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
Domino Data Lab, provider of the leading Enterprise AI platform trusted by over 20% of the Fortune 100, 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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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.”1Â 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.
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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.
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