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As Senior Cloud Software Engineering Manager at Intel Corporation, Mrinal leads engineering for Intel Developer Cloud for the Edge, which provides instant remote access to deploy AI applications on the latest Intel hardware and software platforms. The Edge AI and Vision Alliance named the DevCloud a 2020 Vision Product of the Year. She manages an engineering organization to drive telemetry, AI solutions, security, and infrastructure functions. She has managed teams that developed innovative solutions in AI and led the development of the world’s first presence-aware PC experience with Intel Context Sensing Technology which won an innovation award at CES 2019. As an Ethical AI Champion, she provides leadership and clarity on responsible AI practices and champions the cause through talks, panel discussions, and mentorship at forums such as IEEE Conference on Artificial Intelligence, Embedded Vision Summit, Silicon Valley Women in Engineering, and more. She is an IEEE Senior Member and serves as the Vice Chair for the IEEE Santa Clara Valley Women in Engineering chapter to build a strong community of technical women. She volunteers as an ABET (Accreditation Board for Engineering and Technology) Program Evaluator for Computer Science, Software Engineering, and Data Science programs to improve the quality of education.
She often serves on judging panels and reviews content for AI Conferences. She volunteers as a mentor with the Society of Women Engineers and as a reviewer for the NCWIT (National Center for Women & Information Technology) Computing Awards. She has led Intel Software Professionals Conference (Oregon Chapter) featuring technical tracks in Software Engineering, AI, and Open Source to accelerate shared learnings and industry best practices at Intel’s largest site.
Abstracts:
AI for Good: A Framework for Building Ethical AI Solutions
Join us for a conversation that bridges AI technology with ethical foresight. We'll unpack the essentials of responsible AI, focusing on practical measures for ethical development. We'll discuss how to incorporate responsibility into AI systems, champion diversity in development teams, and encourage a human-centric approach throughout the lifecycle of AI projects. Discover how to make AI that not only performs but also respects and enhances our shared human experience, transforming innovation into a force for positive change.
Metrics That Matter in Your Generative AI Journey
The rapid advancement of Generative AI technologies has underscored the necessity for comprehensive metrics that effectively gauge performance and impact across different stages of the AI model lifecycle. This talk outlines a systematic exploration of crucial metrics relevant to each phase of a Generative AI system, particularly focusing on Large Language Models (LLMs). We will delve into four main stages: definition, development, deployment, and post-deployment. In the definition stage, we will focus on establishing clear benchmarks for accuracy, aligning with initial project objectives. During development, safety and fairness metrics are prioritized to ensure the model's reliability and ethical alignment. Deployment metrics will assess real-world applicability and performance, while the post-deployment phase will evaluate long-term sustainability, focusing on the Total Cost of Ownership (TCO) and ongoing ethical considerations.
Generative AI:From Concept To Deployment
As generative AI (GenAI) technologies advance, their impact on industries from healthcare to entertainment is undeniable, with a projected market value exceeding $110 billion by 2030. Gaining an understanding of GenAI solutions is crucial, not just for tech professionals, but for anyone looking to stay relevant in an increasingly AI-driven world. We will walk through the core aspects of building GenAI solutions, covering foundational AI models, the art of prompt engineering, and the technical considerations for selecting Large Language Models (LLMs). Engaging in hands-on demonstrations will bring the technology to life. We will address significant challenges and risks, showcasing the dual-edged nature of these technologies. Ethical considerations will be at the forefront, emphasizing the necessity of responsible innovation. Through real-world examples, attendees will gain a clear understanding of GenAI's potential and pitfalls, equipped to navigate and contribute responsibly to this rapidly evolving field.
Talks:
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