Product Manager Hub (PM Hub)
Cyrus Shirazian
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Top 10 Product Manager Hub (PM Hub) Episodes
Goodpods has curated a list of the 10 best Product Manager Hub (PM Hub) episodes, ranked by the number of listens and likes each episode have garnered from our listeners. If you are listening to Product Manager Hub (PM Hub) for the first time, there's no better place to start than with one of these standout episodes. If you are a fan of the show, vote for your favorite Product Manager Hub (PM Hub) episode by adding your comments to the episode page.
UX for AI Products with TikTok’s Global Head of Monetisation Integrity Services, Simon O’Regan
Product Manager Hub (PM Hub)
09/05/22 • 44 min
In this episode with Simon O’Regan, you will learn:
- What is UX for AI products and why does it matter
- How does UX for AI products change depending on the type of product
- Simon’s overall strategy for UX part of AI Products
Intro music by Peter Boros of The Nameless Citizens
1 Listener
Product Ideation, Validation, and Product Market Fit with CPO of Mira
Product Manager Hub (PM Hub)
05/10/21 • 38 min
How is Product Done at Miro with their Product Lead, Farbod Saraf
Product Manager Hub (PM Hub)
06/09/21 • 40 min
All About Product Strategy with Author of Inspired & Empowered, Marty Cagan
Product Manager Hub (PM Hub)
08/12/20 • 29 min
How to Navigate Your Product Career with the Product Decagon
Product Manager Hub (PM Hub)
05/23/21 • 39 min
The Agile Data Science Playbook: Quarterly Sprints to ML Success featuring Lauren Creedon
Product Manager Hub (PM Hub)
07/07/24 • 44 min
Summary
Summary
In this conversation, Cyrus and Lauren discuss the intersection of Agile and data science, specifically focusing on the challenges of shipping AI-enabled products quickly. They emphasize the importance of democratizing AI within organizations and the need for product managers to understand AI and ML concepts. They also discuss the prioritization of AI ML feature sets per quarter and the balance between quick wins and long-term strategic initiatives. Lauren shares her recommendations for getting buy-in and support from leadership, including listening, scenario planning, and making informed decisions.
Takeaways
- Democratizing AI within organizations is crucial for enabling more people to understand and work with AI and ML.
- Product managers should prioritize AI ML feature sets based on business goals and market expectations.
- Balancing quick wins and long-term strategic initiatives is important for delivering outcomes and driving growth.
- Getting buy-in and support from leadership requires listening, scenario planning, and making informed decisions.
- Understanding the constraints and goals of different teams and stakeholders is essential for successful product management in the AI ML space.
Chapters
00:00 Introduction and Background
03:25 Challenges of Delivering Business Value Quickly
06:52 Democratizing AI within Organizations
11:05 Scoping AI/ML Feature Sets for Revenue Outcomes
14:12 Staying Up-to-Date with New Technologies
27:40 Incorporating AI into Product Strategies
28:54 Aligning Organizational Expectations and Goals
30:09 Understanding Constraints and Goals
33:10 Planning and Execution
36:04 Balancing Quick Wins and Long-Term Strategic Initiatives
40:17 Gaining Buy-In from Leadership
43:10 Democratizing Knowledge about AI and ML
Keywords
Agile, data science, intersection, challenges, shipping, AI-enabled products, democratizing AI, product managers, prioritization, feature sets, quick wins, long-term strategic initiatives, buy-in, leadership
Four Mindsets of Influential Product Managers with Author and Product Executive, Ken Sandy
Product Manager Hub (PM Hub)
10/15/20 • 54 min
Stakeholder Management for AI Products with Consultant, coach, keynote speaker, and author, Paul Ortchanian
Product Manager Hub (PM Hub)
09/04/22 • 41 min
In this episode with Paul Ortchanian, you will learn:
- How do you figure out the right stakeholders for an AI product that you’re working on
- What are some unique challenges for stakeholder mgmt for AI products?
- Paul’s overall strategy for managing stakeholders for AI products?
Intro music by Peter Boros of The Nameless Citizens
The Language of Innovation: Navigating the NLP Revolution with Ivan Lee, CEO of Datasaur
Product Manager Hub (PM Hub)
03/18/24 • 47 min
Summary
In this conversation, Cyrus and Ivan discuss various topics related to NLP (Natural Language Processing) and its impact on AI. They cover Ivan’s background in AI and NLP, pivotal moments in his career, the current state of the NLP industry, best practices for data collection and NLP-powered products, the challenges of scaling LLM-POCs (Large Language Models Proof of Concepts) into production, and the ethical considerations of NLP. They also touch on the future of NLP and AI, including the potential for AI agents and the role of NLP in unlocking human creativity.
Takeaways
- NLP is revolutionizing AI by enabling machines to understand and process human language.
- Data collection and the design and build of NLP-powered products require careful consideration and alignment with business metrics.
- Labeling data for NLP models can be time-consuming and expensive, and automation tools can help save time and money.
- Ensuring consistency and accuracy in NLP models is crucial, especially when dealing with multiple correct answers and user intent.
- The future of NLP and AI holds exciting developments, such as multimodal language understanding and unlocking human creativity.
- Ethical considerations are essential in the application of NLP, and measures must be taken to protect user privacy and ensure fairness.
- Integrating NLP into products and services requires a positive and forward-thinking mindset, embracing the potential of NLP to enhance user experiences and drive innovation.
Chapters
00:00 The Current State of NLP Industry
00:15 Pivotal Moments in Ivan’s Career
03:24 Advancements in NLP and LLMs
14:27 Data Labeling and Saving Time and Money
17:54 Impact of Lawsuits and Real-Time Use Cases on User Experience
18:51 Future-Proofing Products and Fine-Tuning Models
19:52 Standardization and Automation in Model Development
21:19 Scaling LLM-POCs into Production Environments
23:03 Complexity of Multiple Truths and User Intent in NLP
24:20 Best Practices for Labeling and Model Training
27:01 Case Study: Impact of DataSaur’s NLP Technology on the Legal Industry
28:55 Ensuring Consistency and Accuracy in Model Output
34:14 Ethical Considerations in NLP and AI
39:04 Exciting Developments in NLP and AI
45:18 Advice for Integrating NLP into Products and Services
All About Online Marketplaces with Facebook Product Lead
Product Manager Hub (PM Hub)
01/31/21 • 39 min
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FAQ
How many episodes does Product Manager Hub (PM Hub) have?
Product Manager Hub (PM Hub) currently has 50 episodes available.
What topics does Product Manager Hub (PM Hub) cover?
The podcast is about Podcasts and Technology.
What is the most popular episode on Product Manager Hub (PM Hub)?
The episode title 'UX for AI Products with TikTok’s Global Head of Monetisation Integrity Services, Simon O’Regan' is the most popular.
What is the average episode length on Product Manager Hub (PM Hub)?
The average episode length on Product Manager Hub (PM Hub) is 40 minutes.
How often are episodes of Product Manager Hub (PM Hub) released?
Episodes of Product Manager Hub (PM Hub) are typically released every 9 days, 12 hours.
When was the first episode of Product Manager Hub (PM Hub)?
The first episode of Product Manager Hub (PM Hub) was released on Apr 21, 2020.
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