I talked with former Twitter engineers who worked on this code and they said that while the open sourced code is in prod, the *majority* of the recommendation prod code is not published.
It’s also not the actual prod code, just a new repo created.
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In the UK, salaries need to be advertised for positions and the below listing is making the headlines. It’s the Head of Cybersecurity *for the British Treasury* offering £57K.
As comparison, I made £65K as a developer with 2 years of experience in London: more than 10 years ago.
The nice thing about salary transparency is that job adverts like this - offering a third of the going rate for such an important role, demanding significant & hard to get experience - will get the mocking and media attention it deserves - and it does!
What if someone took this diagram, measured the size of the pixels to track back the amount paid out per month, and extrapolated Substack's revenue (10% of this)?
I confess: I did this. Here's the numbers, using pixel measurements from the image below:
To prove that data visualization is an art, you probably look at the above chart thinking "well that's not very fast growth." Month on month: sure.
But let me share the exact same data, visualized annually.
From 2021 to 2022, rev grew 67%. 214% the year before!
Same data:
An interesting observation: revenue jumps in every January! I assume this is because of this being the time for many people to sign up for an annual sub? Or who knows. But it's noticeable.
All data might be incorrect to some extent ofc, as it's based on me measuring pixels.
After I wrote my analysis on Lyft yesterday (that I see several signs for concern), I got a surprising amount of messages assuming I must have a stake in eg Uber.
I'm now glad I had an ethics policy since starting to write @Pragmatic_Eng. This policy is still the same:
Of course, I will naturally have biases based on my past experiences (where I worked) or financial interests (how I make money). I do the best to acknowledge these, share what these are, and to counter them.
DoorDash has a market cap of ~$24B w $6.5B annual revenue in 2022. #1 food delivery app in the US.
Lyft a market cap of ~$3.4B w $4.1B revenue in 2022. #2 ridesharing app in the US.
With Lyft trading under its market cap, there’s now a question that was not realistic before:
Would it make sense for DoorDash to buy Lyft while it’s trading at a discount, with the goal to eventually become the #1 food delivery and ridesharing app in the US?
There are a lot of questionmarks here, mostly because both DoorDash and Lyft are losing money - for now.
But any company with a market cap below their annual revenue can become an interesting acquisition target: esp with a buyer who expects to be able to operate it with more efficiency (leveraging their existing business).
Don’t forget Uber paid $3.1B for a much smaller Careem!
Let's assume that LLMs and "AI" *do* make white-collar workers much more productive and reduce the barrier to this work. What happens then?
A potential outcome: professions that cannot be automated with sw increase in value more.
E.g. construction, plumbing, gardening etc.
For decades, people took longer time to study to have better earning opportunities: college jobs paying much better.
But what if the trend changes? LLMs and "AI" looks to be a massive productivity gain with knoweldge-based professions. But makes no dent with physical work.
In the replies: "automation will come to construction work as well."
Well, I see none, at least for eg house renovations. Try replacing a cracked tile in a house, or put in a custom-made smallish cabinet: the time, effort and cost are surprisingly high.