251–260 of 392 posts
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>AI is linear algebra that costs x1000 because of the brand name. Sure, but we've learnt to apply linear algebra to achieving things we could only dream of 10 (or even 5) years ago.
Current AI is still mostly trash of the high school level project quality, linear algebra taken to the absolute possible level of insanity.
It has always been mindboggling to me that startups are still so all in on the Bay Area. Most problems mentioned in the article go away if/when you are willing to staff developers in an area that is not as ridiculous in terms of cost of living as the Bay area. According to StackExchange data, the 50th percentile pay for a Full Stack Developer with a Bachelors degree and 3 years experience (a profile that would seem r…
That $140k number might be a reasonable 50th percentile for what a junior engineer would make at a startup in the Bay Area, but compensation can increase quite a bit after several years in the industry, especially for engineers who move to large companies which give stock compensation. They will far outpace the earnings growth of engineers elsewhere.
It's much easier to achieve that kind of career trajectory in places with high concentrations of tech companies, e.g. the Bay Area and Seattle.
I've had a related discussion with a few VCs in recent months. Some kinds of startups are effectively impossible to build given current structural constraints on financing them, creating an adverse selection for startups that fit the classic model rather than startups with the highest expected ROI. Broadly speaking, engineers will work at a discount to market-clearing wages of maybe 20% if they really like the startu…
I generally agree with this, except I would change "impossible" to "exceptionally hard." You're right that a lot of startups innovating on deep tech need to hire people who would earn $500k+ elsewhere, and that a typical startup can't afford that.
However, very exceptional founders can often raise unusually large rounds early on. I.e. some founders can raise a $10m or $20m "seed" round at inception, which allows them to afford to pay $500k salaries. It's the top 1% or 0.1% founders within their fields, but it is possible.
(Source: I'm a VC)
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This is a good summation of the current challenges with startups that are attempting to compete on technical merit. I know this first hand as I started a computer vision company right around 2012 when the "AI" boom was really picking up steam. I would never dream today of starting a very technical company because every major will poach your talent (happened to me), invest in your competitors or attempt to acquire you…
> I would never dream today of starting a very technical company because every major will poach your talent (happened to me), invest in your competitors or attempt to acquire you (some people don't want to be acquired). Damn, this is exactly what I want to do. Computer vision too. Do you have any advice other than "don't"? Would basing the company on the East coast near a tier-1 research university help with talent?…
I think the answer is, know exactly how you want to exit before you start and plan for that. Realize also that is 180 degrees polar opposite of how the major VC's want you to approach it - so if you wanted institutional money from Sequoia etc... they won't invest if they know that is the case. There are a lot of good reasons why they take that approach, power law and all.
The reality is, your best case scenario is most likely an acquisition. Which might be exactly what you want, and if so absolutely go for it, but you need to really understand how and why and when the companies you are targeting do their acquisitions. This is incredibly hard to do if you haven't gone through multiple acquisition Due Diligence processes before, but I know of people who have repeatedly done this, so it can be done.
As to the other points, there are too many variables to say whether those are good ideas or not, totally depends on what you're trying to do.
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> Kubernetes is a solution worse than the problem. Not if you're a 1,000+ engineer org with an SOA. > Microservices are unix pipes but slower. Humans are way more expensive than the machines running our code. You can always spend more on spinning up additional instances. In reality the overhead isn't that bad. The principles of immutable stateless deploys free up so much mental energy when it comes to thinking about…
>Not if you're a 1,000+ engineer org with an SOA. That's the problem. With a sane simple architecture instead of 40 years of crap on top of crap you wouldn't need thousands of engineers to spin up instances. >In reality the overhead isn't that bad. Over 1e2 times if the solution is in software, over 1e5 times if it's an fpga. Around 1e8 if you do it in silicon. You make the savings from not hiring the 1000s of engine…
It's all new.
> wouldn't need thousands of engineers to spin up instances
If thousands of engineers had to worry about deploys, that'd be a problem. The deploy team is small. K8S makes this dead simple.
> Over 1e2 times if the solution is in software
That's ridiculous. Where did you get those figures?
> 1e5 times if it's an fpga. Around 1e8 if you do it in silicon
If you're writing code for FGPAs or burning it to silicon, you're far removed from application server development. That would move at a glacial pace.
> bloated horror
Our containers are thin.
> Has nothing to do with k8s.
You're just hating on k8s at this point.
> Like everything else you listed there this is a hardware improvement.
Kubernetes. :P
Honestly there's been a metric ton of software improvements. Literally everywhere.
Git, modern kernels, Rust, Paxos (popularized in the 90s), LLVM, modern game engines, tmux, Wikis, bittorrent, blockchain, protobufs, gRPC, Bazel, Redis, modern PL idioms, futures, TOTP, U2F, Markdown, RSS/Atom, so many algorithms, seam carving...
Personally I work for startups, but only because they let me work remotely, something I wouldn't be able to do at any FAANG. I would only go back to an office job to work at a FAANG, since compared to a startup the money, "exit ops", work life balance, and job security are probably going to be way better.
If startups want to be more competitive and have access to more talent, then they'd be wise to open to hiring remote workers. Otherwise they're going to struggle to compete with FAANG type companies. Remote is the one perk that FAANG companies don't offer, and unfortunately probably won't for the foreseeable future short of some serious cultural change.
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> Kubernetes is a solution worse than the problem. I disagree. Maybe it's because we haven't gone "full Kubernetes" where every cronjob is now a Kubernetes cronjob, or what have you, but for all the complexity we've had to overcome, we've seen substantial benefits. For example, autoscaling instances of my data pipeline apps based on Kafka lag. Was it complex? Yes. We had to expose Kafka topic lag as a metric to Prome…
How much data do your "data pipeline apps" process with Kafka, Kubernetes and probably other K-named things?
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$1M is not FU money for someone in a major metropolitan US city with kids.
If someone doesn't hit FU at $1M in the bank, you probably never will, which is ok. $1M is about 20 years of coast on a modest bay area mortgage + family healthcare.
To me, FU money is passive investments which yield a couple hundred thousand a year from businesses that can keep up with inflation.