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Prediction market?

> you also understand what the point of the interview is

Exactly, it's also a test of ability to conform. Especially useful to weed out rogue behavior picked up in startups.


No, the point was to demonstrate how you’d design a complex system.

If a valid answer was “just use Postgres” then it just wasn’t a very good interview question.

In real life, the answer almost certainly would be “just use Postgres” and everyone would be happy.


No, it was a perfectly fine question IMHO. it is a broken incentive - it is expected that you design complex systems regardless whether they are useful or not. Try to interview for the role you have to fill, nor for a role you a dreaming you would love to have whenever you're Google2.

If the interview wants you to think about stuff that never happens in your role, I think it is a sign that in your role, you're expected to solve the problems like in the interview.


> any time our instinct says "don't build that, it's not worth the time" fire off a prompt anyway

I disagree with this sentiment. This approach leads down to huge maintenance burden.


In context, this bit is about how to deal with the fact that our intuitions on what's worth it vs not worth it in terms of the time it takes to build are likely out-of-date with these new tools:

> For now I think the best we can do is to second guess ourselves: any time our instinct says "don't build that, it's not worth the time" fire off a prompt anyway, in an asynchronous agent session where the worst that can happen is you check ten minutes later and find that it wasn't worth the tokens.

This shouldn't lead to huge maintenance burden because most of the time you'll throw away the result. It's a learning exercise.


I think I misread this as an encouragement to pick up work out of order w.r.t prioritization.

That coding got cheaper shouldn't change prioritization post planning. It should definitely factor into prioritization at planning time.



> Was it in danger of being knocked down?

Abolishing the listings mechanism in favor of an ad-hoc protection mechanism (when destruction is imminent) seems worse.


> It’s kind of crazy that they have been slow to create real products and competitive large scale models from their research.

I always thought they deliberately tried to contain the genie in the bottle as long as they could


Their unreleased LaMDA[1] famously caused one of their own engineers to have a public crashout in 2022, before ChatGPT dropped. Pre-ChatGPT they also showed it off in their research blog[2] and showed it doing very ChatGPT-like things and they alluded to 'risks,' but those were primarily around it using naughty language or spreading misinformation.

I think they were worried that releasing a product like ChatGPT only had downside risks for them, because it might mess up their money printing operation over in advertising by doing slurs and swears. Those sweet summer children: little did they know they could run an operation with a seig-heiling CEO who uses LLMs to manufacture and distribute CSAM worldwide, and it wouldn't make above-the-fold news.

[1] https://en.wikipedia.org/wiki/LaMDA#Sentience_claims

[2] https://research.google/blog/lamda-towards-safe-grounded-and...


The front runner is not always the winner. If they were able to keep pace with openai while letting them take all the hits and miss steps, it could pay off.

Time will tell if LLM training becomes a race to the bottom or the release of the "open source" ones proves to be a spoiler. From the outside looking while ChatGPT has brand recognition for the average person who could not tell the difference between any two LLMs google offering Gemini in android phones could perhaps supplant them.


I swear the Tay incident caused tech companies to be unnecessarily risk averse with chatbots for years.


Attention is all you need was written by Googlers IIRC.


Indeed, none of the current AI boom would’ve happened without Google Brain and their failure to execute on their huge early lead. It’s basically a Xerox Parc do-over with ads instead of printers.


> Computer science has been advancing language design by building higher and higher level languages

Why? Because new languages have an IR in their compilation path?


This touches the toupet fallacy: "I never saw a large company fail to grow large because of deferred scaling"

Friendster might fit though: https://highscalability.com/friendster-lost-lead-because-of-...


Even that would be wrong. Von der Leyen was strong armed into her position by Merkel and the other heads of states, overruling Timmermans nomination.


Isn't every AI datacenter chip manufacturer critically dependent on EU (ASML)?


Sure but the US isn’t vowing to eliminate all dependencies on EU goods. (Just burning all their good will.)


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