dilippkumar

Can someone explain why git is insufficient and how got tries to improve upon it?

> I am having a hard time understanding why this is a useful way of thinking about equity investment. In the most common case i.e. in secondary markets, you aren't giving the company any money by buying stock. And in the most common case you don't want the company to return the money.

I don’t know how well this translates to different people with different approaches to life and investing styles, but here’s my thoughts on it.

If you want to start with first principles and understand how to invest, you need a foundational model to start building theory on.

Modeling investing as a loan made to a company where the company can choose to not return money at all comes with all sorts of nice properties. The first question you ask is “if I give them money, will they eventually be able to return it?” which will make you look into their business and figure out how much money they need to make to pay you back and when they can pay you back and who else they need to pay back and ultimately how much paying everyone back will cost them. Share buybacks then look a lot like companies paying back some investors and dividends look a lot like interest payments. This is fits very cleanly into all sorts of other models we have today.

Take a look at a plot of number of outstanding apple shares over the past 15 years. It’s abundantly clear that they’ve been “paying back” consistently over time. If that were a person looking to borrow money, you would happily lend money to them!

Take a look at American Airlines. They have a monumental amount of corporate debt and then they need to pay $10B back to all share holders. They were “paying back” their share holders at a steady clip until around covid and then they had to “borrow” more from investors and doesn’t look like they’re ready to go back to “paying” back just yet.

Obviously these are very unsophisticated models. But as a simple approximation, they work really well (for me).

If I were to go to a VC and “borrow” money from them, it’s very helpful to think about how much I can pay them back - it’s super easy to model that like borrowing any other amount of money.

And ultimately, it really does function as a loan from the investor’s perspective. You give away money to an entity expecting to get back that amount and then more. If that entity goes broke, you will not get your money back. If that entity does really really well, they can pay you back a lot more money and so on.

> However, I have been struggling to come up with business ideas.

My email is in my HN profile. Shoot me an email, I’m happy to share my worksheet in exchange for feedback.

You are right that it does muddle definitions. However, in this case, it actually helps to squint and see a blurry picture to get a better sense of the bigger picture.

Unless you are buying enough of a company to get access to a board seat, you effectively have zero control over a company. Buying 1 share of Google gets you such an insignificant fraction of a company.

Yes, buying shares is theoretically equivalent to buying an ownership into a fraction of the company.

But that’s not actually a useful model. Asking “do I want to give money to this company that they may choose to never return?” helped me understand a lot of what investing really was much much better.

A couple of books here.

1. Caesar by Adrian Goldsworthy.

This is a biography of Julius Ceasar. There’s a story in here about a teenage Ceasar, with no institutional authority and effectively a student at this point, raising a navy to go capture pirates who had previously kidnapped him. I spent many years thinking about influence without any authority after reading this story and it’s probably had a significant shift in how I see the world and my role in it.

2. The WEIRDest people in the world by Joseph Henrich

I grew up in India. This book helped me understand so much of the cultural differences between American culture and what I grew up with that it is easily one of the most valuable books for any immigrant or anyone from America who has to work across cultures.

3. Debt - The first 5,000 years by David Greber.

The single most valuable thing I took away from this book came pretty early in the book - Buying stocks in a company is effectively loaning money to the company. This book shifted my perspective significantly- I use to see the world as a network of power relationships. Now I see the world as a network of debt relationships. I can not recommend it enough.

100% compliance achieved.

The Taylor Swift episode on the Acquired podcast actually does a fantastic job of explaining how this works and why artists barely make money on streaming services - as opposed to radio broadcasts for example.

> In 2018, the city created a pooper scooper team, each member of which received annual compensation of about $211,000 that year. Given the inflation that has occurred since that time, scooper compensation may be close to $250,000 per year today.

I needed to read this to convince myself that I’m not asking for or expecting outrageous compensation at work.

ew.reddit.com is even better.

Tangentially related question:

Do we think dark matter stars, black holes and supermassive black holes exist?

Can anyone in the know share details on when arm servers with CHERI extensions can become generally available to developers and for deploying to production?

What’s the current consensus on how this rollout and transition is expected to happen?

How far does this analogy go?

For example, if I plot how long both programs take at various scales, at some point I should be able to determine which one is O(n log(n)) right?

Is the efficiency gained by capturing it from a stronger concentration enough to offset the costs of building pipelines?

Why not burn wood in a room near the destination site and get extremely concentrated CO2 right there and capture that instead?

Are pipelines somehow even more economical than that?

Ummm. Dumb question here.

Why do we have CO2 pipelines?

Wouldn’t it be cheaper to capture CO2 from the atmosphere at the location where the CO2 was needed?

Why does OpenAI not address this concern directly? I’m sure it’s better for both Apple and OpenAI if there was a business agreement to not use their data.

I also want to point out that there’s also the extreme-crazy option that is Gentoo linux.

All packages are distributed as source and compiled on the destination machine before being installed there. And yes, you can modify build flags per package to enable/disable compile flags.

I recommend doing it for fun. It’s a crazy world.

Actually, it has not. There have been 0 advertisements on WhatsApp for me.

Also, half my friends have migrated over to Signal anyways, advertisements on whatsapp will just speed up that transition I suppose.

> Then he did it again with WhatsApp.

