Fri.Feb 09, 2024

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Private Equity Done Right: Partners who help their entrepreneurs thrive

Paul G. Silva

There is no lack of coverage of when Private Equity is done wrong. John Oliver, by himself, has numerous well-regarded pieces on the topic. This is not dissimilar to when bad venture capitalists or angel investors tarnish the reputations of investors in general. And this reporting is important. We should know about bad actors, how to avoid them, and call shame on them!

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Microsoft Teams Up with Indian Startup Sarvam AI to Boost Indic Languages on Azure

AsiaTechDaily

Microsoft has collaborated with Indian generative AI startup Sarvam AI, aiming to integrate its Indic voice large language model (LLM) into Microsoft’s Azure cloud platform. During CEO Satya Nadella’s recent visit to India, Microsoft announced its support for Sarvam AI.

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Preventing & Overcoming Leadership Burnout for CEOs

Mark MacLeod

Burnout is real. It is increasingly common in society at large. And is likely the default state for most CEOs. This is tragic and I am on a mission to change it! I was that person. I have been there. […] The post Preventing & Overcoming Leadership Burnout for CEOs appeared first on Mark MacLeod.

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[D-ID in Inc.] Inside D-ID’s ‘Digital Humans’ Build

OurCrowd

Why are there so few startups taking the lead in Generative AI? Due to the high cost of training and operating Large Language Models, few Generative AI startups can operate without huge amounts of capital.

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From Curiosity to Competitive Edge: How Mid-Market CEOs Are Using AI to Scale Smarter

Speaker: Lee Andrews, Founder at LJA New Media & Tony Karrer, Founder and CTO at Aggregage

This session will walk you through how one CEO used generative AI, workflow automation, and sales personalization to transform an entire security company—then built the Zero to Strategy framework that other mid-market leaders are now using to unlock 3.5x ROI. As a business executive, you’ll learn how to assess AI opportunities in your business, drive adoption across teams, and overcome internal resource constraints—without hiring a single data scientist.