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These early conversations helped shape Databricks product, pricing, and go-to-market strategy. Pricing: Keep It Simple (At First) Databricks started with a simple, consumption-based pricing model. Because thats how their customerswho were used to AWS, Azure, and GCP pricingexpected to buy. Talk to users. Ron recalls.
GCP data is a bit more noisy as they don’t disclose GCP itself, but rather Google Cloud which includes GSuite. Change in Share Price At the end of the day what investors care about is what happened to the stock after earnings were reported. In these situations the stock’s earnings reaction could be flat.
Both Google & Microsoft announced growth rates in GCP & Azure that held steady from one quarter to the next. There are two forces in tension : overall cost reduction efforts by companies & the desire to invest in AI. The desire for AI is broad.
Subscribe now Foundation Models Are to AI what S3 was to the Public Cloud Many people look at 2006 as the birth of the public cloud - the year Amazon launched AWS. Microsoft launched Azure in 2010, and Google launched GCP to the public in 2011 (they launched a preview of Google App Engine in 2008, but made it publicly available in 2011).
When I think about the monetization of AI (and which “layers” monetize first) I’ve always thought it would follow the below order, with each layer lagging the one that comes before it. Model providers (OpenAI, Anthropic, etc as companies start building out AI). 2024 will be the year of AI applications!
This can lead to an airpocket of valuation as companies transition to a different primary valuation metric Outside of the hypserscalers (Azure, AWS, GCP) who have uniquely benefited from AI revenue (mainly selling compute), everyone else has largely struggled. Coming in to Q1 there was broader optimism. Q4’s were generally good!
So far - you’re either tied to AI tailwinds, or it’s rough out there. And in the public universe, it’s really only been the hyperscalers who’ve benefited from AI.
Cloud Giants Report Q2 We also got the Q2 quarters from AWS / Azure / GCP this week! Our expectation, obviously again, is that we are going to significantly increase our investments in AI infrastructure next year, and we'll give further guidance as appropriate.”
This conversation is part of our AI Revolution series, which features some of the most impactful builders in the field of AI discussing and debating where we are, where we’re going, and the big open questions in AI. Find more content from our AI Revolution series on www.a16z.com/AIRevolution. Ali: Enterprises move slow.
AI = Data + Compute I’ll continue beating this drum, but we got two great quotes from Azure and AWS this week. Satya at Microsoft said “Every AI app starts with data and having a comprehensive data and analytics platform is more important than ever.” Subscribe now Busy week! AWS reports next week.
And everyone hoping for AI acceleration will need to wait. The hyperscalers (AWS, Azure, GCP) are seeing some uptick, but this is largely from selling compute (ie cloud GPUs). In summary, I don’t expect real AI tailwinds to show up in non-hyperscaler businesses in a meaningful way through the rest of 2023.
Bonus points : Experience with cloud platforms (AWS, Azure, GCP). new features, pricing models). Making Data Simple : Hosted by AI VP at IBM, Martin AI, this podcast focuses on making complex data science concepts understandable for a broader audience. Excellent communication and collaboration skills.
“AWS’ AI business is a multibillion-dollar revenue run rate business that continues to grow at a triple-digit year-over-year percentage and is growing more than 3x faster at this stage of its evolution as AWS itself grew, and we felt like AWS grew pretty quickly.” GCP 23 35 52.2% Azure 26 33 26.9%
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