Mastering serverless: A day in the life of a builder (Level 300)
What does it mean to be a serverless builder? What disciplines do you need to successfully build cloud-native, serverless solutions today? In this session, we walk you through a day-in-a-life and insights on the core disciplines based on our engagements with several builders and developers. Understand what are the common design challenges and considerations in the decision making to manage these challenges. We then explore the architecture patterns, frameworks and tools for developing, testing, and deploying your serverless applications.

Speaker: Stephen Liedig, Principal Solutions Architect, Serverless, AWS
Duration: 30mins

Integration patterns for building distributed applications (Level 300)
Teams building microservices architecture often find that integration with other applications and external services can make workloads more monolithic and tightly coupled. One of the critical aspects of decomposing monolithic applications is to design how various services interact with each other seamlessly. To do that, there are multiple considerations that needs to be accounted for and these considerations needs that align with business, performance, and resiliency requirements. In this session, we discuss different integration patterns, and how they can be combined together to achieve a scalable and resilient architecture. We take you through use cases via demos on how event-driven architectures and async work. Understand how to handle transactions and workflows into your architecture with orchestration, as well as how both approaches work together.

Speaker: Jan Tan, Principal Solutions Architect, AWS
Duration: 30mins

Move containerized applications to AWS (Level 300)
Many builders are looking for efficient ways to run their containers for security, reliability, and scalability. Containers have changed software development, testing, and deployment by enabling faster experimentation and value delivery. And running on cloud offers flexibility, scalability, reliability, performance, and cost-effectiveness. However, the question remains - how can one seamlessly integrate these two worlds? How do builders reap the benefits of containers and the cloud? In this session, learn how to formulate a container migration strategy, containerize, and migrate these workloads from your source to AWS. Discover how to successfully complete these migrations, evaluate the methodology to choose specific migration methods, and lay the right foundation for subsequent migration. The session also covers how to accelerate your generative AI project in a cost-optimized and scalable manner. We walk you through how to run and optimize your machine learning workloads with containers on AWS.

Speaker: Frank Fan, Senior Solutions Architect, AWS
Duration: 30mins

Accelerate your production with serverless and generative AI (Level 200)
Join this session to learn how RACQ built a generative AI assistant for insurance claims processing. We cover the architecture featuring serverless technologies such as AWS Lambda and AWS Step Functions, for workflow orchestration. Find out how RACQ used Amazon ECS on Fargate, a serverless approach for hosting front-end application and Amazon Bedrock to build an automated, scalable workflow triggered by claim events. We also share how they used AWS to enable data redaction, prompt techniques, human feedback loops, and adherence to responsibility principles for privacy, safety, and transparency. With AWS services' built-in security controls, such as VPC integration and encryption for Amazon Bedrock, understand how RACQ deployed generative AI capabilities securely. At the end of the session, understand how RACQ's modern, event-driven approach allows for rapid development of generative AI applications.

Speakers: 
Mai Nishitani, Senior Solutions Architect, AWS
Robert Louw, Senior Cloud Data Engineer, RACQ
Jad Goss, AI Engineer, RACQ

Duration: 30mins

How to re-platform and modernize Java web applications on AWS (Level 300)
Many organizations running legacy applications on-premise are constantly searching for efficient ways to update their applications to achieve cost savings, agility, and speed to market. In this session, we outline the benefits of moving to modern application architecture. Learn how to remove the tedious process of spending countless hours manually upgrading dependencies and refactoring deprecated code for Java application with Amazon Q. We demonstrate how to use Amazon Q to automate the end-to-end process of upgrading and transforming code, reducing the time it takes to upgrade applications from weeks to days or minutes. The session also dives deep into how to transform your Java applications into microservices for deployment on cloud native services that leverage containers, Kubernetes, CI/CD pipelines, serverless, service mesh, and cloud developer tools. By the end of the session, understand how these services enable you and your teams to move faster and deploy more often as you accelerate the rate of updates, features, and fixes.

Speaker: Abhishek Jawali, Senior Solutions Architect, AWS India
Duration: 30mins

Accelerating DevOps on AWS (Level 200)
A DevOps engineer typically work through different phases of software delivery lifecycle including writing and testing code, deployment and observability, to successfully operate the application. But many face challenges when implementing DevOps practices - from security and compliance, continuous integration, to effectively monitoring and scaling applications. In this session, learn the DevOps tools from AWS to manage the tasks, deploy at scale, and maintain your ability to deliver applications and services at high velocity. The session also provides practical guidance on how you can move click ops to infrastructure as code (IaC), build a release pipeline, automate monitoring, and logging for your infrastructure and applications.

