Automating software tasks is an entirely different skillset than building a Machine Learning model for automating something like driving. Automating software tasks involves slowly documenting and analyzing each best practice, finding what is repetitive and creating scripts/pipelines for those repetitive tasks. It's not AI based it's more a bunch of if else statements that you slowly build over years. Even if the skillset was the same and Elon brought on one engineer for every tech employee at Twitter it would still take months if not years of documentation and slow replacement to make up for the kind of skill drain that has happened at Twitter over the past two weeks. Nine women can't make a baby in a month and all that

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Well, I myself am a developer and familiar with CICD and devops etc. If you approach the problem from automating those things, I'd have the same take as you. However, if you approach the problem as automating the actions of the engineers themselves on their machines, it becomes a totally different problem with some machine learning solutions available that closely resemble the ones you can use for self driving. For instance, large neural network architectures.

Karpathy has said that while at Tesla they had been working on AI that would autopilot computers at the mouse and keyboard level. He talks about it in the Lex Fridman podcast he did

Guys why does this comment transpire wishful thinking

Even with the farthest stretch of the imagination as to what the ML researchers/developers at Tesla are capable of you would still need a significant amount of data on the tasks that need to be automated. If entire teams are laid off how will their tasks even be explained to the model let alone demonstrated enough times for the model to understand?

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But seriously, did they need 8000 people to run twitter?

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definitely not, in my opinion. most companies are like that, some worse than others, but I'm not convinced it's an overall bad thing for society as a whole. everyone does ultimately need to work and the alternative is further lining the pockets of shareholders with increased profits. employment seems better

the only way it could work is through natural language description of the jobs, maybe training against internal documents. it's not outside the realm of possibility at all, although admittedly doing something this large in such a narrow time window seems very implausible

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This is vaguely possible eventually but as you know DevOps is incredibly fragile. You can't just get close you need the exact correct commands to merge repos, build the codebase, run unit tests etc.

This isn't really automatable with current or plausible future AI ML tech. Note I do work in AI, have also done some DevOps, and am very enthusiastic about AI/ML for task spaces where the goal is clearly defined, the task environment can be adequately simulated, and performance is differentiable.

For example a robot moving boxes in a warehouse fits that criteria. It's relatively simple what the goal is and what not to do, and expressible in a robust sim. DevOps has many many subtle consequences and you need the solution to get every relevant detail right.

Software that code translates from one language to a faster language without loss of correctness is also possible a similar way.

Fuck off, musk is a con man and a bigot

They weren’t there for long enough to do this. Are you familiar with how long it takes to even train large models?

Its an interesting idea for the future, but not realistic in the slightest for the present.

The reality was that tesla engineers use a similar tech stack to twitter. So elon pulled them over to help him gauge how best to reduce the twitter employee count and also get a general idea of what the twitter code base looked like.

I would assume that if this could have been automated, Twitter engineers would have done so by now and potentially open sourced a relevant solution. Having engineer bloat does not indicate overlooked engineering opportunities, and none of us knows the technical debt at that company.

I argue that this would have been automated already simply because it's a big opportunity for Productization, and thus a revenue stream, if it would work. A common argument that the engineers wouldn't want to automate because they would automate themselves out of a job is not one I've seen hold water in the real world. Engineers like to solve problems, and hundreds of engineers deciding not to automate is not plausible.

Any company as old as Twitter is also going to have a nasty codebase with old ass code that's held together with gum and tape. All that would need to be refactored, based on my experience, to cohere with a novel solution to automate what was previously not automated. This is a nightmare no company tackles except in trickles here and there.

With the lack of actual innovation at Twitter for many years now, the tech can probably run on around 200 dedicated employees. Few dozen devs, dozen or so dedicated qa engineers and a dozen infra/ops/automation experts, some chaos testing and security engineers, handful of product managers, scrum masters, some tech support.

people already know this. plenty of apps and what not are built by a team of engineers and those engineers are never used again until they want changes made, improvements, new features, bug fixes, etc. did twitter need all these engineers? it was obviously making enough money to keep them on staff or it wouldn't have them. you'd rather that money go to executives and shit like that? this isn't anything new. musk isn't traversing new ground. of course once an app is done few engineers are needed.

It's a website to post messages that aren't even a paragraph each. A dozen people could maintain that code base with proper knowledge and documentation. You only need manpower if you want to alter things or add features.

They have already scaled out, twitter is refreshingly open about their tech and historically a big player in open sourcing some of their concepts

It's one banana, what could it cost, $10?

they wouldn't need to train an entirely new model, necessarily. they have been working on a model which controls interfaces through mouse and keyboard based on natural language instructions, according to Karpathy. Such a model may be designed to work on fine tuning, or few shot learning

ok? I don't disagree? Why the hostility to me?

this is just patently wrong. engineers "never get used again" until new features are needed? Do you have any idea what an on call rotation is? Prod issues? Critsits?

I don't necessarily think this is the case simply because Twitter isn't exactly a hub of innovation. They did have a machine learning program, but nothing on the scale of Tesla or OpenAI.

yeah, i only have 20+ years experience, genius

entire teams are hired to create a product and then not used again.

What you are suggesting basically means they have software agi (not sentient)

I think your partly right... but keep this in mind... infrastructure projects can take years sometimes. But when cities/companies have budgets that are unused and must be spent by a certain time we watch amazing things happen lol. In my city we watched a 2 year Bridge project be finished in roughly 90 days because they had to spend the money by a certain time lol. I know my analogy is low level compared to working on the things you are talking about. But I can't help but think that Twitter was on manual autopilot... you would be amazed what motivated humans can do... I truly think the employee model of the future is not a set time of work hours. Example 9-5... 70% of the employees time is wasted passing time.. most people could finish a day's works in 2-4 hours if there was enough incentive, ie being able to go home when they are done their work. I totally think it will still take a long time to automate Twitter but might be alot faster than we think.

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yeah, that is what I'm saying.

He doesn't handle any of that though, he hypes things up for investors and whines on twitter when his beloved free market is doing its job for once. Not to mention the sexual assault allegations, he and his father's weird obsession with breeding (in a eugenics sort of way, based on how they talk about it), and just all around bigotry.

That's unlikely

yay tech debt

fair enough. it is unlikely. I'm an optimist I suppose

edit: dat name 🤨

well yeah, that's the point isn't it? the question is whether you have a full time staff squashing the debt as it's acquired, potentially wasteful, or you hire a team to come back in once the debt accumulates enough that it becomes a problem then send them off again.

arguments can be made for both positions but it's certainly not anything new.