Other than whats publicly available, an interesting thought about this is how they were able to launch and create something within the highly corrupted political system. Every launch, stage and approval probably required sometype of bribe (even with the current governments focus on deep tech and scientific development)
I think an important thing here is that the company is almost 8 years old. Which, is not old for a defense tech manufacturer, but does give them leeway to develop and test
Really interesting when you start to think with how people will interact with AI in the coming months. A ton of devs in Berkeley are not interacting with claude through the iMessage extension, just because it's so easy. And they trust claude does a good job of understanding the message and implementing whatever they need
Something I havent heard alot of people talk about is meat. I dont think you can be against data centers, but also buy cheap meat. I understand food != compute, and thats a fact. BUT the same people who are protesting against AI data centers are the same people who fly every year, eat steak in every other dinner, and generally indulge in activities that are bad for the planet (and theres no acknowledgement).
lebovic answered this, but it isnt just claude cowork especially with connection and abilities related to SPC clusters. I could defientiyle see my former team at a national lab integrating this with their systems, and forgoing the use of Claude Code all together
But I think the important part of this is the reach that the Industrial Revolution had. Consumer facing software, or the endusers who were able to "benefit" from the Industrial Revolution, and individual needs for all of these mass produced goods.
The important thing is that goods =/= software. I, as an end user, of software rarely need specialized software. I dont need an entire app generated on the spot to split the bill and remember the difference if I have the calculator.
So, yes, we are industrializing software, but this reach that people talk about (I believe) will be severely limited.
I think I super important aspect that people are overlooking, is that every VC wants to invest in the next "big" AI company, and the probability is in your favor to only give funding to AI companies, bc any one of them could be the next big thing. I think, with a downturn of VC investment, we will see some more investment in companies that arent AI native, but use AI as a tool in the toolbox to deliver insights.
Why is the native picture (fig 1) in grayscale? or more generally why is black and white the default of signal processing? Is it just because black and white are two opposites that can be easily discerned?