What special considerations are needed when implementing Generative AI tools at the enterprise level?
Chief Strategy Officer, Self-employed
Would like to know the views of other leaders in the community about the issues faced and mitigating actions undertaken in their respective field of work ? Associate Director of Data Science & Analytics in Healthcare and Biotech, 10,001+ employees
Cost. Training these models is extremely expensive. A large internal LLM can cost tens of millions of dollars in compute. And that is assuming your organization has the proper infrastructure to support it, and the right expertise to optimize it. Content you might like
We already have this15%
We are working on it65%
We are planning to13%
We don’t have any plans for this7%
71 PARTICIPANTS
Community User in Software, 11 - 50 employees
organized a virtual escape room via https://www.puzzlebreak.us/ - even though his team lost it was a fun subtitue for just a "virtual happy hour"
Data management23%
Algorithms62%
Something else7%
I’ve never developed a custom AI system9%
104 PARTICIPANTS
CTO in Software, 201 - 500 employees
Without a doubt - Technical Debt! It's a ball and chain that creates an ever increasing drag on any organization, stifles innovation, and prevents transformation.
Business and technology leaders will need to collaborate and strategize on the best approach which is ‘human-centric’ :
Focus on and address questions of responsible and ethical use of AI (e.g., data bias, proprietary information, etc.)
Decide whether you will use large publicly available models with some APIs and consideration towards cybersecurity or initiate smaller very niche models for specific use cases which are fine tuned to meet your requirements.
Include the team by educating and clarifying that this implementation will augment but not replace human effort. The idea is to empower the employees and serve the stakeholders better more effectively and efficiently.