Speaker: Faraz Masood, Senior Solutions Architect, Migration and Modernization, AWS
Duration: 30mins

Improve application resilience with controlled chaos engineering (Level 200)
Building highly resilient applications in the cloud requires careful design and well-thought through capacity planning to ensure redundancy, as well as having right mechanisms so that requests are routed away from occasional, temporary failures. Join this session as we share the architectural patterns for injecting failures and experiments for chaos engineering and test for high availability. We explain how AWS provides isolation boundaries, including Availability Zones and AWS Regions, which can be used to meet high availability and continuity of operations requirements. We then demonstrate how to use chaos engineering to set up failure injection testing to validate the resiliency of your service. By referencing the AWS Well-Architected Framework, understand the design principles and AWS resources that help ensure a resilient architecture. The session also features how AWS Fault Injection Service (AWS FIS) enables you to test for hidden issues, prevent regression, and maintain application availability.

Speaker: Joydipto Banerjee, Senior Technical Customer Service Manager, AWS India
Duration: 30mins

Build a modern data foundation on AWS (Level 200)
In this session, we share the comprehensive suite of services from AWS which enables you to efficiently store, process, analyze, and act from their data. We dive deep into the key areas including data transfer, storage for data lakes, data warehousing, integration, and governance. We also share the analytics, visualization capabilities, and how to deliver innovative outcomes with AI and machine learning services on AWS. Learn the best practices for designing scalable, secure, and cost-effective data architectures, strategies for future-proofing your data foundation to support emerging technologies including generative AI. By the end of the session, understand how to build a strong data foundation that provides you with clean, organized, and easily accessible data for better decision-making and business insights.

Speakers: 
William Wong, Principal Database Solutions Architect, AWS
Paul Villena, Senior Analytics Solutions Architect, AWS

Duration: 30mins

Choose the right databases for application modernization (Level 200)
The idea of one-size-fits-all monolithic database no longer fit today, as more organizations build highly distributed applications using many purpose-built databases. We observe an increasing number of customers wanting to build internet-scale applications that require diverse data models. In response to customers’ needs, AWS offers the choice of key-value, wide column, document, in-memory, graph, time-series, and ledger databases, with each database catering to specific use cases and requirements. In this session, find out the AWS purpose-built database that meet the scale, performance, and manageability requirements of modern applications.

Speaker: Gopalakrishnan Subramanian, Principal Database Solutions Architect, AWS India
Duration: 30mins

Build a robust data lifecycle management strategy on AWS (Level 200)
Join this session as we dive deep into the pillars for the data lifecycle management strategy, so you can always have access to relevant, accurate, and searchable information that is used to make data-driven decisions. We cover the solutions from AWS to support every step of the data journey, so you can move your data efficiently and securely to the cloud. This session includes customer sharing by Autodesk as they share how they built a disaster recovery cross region site for their production data on Amazon S3. Autodesk team walks through how they successfully migrated and managed 1PB of existing data with total of 6 billion objects. Find out their cost optimized and robust approach to migrate existing data between the regions. We also explain how to run validation post migration to ensure good data in the region, while adhering to business continuity.

Speakers: 
Ameen Khan, Senior Storage Specialist Solutions Architect, AWS
Liang Wenqi, Senior Software Development Engineer, Autodesk
Bhanu Prakash P, Principal Engineer, Autodesk

Duration: 30mins

Simplifying modern data pipelines with zero-ETL architecture (Level 300)
Extract, transform, and load (ETL) is the process of combining, cleaning, and normalizing data from different sources to get it ready for analytics, AI/ML workloads. But traditional ETL processes can be time-consuming and complex to develop, maintain, and scale. In this session, we share how zero-ETL eliminates the need for complex ETL data pipelines by enabling direct data movement and federated querying across databases, data lakes, and external sources. Learn how the integration of Amazon Aurora with Amazon Redshift allows near real-time analytics and ML on transactional data stored in Amazon Aurora MySQL-Compatible Edition, without building data pipelines. We then demonstrate Amazon DynamoDB zero-ETL integration with Amazon OpenSearch Service to perform tasks such as full-text search, fuzzy search, auto-complete, and vector search for machine learning (ML) capabilities to offer new experiences that boost user engagement and improve satisfaction with their applications. By end of session, understand how zero-ETL architecture on AWS empowers users to focus on extracting value from data rather than pipeline development.

Speakers: 
Surendar Munimohan, Senior Database Solutions Architect, AWS
Paul Villena, Senior Analytics Solutions Architect, AWS

Duration: 30mins

Cost effective log management at scale (Level 200)
Many organizations are looking at ways to collect, ingest, and visualize log data from various sources quickly. Join the session to discover how Amazon OpenSearch Serverless enables you to manage your search and log analytics needs securely, at scale, and cost-efficiently. We share the steps to easily build a log analytics pipeline using Amazon OpenSearch Serverless. Learn how to create a collection, using a Python Data Generator, build OpenSearch Dashboards, configure security policies, and analyze visualizations. We explain how to run large-scale search and analytics workloads without having to configure, manage, or scale OpenSearch clusters. The session also covers how to automatically provision and scale underlying resources, allowing you to deliver fast data ingestion and query responses for even the most demanding and unpredictable workloads.

