersectional
- Many great resources are available from thought leaders in industry, academia, and nonprofits like WEF

Enterprise Governance in a Responsible AI World

Discover where you stand, where to go next, and how to capture the transformative potential of Generative AI:
- Navigate the progression from novice experiments to sophisticated AI-driven solutions
- Discover where you stand, where to go next, and how to capture the transformative potential of Generative AI

AI Maturity Model

Learn how to build an AI-powered chatbot with Astra DB and Google’s Vertex AI.

Building an AI Chatbot with Vertex AI and Astra DB

Learn how to rapidly build production-ready Gen AI applications and see a real-world demo of Q&A against your data:

- LangStream is a new way to create and run Gen AI applications
- Bring your data to AI when creating LLM prompts
- Rapidly build streaming AI agents with little or no code

Build a Streaming AI Agent using OpenAI, Vercel, and AstraDb in 10 lines of code

Build proactive Generative AI apps with real-time events easily:
- Real-time data processing unlocks powerful new types of reactive and proactive generative AI applications
- Thanks to recent advances in AI tooling (foundation models, AI-as-a-service, modern event processing) it’s possible to rapidly build working Gen AI applications
- Kaskada provides a data foundation for real-time Gen AI applications, democratizing this powerful new type of Gen AI

Real-time events to LLMs, built in 15 minutes with no data science experience

Learn the key building blocks that will deliver a successful, scalable, secure data foundation for your Gen AI strategy.

Generative AI for the Enterprise: Secure, Scalable, Compliant and 5X cheaper

Learn how Gen AI, LLMs, AI assistants, and intelligent agents are all powering next-generation customer experiences to transform every business.

There’s No AI Without Data: Vectoring the Enterprise

Are you struggling with the challenges posed by massive datasets and AI applications? Vector Search is a transformative solution that can help you address these issues. As a decision-maker, you always look for ways to optimize your organization's operations and maximize ROI. Luckily, integrating Vector Similarity Search into Cassandra can help you achieve these goals.

Join Patrick McFadin Apache Cassandra Committer and discover how: 

1. Vector Search can revolutionize handling AI workloads and managing large datasets.
2. Real-world applications of Vector Similarity Search in content-based image retrieval, recommender systems, and natural language processing.
3. Integrating Vector Similarity Search into Cassandra enables faster and more relevant data retrieval, boosting the performance of data-driven applications.
4. Vector Similarity Search in Cassandra can solve data management challenges, drive efficiencies, and maximize ROI for your organization.

Don't miss this opportunity to learn how the cutting-edge Vector Similarity Search functionality in Cassandra can solve your organization's data management challenges, drive efficiencies, and propel your business forward. This strategic move towards enhancing Cassandra's offering underscores its position at the forefront of scalable data management solutions and reaffirms its commitment to meeting the evolving needs of developers and businesses alike.

Vector Similarity Search in Apache Cassandra®

You have all this data coming into the system, what are you going to do with it? Maybe store it in some lake ‘o data to never be spoken of again? Or better yet, write it to a microservice’s dedicated store where no one has access to.

Let’s think about things in a different way - use that data in real time! Make decisions on the fly to help your customers with a better experience! Store the decisions as a record of business value already realized.

In this session, we are going to look at how streaming and real-time AI enables enterprises to do more with data. But we’re not going to weigh you down with all the boring business trends and percentages. We are going to review a working example of an ecommerce site watching the viewing trends of a live customer and promoting related items that are of strong interest to the person. It doesn’t get any more real time than this!

Real-Time AI Explained. Enabling Ecommerce Instant Decisions with Streaming

DataStax and Temporal are on a mission to help developers build durable, resilient apps that never fail, no matter how fast they scale or how demanding the business. But building reliable apps can be complex, creating obstacles and delays for developers working under intense pressure. 

Temporal and DataStax are delivering a new programming model for developers: cloud-native, invincible apps, without the burden of complexity, helping you focus on what you do best: building great software, fast.  Join us and hear:

- Temporal’s durable execution paradigm provides extreme reliability, and makes it trivial or unnecessary to implement distributed systems patterns like event-driven architecture, task queues, sagas, circuit breakers, and transactional outboxes.
- DataStax’s Astra platform provides the tools to build out real-time systems.
- Temporal and DataStax together provide a robust platform on which to build scalable, fault-tolerant applications.

We’ll also explore why Temporal chose Cassandra as the highly-reliable, scalable database for their own platform. And how this combination can deliver invincible apps for your business as well.

