Shreyas Subramanian

Organizations struggle to customize AI models for complex tasks due to the extensive human annotation required for traditional fine-tuning approaches. Learn how Amazon Bedrock's new Reinforcement Fine Tuning (RFT) capabilities enable developers to train models using custom evaluators instead of large labeled datasets.

Bring existing agents to AWS with Amazon Bedrock AgentCore. Whether you've built custom agents or use frameworks like LangChain, LangGraph, CrewAI, or LlamaIndex, this session shows how to run them on secure, scalable AWS infrastructure without rewriting your logic.

Unleash the power of customized AI by fine-tuning generative AI models in Amazon Bedrock to achieve higher quality results. Discover how to adapt foundation models like Meta's Llama and Anthropic's Claude models to your specific use cases and domains, boosting accuracy and efficiency.

Financial institutions are using large language models (LLMs) to improve employee productivity and transform the customer experience. But LLMs are not always the right choice for every application.

In recent years, machine learning (ML) has emerged as a promising method to augment traditional engineering simulations and help designers explore a large set of design points at a lower cost when compared to traditional approaches.

In this workshop, learn how to orchestrate machine learning (ML) workflows across each step of the ML process, including exploring and preparing data, experimenting with different algorithms and parameters, training and tuning models, and deploying models to production using Amazon SageMaker Pipelines and SageMaker projects. SageMaker Pipelines makes it easy to manage dozens of ML models and...

Figuring out if a part has been manufactured correctly, or if machine part is damaged, is vitally important. Making this determination usually requires people to inspect objects, which can be slow and error-prone.

In this workshop, learn how to use Amazon SageMaker Neo deep learning compiler to compile your trained TensorFlow models and deploy them on the cloud or on edge devices using AWS IoT Greengrass. Learn how Neo deep learning compiler optimizes the trained models by improving efficiency and reducing the memory footprint of the compiled model and how Neo runtime abstracts the underlying hardware...