Achin Bhowmik

Achin Bhowmik

Starkey，首席技术官兼工程执行副总裁

Starkey, CTO & Executive Vice President of Engineering

Achin Bhowmik, PhD

Chief Technology Officer at Starkey Hearing & Adjunct Professor at Stanford University

Dr. Achin Bhowmik is the Chief Technology Officer and Executive Vice President of Engineering at Starkey, a global leader in hearing technology, where he leads the transformation of hearing aids into multifunctional, AI-powered communication and health devices. Previously, he served as Vice President and General Manager of Perceptual Computing at Intel, where he founded RealSense and led pioneering work in three-dimensional sensing, computer vision, interactive devices, and autonomous systems.

Dr. Bhowmik is an adjunct professor at Stanford University and an affiliate faculty member of the Stanford Institute for Human-Centered Artificial Intelligence and the Wu Tsai Neurosciences Institute. He has authored more than 200 publications, including three books and over 80 patents worldwide.

He is a Fellow of the Society for Information Display (SID), the Institute for Electrical and Electronics Engineers (IEEE), the International Academy of Artificial Intelligence Sciences (AAIS), and the International Artificial Intelligence Industry Alliance (AIIA). He has served as the President of SID and is on the boards of RealSense, Mojo Vision, AstraNu, and the National Captioning Institute. His work has received numerous honors, including TIME’s Best Inventions, the Red Dot Design Award, and the Artificial Intelligence Excellence Award.

人工智能基础：从视觉到语言模型

摘要：

人工智能（AI）正深刻改变着我们与技术的互动方式，重塑各行各业，并解锁曾被视为科幻小说的可能性。本短期课程将全面介绍人工智能技术，旨在为新手与资深专业人士提供兼具广度与深度的学习体验。

课程将从机器学习的基础知识切入，探究算法如何从数据中学习规律模式。随后我们将深入解析用于图像识别与视觉任务的卷积神经网络，进而探讨支撑当今大型语言模型（如GPT、Gemini、Grok、Llama、DeepSeek等）的Transformer架构，揭示注意力机制如何赋予AI多模态推理与感知能力。通过类比人类认知神经科学的感知原理、解析算法的计算实现路径，并结合交互式演示体验，参与者将深入理解AI系统处理、感知及生成信息的运作机理。

无论您是希望了解AI的潜能，还是想深化对前沿技术进展的认知，本课程都将助您把握当前技术版图，并激发对未来应用场景的想象。无需专业技术背景，仅需具备高中或大学阶段的线性代数基础知识即可参与。

Fundamentals of Artificial Intelligence: Vision to Language Models

Abstract：

Artificial Intelligence (AI) is transforming the way we interact with technology, reshaping industries, and unlocking possibilities once thought to be science fiction. This short course provides a comprehensive introduction to AI technologies, designed to engage both newcomers and seasoned professionals.

We will begin with the fundamentals of machine learning and explore how algorithms learn patterns from data. From there, we examine convolutional neural networks for image recognition and vision tasks. The course then advances to transformer architectures that underpin today’s large language models (e.g., GPT, Gemini, Grok, Llama, DeepSeek, etc.), explaining how attention mechanisms enable multimodal reasoning and perception. Through drawing parallels with human perception and cognitive neuroscience, exploring the computational implementations, and engaging with interactive demonstrations, participants will gain an appreciation of how AI systems process, perceive, and generate information.

Whether you're curious about AI’s capabilities or looking to enhance your understanding of recent advancements, this course will equip you with the knowledge to grasp the current technology landscape and inspire you to envision its future applications. No prior technical expertise is required, just a basic understanding of linear algebra from high school or college.