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Domino Fall 2023 Release Expands Platform to Fast-Track All Enterprise AI, Including GenAI, Responsibly

(PRNewsfoto/Domino Data Lab)

News provided by

Domino Data Lab

Oct 31, 2023, 09:00 ET

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Pre-Built Projects and Best Practices in Expanded AI Project Hub Jump-Start Generative AI Development

Expanded Data Connectivity, New Data Source Audit and Governance Capabilities Help Teams Overcome Barriers to Deploying All AI with Confidence

SAN FRANCISCO, Oct. 31, 2023 /PRNewswire/ -- Domino Data Lab, provider of the leading Enterprise AI platform trusted by over 20% of the Fortune 100, today announced powerful new capabilities for building AI, including Generative AI (GenAI), rapidly and safely at scale. Its fall 2023 platform release jump-starts GenAI innovation by transforming Domino's AI Project Hub into an AI ecosystem hub with contributions from cutting-edge AI companies, reduces time to value with expanded data connections and code generation tools, and further supports responsible AI with new data source audit capabilities.

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Domino’s fall 2023 release transforms its AI Project Hub into an ecosystem hub to jump-start all enterprise AI.
Domino’s fall 2023 release transforms its AI Project Hub into an ecosystem hub to jump-start all enterprise AI.

According to a Gartner® report, "By 2026, more than 80% of enterprises will have used generative AI APIs or models, and/or deployed GenAI-enabled applications in production environments, up from less than 5% in 2023."1 With companies testing hundreds of AI proofs of concept, it is imperative to accelerate these experiments and scale AI in production as demand grows. Domino now helps customers do both in real-world enterprise environments.

"Today, everyone can do AI proofs of concept — but the organizations that quickly productionize AI innovations will be the ultimate winners," said Nick Elprin, CEO and co-founder at Domino. "Our fall release gives enterprises the agility they need to innovate and the controls necessary to do so responsibly."

Accelerating AI Innovation with Best Practices Built In
By enabling data scientists with the latest in open-source and commercial technologies, Domino's AI Project Hub now accelerates the development of real-world AI applications with pre-packaged reference projects integrating the best of the AI ecosystem. Domino customers and partners can contribute templated projects to the AI Project Hub. Customers can adapt contributed projects to their unique requirements, IP, and data—to build AI applications such as fine-tuning LLMs for text generation, enterprise Q&A chatbots, sentiment analysis of product reviews, predictive modeling of energy output, and more.

AI Project Hub templates pre-package state-of-the-art models with environments, source code, data, infrastructure, and best practices - so enterprises can jump-start AI productivity for a wide variety of use cases, including natural language processing, computer vision, generative AI, and more.

Domino AI Project Hub includes templates to build machine learning models for classic regression and classification tasks, advanced applications such as fault detection using computer vision, and GenAI applications using the latest foundation models from Amazon Web Services (AWS), Hugging Face, OpenAI, Meta, and others. Domino and NVIDIA are creating templates based on the NVIDIA NeMo framework and other NVIDIA AI software to help developers build, customize and deploy generative AI virtually anywhere.

Additional participants in Domino's AI Project Hub launch include industry leaders bringing the latest in applied vertical and domain-specific AI solutions, including:

  • AWS: Summarizing product feedback and generating email text for customer service use cases with Amazon Titan and Anthropic's foundation models, using LangChain to augment additional context.

  • Fiddler AI: Evaluating the robustness, correctness, and safety of LLMs and prompts in pre-production using Fiddler Auditor, the open-source robustness library for red-teaming of LLMs.

  • Deci.ai: Simplifying and accelerating the development of AI applications for code, image and text generation, chatbots and robust object detection using precise low-latency and high-throughput models.

  • Artefact: Generating structured data-driven digital marketing reports using automated, natural language insights.

  • KSM Technology Partners: Accelerating BioPharma discovery and development by automating complex, polyglot biostatistical and bioanalytical computations.

Domino will continue to scale its number of participants and solutions to enrich the ecosystem of templated, pre-packaged projects and AI applications in its AI Project Hub.

Code generation assistants are revolutionizing software development productivity. In this way, Domino's fall release further turbo-charges model development for enterprise data scientists with the Jupyter AI conversational assistant, a user-friendly chat interface that can generate entire notebooks from a natural language prompt. Data science teams can now accelerate productivity, using generative AI to summarize content, fix errors, and work with a wide range of  supported foundation models from Anthropic, AI21, OpenAI, and Cohere — all without leaving the Domino standard environment.

Enhancing Data Access and Governance
To further accelerate responsible GenAI innovation, Domino now provides immediate, governed access to the most popular data sources across the enterprise, whether on premises or in any cloud. This includes new connectivity with more than a dozen sources including Databricks clusters, IBM DB2 and Netezza, SAP HANA, and virtually any other data source. Customers using Domino can eliminate data movement, transformation, and integration complexities, reduce time-to-insight with rapid data access, and responsibly govern sensitive data with secure access controls.

Furthering its commitment to support responsible AI, Domino is also introducing new Data Audit Logging integrated into all Domino workflows. Designed to ensure governance and validation, it provides teams with complete visibility of all data sources accessed from development to production deployment. Enhancing Domino Model Sentry, this new capability transforms policies into responsible actions with governance across the entire data pipeline, and comprehensive model monitoring across the model lifecycle.

Availability

  • New ecosystem-contributed templates in the Domino AI Project Hub and Domino's Jupyter AI conversational assistant all are available in public preview today.
  • Expanded data connections and Data Audit Logging are generally available to customers today.

Additional Resources

  • Read about new capabilities in Domino's Fall 2023 Release on Domino's Data Science Blog.
  • See the new capabilities for accelerating GenAI innovation in Domino's AI Project Hub.
  • Learn more about the latest innovations in the Domino Enterprise AI Platform.
  • Join us on Nov. 30 to see these latest Domino capabilities in a Fall 2023 Release Demo.
  • Reach out to [email protected] for more details on how Domino partners can submit templated projects to the Domino AI Project Hub.
  • Learn about the top 5 paths to rapid impact with GenAI in Domino's new guide.
  • Follow Domino on LinkedIn and X/Twitter.

About Domino Data Lab
Domino Data Lab empowers the largest AI-driven enterprises to build and operate AI at scale. Domino's Enterprise AI platform unifies the flexibility AI teams want with the visibility and control the enterprise requires. Domino enables a repeatable and agile ML lifecycle for faster, responsible AI impact with lower costs. With Domino, global enterprises can develop better medicines, grow more productive crops, develop more competitive products, and more. Founded in 2013, Domino is backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake, and other leading investors. Learn more at www.domino.ai.

1 Gartner, "Hype Cycle for Generative AI, 2023," Arun Chandrasekaran and Leinar Ramos, September 11, 2023. Gartner and Hype Cycle are registered trademarks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.

SOURCE Domino Data Lab

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