What, you mean you're not convinced to grab the no-name alpha-release "privacy browser" that cripples yourself if you don't let them MITM you?

It wasn't that hard - Netscape came on floppies, too.

Well, the courts have already ruled on very similar things, multiple times. If the code is machine created, even if the user is pushing buttons to tell the computer to run, the end work can not be copyrighted.

I have not seen any appeals ruling yet on this. But I also do not expect one as this follows many other such copyright rulings in the past, such as the cases like the "monkey selfie" case, which the Copyright office issued a Compendium of U.S. Copyright Office Practices 12/22/2014 which stated:

Then there is the case of the copyright of comic book "Zarya of the Dawn", authors by artist and AI consultant, Kris Kashtanova, which the images were all created/generated through the use of Midjourney. They Copyright office provided a copyright only on the compendium of the book itself, but all the individual images generated via Midjourney are not copyrightable and are in the public domain to be free for use by anyone, as the simple operation of prompts and instructions to Midjourney was insufficient human authorship to be able to claim a human created the work.

You do realize (well I guess you don't) that all PhDs are philosophy right? It is the VERY DEFINITION OF PhD (Philosophy Doctorate = PhD).

Seriously, anyone using a smart TV should have it extremely limited with what it can reach on the internet, and really, probably should have it blocked entirely. I mean, we have cameras in TV's that take photos of who is in the room, and internal snapshots of what is being displayed on the HDMI connections so that it can lookup the show/video/content and match against what (male/female, baby/toddler/child/teen/young adult/adult/senior) and how many people are watching it.

If your computer connects to your TV via HDMI, they already know.

Wow, somebody needs a lesson on proper money management if they can't get by with a six figure income. As stated by some other posters, that is well above the average of $66,622, and also above the median income of $83,730 (in other words, you make more than 1/2 the people in the nation!), even if it is just at $100,000. In fact, only 18% of people in the USA make $100,000 or more per year!

So you are in the top 20% of earners in the USA, and globally, you are somewhere in the top 0.1% of earners (to put some perspective on it)....

So now that you realize you are not only part of the 1%'ers (you are well beyond it from a global point of view, as you only needed ~$34,000 a year to join that club), you need to seriously rethink and put some perspective on a six figure income. You also need to put some thought into the difference between high wealth and high income. If you are simply p!ssing it all away and living paycheck to paycheck trying to "keep up with the Jones's lifestyle", you are absolutely doing it wrong. Trying to follow the latest fad, or fashion, or car craze, or instagram vacation lifestyle just isn't possible without a high wealth, not a high income. When your wealth is such a way that the money you have saved, and invested in stocks, bonds, real-estate, rental properties, and/or businesses simply grows on its own to the point that you don't need to do anything, and it well outpaces what your traditional 6 figure income, well, then you can do things like buy that latest fashion outfit, or go on a six week vacation around the world.... And you get there by working your @ss off when you are young and saving everything you can, eating things like ramen noodles for $0.50 a meal, and drink tap water or home made tea, and only going out to eat a couple times a month, as well as drive a modest car till it is well into it's teenage years of age and finally ditching it when a repair bills to keep it going for the year begin to exceed ~1/8th the price of a new one, and save/invest every remaining dollar you have. You manage to do that in your 20's and 30's and you will be set in your 40's and older, especially if you were earning 6 figures, or even the median US income. The 30 years of interest and growth on properly invested savings should have allowed it to compound ~16x. So if you earned $100,000 and simple saved the approx $16,000 that would have dropped you down to the median income in the USA, in the first year, in 30 years even without saving a single penny more, it would be around $256k, and at around 45 years it would be over $1million. Now image you had been saving $16k each and every year of those 45 years, and never touched it for another 45 years, if you started that at 20 and went until you were 65 year old, you would have effectively 1 million dollars each year showing up in your bank account each year from age 65 until you were 110.

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).

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)...