post

Footer About

Footer Contribute

Footer Get Involved

Footer Links

Mind the Product

Product Management

Sunday Rewind: Whose job is it anyway? The rise of Product Ops and why it deserves to be an independent function

Guest Post

Creating metrics that matter

B2B product management

Artificial Intelligence (AI) & Machine Learning (ML)

Building Product Teams

Business Strategy

Data Driven Product Management

Digital Transformation

Diversity and Inclusion

Minimum Viable Product

OKRs

Prioritisation

Product Design

Product Research

Product Development Process

Product Ethics

Product Discovery

Product Leadership

Product Management Career

Product Strategy

Stakeholder Management

🌎 <a href="https://www.mindtheproduct.com/world-product-day/" style="color:#FFFFFF;text-decoration:underline;">Happy World Product Day!</a> Be sure to celebrate product, yourself, and your peers today! 🎉

How much are product managers getting paid in 2024?

Leading product ops at Delivery Hero with Koen Dubelaar

Connecting fans to creators at Spotify (Dariusz Dziuk, Product Lead, Spotify)

“You’re not as competent as you think” 5 lessons from Ken Chin on navigating a product career (CPO, Spark Networks)

Everything wrong with the product management job market. And how to fix it

Eira is an editor for Mind the Product. She's been a business journalist, editor, and copywriter for longer than she cares to think about.

Eira Hayward

<p>This week’s Sunday Rewind takes us back to an in-depth talk from mtpcon San Francisco 2017, where <a href="http://twitter.com/aparnacd" target="_blank" rel="noopener">Aparna Chennapragada</a>, formerly Product Director and Technical Assistant to the CEO at Google, unpacks 4 ideas on how artificial intelligence (AI) will change how we think about products and experiences.</p>
<p>Aparna starts by looking at the changes to machine learning and the breakthroughs that have been made in the previous decade: algorithms have become better through modelling the human brain, there is much more data available to train systems, and more raw computing power than ever before to bring it all together. These factors change how we develop products from endless if/else statements to simple algorithms with deep learning systems behind them.</p>
<h3>1. Computers adapt to humans</h3>
<p>Rather than humans adapting to computers. Interacting with our computers through a mouse and keyboard is better than punch cards, but it is still a slightly unnatural interaction that separates the interface from the input. Smartphones have made this a little better by allowing direct manipulation of the interface, but machine learning and AI allows for more natural interaction through voice, gestures, and more.</p>
<h3>2. What superpowers can you give your users?</h3>
<p>One way to decide where to use AI in products is to think about the superpowers you want to give your users. Is there a way you can help users discover new content at scale? Is there a power tool you can give to experts?</p>
<h3>3. Building a product involves training a product</h3>
<p>Think about user goals, not just user flows. And as technology gets horizontal, Product needs to get vertical so that algorithms and processes behind building machine learning are applicable to any industry. Differentiation comes from picking the right problem to solve with machine learning, the right goal and the right training data.</p>
<h3>4. New product ideas come from new capabilities</h3>
<p>Snapchat and Instagram could only happen because of the cameras in smartphones, and ride-sharing apps could only happen because of GPS location. What capabilities will machine learning and AI give us?</p>
<p>Read the original article and watch Aparna’s talk: <a href="https://www.mindtheproduct.com/building-products-ai-first-aparna-chennapragada/" target="_blank" rel="noopener">Building Products AI-First by Aparna Chennapragada</a></p>
<hr />
<p><i>If you want to elevate your product management game and witness inspiring and actionable keynotes at one of our #mtpcon conferences then you can </i><a href="https://www.mindtheproduct.com/mtpcon/san-francisco/?utm_source=InternationWDContent&amp;utm_medium=content&amp;utm_campaign=mtpconsanfran"><i>secure your place at #mtpcon San Francisco today!</i></a><i> Happening on June 14 – join us in-person or online.</i></p>
<div class="g g-21"></div>

core/freeform

AI ethics advice from former White House technologist – Kasia Chmielinski (Co-founder, The Data Nutrition Project)

How Google makes AI work at Enterprise scale – Miku Jha (Director, AI/ML and Generative AI, Google Cloud)

LLM workflows for product managers: 3 key takeaways (Niloufar Salehi, Assistant Professor at UC Berkeley) – ProductTank SF

The future of product management: Insights from ProductTank San Francisco

Product lessons learned making early moves with AI in media: Lindsey Jayne (CPO, Financial Times)

A year with ChatGPT and product innovation: Navigating the AI landscape

How to keep your head about generative AI (when everyone is losing theirs) by Claire Woodcock

SUNDAY REWIND: Building products AI-first by Aparna Chennapragada

Eira Hayward

Read more

Comments