Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Fortanix Introduces Confidential AI to Advance the Development of Richer AI Models and Applications

New Service Leverages Confidential Computing to Securely Use Sensitive Data Without Compromising Privacy or Compliance, and Keep Models Secure

Fortanix Inc., the data-first multi-cloud security company, introduced Confidential AI, a new software and infrastructure subscription service that leverages Fortanix’s industry-leading confidential computing to improve the quality and accuracy of data models, as well as to keep data models secure. With Fortanix Confidential AI, data teams in regulated, privacy-sensitive industries such as healthcare and financial services can utilize private data to develop and deploy richer AI models.

“For today’s AI teams, one thing that gets in the way of quality models is the fact that data teams aren’t able to fully utilize private data”

As AI becomes more and more prevalent, one thing that inhibits the development of AI applications is the inability to use highly sensitive private data for AI modeling. According to Gartner ®, “Data privacy and security is viewed as the primary barrier to AI implementations, per a recent Gartner survey. Yet, many Gartner clients are unaware of the wide range of approaches and methods they can use to get access to essential training data, while still meeting data protection privacy requirements.”1 Data teams, instead often use educated assumptions to make AI models as strong as possible. Fortanix Confidential AI leverages confidential computing to allow the secure use of private data without compromising privacy and compliance, making AI models more accurate and valuable. Equally important, Confidential AI provides the same level of protection for the intellectual property of developed models with highly secure infrastructure that is fast and easy to deploy.

Recommended AI News: Acoustic Forges Alliance With KPMG To Deliver Consistent, Personalized Marketing Across Channels

“For today’s AI teams, one thing that gets in the way of quality models is the fact that data teams aren’t able to fully utilize private data,” said Ambuj Kumar, CEO and Co-Founder of Fortanix. “Fortanix Confidential AI makes that problem disappear by ensuring that highly sensitive data can’t be compromised even while in use, giving organizations the peace of mind that comes with assured privacy and compliance.”

Related Posts
1 of 21,690

PREDICTIONS-SERIES-2022Confidential AI is the first of a portfolio of Fortanix solutions that will leverage confidential computing, a fast-growing market expected to hit $54 billion by 2026, according to research firm Everest Group. Fortanix utilizes Intel SGX secure enclaves on Microsoft Azure confidential computing infrastructure to provide trusted execution environments, and the company’s Confidential Computing technology has already demonstrated proven use cases.

Recommended AI News: Hakimo, An AI-Informed Physical Security Platform, Announces $4 Million Seed Round

“As AI use cases become more and more complex, there is a clear need to develop the richest models possible, which requires the use of private data,” said Tanner Johnson, Principal Analyst for Data Security at Omdia. “Fortanix’s confidential computing has shown that it can protect even the most sensitive data and intellectual property, and leveraging that capability for the use of AI modeling will go a long way toward supporting what is becoming an increasingly vital market need.”

“Fortanix is helping accelerate AI deployments in real world settings with its confidential computing technology,” said Glen Otero, Vice President of Scientific Computing at Translational Genomics Research Institute (TGen). “The validation and security of AI algorithms using patient medical and genomic data has long been a major concern in the healthcare arena, but it’s one that can be overcome thanks to the application of this next-generation technology.”

Recommended AI News: Amica Insurance Simplifies Customer Communications With The Hi Marley Insurance Cloud

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.