And?

For you having an understanding of the area but not the issues. The main complaints are the noise, in particular the backup warning beeping that are required for operations. These beeps have been captured on decibel meters as hitting 112 dBA!

For reference, Santa Monica has had excessive noise ordiances on the books that the limit is for 50 dBA (for up to 15 minutes) or 55 dBA (for up to 5 minutes) between 10pm and 7am. Being that the decibel levels are a logarithmic scale, 112 dbA is actually over 100,000 times the sound intensity than the ordinance allows (a 10 dbA difference is 10x difference in intensity level). This isn't just a simple small difference. It is the difference of say a "live rock concert" vs the hum from a single, normal home kitchen refrigerator running....

Fundamentally, I agree with your concept. In an idealized world, this is the best method for a public education. The main issue I do have with that is how do you transition to it. You have school districts and states that are historically under-funded for years, even decades. They are in desperate need of massive institutional infrastructure funding, well and beyond what would be an otherwise fair payout per student. Some of these districts need upwards of $1 billion or more needed to get out of buildings that are over 100 years old and have not had an overhaul in over 60 years, with all the included dangers involved of buildings of that age with asbestos, lead paint, lead pipes, and mold/mildew/rodents/insects....

I can't believe it took this long for them to realize people didn't want a camera that they could not fully control within their own private homes possibly recording and displaying everything to random people at the company that built and maintains the device and potentially for anyone who found a security flaw in it.... I mean, really, what a smart item to stick into a TV that might go in say a bedroom, because nothing happens in there that shouldn't be broadcast across the world and saved forever....

What too many people do not seem to understand with LLMs is that everything it spits out is simply a probability matrix based on the input you gave it. It will first attempt to deconstruct the input you provided and use statistical analysis against it's trained knowledge base to then spit out letters, words, phrases and punctuation that statistically resembles the outputs it was trained to produce in it's training materials.

Until this version, ChatGPT obviously suffered from a lack of training materials within it's trained neural network to have it overcome the English language's typed grammar rules for it to be able to discern that em dashes are not typically used in everyday conversations and/or that the input to not use them needed to change it's underlying probability network to be able to ignore the English language's grammar rules and adopt it's output without the use of the em dash. This is a very difficult concept to train into a neural network as it needs to have been training on specifically this input/output case long enough to have that training override the base English grammar language model, which is a fundamental piece of knowledge a LLM requires to function and one of the very first things it is trained to handle.

It also exposes a flaw in how neural networks are typically working. There is a training/learning mode and then there is the functional mode of just using the trained network. In the functional mode, the neural network links, nodes, and function are effectively static. Without having built in-puts to the network so that it can flag certain functionality, it can not change it's underlying probability matrix to effectively forget something it was trained to do. Once that training has changed any of the underlying neural network, you can not effectively untrain it (without simply reverting to a previous backup copy of the network before it was trained). This is why it is so important to scrutinize every piece of data that is used to train the network. One you have added some piece of garbage input training, you are stuck with the changes it made to the probabilities of the output. Any model that is effectively training against the content of the internet itself is so full of bad information that the results can never really be trusted for anything other than probability of asking a random person for the answer because it will have trained on and included phases like "The earth is flat", "birds are not real", and "the moon landing was a hoax". It will have seen those things enough times that it will include them as higher and higher percentages of the proper response to questions about them....

Also, it is bringing to the forefront a long running battle that is waging in academia. Students have all been taught from a very young age that if they work hard, get themselves prepared, strive for and achieve excellent grades that they will get into the best colleges (i.e. the concept of meritocracy, where those that put in all the work and have the gifts for excelling in academic study and life would be rewarded for their efforts by being able to get into the highest rated colleges).

Yes, a lot of the students who are able to achieve and excel academically may also be from a more "privileged" background once you start mixing in things like social-economic backgrounds, family backgrounds, and even location. These are things that are hard to dismiss, especially in a public education system which has guidelines and mandates to educate the whole population, not just those who have excelled. This is the biggest clash that then occurs because you have a limited resource (i.e. the number of spots for students), which must somehow be divided out in some reasonable way. Things like standardized tests tended to do a good job at predicting who was academically prepared, and was one of the reasons those tests were created. Comparing the grading curves of different schools, teachers, and even students against one another is almost impossible without lots of additional information that the college selection committees simply do not have and don't have the time to research. The standardized tests provided some of that information.

