Here's a pretty impressive demo.
https://www.youtube.com/watch?v=SGUCcjHTmGY
I think they said it handles something like 37% of requests.
Btw, don't watch it if your worried at losing your job to a computer.
https://www.youtube.com/watch?v=SGUCcjHTmGY
I think they said it handles something like 37% of requests.
Btw, don't watch it if your worried at losing your job to a computer.
I am also looking for reasons not to be worried!
In the last years "AI" started to make surprising leaps every few years. What we got now is the "child of a new species". It's still a child. But it can grow. The species we are seeing scares me, as an overpaid codemonkey. I can compete with a child of it, but I could not compete with an adult of it. Imagine this system, but more advanced, more tuned to your specific domain.
The systems we work with are all trapped in mind boggling complexity, but what if AI starts to untangle this, what if AI starts to truly become the only human-machine interface to produce software?
As AI becomes more advanced it becomes harder to understand and then control. Everything that isn’t AGI is still easy to control.
My vision would be a brain computer interface, which lets you perceive the data processed by the AI and so on like you’d perceive sounds or colors. It would be like synesthesia where you perceive multiple modes of qualia correlated with together.
You’d have an extremely high level “programming language” using your thoughts, the brain computer interface automatically interprets that to machine instructions.
In this scenario the AI doesn’t become a human machine interface. The AI is the machine and the brain-computer interface is the human-machine interface you described.
In theory you could use this to access cloud compute and delegate tasks to machines like you would today with a computer. I suspect this will help us compete with and survive artificial general intelligence.
I always think of the example of supermarket cashiers. Formerly a fairly skilled job but now merely providing cheap meat-robot manipulators for a scanner. The person is still there but has a job concentrated down to the few things a person does better, and those things aren't always the fun things.
Look at your work as a craft, invest time into getting incrementally better and you shall know no fear.
Coders are always climbing the learning ladder and should add co-working with a code-writing AI to their toolkit, especially if it truly is 'open' (CoPilot will be a paid service I believe?).
The long term possibilities for eliminating many types of labour seem enormous. It is not so easy yet to understand what forms of labour will be not only resilient in the face of this developing tech, but even 'antifragile' to it. If these are few (could by definition be an oxymoronic assumption), how will the relative returns on labour vs returns on asset ownership diverge? Will a fundamental revision of socio-economic systems be required?
It depends on what you mean "early days". If it's about Codex itself, then that's probably right, it's a new-ish system. However, the task of creating a computer program by another computer program, variously known as "automatic programming", "program synthesis", "program induction", "inductive programming" and so on is not new, rather it goes back to the 1970s and probably earlier still. Very briefly, these terms describe a constellation of approaches that automatically create a program according to a specification.
Placing Codex in the context of this earler work, it is an example of program synthesis system that composes programs from incomplete specifications, variously given as natural language specifications or what we can call "code snippets" (i.e. you start writing code and the system completes it; I don't know the propper term for this kind of specification). As such, it is one in a long line of systems that predate it and it is not even the most impressive of those systems (37% accuracy is nothing to write home about).
The reason that you misidentify it as something new, by your "early days" turn of phrase, is a peculiar tendency of deep learning researchers to ommit any references to relevant prior work, for reasons that are difficult to discern. Sometimes the reason seems to be honest-to-god lack of familiarity with other approaches than deep learning (even other neural networks approaches). Sometimes it seems to be more of an attempt to claim well-trodden territory as brand new and trumpet a small step forward (or not even that much forward) as the breaking of new ground. Sometimes there seems to be an attempt to avoid unwanted comparisons to different approaches with different trade-offs, that could make the deep learning system look more lackluster than desired.
In any case, there you have it. Codex is not any kind of breakthrough or innovation. What is new is the sudden interest in program synthesis. Perhaps this is a positive thing and program synthesis approaches will finally begin to be adopted in the industry. But knowing how these things work, and how what gets hyped and what doesn't is altogether without any rationality, I'd guess probably not.
The real problem facing our elites will be how to both control their immiserated and angry population, and the AIs now running most of the economy.
I propose cyborgization for such people and will advise the rich people I know to invest in brain computer interfaces and related tech.
We are going to have to think long and hard about the social contract we live under.
How do we deal with never before seen unemployment rates? Is liberalism able to cope with that? How do we stop something much worse from exploiting the coming automation crisis?