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Anthropic just raised $65 billion at a $965 billion valuation.
That's the second-largest private funding round in history, behind only OpenAI. The new valuation puts Anthropic ahead of OpenAI as the most valuable AI company in the world, private or public. Quick transparency up front. I'm not a private equity guy. No insider info on Anthropic. Just trying to make sense of this out loud. Here's what I see happening. Most companies raise pre-seed, seed, then Series A through D. After that they either IPO, get acquired, or run out of road. Anthropic just hit Series H. That isn't necessarily an indication of good or bad. Stripe and SpaceX stayed private on purpose to avoid public-market scrutiny. Slack and Lyft reached Series H and IPO'd within a year. Every company takes a different path. What it does tell you: Anthropic chose to stay private through eight rounds. Bloomberg reported an IPO could come as soon as October of this year. Anthropic's annual revenue jumped from $1 billion in December 2024 to $47 billion this month. Widely cited as the fastest revenue ramp of any software company in history. They now run higher revenue than OpenAI, and the latest projections show them hitting profitability first. Not saying one is "winning" here. Both are still burning billions a year. But the underdog framing for Anthropic is getting harder to defend. What this news has me thinking about is why a company growing this fast still needs another $65 billion. The answer is compute. Dario (the CEO) said it himself a few weeks ago. They planned for 10x growth in 2026. They saw 80x. They literally cannot build datacenters fast enough. Earlier this month, Anthropic leased the entire Colossus 1 datacenter in Memphis from SpaceX. 300 megawatts, over 220,000 Nvidia GPUs, $1.25 billion a month. They didn't pick SpaceX over Amazon or Google. Colossus was the only compute available right now. The rest doesn't come online until 2027. This Series H also brought chip manufacturers Samsung, SK Hynix, and Micron on as investors. Those three make the high-bandwidth memory that sits on every Nvidia GPU. Getting them invested locks in supply at the most constrained part of the chip stack.
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Everyone is talking about AI models. I'm starting to think the real winners of the next decade might be the companies building the infrastructure behind them. If you had to invest in one area today, would you choose: 🔹 AI Models 🔹 Data Centers 🔹 Chips (NVIDIA, Samsung, etc.) 🔹 AI Applications Why?
🚀New Video: The AI Career Opportunity Nobody is Talking About in 2026
Everyone in the AI space is being told the same thing right now: start an AI automation agency. But there's a bigger, quieter shift happening that fits way more people. In this video I break down a recent IBM study of 2,000 CEOs, the new chief AI officer wave, the 61-point gap between who can use AI and who actually does, and the two paths into that seat. By the end, you'll know which one fits you and why playing to your strengths matters more than chasing the loudest trend. The IBM study: https://newsroom.ibm.com/2026-05-04-ibm-study-ceos-are-reshaping-c-suite-roles-for-the-ai-era
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@mr-biswas-8739
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