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rnimmer t1_iwvlk7a wrote

Reply to comment by ProShortKingAction in Full Self-Driving Twitter by [deleted]

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

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ProShortKingAction t1_iwvoojk wrote

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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rnimmer t1_iwwdvna wrote

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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pandasashu t1_iwx7h7d wrote

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.

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rnimmer t1_iwyfeaf wrote

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

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X-msky t1_iwyvkym wrote

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

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rnimmer t1_iwzmyis wrote

yeah, that is what I'm saying.

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X-msky t1_iwzoph5 wrote

That's unlikely

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rnimmer t1_ix061es wrote

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

edit: dat name 🤨

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SoylentRox t1_iwwq5w1 wrote

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.

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