Is the current level of AI funding and investment rational or irrational? Is it possible that it’s both at the same time? Let’s look at some numbers and the thought process behind them.
SHOW: 976
SHOW TRANSCRIPT: The Cloudcast #976 Transcript
SHOW VIDEO: https://youtube.com/@TheCloudcastNET
CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw
CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"
SHOW SPONSORS:
- [TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast
- [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.
SHOW NOTES:
DO WE HAVE ANY IDEA HOW TO MEASURE THE IMPACT OF AI?
- How much is one model better than another (e.g. Gemini vs. CoPilot)?
- How much improvement should a software developer get?
- How much improvement should a knowledge worker get?
- How much cost savings should a chatbot provide?
- How long should it take to make a model understand a company’s data?
- How many workers can a company displace with AI?
- OpenAI in 2030 - 26 gigawatts could power between 3.7 million to 17.3 million modern GPU servers
- OpenAI in 2035 - 50 gigawatts could power between 37 million to 173 million modern GPU servers
FEEDBACK?
FEEDBACK?