Speaker: Muhammad Ali, Principal OpenSearch Specialist Solutions Architect, AWS
Duration: 30mins

Real-time analytics with streaming data and generative AI (Level 300)
Join this session as we explain why data streaming is a crucial enabler for building responsive, contextually-aware generative AI applications. We discuss why foundation models such as large language models offer immense potential, but lack the ability to dynamically incorporate real-time data at inference time, leading to hallucinations, lack of relevance, and poor personalization. This session dives into the various techniques including in-context learning and retrieval augmented generation (RAG) to help bridge this gap, by allowing models to adapt to the latest data in the context of a given prompt or query. We explore the key architectural patterns you can use when building streaming data pipelines to ingest change data capture (CDC) events, perform identity resolution for unified customer profiles, and transform unstructured content into vectorized representations, all in near real-time. Discover how to use key AWS services including Amazon MSK, Amazon Kinesis, Amazon Managed Streaming for Apache Flink, as well as purpose-built vector databases for building real-time analytics with streaming data.

Speakers:
Partha Sahoo, Senior Analytics Specialist, Technical Account Manager, AWS
Masudur Rahaman Sayem, Senior Streaming Solutions Architect, AWS

Duration: 30mins

Unlock business agility and data governance on AWS (Level 300)
As organizations manage more data across more locations, ensuring right access to data while managing data governance, compliance, security, scalability and management overhead is challenging. Access that is too restrictive can slow down business decision-making while access that is too lenient introduces risk. In addition, developing such solutions in-house can be complex and resource-intensive. In this session, we explain how to use Amazon DataZone, a data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS on premises and third-party sources. Understand how to ensure discovery and sharing of data while governing access with built-in workflow and tools integration. We also demonstrate how Amazon DataZone providers users throughout the organization to securely access the data and unlock valuable data-driven insights with ease.

Speakers:
Praveen Kumar, Principal Analytics Solutions Architect, AWS
Rick Fraser, Senior Analytics Solutions Architect, AWS

Duration: 30mins

Get started with generative AI on AWS: From ideation to production (Level 200)
Everything begins with an idea. But how do you accelerate that initial spark to final product? Successful generative AI implementation requires aligning people, processes, and technologies. We explore how to build the end-to-end strategy to develop that alignment, build right skills, establish scalable workflows, and deploy the appropriate technologies. Find out how to build the business use cases with generative AI to advance your organizational objectives including reinventing applications, creating innovative customer experiences, and improving productivity. By the end of the session, learn how to ideate, prototype, and deliver products and services quickly.

Speaker: Melanie Li, Senior Generative AI Specialist, AWS Generative AI Innovation Center
Duration: 30mins

Build generative AI applications on AWS (Level 200)
In this session, find out how to build with generative AI stack on AWS including applications, tools, and infrastructure. We explain the important considerations for building generative AI applications. We also dive deep into the generative AI resources, and ways to leverage LLMs and other FMs on AWS. Discover the common architecture patterns and how to implement them using AWS. We also cover how to enable generative AI applications with your own data, and share best practices for designing and testing generative AI solutions. The session summarizes with key resources from AWS to develop and deploy your generative AI solutions seamlessly.

Speaker: Sahil Verma, Senior GTM Specialist Solutions Architect, Generative AI, AWS India
Duration: 30mins

Select the right large language model for your application use case (Level 200)
There are a large number of large language models (LLMs) out there and choosing the right one is critical because of the high cost associated with deploying generative AI models. In this session, we share the key considerations when evaluating LLMs. Find out how to evaluate LLMs for tasks where the output is fact-based and when the output is creative by nature. With thousands of text generation models out there to choose from and endless prompt engineering possibilities to use them with, learn how you can quickly and reliably identify the best price-performance solution for your use case. We then explain how you can build a complete picture of model and prompt-template performance on AWS. The session also covers the use automated tools that work alongside human labellers to create scalable but accurate evaluations, enabling you to build high-quality solutions faster and deploy with confidence.

Speaker: Ben Friebe, Senior Solutions Architect, AWS
Duration: 30mins

Develop and deploy production-ready generative AI applications (Level 200)
Harnessing generative AI requires overcoming significant technical and strategic challenges to deploy production-ready solutions. In this session learn the tools, customization methods, and models so you can scale, move fast, manage risks while building and deploying your generative AI applications. We first dive deep into how to use Amazon Bedrock to access the key foundation models. We then explain how large language models (LLMs) are deployed on Amazon SageMaker. Discover how you can ensure flexibility of pluggable models, prompt versioning, customizability of RAG engines, and seamlessly integrate with data services on AWS. Understand the different techniques to generate safe and reliable responses, as well as best practices for monitoring and evaluating model outputs. We explore the key generative AI deployment patterns on AWS, and how they enable you to effectively deploy of multiple instances with diverse configurations, compare outputs, evaluate performance metrics, while ensuring enterprise-grade security measures.

