The AI Accelerator from the telecoms giant aims to reduce the months-long AI prototype-to-production process to six days by next March.
BT Group has unveiled a new machine learning operations platform that promises to shorten the roll-out of AI from six months to six days.
Developed by BT’s digital unit, the AI Accelerator is poised to drastically reduce the administrative and technical processes involved with taking a new AI use case from prototype to production using common frameworks and templates.
“A core driving principle for BT Group is to find a way to safely accelerate the time to value, pound per petabyte, of data,” said Adrian Joseph, managing director of data and AI at BT.
“AI Accelerator gives us a path to more rapid value with clear oversight of AI use case parameters and performance.”
The London-headquartered telecoms group said that the new platform orchestrates, accelerates and monitors AI model deployments developed by the company’s data community, assessing their efficacy and behaviour to drive value from its 29-petabyte data estate.
AI models are crucial for classifying and making predictions from data in ways that humans can’t.
The tech, built in partnership with AI consultancy and Google Cloud partner Datatonic, is expected to reduce the core of the prototype-to-production process from six months in April 2022 to six days by March 2023.
“Thanks to the work the team has done accelerating our migration into Google Cloud, we’ve a healthy testbed for AI Accelerator and are seeing it catalyse AI acceleration across the group,” said Dr Zoe Webster, AI director in BT’s data and AI team.
The acceleration of deployment will give BT data scientists more time to focus on future projects instead of having to constantly maintain each AI model. BT hopes this will help boost innovation and AI use within the company.
To address concerns around data privacy and security, BT said that the new platform has built-in triggers to make sure the new AI use cases are properly assessed in line with the company’s responsible tech principles for ensuring AI safety.
“As we progress, we’ll be able to track the health and the performance of our AI use cases in real time, ensuring consistent, safe, ethical delivery of value from our phenomenal data resources,” Webster added.
Last year, BT pushed further into the security space with Eagle-i, a platform that uses AI and automation to detect and neutralise cyberattacks before they can cause damage.
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