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Mind the Product

Artificial Intelligence (AI) & Machine Learning (ML)

Microsoft lays off 3% of workforce while renogiating partnership with OpenAI

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How to build the right product culture during transformation – Joca Torres (Product Consultant)

B2B product management

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Context, intent, change, purpose, constraints – a model for communicating requirements

5 difficult conversations and how to have them

DoorDash eats Deliveroo while OpenAI makes its biggest buy: This week’s news roundup

Why great product managers think like therapists

Tools and techniques to scale product teams – Charlotte King (Lead Product Manager, eBay)

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>
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<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>
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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

What we get wrong about technology by Tim Harford

Product management in the age of ChatGPT by Yana Welinder

How Canva uses AI-powered features to drive PLG

SUNDAY REWIND: Building products AI-first by Aparna Chennapragada

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SUNDAY REWIND: Building products AI-first by Aparna Chennapragada

Eira Hayward

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