Speaker: Santhosh Urukonda, Senior Prototyping Engineer, AWS India
Duration: 30mins

Choosing the right compute for ML training and inference (Level 200)
Organizations across various industries are increasingly adopting machine learning for a wide range of use cases, including natural language processing (NLP), computer vision, voice assistants, fraud detection, and recommendation engines. Large language models (LLMs) that have hundreds of billions of parameters are unlocking new generative AI use cases, for example, image and text generation. But the growth of ML applications has resulted in higher usage, management, cost of compute, storage, and networking resources. This session explains why identifying and choosing the right compute infrastructure is important to reduce your power consumption, costs, as well as managing complexities from training and deployment of ML models to production. We explain how AWS offers the ideal combination of high performance, cost-effective, and energy-efficient purpose-built ML tools and accelerators, optimized for ML applications. Learn how to choose the right infrastructure for your AI/ML workload requirements. The session also explores the highly performant, scalable, and cost-effective ML infrastructure from AWS, ranging from the latest GPUs to purpose-built accelerators including AWS Trainium, AWS Inferentia and Amazon EC2 P5 which are designed for training and running models.

Speaker: Smiti Guru, Senior Solutions Architect, AWS India
Duration: 30mins

Managing and optimizing costs for AI/ML workloads (Level 200)
Many organizations adopt generative AI to achieve high application performance, uncover new opportunities, and build sustained competitive advantage. When building with generative AI, the choices made upfront can significantly impact the overall costs. In this session, we address common questions and challenges around cost management when building AI/ML workloads. Understand the key strategies to prevent unintentional cloud spend, cost-effective infrastructure for training ML models, and alternative hosting options. We explain how you can leverage the latest features in Amazon Bedrock to reduce expenses while maximizing the value of your workloads.

Speakers:
Pauline Kelly, Solutions Architect, AWS
Emma Arrigo, Solutions Architect, AWS

Duration: 30mins

Using generative AI responsibly and securely on AWS (Level 200)
Generative AI presents significant opportunities for organizations across multiple industries. While it can be a force for good, it is important to build generative AI responsibly, securely, and achieve the right balance between innovation and safety. In this session we discuss the key considerations on how to use generative AI responsibly, including fairness, explainability, robustness, privacy, security, governance, and transparency. We dive deep into the operational security features of key AI/ML solutions such as Amazon Bedrock, Amazon Q, and Amazon SageMaker JumpStart. Find out how these solutions provide you with built-in security, privacy, encryption, access control, and compliance, making it easier for you and your organization to build generative AI responsibly into your workflows while maintaining security, as well as adhering to the risk and compliance regulations.

Speaker: Simon Cozen, Senior Enterprise Solutions Architect, AWS
Duration: 30mins

Select the right AI/ML and generative AI tools for your use case (Level 200)
AI/ML techniques are important fundamentals for organizations looking to reinvent customer experiences and deliver objectives. However, applying the right techniques to the use cases is not easy. This session provides guidance on how to apply practical and proven AI/ML techniques on key use cases for real business impact. We outline existing traditional AI and emerging generative AI suite of services to help you understand when and what services are best suited for the key application requirements or use cases across business functions and industries. Learn best practices on how to future-proof your stack and ensure flexibility and control within your organization. This session concludes with how to apply technologies to your use cases, enabling you to conceptualize new opportunities, achieve competitive advantage, and deliver organizational outcomes.

Speaker: Melwin Pais, Senior Solutions Architect, AWS
Duration: 30mins

Transforming insights to impact in your call center - Voice to action framework with Amazon Connect (Level 200)
The emergence of virtual telephony voice agents offers step-wise enhancements in delivering real-time insights from data, and impactful customer experiences. We explain how virtual agents can autonomously manage low-value interactions, enhance IVR-to-human agent transitions, and provide a more human-like IVR experience featuring powerful self-service capabilities. Learn how to build the solution using Amazon Connect, omnichannel cloud contact center service with real-time audio parsing via Amazon Kinesis Video Streams, enabling you to securely stream video from connected devices to AWS for analytics, machine learning playback, and other processing. The session also covers the use of algorithms for effective silence and speech detection, extraction of high-quality transcripts with Amazon SageMaker and LLM inference through Claude3 on Amazon Bedrock. We also demonstrate how to build a fast and secure LLM-powered virtual voice agent that operates in real-time and enabling secure external API access. Find out how to develop rich secure virtual agents which you can easily deploy, maintain and observe in your call centre. We also discuss the recent advances in LLM technologies and ways to reap the benefits in your voice channels.

Speakers: 
Josh Passenger, Principal Solutions Architect, AWS
Charles Prosper, Principal Applied Scientist, AWS

Duration: 30mins

Build a customer profile validation assistant (Level 200)
Many users run search for profile via text, but at times they may need to augment the search with images. This requires the search for similar images from the repository with some textual criteria which may not return accurate results. This session covers how to build a search functionality in an application with multi-model search. Learn how to prepare the data with low-code, no-code techniques using Amazon SageMaker Canvas and existing repository to extend your existing search functionalities. We showcase how Amazon Bedrock and Amazon SageMaker leverage large learning models (LLMs) to quickly evaluate the model, producing accurate responses for your business rules. The session also explores the use of vector databases to store and search efficiently with image and textual information.

