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Requests for Startups in 2024

VC Cafe

Technological Convergence – The global equity market value associated with disruptive innovation could increase to 60% by 2030. Artificial Intelligence – Scaling global intelligence and redefining work: AI training costs should continue to fall 75% per year.

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Bridging the Gap: How Semantic Web can move into the mainstream through SXSW

Austin Startup

Personally, I believe that the Semantic Web will become mainstream in the next few years (I actually have a bet on this with some college friends). After reading the wonderful blogpost on the BBC’s dynamic semantic publishing system , it reminded me that the Semantic Web has two audiences: the common web user (my mom) and developers.

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Building Competency in Semantic Web Technology

semanticuniverse.com

This tendency poses a challenge when teaching any new technology (and Semantic Web technology in particular); the key to communicating the innovative value of the new technology lies exactly at the point where previous experience fails to be applicable. Moments While the Semantic Web standards are fundamentally very simple (e.g.,

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Why Has LA Suddenly Gotten So Much Attention from VCs and Entrepreneurs?

Both Sides of the Table

The monetization engine of the Internet that powers the most profitable business perhaps in history was invented and perfected in Los Angeles and is what you now know as Google Ad Words. But the “monetization heart of the Internet” doesn’t stop at Overture, Applied Semantics and MySpace.

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How to Balance AI Magic with Human Expertise

Duct Tape Marketing

Jeff is a data-driven search engine marketing executive with 20+ years of experience in the search industry. He is focused on helping content marketers, search engine marketers, agencies, and e-commerce managers build topical authority, improve content quality and turn semantic research into actionable insights.

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Why You Should Not Build a Recommendation Engine

datacommunitydc.org

Why You Should Not Build a Recommendation Engine. Recommendation engines are arguably one of the trendiest uses of data science in startups today. However, recommendations engines are widely misunderstood both in terms of what is involved in building a one as well as what problems they actually solve. Bookmark the permalink.

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Lessons Learned: The engineering manager's lament

Startup Lessons Learned

Lessons Learned by Eric Ries Monday, October 20, 2008 The engineering managers lament I was inspired to write The product managers lament while meeting with a startup struggling to figure out what had gone wrong with their product development process. This engineering manager is a smart guy, and very experienced.