As an outsider, it hasn’t been clear that whatsapp has generated any meaningful amount of cash flow 9 years after acquisition.

For a price tag of $19 billion, I’m not sure how to see this as a win.

I wonder if it’s time to start seriously looking at why some people have completely embraced copilot/chat-gpt and others can not get it to work at all.

I’d love to see which of the following might have any correlations with reported usefulness of chatgpt/copilot:

1. How articulate a person is.

2. How much of an expert they are in what they are trying to do with the tool.

3. How successful they are at giving instructions to a human to perform the same task.

4. How much experience they have managing/coaching junior devs/interne/newbies.

5. How much experience someone has at decomposing a problem into smaller parts and identifying the simple parts and complicated parts

There are huge consequences to either answer to the question: “Is using an AI tool effectively a coachable skill?”. I’m sure someone has already looked into this or is looking into this - if it turns out to be a coachable skill, and we can identify what those are, there’s a lot of money to be made in bringing a coursework to market.

That’s fascinating!

Where can I read more?

Any demographers in here?

I wonder if this has anything to do with the baby boomer generation all hitting retirement around now, and the incoming cohort being smaller than the retiring cohort.

I’m stealing this excellent phrase.

Generalizing the question a little in case someone passes through with an answer:

Why should a couple of hackers working out of the proverbial garage building the next unicorn consider IBM as their infrastructure vendor?

What are their offerings? How do those stack up against the defaults of aws/Azure + Linux + Postgres/MySql?

Assume said hackers are broke.

> Isn't it an inherent problem with phones that if they are left on charge forever that their battery will explode?

Not necessarily, it depends on how much care went into making the phone.

Ever since Samsung had the unfortunate experience of having every airline announce that their phone wasn’t allowed on board (even when switched off), battery management has received as much attention as is possible. Most implementations today have multiple fail safes in place to prevent the chances of a battery exploding.

Today, several extremely improbable events must happen in a row to make a battery explode from just being connected to a charger 24x7.

Source: Implemented battery charging on a different Lithium Ion battery bearing consumer product.

I genuinely did not know this. Thanks for sharing!

Two books that specifically address your question with very different answers. Both books are completely worth your time reading.

1. The Innovation Stack: Building an Unbeatable Business One Crazy Idea at a Time by Jim McKelvey

This is a founder of Square talking about how he survived Amazon entering the market with a copycat product. He also uses examples from other companies that survived competition using similar techniques.

2. 7 Powers: The Foundations of Business Strategy by Hamilton Helmer

This book is a collection of 7 different types of “moats” that can exist. The authors claim (if I understood them correctly) that this list is exhaustive - there can only be these 7 types of moats to protect a business.

> 10 years

From the Congressional research service's report on immigration backlog [1] (note: this was before covid), for applicants from India, the projected backlogs for various employment-based green card applications applying in 2020 were:

    EB-1: 8 years.
    EB-2: 195 years.
    EB-3: 27 years.

Projecting out to 2030, the report says (for Indian applicants):

    EB-1: 18 years.
    EB-2: 436 years.
    EB-3: 48 years.

I performed a linear extrapolation using the 2020 and 2030 estimates. Two points and a straight line through them gives:

         eb-1 eb-2 eb-3
    2024 12   292  36
    2023 11   268  34
    2022 10   244  32
    2021 9    220  30
    2020 8    195  27
    2019 7    171  25
    2018 6    147  23
    2017 5    123  21
    2016 4    99   19
    2015 3    75   17
    2014 2    51   15
    2013 1    27   13

All numbers in years. The numbers are rounded up to the next highest integer. Note that a straight line through these two points isn't necessarily the correct model but whatever. Also, the covid era immigration policy moved a bunch of dates around, so this may not be as accurate. But it is still the best numbers I could find.

In any case, it is reasonable to assume that anyone with a priority date of 2017 or so will likely retire before your priority date is current.

You (and me) will probably spend an entire career paying for social security and never be eligible for it.

[1]. https://crsreports.congress.gov/product/pdf/R/R46291

This is the script used to talk to the coffee machine:

https://github.com/NARKOZ/hacker-scripts/blob/master/fucking...

I wonder how many other devices talk telnet and have a weak password. Would be cool to have a database of such models.

> According to Tindell and Tabor's research, the attack, called CAN (controller area network) injection, works by sending fake messages that look as if they come from the car’s smart key receiver, the research continues. The underlying issue is that vehicles trust these messages without verifying them. Once the thieves have accessed the necessary cables by removing the headlights, they can use their device to send these messages, it adds.

I have to ask - does the automobile industry hire from a different pool of systems engineers than the usual pool I’m used to interacting with? It seems like everyone I know would say “obviously you should verify that the security mechanism first”.

Or is this a result of how the automobile industry is structured and what is outsourced to vendors/suppliers and what is done in house?

I’m not going to be buy that this isn’t solvable for a technical reason at this point. We have had a lot of experience dealing with PKI infrastructures and zero trust architectures in other parts of the industry.

Thanks.

The Nadir vector moved more “right to left” than “down to up” in that video, but the velocity vector is very clearly pointing just “downwards”.

Is this mostly because of the velocity of the camera bearing satellite w.r.t the imaged satellite and earth?