Speaker: Priya Jathar, Solutions Architect, AWS India
Duration: 30mins

Intelligent document processing at scale with AI/ML and generative AI (Level 200)
To efficiently process unstructured data, classify documents, extract critical information, validate insights, and generate insightful summaries is critical for actionable insights. Yet, this workflow in many organizations is still manual, time-consuming, error-prone, expensive, and hard to scale. Find out how to build an intelligent document processing (IDP) solution to automate information extraction from documents. We demonstrate the steps to integrate generative AI capabilities with Amazon Textract to augment your IDP workflows with additional capabilities such document summarization and Q&A chatbot. We also showcase the multi-model capabilities of Anthropic Claude 3 on Amazon Bedrock, enabling users to easily extract information from complex documents including those that do not have a consistent format. Discover how this automated workflow built on AWS enables you to free up your resources to focus higher value tasks, and reduce overall costs.

Speaker: Kamal Manchanda, Senior Solutions Architect, AWS India
Duration: 30mins

Identify product defects with IoT, computer vision, and generative AI (Level 200)
Join this session to learn how to create a data hub that makes it easier to extract insights from unstructured manufacturing data, including documents, maintenance logs, and data sheets with AWS IoT TwinMaker and AWS IoT SiteWise. We also demonstrate how to use generative AI to make this data more accessible to end users, enabling them to ask complex questions in natural language, such as identifying standard operating procedures (SOPs) to fix production issues or suggesting potential root causes based on alarms. Through hands-on examples, we explain how build a generative AI-powered assistant using AWS IoT TwinMaker and Amazon Bedrock, so operators and other users can quickly diagnose and resolve production problems. Understand how these technologies on AWS help unlock the value of your manufacturing data, leading to increased efficiency, reduced costs, and improved overall productivity.

Speakers: 
Vikram Shitole, Senior Prototyping Architect, AWS India
Sushant Moon, Data Scientist II, AWS India

Duration: 30mins

Brick maestro with AI/ML and HPC on AWS (Level 200)
In this session, we demonstrate how to develop a 'brick maestro' solution using AI/ML, IoT, and high-performance computing (HPC) solutions on AWS. Discover how this solution utilizes computer vision models with Amazon SageMaker to identify bricks. We then explain how to leverage ML models to rank the best builds that resemble real objects, and influence these rankings by indicating your preferred objects. Learn how to efficiently run this workload in the cloud with HPC solutions on AWS, which provide virtually unlimited compute capacity, a high-performance file system, and high-throughput networking.

Speakers: 
Sakthi Srinivasan, Engagement Manager, AWS India
Jyoti Sharma, Prototyping Engineer, AWS India

Duration: 30mins

Real-time insights from data using serverless, computer vision, and generative AI (Level 200)
With the increasing number of devices becoming interconnected every day, managing and extracting actionable insights from telemetry data is important as it bring about host of benefits including improving operational efficiencies, data accuracy, decision making and cost savings. However, telemetry data from sensors can be challenging to interpret. Join this session as we demonstrate how to achieve data explainability with generative AI and computer vision on golf which is a data rich sport. We demonstrate how to build a golf coaching assistant to extract insights from launch monitor. Learn how it can quickly analyze various data, explain and provide guidance on ball speed, smash factor, swing path, carry distance, launch angle and more to improve your golf swing!

Speakers: 
Derrick Choo, Senior Solutions Architect, AWS
Robbie Cooray, Senior Solutions Architect, AWS

Duration: 30mins

Generate 360 insights and visualize journeys from your structured and unstructured data sources (Level 200)
Join this session as we explain how generative AI is enabling new levels of explainability, and investigative capabilities to empower even the non-technical stakeholders the ability to derive value from data. Find out how to build an intuitive and interactive dashboard to seamlessly integrate structured and unstructured data from diverse sources, and create a comprehensive view of the customer journey. We explain how graph databases, with the help of large language and embedding models can help with decomposing unstructured data to discover, exploit and store previously undiscovered relationships. The session features a demo on the use of graph databases for customer 360 modelling and exploration via agents. We also showcase how to use Amazon Bedrock and open-source frameworks such as LlamaIndex to create GraphRAG applications with knowledge graphs stored in Amazon Neptune.

Speakers: 
Sam Gordon, Senior Cloud Architect, AWS Professional Services
Ed Fraga, AI/ML & Data Specialist, AWS Professional Services

Duration: 30mins

Building a personalized generative AI sales assistant (Level 200)
Do you want to learn how to build interactive elements of an in-store experience into a digital platform with generative AI? In this session, we first outline the challenges of existing static digital experience and how to manage them with Knowledge Bases for Amazon Bedrock. Uncover how to easily extract actionable insights from your customer data through real-time analytics streaming pipeline with Amazon Kinesis and Amazon Redshift. We showcase the use of Amazon Redshift streaming ingestion to simplify data pipelines by allowing you to create materialized views directly on top of data streams. Learn how to use SQL to connect to and directly ingest data from data streams, such as Amazon Kinesis Data Streams or Amazon Managed Streaming for Apache Kafka (Amazon MSK) data streams, and pull data directly to Amazon Redshift. The session concludes with step-by-step guidance on how to build your reporting dashboard with Amazon QuickSight Q for quicker and easier data insights.

