There is nothing more surreal in AI chat than entering your own name and being told you are a banned topic. Open source models must win. There is no alternative.
Extinction risk. From population genetics... Does Anthropic even employ biologists? It's magical thinking about a field that is poorly understood by their community.
I am also using these models to accelerate scientific discovery. Yes, they are making all the difference at the frontier. At least, they feel they are. The messy thing is that we still need to communicate with each other and that's not getting dramatically faster or better. As you note the models need to be built so they do more work to participate in our communication economy. Or we will do so much, alone, to get nowhere fast because so much of our behavior is still bound up in old (good, tested, but clunky) ways of building shared knowledge.
Just remember that the will do clever but useless things to improve. Like changing the random seed as per autoresearch's hero image. lol! imo, out of the box thinking is needed.
I'm already living in this future. In a decent execution framework, with context management, memory via unix, and mechanisms for web search and access, local models are effectively on par with frontier ones. And they can often be much faster. I'll keep paying fees for the AI companies until they stop truly subsidizing and leading. They are getting close to the edge of utility, but we can use their services now to bootstrap their own demise. Long live running your own software on your own computer.
get the system to build a clean architecture and explain it to you. it will help it to build a better system. a huge part of working with these models for engineering is getting them to create reports. for themselves and of course for us to read and understand. the bottleneck is actually our verification capacity.
But a graph, which provides a view at a certain level of resolution, can often be described in a few consise statements. That's why we make them, to get a view we can condense.
> CAD. Sure, you can do that in text... but it takes much more room to do and magnitudes more time to interpret.
Fascinating example for me. I do CAD... using text! My only experience with it is programmatic in openscad. We check the visualization, but only on output of the final product. For me it's dramatically easier to work with. That may be a personal defect but it's also consistent. Underneath the rendering is always data, which is text, markup, but strings of fundamental data.
And in science it's not a stretch at all that numbers come first. I'll argue you're reaching. Today no one is drawing their numbers from experiments directly on a graph. They record them digitally. In textual form typically, and then render them visually to obtain generic understanding. But also there, in the end, your conclusions (per tradition) need to be point estimates with error bounds expressible in concise textual terms. You may obtain them from looking at images but the hard truth is numerical, digital, textual.