Biden went around congress to fund a different genocide. Pretty words, but living up to them is another matter.

The problem is that the LLM only does one trick. When you start integrating other software with it, the other software's input has to be fed in the same way as your other tokens. As the last paragraph of TFS says, "every clock check consumes space in the model's context window" and that's because it's just more data being fed in. But the model doesn't actually ever know what time it is, even for a second; the current time is just mixed into the stew and cooked with everything else. It doesn't have a concept of the current time because it doesn't have a concept of anything.

You could have a traditional system interpreting the time, and checking the LLM's output to determine whether what it said made sense. But now that system has to be complicated enough to determine that, and since the LLM is capable of so much complexity of output it can never really be reliable either. You can check the LLM with another LLM, and that's better than not checking its output at all, but the output checking is subject to the same kinds of failures as the initial processing.

So yeah, we can do that, but it won't eliminate the [class of] problem.

Every tech company needs at least three things to start with: The business guy, the brain, and the lawyer. Ideally there should also be a marketing guy, but you can add them in later. Also, none of them have to be male, I just like saying "guy", buddy.

Yes and no, depending. If you are building an application in Excel, yes, all you said is true. If you are using one, no, none of it is. Spreadsheets can be set up such that the user just stuffs data into them where they are supposed to, then clicks a button to get results. Or maybe they don't even have to hit a button.

For the simplest useful example I can think of, I put together a spreadsheet which produces a table we use for asset valuation. This spreadsheet changes every year. If you load my spreadsheet, it will be correct for the current year. No user has to think about that at all, they just load it and get a correct table. You can extrapolate this to basically any level of complexity because Excel has VBA and you can script everything. The user just follows instructions, and they aren't even allowed to edit any cells which could break anything.

In case anyone is going this far down the hole, it turned out great. Even though the item was shipped from the US, because the seller didn't respond I got a refund without having to return it.

So far Aliexpress has been responsive to 100% of my issues and I only have needed to be a little patient and not expect everything to be solved immediately or arrive immediately.

I agree that a database-backed application is the right way to go for that much data. However, Finance used Excel because they could. We all like to talk about how bad an idea it is to do that, but Excel brought financial computations on large data sets to people who can't write any code. It has enabled thousands upon thousands of businesses to do things they couldn't do before without paying a programmer to develop a solution they cannot maintain. The fact that other spreadsheets regularly crater when handed data that Excel has no trouble with is exactly why we have so much Excel.

I like to use Drupal to rapidly create database applications which can handle a lot of data without writing code. But I wouldn't expect someone in accounting to be able to do that at all, and that just shifts the problem domain. Instead of getting stuck with Excel, now I'm getting stuck with Drupal. All of the logic just winds up in a different system that you can't trivially transfer it out of, so you have the same exact maintainability problem, except more people know how to work with Excel.

They could make a note of mileage leaving and re-entering the UK.
Penalty for misplacing the documents would be paying for all the miles.
Or keep it in a database for tax purposes.

Lots of "cute" answers I see. More seriously, the FAA is involved because it involved a flying thing. FAA regulations are designed for flying stuff, and wants a high level of safety.

If a self-driving Fedex truck did what you described, the DOT would likely become involved.

Well, I'm about to find out if I need to do my first chargeback, I have a delayed response on a return authorization for where I was sent the wrong item. They advertised a different version. This might be confusing for them since the difference is small - yet critical. But there really should be no confusion because they advertised the other version both in the images and the product name/listing title.

It's probably overkill in most people's homes. However, it may be more valuable in a commercial setting, such as a convention center or hospital. Cutting down on the crud even by a small fraction could be worth quite a bit.

They have been having decreases in their ability to grow food, so yes they absolutely want Ukraine. You really think people around here know dick.

I have overly expensive cable internet already, I don't need to also pay for CATV.

I got a Google TV because I knew it would have the best app support. Looks like you didn't.

My desktop TV-used-as-Monitor has stupid LG WebOS, but I also don't need a TV-specific app since my desktop is connected to it and I don't connect the TV to the network, only HDMI.

Most iPhone owners didn't buy them outright.

I expect several consequences of this, including:

1. Model collapse. Training LLMs on the output of other LLMs has been shown to lower the model's quality, and it gets worse with each iteration. So, the Internet has become less valuable as an LLM training data source, and this trend will continue, making it more difficult to train new models or improve existing ones.

2. Increased demand for guaranteed human-generated content. This is both from competition between LLM training businesses who need original sources to use as training data, AND from humans who want or need something that is not hallucination-polluted slop.

3. Increased incidence of humans submitting LLM generated slop AS human-generated content. We have already seen this happening in every place you might expect, with comical effect from catching people red-handed lying about this.

4. The bursting of the LLM bubble. Recently experts in the field have said that current training methods have already hit "peak AI" even from good data sources. The landscape continues to change rapidly so I don't know if that is true, but it is at least possible given what is known. An overall decrease in the availability of high quality training data will only make this worse. Then ensuing stagnation in LLM improvement will flatten out the demand curve for LLM services in general.

5. Profit! Especially for everyone who managed to eliminate a lot of human employees thanks to LLMs.