Amazon Rakes In Revenue, Apple Enriches More Lives

Amazon had a lot of revenue in Q2. And they're on track to have a lot this quarter too. Imagine that, right? Big-cap US tech earnings wound up on Thursday, when the brainchild of civilian astronaut Jeff Bezos said sales were $134.38 billion last quarter. That was easily ahead of estimates, and well above the mid-point of the company's guide from April. Top-line growth is back in the double-digits, and it'll stay that way based on the Q3 guide. Amazon said sales this quarter should be betwee

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8 thoughts on “Amazon Rakes In Revenue, Apple Enriches More Lives

  1. AMZN report was v good, esp margins, AWS growth (+12% v cons +10%/feared +SD%), NorAm rev +11% (cons +7%, consumer holding up), advertising rev +22% (far above GOOG/META). Guidance intriguing in a good way; hard to get mid-pt of rev guide without AWS ok or better (my opinion). Jassy talking the desired talk: efficiency/margins, lower capex, AWS stabilizing, AI AI AI.

    AAPL report looked meh. iPhone miss, Services beat, Mac/iPad down hard, Wearables flat, GM% up from Services boost. Guiding Sep qtr rev YOY similar to Jun qtr’s -1.4%, FX headwind 200 bp less – so constant currency growth decelerates? Working the segments vs Sep qtr rev and GM% guide, it is hard to see iPhone upside and easy to see downside (my opinion).

  2. H, I recently saw the movie “Oppenheimer”- which I highly recommend.
    Having never met you and only knowing what you have chosen to tell us; to me, you seem more akin to Oppenheimer than Heisenberg. Oppenheimer was not only an intellectual who was capable of building a nuclear bomb; but he was also philosophical about himself and what he had done.

  3. The “more cost effective to train and run models” is an interesting one! As part of that I think he means bc you can spin up resource intensive VMs as needed and terminate them or stop them when you’re done. But, at least for GPU based workloads I am finding it harder and harder to get available GPU VMs, and I have been wondering about what will happen with that. Maybe companies will start to buy a bunch of reserved ones upfront for years. Or maybe some will just decide to leave a subset of static ones up all the time. It can be pretty frustrating to get the “no available capacity” errors! I have been wondering about how that will turn out especially as I see such a huge influx in cloud based gpu node demand on my side. You would think that will start to impact earnings and customer cloud provider preference.

    1. Thanks. That real life Intel is very useful.

      I’m wondering how many firms (Actual users/customers!) really need to run LLMs on huge databases including 25 years of weather data in the Andes and attendance at AA Baseball games in the US over the same period when they simply hope to fine tune their automated call center applications.

      Now we are starting to read more about how edge AI on chips from Intel and eventually AMD may make much more sense than loading up on racks of $35,000 NVDA GPUs designed to run LLMs.

      Whodathunkit?

      1. From a trading perspective I always wonder about the numbers getting calculated and how the team decides if it’s worth the cost of generating them. For example, for Trading Team A if their dashboard doesn’t update that morning with newer versions of those numbers in some way it impacts their trading decisions negatively. But, I don’t know how they assess that quantitatively (despite the fact that they’re all insanely good at math!). Which is to say I don’t know how they assess how much less money they’d make trading that day compared to the costs of running so many compute intensive processes to generate the newer version of the numbers that informed their trading decisions

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