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Comment Re:When I hear they are going to build a datacente (Score 1) 58

How many data centers in your immediate area? Are they the modern high density data centers with thousands of GPU units per rack or the old school 4U's in a rack supporting a few websites kind of data center?

As for employment, when is the last time you saw a data center that was bustling with human activity once construction and move-in was finished?

Comment Re:AI is almost never the limiting factor (Score 1) 177

That was a joke! backhoes breaking fiber is part of the natural order.

That's why you should always carry a length of fiber with you. If you ever get stranded with no cell service, you can just bury the length of fiber in the dirt. When the backhoe guy comes along to break it, ask him for a lift.

Comment Re:Actually, congrats to the cURL team (Score 1) 62

It does nicely illustrate that AI may do a deeper scan, but not necessarily a better one.

There are existing rules based scanners for websites. Running one on any typical site will easily spit out more than 100 flagged issues. Some "consultants" will dutifully hand that report over and call it a day, but if you actually go through them, most if not all aren't even actual security flaws. Yes, if I POST data that includes the correct username and password, it will grant me access just as if I had filled in the login form. So what? Yes, if I give an invalid account number, it returns a page with (non-)error code 200. The page says "Access denied".

That isn't to say the AI tool is bad, just that it represents an EVOlution, not a REVOlution.

Comment Re: Well "just" vibe code you a new API, then eh? (Score 3, Informative) 46

The biggest problem with replicating CUDA is not the technical aspects, but finding VC with enough brains to know whom to hire. Most CS grads have the knowledge, but not the drive. Most liberal arts grads have the drive, the creativity, but not the knowledge. You need to find one with both, because creating the next Nvidia killer will require someone who is boring enough to reinvent the wheel, but has enough creativity to find novel solutions to performance problems.

The computer science and hardware engineering behind the hardware and software (Nvidia/CUDA) have been known for decades. The Nvidia hardware could be replicated with FPGAs - notwithstanding any patents Nvidia might have. The software API could be replicated rather easily; parallelism has been known and studied in computer engineering (again) for decades now. What Nvidia did was political - they provided both the hardware and the API to easily use it in one package which could be understood by the C-Suite class. The challenge was never technical, but marketing.

More specifically, you'd need to understand how compilers work, and how to use YACC or bison, or something similar to generate the compiler code for you. You'd have to understand digital logic and how to create logic functions with NAND gates. If you see an FPGA development kit, know what it is, and think to yourself, "What I could do with that..." you're probably a good fit for the job. And you'd need someone willing to bankroll your project until you could demonstrate that you beat Nvidia on something marketable - like floating point performance. Or power consumption.

From an engineering standpoint, what Nvidia has done is trivial - because the solution could be reproduced by an engineer using already known techniques. But what Nvidia did was to combine technical knowledge with an understanding of their market to produce the dominant position they have today. Any computer engineer worth his diploma could produce a design with FPGAs that would beat Nvidia GPUs, but Nvidia did it first.

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