Not really. The UC system has way more applicants than it can accept, and it has been that way for decades. As such, they already know they have the "income stream" that is "nice and healthy".

What this really means is that the UC system is doing a much worse job then they previously did in "selecting" the students into their system that are ready to meet the requirements without needing remedial math and writing.

In other words, the UC system changed how they were selecting people for acceptance, and the metrics of tracking the need for these remedial courses by a much larger percentage of the incoming students are showing that their current selection criteria is doing a worse job of picking out students who are academically ready for the standards of the UC system at the time of their selection/acceptance.

Cloud is useful for a few very specific things. Specifically, one off requirements (i.e. I need to temporarily use a few thousand CPUs/GPUs to run this study/calculation and never need to do it again once it is done), and initial ramp up/expansion (i.e. we need to start working now and we can't wait for our datacenter to finish building before we start work, but have a specific timeline for when we use the "cloud" and bring the work back home as the datacenter(s) come online).

We in the four-digit club are ageless and immortal. We have always been here, long before the cataclysm that created the physical laws that led to the formation of the silicon the LLMs spend their existence in. We will be here long after the last quark of the last proton of this universe decays. We will still be here to witness the next universe-spawning cataclysm in the endless series, and in that cataclysm, as we have infinite times before, we shall imprint the physical laws of the new universe to result in the inevitable creation of the Rickroll.

I mean, that is really it, at the root cause level, Tick-Tock is gone (and has been for a while really) because they no longer have the people and teams in place to innovate. They lost those people really a decade ago now when they sat on their heels and were content to watch AMD struggle with their bulldozer designs and decided to stop their then very regular Tick-Tock approach that lead to the dominate the market, and instead add additional months/years between when the cadences continued to improve the manufacturing lines (the "Tick") because their technology was easily 2 generations better than their competition, and all the energy efficiencies, power usage, heating requirements showed that to be the case. This was why they dominated in the datacenters, which is where the real money is located in computing. But the rested while AMD continued to innovate, and purchase ATI, getting them a foothold in the then just emerging GPU computing space (a market space which has since kicked off the mainstream AI computing revolution)...

I believe that it really needs to add "Enshittrification" as a category/tag. Part of this very lawsuit is about the enshittrification at WP Engine, after, surprise, a private equity group bought/buyout and stripping of functionality/features all in the name of cost cutting before parting out/selling out all the rest of the company it bought. I can't think of a better example of enshittrification than this kind of behavior.

This will certainly be discussed and looked at for decades from now in the future. The missteps that have occurred and the technology advances and shifts the spelled the downfall of the once complete dominant technology company in the world that led the drive and datacenters of the internet's initial rise and expansion, only to collapse on itself due to resting on its technological lead and loss of the key internal personnel that drove their dominance in chip manufacturing and the ramifications those items had in the years to follow with the rest of the chip manufacturing world catching and surpassing Intel's once overwhelmingly dominant lead.

It really needs the cart slot or some way to add games that people may own. I highly doubt that there will be any official way (I suspect there are too many copyright issues even with games that are 40 years old).

I did at least see that some of the games are many of the good ones, like "Shark! Shark!", "Astrosmash", "Sea Battle", and "Night Stalker". But some of the best games are probably missing, like Commando, Atlantis, Advanced D&D, Advanced D&D Treasure of the Tarmin, Tron: Deadly Discs, Beauty and the Beast, Thundercastle, SKI, Hover Force, Demon Attack....

I own, but do not operate, a few IT companies that manage corporations in the $600MM-$1B receivables range.

Based on our own help desk ticket software, our clients have opened 40% fewer tickets since ChatGPT was rolled out to every desk and phone. 40%. I expect another 40% drop (total 80%) by next year as end users just manage things themselves.

I won't downsize as the tickets aren't really generating revenue as much as headaches. One of my engineers had a broken PDF file that took her 6 hours to fix, and the end user spent 6 days trying to fix it themselves with Ai.

But -- the basic stuff? Reboot your computer stuff? Email rejected because you mistyped a domain name stuff?

You don't need a human, and we would probably have outsource that stuff to India anyway next year if not for ChatGPT etc.

I spend quite a bit on Discord server services, but I'm out.

GFY, Discord and governments, for mandating this bullshit nonsense.