DevOps teams, ML Engineers and Data Scientists
can now store, secure, govern and manage AI components with
confidence, including industry-first platform for detecting
malicious ML models
swampUP — JFrog Ltd. (“JFrog”) (Nasdaq: FROG), the Liquid
Software company and creators of the JFrog Software Supply Chain
Platform, today introduced ML Model Management capabilities, an
industry-first set of functionality designed to streamline the
management and security of Machine Learning [ML] models. The new ML
Model Management capabilities in the JFrog Platform bring AI
deliveries in line with an organization’s existing DevOps and
DevSecOps practices to accelerate, secure and govern the release of
ML components.
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the full release here:
https://www.businesswire.com/news/home/20230913068121/en/
JFrog introduces the first solution to
bridge AI/ML development and DevSecOps (Graphic: Business Wire)
“Today, Data Scientists, ML Engineers, and DevOps teams do not
have a common process for delivering software. This can often
introduce friction between teams, difficulty in scale, and a lack
of standards in management and compliance across a portfolio,” said
Yoav Landman, Co-founder and CTO, JFrog. "Machine learning model
artifacts are incomplete without Python and other packages they
depend on and are often served using Docker containers. Our
customers already trust JFrog as the gold standard for artifact
management and DevSecOps processes. Data scientists and software
engineers are the creators of modern AI capabilities, and already
JFrog-native users. Therefore, we look at this release as the next
logical step for us as we bring machine learning model management,
as well as model security and compliance, into a unified software
supply chain platform to help them deliver trusted software at
scale in the era of AI.”
AI and ML usage continues to grow rapidly. IDC Research
indicates the worldwide AI/ML market, including software, hardware,
and services, is forecast to grow 19.6 percent to over $500B in
2023. However, as more ML models are being moved to production, the
end users often face challenges including cost, lack of automation,
lack of expertise, and ability to scale.1
"It can take significant time and effort to deploy ML models
into production from start to finish. However, even once in
production, users face challenges with model performance, model
drift, and bias," said Jim Mercer, Research Vice President, DevOps
& DevSecOps, IDC. "So, having a single system of record that
can help automate the development, ongoing management, and security
of ML Models alongside all other components that get packaged into
applications offers a compelling alternative for optimizing the
process."
Using JFrog’s new ML Model Management capabilities organizations
can:
- Proxy the popular public ML repository Hugging Face to cache
open source AI models companies rely on, bringing them closer to
development and production, protecting them from deletion or
modification.
- Detect and block use of malicious ML models.
- Scan ML model licenses to ensure compliance with company
policies.
- Store home grown or internally-augmented ML models with robust
access controls and versioning history for greater
transparency.
- Bundle and distribute ML models as part of any software
release.
“Increasing numbers of organizations are starting to incorporate
ML models into their applications and with several government
regulations requiring software vendors to list exactly what’s
inside their software, we believe it won’t be long before these
guidelines grow to include ML and AI models as well,” said Yossi
Shaul, SVP Product and Engineering, JFrog. “We’re excited to give
customers an easy way to proxy, store, secure, and manage models
alongside their other software components to help accelerate their
pace of innovation while remaining well-positioned for tomorrow’s
demands.”
For more information on the beta release of the new ML Model
Management capabilities in the JFrog Platform, read this blog or
visit https://jfrog.com/mlops/.
Like this story? Tweet this: .@jfrog unveils new #MLOps
capabilities in #Artifactory to deliver complete visibility and
governance of ML Models being built and in production:
bit.ly/3Pz4jlY #SoftwareSupplyChain #DevSecOps
About JFrog
JFrog Ltd. (Nasdaq: FROG) is on a mission to create a world of
software delivered without friction from developer to device.
Driven by a “Liquid Software” vision, the JFrog Software Supply
Chain Platform is a single system of record that powers
organizations to build, manage, and distribute software quickly and
securely, ensuring it is available, traceable, and tamper-proof.
The integrated security features also help identify, protect, and
remediate against threats and vulnerabilities. JFrog’s hybrid,
universal, multi-cloud platform is available as both self-hosted
and SaaS services across major cloud service providers. Millions of
users and 7K+ customers worldwide, including a majority of the
Fortune 100, depend on JFrog solutions to securely embrace digital
transformation. Once you leap forward, you won’t go back! Learn
more at jfrog.com and follow us on Twitter: @jfrog.
Cautionary Note About Forward-Looking Statements
This press release contains “forward-looking” statements, as
that term is defined under the U.S. federal securities laws,
including but not limited to statements regarding JFrog’s Machine
Learning Model Management capabilities, the anticipated benefits to
customers, the projected growth of the AI/ML market and potential
government regulation.
These forward-looking statements are based on our current
assumptions, expectations and beliefs and are subject to
substantial risks, uncertainties, assumptions and changes in
circumstances that may cause the impact of JFrog’s products to
differ materially from those expressed or implied in any
forward-looking statement. There are a significant number of
factors that could cause actual results, performance or
achievements, to differ materially from statements made in this
press release, including but not limited to risks detailed in our
filings with the Securities and Exchange Commission, including in
our annual report on Form 10-K for the year ended December 31,
2022, our quarterly reports on Form 10-Q, and other filings and
reports that we may file from time to time with the Securities and
Exchange Commission. Forward-looking statements represent our
beliefs and assumptions only as of the date of this press release.
We disclaim any obligation to update forward-looking
statements.
____________________
1
IDC, “MLOps – where ML meets
DevOps,” by Jim Mercer, Research Vice President, DevOps &
DevSecOps, March 2022
https://www.idc.com/getdoc.jsp?containerId=US48544922&pageType=PRINTFRIENDLY
View source
version on businesswire.com: https://www.businesswire.com/news/home/20230913068121/en/
Media Contact: Siobhan Lyons, Sr. MarComm Manager, JFrog,
siobhanL@jfrog.com Investor Contact: Jeff Schreiner, VP of
Investor Relations, jeffS@jfrog.com
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