Opportunities and Challenges in Building Startups in AI and Machine Learning

Muddu Sudhakar, entrepreneur and angel investor


Date: 2017-10-02
Time: 11am
Location: Room 1202, CSE Building, UC San Diego

Guest Speaker: Muddu Sudhakar, Entrepreneur and Angel Investor

Host: CSE Prof. Andrew Kahng


This talk by entrepreneur and former Silicon Valley executive Muddu Sudhakar is part of the CSE Distinguished Lecture Series for Fall 2017.

Enterprises of all kinds are going through tremendous disruption in their business models due to unique disruptive technologies such as AI, Machine Learning, Deep Learning, Cloud. These new technologies are enabling new startups to disrupt existing large and legacy businesses. The democratization and massive proliferation of data are resulting in a massive shift in the world of AI/ML and data-driven applications.

In this talk I will highlight both opportunities and challenges in building startups in the latest technology trends of AI and Machine learning. The talk will also cover how AI and ML technologies affect Value Creation in the startup ecosystem. The growing Enterprise customer needs for data-driven applications have created the need for next generation digital platforms to build these apps. AI and Machine learning are creating new requirements that developers need in the building of next-gen apps.

An important aspect in this new AI/ML era is the extensive use of open source technologies, an area we will cover with emphasis on how to differentiate in an ever-growing crowded landscape discussing the tradeoff of innovation vs leveraging existing technologies. My goal is to share with you several areas of opportunities to build startups and cover wide range of large opportunities to point products to solution approaches.

Bio:  Dr. Muddu Sudhakar is a successful entrepreneur, executive and angel investor in Silicon Valley. Muddu was SVP & GM of IT Operations Management (ITOM) at ServiceNow from 2016-2017. Prior to that, Muddu was VP & GM of Big Data, Machine Learning/AI, Security and IoT at Splunk (www.splunk.com) from 2014-2016.  At Splunk, Muddu worked on applications of AI/Machine learning, Big data platform, Thin & Thick AI AI/ML Apps, Open source technologies, IoT Analytics solutions and Cyber Security products. Before that, Muddu was CEO of Caspida (www.caspida.com), a leader in next-generation Cyber Security & Threat detection using machine learning. Muddu and the Caspida team were instrumental in creating a new cybersecurity market category called “User Behavioral Analytics (UBA)”.  Earlier, Muddu was co-founder and CEO of Cetas (www.cetas.net) which was acquired by VMware in 2012.  Muddu then served as VP & GM at VMware (www.vmware.com) and Pivotal (www.pivotal.io ) for Big Data Analytics, Machine learning and Cloud Services from 2012 to 2014.  From 2003 to 2010, Muddu was CEO & Founder of Kazeon (www.kazeon.com), which was acquired by EMC (www.emc.com). Muddu led Kazeon to be a leader in Information Security, eDiscovery, and Enterprise Search markets within the Enterprise Informatoin Management sector.  At EMC (www.emc.com) Muddu was Chief Strategy Advisor, VP & GM for Cloud Information Services. Before Kazeon in 2003, Muddu was Co-founder & President of Sanera Systems, a next-generation SAN technology company. Sanera was started in 1999 and was acquired by McData (Brocade) in 2003.  From 1996 to 2000, Muddu was lead architect and designer of CPU and server technology at Silicon Graphics, Inc.

Dr. Muddu Sudhakar holds Ph.D. and M.S. degrees in Computer Science from University of California, Los Angeles and a B.Tech. in Electronics & Communications Engineering from Indian Institute of Technology, Madras.  He is widely published in industry journals and conference proceedings and has more than 40 patents in Cyber Security, Big data analytics, Machine learning, Analytics, Cloud Services, SaaS Apps, Enterprise Search, Information Management, Distributed systems, Storage technologies, SAN/NAS, Server technologies, Virtualization, Search, Information security, Networking technology and VLSI chip design.