Data processing can quickly gum up the works of edge AI.
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With data becoming increasingly valuable, keeping it safe is a constant concern.
Cloud computing and AI are massive parts of Google’s business.
The technique is particularly useful for open source models that often involve many contributors.
Enterprises are still grappling with balancing innovation and risk as the AI race rages on.
Oracle’s patent highlights a key issue that AI developers are still reckoning with: Data privacy.
“Biases can significantly impact the equity of machine learning models and their decisions.”
AI models are only as good as the data they’re built on.
Security has to come first when deploying AI.
Plenty of other tech giants have sought to solve the ever-present AI data security problem.
AI integrations are causing many cybersecurity teams to rethink their strategies.
Ransomware with stolen data gives attackers multiple opportunities to blackmail enterprises, one expert said.
“There are still going to be things that classical computers are better at.”
Its recent filing could dynamically keep models in check, adjusting to the environment over time.
“You have to be tracking open source as an option.”
“AI is only as useful as the data you give it,” said Cohere’s Autumn Moulder, director of infrastructure and security