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Building AI-Powered Chatbots
Gain practical advice for developing your own AI-powered chatbot by learning more about how created its own AI tool called Atom Ai. In this episode, Marc DeSantis and Kevin Dana talk about the origins of the tool, its development process, the challenges they faced and the implementation of various technologies such as vector databases, storage and semantic search.
Integration and Impact of AI and Automation
Learn about how WWT is using AI to complement human capabilities and how we are optimizing processes before automating them. It's an important topic you'll need to gain clarity on when developing or deploying AI assistants.
Identifying Value in AI Solutions and Projects
Learn about how WWT identifies and values AI solutions, considers build vs buy options and develops AI use cases we've found within our own business. The conversation includes topics such as identifying business problems, assessing solutions, the impact of AI on society, and the importance of human oversight in AI applications.
Practical Use of AI in Data Analysis and Business Intelligence
Learn how WWT thinks about generative AI and its application in various contexts such as data analysis, reporting and software development. Kevin and Marc also talk about limitations of AI in understanding complex data and the potential future of AI in business intelligence and data APIs.
How to Build an AI Center of Excellence
Learn how WWT began integrating and optimizing AI within enterprise systems, focusing on search capabilities, building an AI Center of Excellence and the challenges of integrating AI into existing systems.
AI AI, Captain!
Explores the challenges and opportunities of implementing generative AI at scale within the enterprise and learn from WWT's own AI journey.
Integrating Gen AI Into an Enterprise Setting
Learn how to start implementing generative AI in the enterprise, assess AI tools and maturity, and think about AI governance and business alignment.
How to Get Started with Gen AI in the Enterprise
Learn how to separate fact from fiction when it comes to AI in the enterprise, start thinking strategically about AI projects and build technical foundations for future progress.