An Artificially Intelligent Enterprise learning event brought to you in partnership with Docker and MongoDB
Tech Talk: How to Accelerate AI Applications to Deployment
Get Key AI Insights in this Exclusive Online Event with Docker, MongoDB, and The AIE Network
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As AI becomes an essential tool in every developer’s toolkit, speed and precision in deployment have become critical. This exclusive, online expert-led tech talk is designed to equip software developers and IT leaders with actionable insights and best practices to streamline AI application deployment. Don’t miss out on learning how to stay competitive in the fast-evolving world of AI.
Register today to hear AI experts discuss how to build AI applications that you can deploy quickly and at scale using the best practices in software development. Attendees will be invited to exclusive instructor led workshops.
Speakers
Mark Hinkle
Publisher, The AIE Network
Mark Hinkle is the Publisher of The AIE Network, a specialized network of over 250,000 AI professionals and business leaders who connect to leverage artificial intelligence for strategic advantage. With over 30 years of experience in enterprise software, open source, and emerging tech, Mark combines deep industry knowledge with a focus on accessible AI applications. Under his leadership, The AIE Network delivers tailored AI guidance, fostering a robust community of AI-savvy professionals.
John M. Willis
Evangelist, MongoDB
John Willis has worked in the IT management industry for more than 40 years and is a prolific author, including "Deming's Journey to Profound Knowledge" and "The DevOps Handbook." He has a long history as a systems management executive at Chef, EnStratus, Socketplane, Docker, and Red Hat. Today is a developer relations strategist with leading AI companies including MongoDB where he helps users understand how to deploy GenAI infrastructure using DevOps.
Michael Donovan
VP of Product, Docker
Mike Donovan is VP of Product at Docker, the leading platform designed to help developers build, share, and run container applications. After spending 15+ years as a Software Engineer in multiple industries, he transitioned into the role of Product Management. Before joining Docker as VP of Product, Mike was SVP of Product at Sauce Labs. His focus as a Product Leader has been on improving the lives of developers and continues that journey at Docker.
Kate Soule
Director of Technical Product Management, Granite
Kate Soule is Director of Technical Product Management, Granite at IBM Research where she specializes in translating AI insight into business impact. Prior to working at IBM Research, Kate earned her MBA at MIT Sloan where she researched techniques for communicating AI and ML insights to nontechnical audiences. Her prior work experience includes building and delivering AI solutions for clients as a Senior Consultant within Deloitte’s Strategy & Operations – AI & Cognitive practice. Kate also holds a B.S. in Statistics from Cornell University.
Why You Should Attend
Practical Insights: Learn directly from AI and DevOps experts who’ve mastered the art of deploying scalable, reliable AI applications.
Network with the Best: Connect with an elite community of AI developers, leaders, and innovators.
Exclusive Access: Attendees gain entry to a hands-on workshop with live instructors and a curated library of AI tools and resources.
Simplifying AI Development for Enterprises
AI development isn’t just for data scientists anymore—it’s now part of a developer’s toolkit. But with the rapid pace of AI advancements, knowing the right tools to use, and how to effectively deploy AI applications, can be overwhelming. Software developers are facing unprecedented challenges.
If you’re not leveraging the best practices and tools for AI, you’re falling behind. But there's hope.
Just as containers have been mission-critical for deploying infrastructure cloud infrastructure. Containers and reliable developer tooling like Docker and MongoDB continue to be essential to AI application development by providing development teams with tools, services, and experiences that help them in their development workflows.
By curating trusted content, a selection of high-quality, secure images, curated by Docker and Verified Publisher partners like MongoDB. These images are stable, up-to-date, and follow industry best-practices. They provide a strong foundation for scaling application development securely.
Simplifying AI Development for Enterprises
Docker brings a streamlined, comprehensive experience to developers by hosting a curated selection of tools, models, and frameworks specifically designed for AI development. With a focus on trusted and verified content, Docker provides everything from pre-configured AI stacks to scalable deployment options. This setup reduces the complexity of deploying and integrating AI models, enabling developers to focus more on building and less on managing infrastructure.