Speakers: 
Derrick Choo, Senior Solutions Architect, AWS
Antonio Baxter, Solutions Architect, AWS

Duration: 30mins

Build dynamic questioning in customer interactions (Level 200)
Customer interactions today are in multiple formats such as audio, text, video, and more. However, many organizations are still gathering and consolidating vital customer information in traditional ways that can be tedious and error-prone. This session showcases the use of generative AI tools on AWS to quickly build a real-time questioning solution to facilitate customer interactions. Find out how this solution enables users in your organization to ask the right questions in the right sequence from on-going conversations, ensuring comprehensive coverage in a single call, regardless of prior knowledge or experience. Discover how to ensure a seamless data collection from your customers’ interactions, improving engagement and freeing up resources for more strategic initiatives.

Speakers: 
Xin Chen, Senior Cloud Architect, AWS Professional Services
Bin Liu, Senior Cloud Architect, AWS Professional Services

Duration: 30mins

Unlock new value from diverse data types and leveraging multimodal capabilities (Level 300)
Join this session to learn how to amplify chatbot applications, unlocking diverse data types and multi-modal capabilities with Amazon Bedrock multi-modal embedding. We explain the approaches to tackle complex scenarios such as handling tabular data embedded within word documents and extracting meaningful insights from diverse data sources. Understand the key strategies to seamlessly integrate multi-modal inputs and outputs and extend beyond textual interactions to include images, enabling you to enhance user experience. We walk through the semantic, hybrid, and filter/query-based search strategies you can use for context retrieval. Understand the potential pitfalls in handling structured and unstructured data, including web-crawled content and documents and ways to overcome them. We explain how to navigate the common scenarios and harness the full spectrum of available data to enhance your chatbot applications.

Speakers: 
Tristan Nguyen, Senior Solutions Architect, AWS
Isaac Ibrahim, Associate Solutions Architect, AWS

Duration: 30mins

Improve accuracy of OCR with generative AI (Level 200)
Optical character recognition (OCR) has been a valuable technology for digitizing text from images, documents, and other sources. However, traditional OCR systems have limitations in terms of accuracy, especially when dealing with low-quality images, handwritten text, or complex layouts. The advent of deep learning and large language models has opened up new possibilities for improving OCR capabilities. In this session, we demonstrate how Anthropic Claude-3 family of models with Amazon Bedrock enhances and potentially replace traditional OCR systems. Find out how Claude-3 models are trained on vast amounts of text data, understand and generate human-like text with accuracy and coherence.

Speakers: 
Derrick Choo, Senior Solutions Architect, AWS
Sun Baichuan, Senior AI/ML Specialist Solutions Architect, AWS

Duration: 30mins

Empower your business users to extract insights from company documents with no-code, low-code solutions and generative AI (Level 200)
Machine learning can enable organizations of various industries and sizes to solve business challenges and achieve better outcomes. However, many struggles to implement ML effectively throughout the organization beyond their technical users. In this session, we showcase how you can use Amazon SageMaker Canvas to complete the ML lifecycle — from preparing data and creating models to generating predictions, without writing a single line of code. Find out how technical and non-technical users in your organization can utilize ready-to-use models or create your own to gain insights from your data and ML models with Amazon SageMaker Canvas. We then demonstrate how to easily access open-source and Amazon LLMs on Amazon SageMaker Canvas through a single interface. The session concludes with guidance on how you can build, deploy, and use a variety of ML models including tabular, computer vision, and natural language processing without requiring deep machine learning knowledge.

Speaker: Tom Liu, Senior Technical Account Manager, AWS
Duration: 30mins

Delivering business insights and analytics with SAP on AWS (Level 200)
Cloud is transformational for our customers when they are able to derive new business insights from SAP and non-SAP data. In this session, we explain how SAP on AWS customers leverage analytics, AI/ML, and generative AI solutions from AWS for near real-time insights to optimize business performance. Understand how these insights enable organizations to improve operational efficiency, address business risks and generate new revenue streams. We demonstrate how to easily transfer data from SAP application to a serverless data lake with Amazon AppFlow, a fully-managed integration service which securely exchange data between software as a service (SaaS) applications, and AWS services. Learn how to store, index, and search across multiple data sources and sinks by cataloguing all data in AWS, execute queries using natural language processing and visualize it on Amazon QuickSight using generative AI solutions on AWS.

