... they can force them and they will - I think it is telling that they are beginning to consider extracting software rents, which could indicate they are beginning to prepare for some lack of sustainability in hardware sales - though right now they cannot make them fast enough, 'em chips.-
Not that I necessarily agree with their rationale, but you're framing it differently.
> Lack of sustainability in hardware sales
Doesn't necessarily imply competitors will be eating market share, it can imply the market will shrink. e.g. data center commitments and AI dries up. Or, it can imply hardware development will slow or become "good enough" and slow sales of latest and greatest.
Totally agree, and was more my thinking: Commitment weakening (we are seeing signs of that overall, I believe) and to some degree hardware being sufficient (baring some qualitative paradigm shift ...).-
languages with dynamic types will be obsolete thanks to AI, you heard it here first. It is just introduces more errors, with AI you want formal checking, sure static types are not that, but it is a small piece of it. If 10 percent of errors are types, with a typed language keeping everything the same you have 10 percent less errors, simple as that.
100%. This is a solution to a problem you wouldn't have if you were just using a statically typed language. AI will naturally drive us to more rigid languages.
I agree. Just scanned it and not getting anything of this word salad. What is the main point, is it anything significant? Some of the pictures are interesting that is about it.
The operating system and user programs including the application is the application. Worrying if it is unikernel or kernel is irrelevant at this point.
There is tremendous investment and work being done in creating new high quality data sets. Some of this is happening in-house at various firms, such as Meta making their employees use AI for their workflow to generate high quality training data.
Also, AI companies get huge amounts of human input when people use their cloud models, including thumbs-up or thumbs-down on millions of outputs. So the usage of these cloud models is itself producing new, high quality datasets.
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