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Google Cloud Platform (GCP) & Microsoft Azure had strong quarters with about 28% annual revenue growth each. But the story in this quarter’s reports is AI. The total customer count for Azure’s OpenAI has grown dramatically. All of that usage is creating a massive business.
Because thats how their customerswho were used to AWS, Azure, and GCP pricingexpected to buy. Enterprise sales require a field presence, strategic account management, and a drive to go where your customers are. Pricing: Keep It Simple (At First) Databricks started with a simple, consumption-based pricing model.
There are 4 questions a startup should ask themselves about building a startup that uses generative AI. The narrative is : AI is a massive platform change that Goldman Sachs projects will increase GDP 300x more than the PC. There are 4 questions startups should ask themselves about building with generative AI.
It’s worth pointing out that Azure is a bit above the long term trendline, while AWS is still below (but accelerating up). It’s worth pointing out that Azure is a bit above the long term trendline, while AWS is still below (but accelerating up).
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. The acceleration is really quite broad.
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" As with many other companies reporting strength in the market, AI & unstructured data workloads are fueling growth. “I don’t even hear the words AI and budget in the same sentence.” “Yes, we actually saw quite a bit of energy coming from the Azureplatform this quarter.
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.”
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).
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. We’ll see if anything improved in the month of April, or if it was another challenged month.
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.
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.
If next quarter we get similar commentary that Azure gave us this quarter (“still a couple quarters away” without any specific guidance), then we may see market loose a little patience. And everyone hoping for AI acceleration will need to wait. The question is how patient will they be waiting for this?
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.
The rise of foundation models and generative AI only furthers this trend. But this isn’t another post about AI, it’s about the future of data infrastructure. As Frank Slootman (Snowflake CEO) said, “Enterprises are also realizing that they cannot have an AI strategy without a data strategy to base it on.”
Bonus points : Experience with cloud platforms (AWS, Azure, GCP). 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. Experience with data visualization tools (e.g., Tableau, Power BI).
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“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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