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Amazon announced their earnings yesterday. Like Microsoft & Google, Amazon’s Web Service business is seeing a surge of growth, up from 13% annual to 17% annual growth (16% when excluding the leap year).

Aside from the overall growth of these clouds increasing, the massive investment in CapEx data centers, power plants, and GPUs is stunning.

These are not one-time investments, but part of a broader trend that started to occur after the introduction of GPT 3 in mid-2020 Amazon was the first to invest significantly.

What drives the acquisition market of startups? It’s the big deals.

In the last decade, the total number of venture backed software M&A by count has remained relatively constant. The black line shows the linear trend across US venture backed companies with disclosed values of $50m or more.

The average & median counts by year total 58 & 55 respectively.

If it wasn’t clear before, AI is the single biggest revenue driver in cloud.

Microsoft’s Azure is winning share directly from Amazon. In Feburary, Microsoft grew 2% & Amazon lost 2%. Google is also taking share - 1% in the last year. A one percentage point share shift represents about $750 million of spend or about $5b in market cap.

“We’re fundamentally a share taker there because if you look at it from our perspective, at this point, Azure has become a port of call for pretty much anybody who is doing an AI project”

Enterprises spend more on security but aren’t benefitting from the extra spend. Palo Alto Networks’ customers who buy security across 3 platforms spend more than 40x those that secure just one.

Despite those dollars…

“Adding incremental point products is not necessarily driving a better security outcome for them.” - Nikesh Arora, CEO of Palo Alto Networks

The average enterprise uses upwards of 70 security products. Many of these products produce alerts identifying phishing emails or network access issues or odd device behavior.

Snowflake announced Arctic, their open 17b model. The LLM perfomance chart is replete with new offerings in just a few weeks. Overall knowledge performance is asymptoting as expected. It’s hard to discern the most recent dots.

One thing stands out from the announcement - the positioning of the model.

“The Best LLM for Enterprise AI”

Snowflake focuses on the model’s enterprise performance : SQL generation, code completion, & logic. This push will be echoed by others as models start to specialize.

On Friday May 3rd at 9:30 Pacific time, Office Hours will host Jordan Tigani, CEO of MotherDuck.

Jordan’s path through data starts with being the founding tech lead on Google Big Query to SingleStore’s Chief Product Officer to MotherDuck’s CEO.

He wrote the Big Data is Dead, explaining that a power law applies to most companies’ data.

One of the most innovative things about DuckDB & MotherDuck is the ability to start querying with local data & then use the cloud when necessary. This also works in reverse.

In “Do software companies actually have good margins?”, Benn Stancil makes a case for a counterintuitive point : Software companies are much less profitable than they might seem.

Why?

Because the research & development costs associated with software should be part of their cost of goods sold. Software companies don’t invest once in R&D & then sell copies of the software as we did in the 90s on CDs.

It’s software-as-a-service. So the costs of developing & maintaining the software are ongoing.

Ethereum generated $370m in profit on $825m in revenue for about a 45% net income margin.

The chart above shows both the historical performance & also explains how web3 blockchains like Ethereum generate revenue & profits.

How does Ethereum compare to other software companies?

If Ethereum were to trade on the New York Stock Exchange or the NASDAQ, it would top the net income margin (%) charts, with Microsoft, Adobe and Veeva thereafter.

Over the weekend, Tobi, the founder and CEO of Shopify, discussed the major reason investors passed on Shopify in the early days : market size.

Good supercut about why Shopify worked https://t.co/pw92KutpEn

— tobi lutke (@tobi) April 14, 2024

I remember that financing round, & I remember having the same concern, & making the same mistake. Living in the valley & driving on 101, the billboards & logo-adorned headquarters of successful companies provide a daily infusion of all the mistakes in I’ve made in guessing how a company or a market might evolve.

Recently, I was at the library & stood in front of a book that might be a good read. I fired up Gemini, asked it for a plot summary & a digest of the reviews before deciding to read it.

So I started a list : what are the ways I use AI that are new in the last year?