Category: Artificial Intelligence

QuesTek, a leader in Integrated Computational Materials Engineering (ICME), and AllCloud, an AWS Partner, collaborated to integrate generative AI into QuesTek’s ICMD (Integrated Computational Materials Design) platform. In this post, we will provide a high-level overview of the generative AI use cases that transformed the ICMD platform.

By Saibal Samaddar — Infosys Consulting By Tanushree Halder — Infosys Consulting By Supriya Pandey — Infosys Consulting By Sanchit Jain — Infosys Consulting By Dhiraj Thakur — AWS Infosys Critical infrastructure like consistent and predictable electricity supply serves as a foundation for a country’s development and advancement. India’s development pace relies heavily on a […]

By Hiranya Bharadwaj — DXC Technology ByLucy Bailey — DXC Technology By Akash Subramani — DXC Technology By Dhiraj Thakur — AWS DXC Technology Global Pharma companies need to prepare extensive documentation to seek regulatory approvals to market their drugs in the country. For each new drug application, thousands of documents must be drafted and […]

By Kelvin Kok, Chief Architect & CEO – Axrail By Cara Lee, Account Manager – Axrail By Brendan Child, Sr. AI/ML Partner Development Specialist – AWS By Vasileios Vonikakis, Sr. AI/ML Partner Solution Architect – AWS Axrail Introduction Generative AI enhanced solutions, such as virtual assistants and enterprise search, have already demonstrated their potential in […]

Learn how AWS and ThinkCol collaborate to build responsible AI solutions using guardrails and safeguards. With ThinkCol’s Guardrail Solution, businesses can now harness generative AI’s power while mitigating risks of toxicity, hallucination, and misuse. Additionally, organizations have the ability to maintain brand integrity and customer trust through a framework that includes pre-checking queries, generating accurate answers, and post-checking for relevance.

This post discusses an approach to creating a privacy-preserving chatbot using Amazon Bedrock and Skyflow Data Privacy Vault. We explore an architecture pattern for protecting sensitive information, such as personally identifiable information (PII) and intellectual property. The integration of Skyflow into a multi-tenant RAG model allows for an effective data privacy, compliance, and security framework to protect sensitive data throughout a generative AI application’s lifecycle.

Learn more about the Next-Gen Digital Analytics, a solution built on Amazon Web Services, using Snowplow and Snowflake. This joint solution empowers organizations to unlock the untapped value of customer behavioral data. It improves data quality, governance, and real-time activation within their AWS environment. By implementing this solution, customers can supercharge the use of Artificial Intelligence (AI) and generative AI adoption to help address key business objectives, such as user acquisition, retention, and customer lifetime value.

The MuleSoft Bedrock Connector for Amazon Generative AI is a powerful integration solution that bridges the gap between MuleSoft’s Anypoint Platform and Amazon’s cutting-edge generative AI services. This open-source connector enables organizations to seamlessly incorporate Amazon’s Bedrock capabilities into their existing systems and applications, unlocking the ability to build innovative AI-powered workflows, automate complex processes, and enhance customer experiences. By leveraging this connector, businesses can drive accelerated innovation, deliver exceptional customer service, boost operational efficiency, and enable data-driven decision-making through the combination of MuleSoft’s integration capabilities and Amazon’s generative AI capabilities.

Evaluating Large Language Models (LLMs) for the responsible deployment of Generative AI applications is a critical aspect of this journey. Learn how Caylent’s solution enables customers to build a human-in-the-loop LLM evaluation and benchmarking workflow.

The AWS DeepRacer platform provides a fun and engaging way to get into AI and machine learning. Exposure to the AWS DeepRacer platform provides racers the opportunity to learn about reward function strategy, hyperparameter tuning, and Python programming. Eviden recognized the potential to expand the learning outcomes beyond these core concepts.