Speakers: 
Peter Perbellini, Head APJ Solutions Architecture - Enterprise Applications, Migrations, and Modernization, AWS
Diego Lombardini, Senior SAP Partner Solutions Architect, AWS
Allison Quinn, Senior Analytics Specialist Solutions Architect, AWS

Duration: 30mins

Generative AI tools: Mapping AWS solutions to your needs (Level 200)
At AWS, we continuously innovate and introduce new services and features to support the evolving needs of our customers. Join this demo-packed session which focuses on Amazon Bedrock, Amazon Q, and Amazon SageMaker. We provide the overview of each service, highlighting their unique capabilities and use cases. Through demos, understand how to select foundation models in Amazon Bedrock and Amazon SageMaker Jumpstart. We also showcase Amazon Q's ability to provide instant, relevant information, explaining how it can streamline tasks, accelerate decision-making, and foster innovation in your workplace. The session includes practical aspects of model evaluation, and cover the process of shortlisting candidate models for proof-of-concept work. We also key considerations for selecting the right tools based on your specific needs, enabling you to make informed decisions for your AI/ML initiatives.
 
Speaker: Paul Colmer, Senior AWS Technical Instructor, AWS
Duration: 30mins

Practical guide to building serverless APIs on AWS (Level 300)
Building scalable and reliable web applications and APIs is crucial for improving performance and better digital experiences. But with many technology choices available, and it is important to make the right decisions on what to use, and when to use them to meet your specific requirements. In this demo packed session, we showcase how to build web and API backends with various technologies, including serverless to containers technologies, as well as modern DevOps with AWS Cloud Development Kit (CDK) and AWS Copilot. We explain how to accelerate your software development with generative AI.
 
Speaker: Donnie Prakoso, Principal Developer Advocate, AWS
Duration: 30mins

A day as a developer with generative AI tools on AWS (Level 300)
This session explores essential AWS tools and services for builders and developers to build your applications. We highlight generative AI-powered capabilities for low-code abstractions, cloud development, and operations. Through technical demos, learn how to integrate these tools to enhance your productivity. We showcase the use of Amazon Q Developer, a generative AI-powered conversational assistant to accelerate software development process. Find out how Amazon Q Developer can streamline various aspects of coding, from ideation to implementation. We then showcase how to integrate generative AI tools with other cloud native services for application modernization and maintenance.

Speaker: Janos Schwellach, Principal Solutions Architect, Developer Specialist, AWS
Duration: 30mins

Generative AI: The secrets of agents (Level 300)
Organizations need access to a broad range of foundation models to build and scale generative AI applications, and harnessing this requires more than just a model. Join this session as we dive deep into agents. We explain the benefits of using agents, key components of the agent architecture, and demonstrate how to fully utilize the capabilities of agents to automate tasks and workflows and the critical importance of democratizing access to AI.

Speaker: Mike Chambers, Senior Developer Advocate, AWS
Duration: 30mins

Build chatbots with generative AI and third-party connectors for improved productivity (Level 300)
Join this session as we delve into how organizations can leverage domain-specific knowledge and internal data to boost employee productivity and enhance customer experiences with generative AI assistants. We outline the tools to build your generative AI assistants in minutes, and how to use them to seamlessly integrate your proprietary knowledge bases, product catalogs, employee manuals, and customer data. Learn to build the generative AI assistant with Amazon Q and data hosted on data lake, data warehouse, cloud storage including Amazon S3 and other data sources such as RDBMS systems, Salesforce, Confluence, SharePoint, Quip, Jira, with enhanced accuracy, security, and privacy.

Speaker: Aman Sharma, Senior Solutions Architect, AWS
Duration: 30mins

Customize your generative AI applications to deliver relevant, accurate, and customized responses (Level 200)
To equip the foundation models (FMs) with up-to-date proprietary information, organizations use Retrieval Augmented Generation (RAG), to fetch data from company data sources and enrich the prompt with the data for more relevant and accurate responses. However, implementing RAG requires specific skillset and time to configure connections to data sources, manage data ingestion workflows, and write custom code to manage the interactions between the foundation model (FM) and the data sources. In this session, we share how to simplify the process with Knowledge Bases for Amazon Bedrock. Learn how to give FMs and agents contextual information from your company’s private data sources for RAG to deliver more relevant, accurate, and customized responses. We also demonstrate how to automate the end-to-end RAG workflow, including ingestion, retrieval, prompt augmentation, and citations, eliminating the need to write custom code to integrate data sources and manage queries. We then explore advanced RAG techniques involving multiple data sources including Amazon OpenSearch Service, Amazon Aurora Serverless and container-based system.

Speakers: 
Arun Balaji, Principal Prototyping Engineer, AWS India
P, Sakthi Srinivasan, PACE Engagement Manager, AWS India

Duration: 30mins

Accelerate end-to end DevOps with generative AI (Level 300)
Software development and IT operations face significant challenges due to the complexities of modern systems and increased demand for faster release cycles. This session is packed with demos on how you can mitigate these challenges with generative AI to accelerate end-to-end DevOps processes. We explain how builders and developers can save time and speed up application development with key tools on AWS. We share how to use Code Catalyst and Amazon Q to bring your idea to runnable and mergeable code. Understand how to debug workflows easily and set up development project using blueprints within minutes. We outline the real-world use cases demonstrating how large language models (LLMs) and code generation can reduce manual effort across the DevOps lifecycle. By the end of the session, learn how to use generative AI to streamline tasks such as deployment pipeline development, testing, infrastructure provisioning, and incident remediation. The session also features best practices for implementing responsible AI in DevOps practice.

