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Before delving into artificial intelligence (AI) projects, it is crucial to avoid the 'shiny object trap.' Instead of pursuing AI for its own sake, focus on identifying real problems and pain points that require innovative solutions. Once the problem and a high-level solution are recognized, the next steps involve discovering how to implement the solution effectively.
Keeping abreast of developments in AI involves subscribing to impactful newsletters and exploring sources like MIT's Technology Review and arXiv. While these resources may not be AI-centric initially, the future suggests AI's integration across various domains. Engaging with research papers and online blogs can offer insights beyond traditional AI applications.
AI tools available today offer valuable enhancements in tasks such as creating mission statements and user segments. Tools like chat GPT can facilitate brainstorming unique ideas and refining mission statements to resonate with diverse audiences. By incorporating AI into workflows, professionals can generate AI-enhanced ideas and segment users more effectively.
The evolving landscape of product management predicts a shift towards AI product management, emphasizing personalized user experiences and efficient automation. PMs are encouraged to collaborate with data scientists to integrate AI elements into their products, enhancing personalization, automation, and recommendation systems. Embracing uncertainty and research partnerships can lead to successful AI product development.
Aspiring AI product managers should focus on gaining technical understanding without the need for extensive coding. Initiatives like no-code approaches for model training allow PMs to integrate AI elements into products without extensive technical backgrounds. By leveraging tools like AutoML, individuals can enhance their product management skill set with AI implementation.
Brought to you by Amplitude—Build better products: https://amplitude.com/ | Eppo—Run reliable, impactful experiments: https://www.geteppo.com/ | Pando—Always-on employee progression: https://www.pando.com/lenny
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Marily is a computer scientist and an AI Product Leader currently working for Meta’s reality labs, and previously at Google for 8 years. In 2014 she completed a PhD in Machine Learning. She is also an Executive Fellow at Harvard Business School and she has taught numerous courses, actively teaching AI Product Management on Maven and at Harvard. Marily joins us in today's episode to shed light on the role of AI in product management. She shares her insights on how AI is empowering her work, and why she believes that every Product Manager will be an AI Product Manager in the future. We also discuss why PM’s should learn a bit of coding, where they can learn it, and best practices for working with data scientists. Marily shares some insight into building her AI Product Management course and also why she full-heartedly believes you should also create your own course.
Find the full transcript here: https://www.lennyspodcast.com/ai-and-product-management-marily-nika-meta-google/#transcript
Where to find Marily Nika:
• Instagram: http://www.instagram.com/marilynika
• LinkedIn: https://www.linkedin.com/in/marilynika/
• YouTube: https://www.youtube.com/c/MarilyNikaPM
• Website: https://bio.link/marilynika
Where to find Lenny:
• Newsletter: https://www.lennysnewsletter.com
• Twitter: https://twitter.com/lennysan
• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/
Referenced:
• The Download newsletter: https://www.technologyreview.com/topic/download-newsletter/
• TLDR newsletter: https://tldr.tech/
• ChatGPT: https://chat.openai.com/auth/login
• MidJourney: https://midjourney.com/home/
• Whisper: https://whisper.ai/
• Machine Learning Specialization course: https://www.coursera.org/specializations/machine-learning-introduction
• Career Foundry: https://careerfoundry.com/
• Coding Dojo: https://www.codingdojo.com/
• Building AI Products—For Current & Aspiring Product Managers course on Maven: https://maven.com/marily-nika/technical-product-management
• arXiv: https://arxiv.org/
• Marginal Revolution blog: https://marginalrevolution.com/
• Automl: https://cloud.google.com/automl
• Inspired: How to Create Tech Products Customers Love: https://www.amazon.com/INSPIRED-Create-Tech-Products-Customers/dp/1119387507
• You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It’s Making the World a Weirder Place: https://www.amazon.com/You-Look-Like-Thing-Love/dp/0316525227
• The Adventures of Women in Tech Workbook: A Life-Tested Guide to Building Your Career: https://www.amazon.com/Adventures-Women-Tech-Workbook/dp/1646871022
• Boz to the Future podcast: https://podcasts.apple.com/us/podcast/boz-to-the-future/id1574002430
• The White Lotus on HBO: https://www.hbo.com/the-white-lotus
• Lensa: https://apps.apple.com/us/app/lensa-ai-photo-video-editor/id1436732536
In this episode, we cover:
(00:00) Marily’s background
(03:20) How Marily stays informed about the latest developments in AI
(04:46) What is overhyped and underhyped in AI right now
(05:59) How Marily uses ChatGPT for work
(08:25) Why product managers will be AI product managers in the future
(11:16) How to get started using AI
(14:12) When not to use AI
(15:47) How much data do you need for AI to work properly?
(17:01) When should companies develop their own AI tools?
(18:35) What an AI model is and how it is trained
(21:25) How Google demonstrated the ability of AI to translate a conversation in real time
(23:02) Why AI will not replace PMs
(23:48) A case for learning to code
(26:21) Where to learn to code
(27:40) How to become a strong AI PM
(29:25) Challenges that AI PMs face
(31:16) Getting leadership on board with investing in AI
(33:10) How PMs will work with data scientists and AI
(35:29) Marily’s AI course
(39:12) AutoML and how a renewable-energy company used it to improve its turbine maintenance procedure
(40:31) How Marily built her course and the modifications she has made
(42:53) Why you should create your own course
(44:08) Lightning round
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.
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