Too many choices - The software landscape of GenAI applications is growing rapidly, architectural patterns are changing and new concepts to learn are coming out daily.
Steep Learning Curve - the learning curve is steep with GenAI technologies, forcing developers to learn about new tools like vector databases, LLMs, and various machine learning concepts like RLHF (Reinforcement Learning from Human Feedback)
Complex software & hardware configurations - running a GenAI application yourself comes with the challenge of deploying very large size applications (LLMs are many GBs in size) and configuring the system to take advantage of GPUs (which dramatically improve performance). These challenges are not usually something an application developer has to worry about because applications are much smaller in size and the easy-to-access CPU architecture is just fine.
Key Benefits for Developers
One-Stop Resource for AI: Docker centralizes a wide variety of pre-configured AI tools and frameworks, eliminating the need to sift through multiple sources and making it easier to find reliable resources for AI projects.
Simplified Integration: Docker offers ready-to-use configurations for popular models, like IBM’s Granite and Hugging Face Transformers, which cut down on setup time and allow developers to jump straight into testing and application integration.
Scalable Architecture: Docker containers facilitate seamless scalability, allowing developers to deploy their AI solutions across cloud, on-premises, and hybrid environments without extensive hardware requirements.
For Software Publishers
Enhanced Visibility and Differentiation: Publishers receive a competitive edge through Docker’s trusted content designation, enabling them to stand out as verified sources in a crowded marketplace.
Data-Driven Insights: Verified Publishers gain access to valuable metrics and insights, helping them understand how their tools are being used and enabling them to tailor content to better serve developers’ needs.
Addressing Key AI Development Challenges
Docker along with their partners deliver a streamlined approach to AI development, reducing the technical burden on developers by providing a trusted platform with scalable, ready-to-use solutions. This focus on simplicity and accessibility empowers developers to concentrate on building impactful applications while giving publishers visibility and actionable insights to grow their audience and refine their offerings. In an often fragmented ecosystem, Docker provides a cohesive, high-performance solution that supports AI development at every step.
Unified Platform for AI ToolsDocker simplifies the development workflow by centralizing essential tools, eliminating the noise of endless AI options, and giving developers a focused platform with AI stacks tailored to specific project needs.Faster Model DeploymentDocker provides pre-configured AI tools that can be deployed in minutes, allowing developers to skip complex setup processes and quickly move to testing and integration.Scalability Across EnvironmentsWith Docker containers, developers can scale their applications efficiently across cloud, on-premises, and hybrid infrastructures, making it easy to adapt to different environments while maintaining performance.Integrated Development ExperienceDocker’s compatibility with popular tools like GitHub Copilot ensures that developers have access to a fully integrated development experience, enhancing productivity and making it easier to build and deploy AI-driven applications.
Docker enables developers to streamline app development, addressing complexity with tools like Docker Desktop and Docker Hub, relied upon by millions globally. In AI, Docker is essential for packaging machine learning models, data tools, and libraries into containers that run seamlessly on any infrastructure—cloud, on-premises, or hybrid. With support for GPU acceleration and pre-configured ML images, Docker accelerates AI prototyping and scaling, freeing teams to focus on innovation over infrastructure.
MongoDB empowers developers to innovate, transform, and disrupt with a platform that integrates live data and advanced features. MongoDB Atlas Vector Search merges vector embeddings with application data in a fully managed, multi-cloud database that addresses transactional, search, analytics, geospatial, and streaming needs. Designed by developers for developers, MongoDB’s comprehensive data platform provides essential tools for varied applications, unifying and simplifying the user experience.
The AIE Network, by Peripety Labs, connects business leaders and AI practitioners with critical resources to drive impactful AI projects. Tailored for high-tech and emerging tech fields, AIE combines tools, expert guidance, and curated content to make AI accessible and actionable. Through hands-on resources and insights, the network supports organizations in streamlining operations, boosting productivity, and achieving a competitive advantage with AI-driven strategies. Their network of artificial Intelligence newsletters connects over 250,000 AI users with AI Insights.