AI Workflows: Hope-Flows and Hard Truths
According to Nic Palmer, head of customer architecture for international at Elastic, AI workflows are crucial for modern enterprises.
However, they often focus too much on the model layer, and failures typically arise from weak infrastructure rather than weak models.
A failure in AI workflow may be a consequence of a ‘hope-flow’.
If a workflow cannot be seen, controlled, or adapted from end-to-end, it cannot be expected to be resilient.
As Palmer notes, when something breaks, especially at critical times, relying on hope is not a viable solution.
Elastic is a company known for its open-source platform that powers search, observability, security, and wider functions.
Author's summary: AI workflows require robust infrastructure.
More News
- ‘Chainsaw Man’ Whips Past $100M WW; ‘One Battle After Another’ Keeps Raging – International Box Office
- Jane Scott, the Preston Poisoner – Blog Preston
- Tourist dies after falling from outer wall of Rome's Pantheon
- Everton 0-3 Tottenham: Match Report & Instant Reaction | Outworked and outclassed
- Broadcast Leaders Call Out Tesla’s 'Misguided' FM Radio Cut - Radio Ink
- Myles Garrett Passes T.J. Watt on Career Sacks List
- Android 16 eligible Xiaomi Devices [Complete List]
- From cocaine to crude: Unmasking the U.S. agenda in Venezuela
- This Celtic board won't sack Rodgers. He's their bulletproof vest.
- Resistance and Repression: From ‘No Kings’ Rallies to Right-Wing Hate and Venezuela Threats | KPFA