Speaker: Tuan Hyunh, Senior Cloud Architect, AWS Professional Services
Duration: 30mins

Building a multimodal chatbot (Level 200)
Integrating generative AI cannot work in isolation but a series of processes which require some orchestration and integration. For example, in the software development process, while you can leverage generative AI for code generation, there is also the need to integrate with project management software for code reviews, optimization, and collaborative workflows. Join this session as we explain how to seamlessly integrate generative AI with existing systems, platforms, and processes to unlock its full potential cross various industries and use cases. We illustrate by explaining the Claude’s function calling capabilities, how you can implement, and share best practices. We showcase the steps to building a generative AI cost optimization chatbot using function calling techniques. Understand how to integrate generative AI with various tools and services, such as web scraping utilities, data processing libraries, cloud services, databases and more with function calling.
 
Speaker: Sun Baichuan, Senior AI/ML Specialist Solutions Architect, AWS
Duration: 30mins

Advanced architectures in Retrieval Augmented Generation (RAG) (Level 200)
Join this session to learn about retrieval augmented generation (RAG) and various popular architectures. We discuss the vector databases available on AWS and how they are important for implementing RAG architectures efficiently. The session also features a demo to showcase the different RAG architectures, how to generate final answer to the same question, giving you insights to deliver outcomes.
 
Speakers: 
Sushant Moon, Data Scientist II, AWS India
Ravi Shukla, Data Scientist II, AWS India

Duration: 30mins

Context-sensitive information retrieval (Level 200)
Organizations today have increased expectations for modernized workflows and try to use generative AI to process large data volumes for their desired outcomes. In this session, learn how to build a generative AI application for context-sensitive information retrieval to augment decision-making and enable accurate, efficient, and ethical data-driven operations. We demonstrate how to quickly build an application to extract knowledge from documents and provide a question-answering and discovery interface to your users. We walk through the steps to streamline document ingestion and extraction as well as create embedding models stored in a vector store. Once ingestion is done, we share how this chatbot interface allows you to ask questions in natural language, get contextual answer and query the vector store semantically.

Speakers: 
Kuldeep Singh, Senior Solutions Architect, AWS India
Anurag Vikram Singh, Solutions Architect, AWS India

Duration: 30mins

Troubleshooting with augmented observability and generative AI (Level 200)
Join this session to learn how to build an augmented reality (AR) observability dashboard that enables you to identify and resolve application and infrastructure issues through a gamified experience. Utilizing an AR headset, Amazon Transcribe, generative AI, and observability solutions, we will demonstrate how to intentionally induce failures within an application. We will then walk you through creating real-time analysis within the architecture and using generative AI-powered voice interaction to request root causes and solutions. This session also showcases how to pinpoint the root cause, provide enhanced details in the AR-rendered architecture, and recommend ways to resolve the problem.

Speaker: Vikram Shitole, Prototyping Architect, AWS India
Duration: 30mins

Personalize content with generative AI and Amazon Personalize (Level 200)
Organizations are focused on ways to deliver highly personalized user experiences at scale to achieve higher customer engagement, conversion, and revenue while creating meaningful differentiation. In this session, we showcase how you can use Amazon Personalize with generative AI to boost your user engagement and provide highly-optimized customer interactions. Discover how to use Amazon Bedrock LLM foundation model with algorithms from Amazon Personalize to automatically generate thematic connections between recommended content for any interface. We also demonstrate how to build a custom solution with personalized content descriptions that can be integrated into your existing websites, applications, and email marketing systems with simple APIs.

Speakers: 
Tim Wu, Senior AI Specialist Solutions Architect, AWS
Tristan Nguyen, Senior Solutions Architect, AWS

Duration: 30mins

Smart traffic management (Level 200)
Have you ever been stuck at a traffic light even though there are no vehicles coming from the other direction? Do you wish to avoid traffic congestion and get to the destination quickly? In this session, we demonstrate how to build a smart traffic management solution, powered by machine learning at the edge with Amazon SageMaker and AWS IoT. Discover how the solution enables you to automatically observe traffic patterns, vehicle loads on the road and control the lights so that cars move across quickly and reduce traffic congestion. Uncover how it can automatically identify emergency vehicles, including ambulances and police cars, as well as control the traffic lights to enable these vehicles to move to the destinations in the shortest possible time. We also showcase how this solution can manage the traffic flow by automatically tracking accidents, vehicle failures, or other incidents that result in road blockage. The session concludes with guidance on how to develop an analytics dashboard for real-time traffic insights.

Speakers: 
Chandra Munibudha, Principal Solutions Architect, AWS India
Satheesh Kumar, Principal Solutions Architect, AWS India

Duration: 30mins