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5 Things To Look For When Evaluating AI Startups

Crunchbase News

Roughly 75% of that value will emanate from productivity gains across customer operations, sales and marketing, software engineering, and R&D. Standard products include employee copilots, content generation for marketing, back-office automation and enterprise knowledge search. trillion to $4.4 trillion annually.

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AI Product Management After Deployment

O'Reilly Media - Ideas

The field of AI product management continues to gain momentum. As the AI product management role advances in maturity, more and more information and advice has become available. One area that has received less attention is the role of an AI product manager after the product is deployed.

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What you need to know about product management for AI

O'Reilly Media - Ideas

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). You’re responsible for the design, the product-market fit, and ultimately for getting the product out the door.

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When is data too clean to be useful for enterprise AI?

CIO

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

Data 211
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Compound aims to be a one-stop shop for tech employees to manage their finances

TechCrunch

Compound, part of the 2019 Y Combinator class , calls itself an all-in-one wealth management platform that shows users a full financial picture of their liquid and illiquid assets, including cash, securities, crypto, real estate and venture investments. . That’s why they started Compound nearly three years ago.

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Predibase exits stealth with a low-code platform for building AI models

TechCrunch

-based companies, 44% said that they’ve not hired enough, were too siloed off to be effective and haven’t been given clear roles. Or they can choose to use a blackbox off-the-shelf ‘AutoML’ solution that simplifies their problem at the expense of flexibility and control.”

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Article: Pipedrive Unfixed - Case Study of a Unicorn Company

InfoQ Culture Methods

Pipedrive would not have become a unicorn company by using a standard off-the-shelf agile framework. In Pipedrive's Agile Framework, the Product Managers pitch new ideas and Software Engineers volunteer to lead their Mission Teams. Instead, the company created its own framework.