Security and Privacy // Day 2 Panel 1 // AI in Production Conference episode artwork

EPISODE · Mar 19, 2024 · 34 MIN

Security and Privacy // Day 2 Panel 1 // AI in Production Conference

from MLOps.community · host Demetrios

// Abstract Diego, David, Ads, and Katharine, bring to light the risks, vulnerabilities, and evolving security landscape of machine learning as we venture into the AI-driven future. They underscore the importance of education in managing AI risks and the critical role privacy engineering plays in this narrative. They explore the legal and ethical implications of AI technologies, fostering a vital conversation on the balance between utility and privacy. // Bio Diego Oppenheimer - Moderator Diego Oppenheimer is a serial entrepreneur, product developer and investor with an extensive background in all things data. Currently, he is a Partner at Factory a venture fund specialized in AI investments as well as a co-founder at Guardrails AI. Previously he was an executive vice president at DataRobot, Founder and CEO at Algorithmia (acquired by DataRobot) and shipped some of Microsoft’s most used data analysis products including Excel, PowerBI and SQL Server. Diego is active in AI/ML communities as a founding member and strategic advisor for the AI Infrastructure Alliance and MLops.Community and works with leaders to define AI industry standards and best practices. Diego holds a Bachelor's degree in Information Systems and a Masters degree in Business Intelligence and Data Analytics from Carnegie Mellon University. Ads Dawson A mainly self-taught, driven, and motivated proficient application, network infrastructure & cyber security professional holding over eleven years experience from start-up to large-size enterprises leading the incident response process and specializing in extensive LLM/AI Security, Web Application Security and DevSecOps protecting REST API endpoints, large-scale microservice architectures in hybrid cloud environments, application source code as well as EDR, threat hunting, reverse engineering, and forensics. Ads have a passion for all things blue and red teams, be that offensive & API security, automation of detection & remediation (SOAR), or deep packet inspection for example. Ads is also a networking veteran and love a good PCAP to delve into. One of my favorite things at Defcon is hunting for PWNs at the "Wall of Sheep" village and inspecting malicious payloads and binaries. Katharine Jarmul Katharine Jarmul is a privacy activist and data scientist whose work and research focuses on privacy and security in data science workflows. She recently authored Practical Data Privacy for O'Reilly and works as a Principal Data Scientist at Thoughtworks. Katharine has held numerous leadership and independent contributor roles at large companies and startups in the US and Germany -- implementing data processing and machine learning systems with privacy and security built in and developing forward-looking, privacy-first data strategy. David Haber David has started and grown several technology companies. He developed safety-critical AI in the healthcare space and for autonomous flight. David has educated thousands of people and Fortune 500 companies on the topic of AI. Outside of work, he loves to spend time with his family and enjoys training for the next Ironman. A big thank you to our Premium Sponsors,  @Databricks  and  @baseten  for their generous support! // Sign up for our Newsletter to never miss an event: https://mlops.community/join/ // Watch all the conference videos here: https://home.mlops.community/home/collections // Check out the MLOps Community podcast: https://open.spotify.com/show/7wZygk3mUUqBaRbBGB1lgh?si=242d3b9675654a69 // Read our blog: mlops.community/blog // Join an in-person local meetup near you: https://mlops.community/meetups/ // MLOps Swag/Merch: https://mlops-community.myshopify.com/ // Follow us on Twitter: https://twitter.com/mlopscommunity //Follow us on Linkedin: https://www.linkedin.com/company/mlopscommunity/

// Abstract Diego, David, Ads, and Katharine, bring to light the risks, vulnerabilities, and evolving security landscape of machine learning as we venture into the AI-driven future. They underscore the importance of education in managing AI risks and the critical role privacy engineering plays in this narrative. They explore the legal and ethical implications of AI technologies, fostering a vital conversation on the balance between utility and privacy. // Bio Diego Oppenheimer - Moderator Diego Oppenheimer is a serial entrepreneur, product developer and investor with an extensive background in all things data. Currently, he is a Partner at Factory a venture fund specialized in AI investments as well as a co-founder at Guardrails AI. Previously he was an executive vice president at DataRobot, Founder and CEO at Algorithmia (acquired by DataRobot) and shipped some of Microsoft’s most used data analysis products including Excel, PowerBI and SQL Server. Diego is active in AI/ML communities as a founding member and strategic advisor for the AI Infrastructure Alliance and MLops.Community and works with leaders to define AI industry standards and best practices. Diego holds a Bachelor's degree in Information Systems and a Masters degree in Business Intelligence and Data Analytics from Carnegie Mellon University. Ads Dawson A mainly self-taught, driven, and motivated proficient application, network infrastructure & cyber security professional holding over eleven years experience from start-up to large-size enterprises leading the incident response process and specializing in extensive LLM/AI Security, Web Application Security and DevSecOps protecting REST API endpoints, large-scale microservice architectures in hybrid cloud environments, application source code as well as EDR, threat hunting, reverse engineering, and forensics. Ads have a passion for all things blue and red teams, be that offensive & API security, automation of detection & remediation (SOAR), or deep packet inspection for example. Ads is also a networking veteran and love a good PCAP to delve into. One of my favorite things at Defcon is hunting for PWNs at the "Wall of Sheep" village and inspecting malicious payloads and binaries. Katharine Jarmul Katharine Jarmul is a privacy activist and data scientist whose work and research focuses on privacy and security in data science workflows. She recently authored Practical Data Privacy for O'Reilly and works as a Principal Data Scientist at Thoughtworks. Katharine has held numerous leadership and independent contributor roles at large companies and startups in the US and Germany -- implementing data processing and machine learning systems with privacy and security built in and developing forward-looking, privacy-first data strategy. David Haber David has started and grown several technology companies. He developed safety-critical AI in the healthcare space and for autonomous flight. David has educated thousands of people and Fortune 500 companies on the topic of AI. Outside of work, he loves to spend time with his family and enjoys training for the next Ironman. A big thank you to our Premium Sponsors,  @Databricks  and  @baseten  for their generous support! // Sign up for our Newsletter to never miss an event: https://mlops.community/join/ // Watch all the conference videos here: https://home.mlops.community/home/collections // Check out the MLOps Community podcast: https://open.spotify.com/show/7wZygk3mUUqBaRbBGB1lgh?si=242d3b9675654a69 // Read our blog: mlops.community/blog // Join an in-person local meetup near you: https://mlops.community/meetups/ // MLOps Swag/Merch: https://mlops-community.myshopify.com/ // Follow us on Twitter: https://twitter.com/mlopscommunity //Follow us on Linkedin: https://www.linkedin.com/company/mlopscommunity/

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Security and Privacy // Day 2 Panel 1 // AI in Production Conference

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This episode was published on March 19, 2024.

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// Abstract Diego, David, Ads, and Katharine, bring to light the risks, vulnerabilities, and evolving security landscape of machine learning as we venture into the AI-driven future. They underscore the importance of education in managing AI risks...

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