JFrog Collaborates with NVIDIA to Deliver Secure AI Models With NVIDIA NIM
JFrog (Nasdaq: FROG) has announced a new product integration with NVIDIA NIM microservices, part of the NVIDIA AI Enterprise software platform. This collaboration aims to meet the increasing demand for enterprise-ready generative AI by combining GPU-optimized, pre-approved AI models with centralized DevSecOps processes in an end-to-end software supply chain workflow.
The integration is expected to allow organizations to bring secure machine learning (ML) models and large language models (LLMs) to production faster, with increased transparency, traceability, and trust. Key benefits include unified management, comprehensive security and integrity, exceptional model performance and scalability, and flexible deployment options.
JFrog (Nasdaq: FROG) ha annunciato una nuova integrazione di prodotto con i microservizi NVIDIA NIM, parte della piattaforma software NVIDIA AI Enterprise. Questa collaborazione mira a soddisfare la crescente domanda di intelligenza artificiale generativa pronta per l'impresa, combinando modelli AI ottimizzati per GPU e pre-approvati con processi DevSecOps centralizzati in un flusso di lavoro di supply chain software end-to-end.
L'integrazione dovrebbe consentire alle organizzazioni di portare modelli di apprendimento automatico (ML) sicuri e modelli di linguaggio di grandi dimensioni (LLM) in produzione più rapidamente, con maggiore trasparenza, tracciabilità e fiducia. I principali vantaggi includono gestione unificata, sicurezza e integrità complete, prestazioni eccezionali del modello e scalabilità, e opzioni di distribuzione flessibili.
JFrog (Nasdaq: FROG) ha anunciado una nueva integración de producto con los microservicios NVIDIA NIM, parte de la plataforma de software NVIDIA AI Enterprise. Esta colaboración tiene como objetivo satisfacer la creciente demanda de inteligencia artificial generativa lista para la empresa, combinando modelos de IA optimizados para GPU y pre-aprobados con procesos DevSecOps centralizados en un flujo de trabajo de cadena de suministro de software de extremo a extremo.
Se espera que la integración permita a las organizaciones llevar modelos de aprendizaje automático (ML) seguros y modelos de lenguaje de gran tamaño (LLM) a producción más rápido, con mayor transparencia, trazabilidad y confianza. Los beneficios clave incluyen gestión unificada, seguridad e integridad completas, rendimiento excepcional del modelo y escalabilidad, así como opciones de implementación flexibles.
JFrog (Nasdaq: FROG)는 NVIDIA AI Enterprise 소프트웨어 플랫폼의 일환인 NVIDIA NIM 마이크로서비스와의 새로운 제품 통합을 발표했습니다. 이번 협력은 GPU 최적화 및 사전 승인된 AI 모델을 중앙 집중화된 DevSecOps 프로세스와 결합하여 기업 준비형 생성적 AI에 대한 증가하는 수요를 충족하는 것을 목표로 합니다.
통합을 통해 조직이 안전한 머신 러닝(ML) 모델과 대규모 언어 모델(LLM)을 더 빠르게 생산할 수 있도록 할 것으로 기대됩니다, 또한 투명성, 추적 가능성 및 신뢰가 증대됩니다. 주요 이점으로는 통합 관리, 포괄적인 보안 및 무결성, 뛰어난 모델 성능 및 확장성, 유연한 배포 옵션이 포함됩니다.
JFrog (Nasdaq: FROG) a annoncé une nouvelle intégration de produit avec les microservices NVIDIA NIM, faisant partie de la plateforme logicielle NVIDIA AI Enterprise. Cette collaboration vise à répondre à la demande croissante d'IA générative prête pour l'entreprise en combinant des modèles d'IA optimisés pour GPU et pré-approuvés avec des processus DevSecOps centralisés dans un flux de travail de chaîne d'approvisionnement logicielle de bout en bout.
L'intégration devrait permettre aux organisations d'apporter des modèles d'apprentissage automatique (ML) sécurisés et des modèles de langage de grande taille (LLM) en production plus rapidement, avec une transparence, une traçabilité et une confiance accrues. Les principaux avantages comprennent une gestion unifiée, une sécurité et une intégrité complètes, des performances exceptionnelles des modèles et une évolutivité, ainsi que des options de déploiement flexibles.
JFrog (Nasdaq: FROG) hat eine neue Produktintegration mit den NVIDIA NIM-Microservices angekündigt, die Teil der NVIDIA AI Enterprise-Softwareplattform sind. Diese Zusammenarbeit zielt darauf ab, der steigenden Nachfrage nach einsatzbereiter generativer KI gerecht zu werden, indem GPU-optimierte, vorab genehmigte KI-Modelle mit zentralisierten DevSecOps-Prozessen in einem durchgängigen Software-Lieferketten-Workflow kombiniert werden.
Es wird erwartet, dass die Integration es Organisationen ermöglicht, sichere Machine-Learning (ML)-Modelle und große Sprachmodelle (LLMs) schneller in die Produktion zu bringen, mit mehr Transparenz, Rückverfolgbarkeit und Vertrauen. Zu den wichtigsten Vorteilen gehören ein einheitliches Management, umfassende Sicherheit und Integrität, außergewöhnliche Modellleistung und Skalierbarkeit sowie flexible Bereitstellungsoptionen.
