For context, I have access to MS Copilot through my workplace. To see what it looks like, I have tried to login through https://copilot.microsoft.com/ , where I was informed that my account, although recognised, is not yet supported. However, I can get more or less the same chat window, with access to all the data, through https://m365.cloud.microsoft/ A redirect could have been useful.
Given the sheer volume of the output, it is conceivably difficult to maintain the quality of the plots/characters, even if the animation is stable or even improving. As a byproduct of that, more and more ambitious/batshit source texts are being animated, which sometimes works well (Dandadan) and sometimes doesn't (Uzumaki).
Yes, they do have money to burn, and this will bring some improvements for sure, but active learning has never really worked out, has it? And even 10% of the educated population doing this for, like, 50 years is not that much data, while normally each accuracy percentage is more and more data-expensive.
Not the worst way to make money, but if internet-scale data were not enough to reduce errors to a somewhat tolerable margin, how much data do they hope to collect in this manner?
> Noone is really caring about hallucinations on point facts these days though, it is much more about complex reasoning tasks.
The boundary is pretty thin there though. E.g., Gemini recently told me that a certain papers claims that two frameworks are mathematically equivalent, while the paper shows the opposite, and yesterday Google's AI overview told me that no World Cup matches were scheduled for that day despite their being several of them. The model probably used complex reasoning to arrive at both (incorrect) answers, but superficially they look like basic errors of fact.
The main problem here is that hallucination suppression doesn’t generalise. We can penalise models for incorrect answers on a wide range of questions, but this doesn’t lead to the emergence of a coherent worldview, which, coupled with logical abilities, is the only true remedy against hallucinations. With current architectures, hallucinations will likely persist on open-domain tasks forever.
TL;DR: "Your body passes through a ring of underwater sensors, each acting like a dolphin, using its echolocation. The sensors send ultrasonic sound waves through your body from every angle. With enough waves, and enough angles, we form an image of what's happening inside your body."
In many places, there is a distinction between "master's through research" (a gateway to PhD) and "master's through study" (more coursework, less independent research, a gateway to r-n-d-level positions in the industry).
But nobody has 4 + 4? The traditional system was in Europe 5 + 3, now we mostly have 3/4 + 2 + 3 (Europe) or 3 + 1 + 3 (UK/Ireland).
I don't have a lot of experience with the US system, but from my experience after 3/4 years newly minted postgrads are probably not yet ready to knowingly commit to 5 years of specialised training. European-style MA/MSc's often feel "useless" because they actually help people switch course and find a new footing. However, good master's programmes are either flexible enough for advanced students to take more specialised modules or have high demands to begin with.
There may be issues with the implementation, but masters only programmes are absolutely commonplace in Europe. Some are better, some are worse, but good ones are genuinely helpful for people to, e.g., upskill before going into industry or decide whether they want to do a PhD.
It doesn't really matter if the model cannot make a good educated guess about calories in the food if it cannot give a consistent response given the same input.
meet.hn/city/53.4625600,-1.9570800/SK13-1EF