It's true that in a project, a novel idea undeclared as such will be shaved off quietly by an llm. You really need to be explicit about wanting to keep it.
You will get pushed into the mean.
However, I'd say 90% of making something (that is useful) is repeating the old thing. We stand on the shoulders of giants. Or at least we should. Getting there can be difficult for most of us.
I say this as someone who chronically re-invents things. I then later get stuck and find someone already thought through my problem and solved it better.
I don't believe being unique in all the ways is useful. You need to be unique in the important ways and not unique in the other places.
There's also a cultural coherence angle that (my) unique things often fail at. Stuff has to look like other stuff enough for people to understand intuitively what it is and how it works. Here the mean is your friend.
I am able to explore more unique spaces because I no longer deal with the minutia of getting the things that should be the same correct. So paradoxically, this has made my output more unique.
As long as I've been an adult, hardware was a commodity, and software was where the value was. Software could capture most of the value that was in the total supply chain.
Now, with AI, software becomes less able to demand the margins it once did.
Meanwhile, the history of low margins of hardware have created a situation where there are so few players able to demand now software-style high margins.
Hardware has always been valuable but was unable to capture it's value. Those days might be over.
I hope this encourages people who would build software companies to look to hardware. A lot of fun challenges there. Deeply technical, interesting ones. And now solutions will pay.
Like all good regulation, it would only kick in after a company has a large reach. So as to not snuff out startups and cause regulatory capture problems that are already so common.
Telling big companies to be transparent about their suggestion algorithms would not be hard. I think governments already do this? wasn't that a tiktok thing in the US? Anyway, it's well within government's reach.
Telling companies to only use signals that people consciously give seems like a no-brainer.
Well, I mean, if you believe that a goal of civilization is to respect the free will of individuals up until the point that that free will becomes a problem for other people.
The alternative is something less than respectful of human dignity.
Engagement metrics fed into recommendations algorithms are the paperclip maximizers that feed humanity's collective poison.
Europe should do the one thing it knows how to do: regulate. For once, it is the answer. Do it only there. The rest of the dominos will fall.
Making a european branded humanity poisoner is not the answer.
Specifically, regulating against silent signals like watch time and comment count. Upvotes/likes can serve a purpose and would not cause the situation we're in now.
I feel the same way as you. But was unfortunately not surprised to see the replies you are getting here.
There are a ton of opportunities available right now to make new things. And make them better, more customizable, and more sovereign.
To the replies: be the change you want to see in the world, guys. That may be trite but focusing only on the negative will just make your own life shitty.
With my own tiny company, I used to answer questions about my code to support. Supporting the support. I remember doing that when working at big companies too.
Now, my support asks claude about the codebase to answer those sorts of questions. He's better than my memory.
Software devs lost their pricing power due to LLMs but not exactly how most people think.
What's missed in understanding is 'how exactly does this functionality work for this specific case?' or 'can we implement this tiny one off feature in some legacy code base'. Both things are why you keep the guy that wrote it around. And you couldn't really replace him. Because digging into what he wrote was hard.
Now, LLMs can do that stuff better than the guy that wrote it.
Software devs were non-fungible. Now they're commodities. When things become commodities, they lose their value.
I'm not sure why I haven't heard people talk about this aspect. It's the biggest effect on jobs.
1. Mythos uniquely is able to find vulnerabilities that other LLMs cannot practically.
2. All LLMs could already do this but no one tried the way anthropic did.
The truth is one of these. And it comes down whether the comparison is apples to apples. Since we don't know the exact specifics of how either tests were performed, we lack a way of knowing absolutely.
So I guess, like so many things today, we can to pick the truth we find most comfortable personally.
I really wanted to like anthropic. They seem the most moral, for real.
But at the core of anthropic seems to be the idea that they must protect humans from themselves.
They advocate government regulations of private open model use. They want to centralize the holding of this power and ban those that aren't in the club from use.
They, like most tech companies, seem to lack the idea that individual self-determination is important. Maybe the most important thing.
They're trying for the vertical integration monopoly.
The times it works, it works well for the company at great cost to society.
Imagine the world we'd have if comcast got to control your web browsing experience.
If ISPs got started today, they'd sell the open web at API prices that no one can afford. Then sell the ISP's lock-in 'internet' for a low monthly fee.
My question is why people who don't want comcast's internet think other vertical integrated lock-in is fine.
Our markets game only works for the benefit of society if we have fair markets.
VC-backed loss-leader dumping to starve competition model breaks the game.
It's weird that most people in these comments are speculating fraud.
Why aren't companies with real money to gain from stars gaming the system to the same degree? Why do the other metrics - issues and pull requests - match up with its popularity? Why would the bots starring the repo mean that those same bots are not popular? Those bots are controlled by their users.
The project is extremely active because this is what everyone being able to customize their computing looks like. A mess.
But it's a good mess.
Github was the old code sharing model clearly not designed for this. I'm sure a new model for code sharing will come to fix the growing pains.
A ton of people who would have never been able to customize their computing experience are finally able to. And it is magical for them.
This means that those same people will finally value having access to source and use of open protocols.
It was always valuable to us because we had the power to make it matter. It never mattered to them because they did not. Now they do.
The last era of computing was defined by dumbing down computing for the masses. Less information, less customizable, and more metric driven. Control in the hands of the companies.
This new era will look more free/libre, more personal, and less enshitified. Control in the hands of the users.
I agree. A mechanism to voluntarily attach a certificate metadata about the media record from the device seems like a better idea. That still can be spoofed, though.
In the end, society has always existed on human chains of trust. Community. As long as there are human societies, we need human reputation.
These sorts of tools will only be able to positively identify a subset of genAI content. But I suspect that people will use it to 'prove' something is not genAI.
In a sense, the identifier company can be an arbiter of the truth. Powerful.
Training people on a half-solution like this might do more harm than good.
The unix commandline tools being the most efficient way to use an LLM has been a surprise.
I wonder the reason.
Maybe 'do one thing well'? The piping? The fact that the tools have been around so long so there are so many examples in the training data? Simplicity? All of it?
The success of this project depends on the answer.
Even so, I suspect that something like this will be a far too leaky abstraction.
But Vercel must try because they see the writing on the wall.
These sorts of doom articles are interesting in that they are from the perspective of tech company valuations. Why is this the important perspective?
For the humanity perspective, this doom is very optimistic. It says that these LLMs currently disrupting the platforms cannot themselves be the next platforms.
Maybe no one will have 'the ability to make people do something that they don't want to do' sort of power with this next stage in computing.
It's true that in a project, a novel idea undeclared as such will be shaved off quietly by an llm. You really need to be explicit about wanting to keep it.
You will get pushed into the mean.
However, I'd say 90% of making something (that is useful) is repeating the old thing. We stand on the shoulders of giants. Or at least we should. Getting there can be difficult for most of us.
I say this as someone who chronically re-invents things. I then later get stuck and find someone already thought through my problem and solved it better.
I don't believe being unique in all the ways is useful. You need to be unique in the important ways and not unique in the other places.
There's also a cultural coherence angle that (my) unique things often fail at. Stuff has to look like other stuff enough for people to understand intuitively what it is and how it works. Here the mean is your friend.
I am able to explore more unique spaces because I no longer deal with the minutia of getting the things that should be the same correct. So paradoxically, this has made my output more unique.