Building Invincible Applications with Temporal & Astra DB

Martin (Marty) Brodbeck joined Priceline as Chief Technology Officer in 2019. Marty is responsible for all product engineering, infrastructure, data and technology operations for Priceline.

At Priceline, Marty has spearheaded the company’s digital transformation, leading a product migration and instituting a new micro-services architecture powered by the cloud. Additionally, he developed a new data platform that powers the brand’s marketing and consumer capabilities, which have been essential to the growth of the company.

Driving Priceline's Digital Transformation with Real-Time Data

Ayushi Singh is a Senior Software Engineer in the Online Datastores team at Netflix. With her expertise in open-source projects like Apache Cassandra, Ayushi is helping drive Netflix's vision to entertain the world through scalable data solutions. Prior to her role at Netflix, Ayushi was a member of the Core Platform and Infrastructure team at PayPal implementing cloud platforms in a hybrid cloud setting. Her contributions empowered PayPal's business teams to scale their applications, serving millions of customers globally and processing billions of dollars in payments.

In this Digital Champions interview, Ayushi emphasizes the importance of creating an inclusive space for learning and collaboration in the technology industry, especially for women. Her insights are invaluable to fostering diversity in the field. Ayushi also discusses the power of Apache Cassandra and provides a glimpse into Netflix's strategic use of real-time data for content creation, infrastructure monitoring, and marketing strategies.

Ayushi Singh Provides a Glimpse of Netflix's Strategic Use of Real-Time Data

Are LLMs (Large Language Models) the most exciting new capability since the advent of mobile? 

ChatGPT has enterprises and developers racing to use LLMs to innovate products, customer service, marketing, and customer experiences.  

Watch this webinar to understand:

- Who should use LLMs
- How it will impact your enterprise
- How it relates to your real-time AI strategy
- How do LLMs relate to other AI and ML services and technology?

We explore the benefits of using LLMs for the enterprise, including the ability to provide real-time insights into customer behaviour and preferences, all while streamlining workflows and reducing costs. 

Uncover the relationship between LLMs and other AI and ML technologies, including their ability to process and analyze vast amounts of data in real-time. Additionally, we discuss the ethical considerations of LLMs, the potential for bias and the importance of transparency and accountability.

This webinar is ideal for enterprise leaders and decision-makers looking to stay ahead of the curve in the rapidly evolving world of AI and ML. Don't miss this opportunity to gain valuable insights into the power of LLMs for your enterprise AI strategy.

Large Language Models (LLMs) for the Enterprise" ChatGPT and Beyond

ACID transactions are coming to Apache Cassandra!  Tune in to learn how you'll be able to leverage Cassandra to apply a group of operations across several partition keys, and have it treated as an atomic, single unit of work.  See how this change is going to dramatically improve the Cassandra developer experience and open the Cassandra world up to a whole slew of new use cases.

We start by introducing the concept of ACID (Atomic, Consistent, Isolated, Durable) transactions within the Apache Cassandra paradigm.  We also discuss the current roadmap for implementation, as well as a little about the computer science behind the enhancement.

ACID Transactions on Cassandra

Looking even further forward into the next few years, how will you use Cassandra? The two areas of our community that will grow the fastest are cloud native and AI/ML workloads. Cassandra was built for the next generation of applications. We are adding even more capabilities to help you develop faster with less effort.

Cassandra Forward: Whats Next in Apache Cassandra Use Cases?

It’s time to bring the power of AI to your data. Join Matt Kennedy, Product Strategist and Dr. Charna Parkey, Real-time AI Product & Strategy Leader to learn:
- Why real-time AI is critical for market-leading apps
- How organizations can build AI-powered apps with proven success patterns
- How to prepare for real-time AI with event data
- And get a preview of how to bring ML to your real-time dataset

Unleash Real-time AI to your Event-based Data

Join us for an introduction to Astra, Cassandra-as-a-Service, and how it can be deployed in the Google Cloud.

In this webinar you’ll learn:

-What is DataStax Astra
-Astra in the Google Cloud Ecosystem
-Astra on GCP: Architecture Teaser

Introduction to Astra: Cassandra-as-a-Service on Google Cloud

Cloud

Google

Cloud Architecture

Developers

Open Source

Cloud Native

Serverless

Cassandra

Database Management

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Introduction to Astra: Cassandra-as-a-Service on Google Cloud

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