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As we look back at 2020 and forward to 2021, we round up our top stories on AI in business, in breakthroughs, in practice. Be sure to subscribe to our enterprise newsletter for monthly updates across all the areas we cov...
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Lakes v. warehouses, analytics v. AI/ML, SQL v. everything else... As the technical capabilities of data lakes and data warehouses converge, are the separate tools and teams that run AI/ML and analytics converging as well?
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Just having data is not enough: it takes an entire system of tools and technology to extract value from data. a hallway style conversation between Ali Ghodsi, CEO and Founder of Databricks, and a16z general partner Martin Casado explore the evolution of data architectures.
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AI/ML development is like reining in the natural world, more like physics and even metaphysics, where data and models are fluid. But this not just a philosophical observation; it has real implications for the margins, organizational structures, and building of such businesses. Especially as we’re in a tricky time of transition, where customers don’t even know what they’re asking for, yet are looking for AI/ML help or know it’s the future. So what does this all mean for the software value chain; for open source collaboration and commodification; for a new type of AI/ML company; and for the future of software businesses?
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AI has enormous potential to disrupt markets that have traditionally been out of reach for software. These markets – which have relied on humans to navigate natural language, images, and physical space – represent a ...
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Gross margins are one of the most important financial metrics for any startup, but figuring out what does and doesn't go into them as a company grows is not as simple as it sounds. In this episode, we discuss why and when margins matter, and how they evolve along the way.
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Today’s episode is one of our intimate hallway-style conversations — or as intimate as remote work allows anyway. It’s all about the history and future of protocol development.
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0/ Is there an Enterprise Margin Crisis? It’s not uncommon to see software startups with surprisingly low margins (30-40%). I believe there is a broader trend going on here, which I explore in this thread.
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Data has long been lauded as a competitive moat for companies, and that narrative’s been further hyped with the recent wave of AI startups. Network effects have been similarly promoted as a defensible force in building...