Now I hear you, but just think about what happened in the food industry when they found out customers would not pay higher prices, but would gladly eat shit if it came in the same box as their childhood reward foods.
To what are you alluding?
Yeah, but that doesn't mean they're ordering so far ahead that they don't have electrical connection approval for the building
You would be surprised. Again Micron is making high bandwidth memory for AI instead of consumer DRAM. They have already announced this.
. Approval for connecting to the grid should happen before they even break ground for the building, after whcih it takes anywhere from one to three years *after* they break ground before the data center opens.
Again you would be surprised by the lack of logistics for some of these data centers. And no one is not saying it does not require that level of planning. What we are saying is some of these data centers are being built on hopes and dreams as the foundation.
but make sure you're referencing one single case that actually happened and add your cited source next to it so I can verify it.
1) I doubt AI is smart enough to do that. 2) Verifying the case exists is trivially easy as the citation explicitly tells everyone how to find the case. The difficulty is in locating cases that are relevant to the legal issue.
If your lawyer does not have a paralegal, you should fire them.
1) So your advice is to only hire lawyers from large law firms? Lawyers with a solo practice may not have a paralegal. 2) A
Law is a very paperwork intensive industry. Now a days you can get away with 1 paralegal serving multiple lawyers, but nobody and I mean nobody goes without a paralegal.
Again small one lawyer firms exist so what you are saying is untrue. They should use paralegals to lighten their work load, but that does not mean they must always use a paralegal.
Smaller shops may have only one person doing the work of a receptionist and paralegal and other things, but they will always have at least one person.
Again I know of one person firms that do not always use a paralegal.
It is inappropriate for a lawyer to have the paralegal check his work, but if you are not going to check it at all, that is incredibly stupid.
You wrote above: "I can easily see a lawyer order their paralegals to fact check their reports" You just contradicted what you wrote.
Stupid as in how the hell did you get into law school and how did they not kick you out.
You literally wrote: "Did they fire their paralegals? Because that would explain why they still have issues. I can easily see a lawyer order their paralegals to fact check their reports ". Do you not remember what you wrote?
You realize that this change has zero effect on any router, no matter its country of origin, that was on the market last Friday
You do realize that only applies to routers in inventory, not every single router forever. Every model of router will need to be "authorized" to be imported from now on.
Unless the companies are completely incompetent, they aren't having the processors manufactured until they have a plan for bringing the building online, including power delivery.
Not from what I can see. NVidia is getting tons of orders for processors. Also the RAM shortage is because AI datacenters are buying all available memory and convincing the RAM foundries to make as much high bandwidth AI server memory as possible. When the bubble bursts, will these companies be left with orders no one wants. For example, Micron has stopped selling consumer memory in order to make HBM3E which is not consumer RAM sticks. Maybe Micron could sell some of that RAM to non AI datacenters, but the vast majority of those datacenters use ECC DDR memory as it is reliable.
Everything else in the data center is pretty much the same no matter what hardware you put in the racks. You still need floors, walls, and a ceiling or roof. You still need places for cables to go between racks (either above or below). The floors still need to be built to handle high static weight loads where the racks are. You still need power infrastructure. You still need cooling infrastructure. And so on.
Again, some data centers are being built without plans for cooling, power, etc. It is as if they just expect the surrounding area just to build all of that for them.
Only if one were to really scrutinize the work would one discover how terrible it is, but why bother doing all that extra evaluation...wasn't AI supposed to save you time?
Unfortunately for lawyers, they are in a field where their opposition checks their work. From what I understand the most difficult part is finding the relevant case or law. If a lawyer cites [court case] or [law], the opposition can quickly check it. It is almost an NP problem.
Because that would explain why they still have issues. I can easily see a lawyer order their paralegals to fact check their reports, but when they get AI they fire their paralegals and just think the AI can handle those duties.
1) Why do you assume paralegals had anything to do with it? If a lawyer is using AI to write their briefs without checking anything before submitting them to courts, it is most likely they do not have paralegals to do that or they were never going to give that work to a paralegal.
2) No matter how the works is produced, the lawyer who submits the filing under their own name is responsible for making sure the filing is correct. In one of the AI cases I remember, the lawyer who submitted the filing was sanctioned just like he lawyer who admitted he used AI to write the filing.
This...I think, has some wiggle room. Sure, training new models requires greater amounts of compute power, and as newer models and services develop, there will be a need to increase compute power. However, that doesn't mean that older models are useless. They may not be front-and-center, but they can still be used in lesser capacities. ChatGPT 3.5 isn't quite as awesome as v5, but if it's what is used to serve up ads in ChatGPT sessions, the hardware is still perfectly fit-for-purpose. Same goes for Google or Microsoft - older boards may not be front-and-center, but they can still do boring, smaller-scope tasks that are still useful.
Older models do not generate investment which is the primary source of AI funding. While better models can be developed over time, the cheat code for all models is just to use more powerful hardware. Also logistics has been ignored by AI companies as vital. They want the most powerful hardware now. The reality that datacenters take years to build means the hardware they buy now will not bet the latest when the datacenter comes online requires forethought and planning. They would rather cancel the whole contract if they cannot get what they want now.
That's what I call DEI. Lesser qualified people hired or promoted in preference to merit because of identity politics. In irony, two of the best employees I ever worked with were women, hired using this metric. But that was accidental meritocracy. They would also have been hired for their ability in a non-checkbox world, not because of their sex.
The problem with many here is the automatic assumption that anyone not a white male was unqualified most likely because they are white males.
FORTRAN is a good example of a language which is easier to parse using ad hoc techniques. -- D. Gries [What's good about it? Ed.]
