The Pitfalls of Building Your Own Generative AI Solution
The allure of building your own generative AI applications may be irresistible — but it’s not as straightforward as it seems.
The allure of building your own generative AI applications may be irresistible — but it’s not as straightforward as it seems.
Vendors offer a bewildering array of GenAI solutions, all of which seem very similar. Some agencies have paused on evaluations to foster consensus, but the question remains: How can government agencies determine whether it is possible to deploy an effective GenAI solution today?
The emergence of generative AI raises important personnel questions: What skill sets do government agencies need to hire or develop? And how can answer engines remove some technical burdens?
Artificial intelligence technology, including generative AI and large language models, provide many important capabilities, but there are misconceptions about how effective AI actually can be.
New employees face many onboarding challenges, including learning how to ask for and access agency information. Answer engine technology, though, is revolutionizing the process.
The answer engine is a groundbreaking solution that harmonizes the power of large language models — such as ChatGPT — with the irreplaceable insights that knowledge management professionals can offer.
Constituents want to find information on your site quickly and easily. Generative AI offers a revolutionary approach to interpreting user questions and providing answers people need.
While generative AI (GenAI) presents a unique opportunity to streamline operations and improve citizen engagement, it’s not a mature technology. How can you overcome internal skepticism and help your leaders consider a practical GenAI project?
While generative AI models like ChatGPT have advanced significantly in simulating human-like conversation, they are not production-ready solutions for comprehensive customer support in government agencies.
Citizens expect Instant, correct, and trusted answers from government agencies when they look for information on the agencies’ websites. Natural language interfaces fulfill this need.