AWS on the future of data lakes, metadata and AI innovation
The Director of Product Management at AWS sat down with Fivetran to unpack how Iceberg and metadata are reshaping the future of data lakes, data warehouses and AI.
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The History of Chatbots: A Timeline of Conversational AI
From ancient Greek myths of talking statues to the modern-day Alexa and Siri, the concept of machines capable of understanding and responding to human language has captivated us for centuries. In recent years, this concept has evolved into AI chatbots, highly sophisticated tools that can read our queries and perform tasks ranging from customer service to automated alerts.
AI Adoption in SMBs: Key Trends, Benefits, and Challenges from 100+ Companies
AI Adoption in SMBs: Key Trends, Benefits, and Challenges from 100+ Companies With larger competitors already using AI to streamline operations and gain a competitive edge, SMBs can’t afford to fall behind. But for many, adopting AI is easier said than done. Limited budgets, lack of in-house expertise, and the fear of wasting time and resources on the wrong tools often leave business owners stuck in decision paralysis.
RAG Application with Kong AI Gateway, AWS Bedrock, Redis and LangChain
For the last couple of years, Retrieval-Augmented Generation (RAG) architectures have become a rising trend for AI-based applications. Generally speaking, RAG offers a solution to some of the limitations in traditional generative AI models, such as accuracy and hallucinations, allowing companies to create more contextually relevant AI applications.
Introducing Testsigma Copilot - GenAI-Powered Assistant for QA Teams
Testsigma Copilot is a GenAI assistant for QA teams that lets you generate test cases and scenarios with just designs, screenshots, or user stories. ️ No manual test development effort️ No missed edge cases️ No delayed or lengthy test cycles.
Episode 11: The future of data lakes: Open table formats, metadata and AI | AWS
Paul Meighan, Director of Product Management at AWS, shares how enterprises are increasingly looking for ways to integrate more data sources in their environment — especially with data lakes. From turning S3 buckets into databases to establishing better metadata layers, Meighan explores the rapid evolution of data lakes alongside data warehouses. He also explains the pivotal role AI, ML and GenAI workloads and applications will play in large metadata environments, driving innovative analytics and business insights.
Why Real-Time Data is Crucial to Developing Generative AI Models
Learn how GEP, an AI-powered supply chain and procurement company, harnesses real-time data streaming through Confluent Cloud to fuel its generative AI solutions. With seamless integration into Azure OpenAI services and GPT models, GEP’s generative AI chatbot delivers document summaries and risk management insights to its customers.
How Confluent Fuels Gen AI Chat Models with Real-Time Data
Discover how GEP, an AI-powered procurement company, utilized Confluent's data streaming platform to transform its generative AI capabilities. Integrating real-time data into their AI models enabled GEP to provide a contextual chat-based service. This chatbot allowed GEP customers to build their own tools simply by communicating in English with a chatbot.
The Impact of AI and Machine Learning In Quality Assurance
Some of the popular AI tools people and corporations are using now include ChatGPT, Google Gemini, and Microsoft Copilot. This has resulted in higher usage and adoption of this technology and this has caused some worry among people, particularly in terms of employment. However, for software testers, these changes should be seen as a chance to improve rather than a threat.
Generative AI: The New Age of Document Processing
What do you think of when you think of generative AI? Generating photos, animations, and videos? Coding and solving math problems? Writing content and brainstorming with a chatbot? These have all driven plenty of excitement around AI, but there’s so much more to it than that! From an enterprise perspective, Generative AI’s impact on intelligent document processing technology is remarkable.