- Integration with NVIDIA NIM microservices to deliver GPU-optimized AI models
- Potential to accelerate deployment of secure ML models and LLMs in production
- Unified management of AI models alongside other software assets in JFrog Artifactory
- Enhanced security and integrity through continuous scanning and auditing
- Optimized AI application performance using NVIDIA accelerated computing infrastructure
- Flexible deployment options including self-hosted, multi-cloud, and air-gap
- None.
The collaboration between JFrog and NVIDIA marks a significant step in streamlining AI model deployment for enterprises. By integrating NVIDIA NIM microservices with JFrog's platform, they're addressing critical challenges in scaling ML model deployments, particularly in security, compliance and performance optimization.
This partnership could potentially accelerate enterprise AI adoption by reducing deployment cycles and mitigating risks of AI initiative failures. The integration offers a unified management system for AI models and software packages, which is important for maintaining consistency and control in complex AI-driven software supply chains.
However, the real test will be in the execution. While the potential benefits are clear, the success of this integration will depend on how seamlessly it can be implemented into existing enterprise workflows and its ability to deliver on the promised performance improvements and security enhancements.
This collaboration positions JFrog strategically in the rapidly growing AI infrastructure market. With Gartner projecting the AI software market to reach
For investors, this move signals JFrog's commitment to expanding its addressable market beyond traditional DevOps. The integration could potentially increase JFrog's revenue streams by attracting AI-focused enterprises. However, it's important to note that the AI market is highly competitive, with tech giants like Microsoft and Google also vying for dominance.
Investors should monitor adoption rates of this integrated solution and its impact on JFrog's customer acquisition and retention metrics in the coming quarters to gauge its success.
While the news is positive for JFrog's strategic positioning, its immediate financial impact remains uncertain. The company's recent acquisition of Qwak AI and this NVIDIA partnership demonstrate a clear push into the AI space, which could diversify revenue streams and potentially boost growth.
However, investors should be cautious. The financial terms of the NVIDIA partnership weren't disclosed and the revenue impact will depend on market adoption. JFrog's Q2 2023 results showed revenue of
Long-term, if successful, this could significantly enhance JFrog's value proposition and market position, potentially leading to accelerated growth and improved profitability. Investors should closely monitor upcoming earnings reports for signs of traction in AI-related offerings.
Aiming to meet the increasing demand for enterprise-ready generative AI, the JFrog Platform integrates NVIDIA NIM to deliver GPU-optimized AI model services
JFrog and NVIDIA Collaborating to Deliver Secure AI Models at Scale (Graphic: Business Wire)
“As organizations rapidly adopt AI technology, it's essential to implement practices that ensure their efficiency and safety, and that incorporate AI responsibly,” said Gal Marder, EVP Strategy, JFrog. “By integrating DevOps, security, and MLOps processes into an end-to-end software supply chain workflow with NVIDIA NIM microservices, customers will be able to efficiently bring secure models to production while maintaining high levels of visibility, traceability, and control throughout the pipeline.”
With the rise and accelerated demand for AI in software applications, data scientists and ML engineers face significant challenges when scaling ML model deployments in enterprise environments. Fragmented asset management, security vulnerabilities, compliance issues, and performance bottlenecks are compounded by the complexities of integrating AI workflows with existing software development processes and the requirement for flexible, secure deployment options across various environments. This compounded complexity can result in very long, expensive deployment cycles and, in many cases, failure of AI initiatives.
“As enterprises scale their generative AI deployments, a central repository can help them rapidly select and deploy models that are approved for development,” said Pat Lee, Vice President, Enterprise Strategic Partnerships, NVIDIA. “The integration of NVIDIA NIM microservices into the JFrog Platform can help developers quickly get fully compliant, performance-optimized models quickly running in production.”
JFrog Artifactory provides a single solution for housing and managing all the artifacts, binaries, packages, files, containers, and components for use throughout software supply chains. The JFrog Platform’s integration with NVIDIA NIM is expected to incorporate containerized AI models as software packages into existing software development workflows. By coupling NVIDIA NGC – a hub for GPU-optimized deep learning, ML and HPC models – with the JFrog platform and JFrog Artifactory model registry, organizations will be able to maintain a single source of truth for all software packages and AI models, while leveraging enterprise DevSecOps best practices to gain visibility, governance, and control across their software supply chain.
The integration between the JFrog Platform and NVIDIA NIM is anticipated to deliver multiple benefits, including:
- Unified Management: Centralized access control and management of NIM microservice containers alongside all other assets, including proprietary artifacts and open-source software dependencies, in JFrog Artifactory as the model registry to enable seamless integration with existing DevSecOps workflows.
- Comprehensive Security and Integrity: Continuous scanning at every stage of development - including containers and dependencies - delivering contextual insights across NIM microservices with JFrog auditing and usage statistics that drive compliance.
- Exceptional Model Performance and Scalability: Optimized AI application performance using NVIDIA accelerated computing infrastructure, offering low latency and high throughput for scalable deployment of LLMs to large-scale production environments.
- Flexible Deployment: Flexible deployment options via JFrog Artifactory, including self-hosted, multi-cloud, and air-gap deployment options.
For a deeper look at the integration of NVIDIA NIM into the JFrog Platform, read this blog or visit https://jfrog.com/nvidia-and-jfrog, where interested parties can also sign up for the beta program.
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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
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 JFrog’s actual results, performance or achievements 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, 2023, 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 except as required by law.
View source version on businesswire.com: https://www.businesswire.com/news/home/20240910858156/en/
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Source: JFrog Ltd.
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