Same here: Picture from rural Austria in the North and it comes up with Hungaria. Location is in the center of Budapest, 300km distance to the original view point. But architectual style looks really hungarian.
That doesn't matter, you are toying with semantics. If astronomers say stellar black hole, they don't mean supermassive black holes at galactic centers. Even if Sagittarius A* was initially a stellar black hole, its more now.
I hadn't heard of the distinction stellar or non-stellar black hole before. It rather sounds like semantics to me to say this is one type of black hole and not another when it's physically the same thing and we don't know how it formed to begin with
The headline confused me as well: 33 solar masses (not sizes) seems tiny to me, I was sure we knew of bigger ones
To add to a sibling comment, the distinction is important, because observed mass of black holes falls largely into super massive (millions to billions solar masses) to stellar (dozens of solar masses). There is very, very, astonishingly few observed black holes with an intermediate mass. So, how super massive black holes form is a mystery, and finding large stellar mass black holes starts filling in (possibly) that evolutionary gap in black holes. Not a physicist, just read/watch a lot of pop astronomy/cosmology.
Also, super massive blackholes can only "swallow" so much matter at a time. Given what we know about how fast a black hole can grow, super massive black holes seem to be bigger than should be possible.
The distinction is clear and relevant because the mass distribution is strongly bimodal. A stellar black hole is the result of the gravitational collapse of a single star (well, or two at most). And maybe some of them have since then merged with a companion body. There are zillions of these in any given galaxy. Whereas there are maybe one or two supermassive black holes per galaxy, sitting in the center, with mass of millions or billions of suns, and we don’t quite know how they first formed and how they have accumulated so much mass. If the difference between "one" and "billion" doesn’t matter to you, well, ok then.
The difference is even more clear-cut because so-called intermediate mass black holes are something of a question mark. For a long time it wasn’t clear whether they even exist in any significant numbers, and even now the evidence is not especially rock-solid, especially with regard to candidate objects in the Milky Way.
Its not semantics. Its precise terminology. Ignoring this and redefining the precis terms because one lacks knowledge about the subject and arguing from faulty assumptions is a waste of everyone's time.
> I hadn't heard of the distinction stellar or non-stellar black hole before.
While it's possible that supermassive black holes were formed from stellar collapse, there are models where they didn't, while they _know_ that this one was formed from stellar collapse.
They don't seem too clear on the science they're reporting, but if I'm understanding it right, this is supposed to be the largest stellar origin black hole. The fact that Sagittarius A* is just a bit under 4.3 million solar masses, which is a bit over 33, was my first thought, too.
[2] "From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples" https://arxiv.org/abs/2404.07544v1
And I'm sure the reason for that is the garbage input. From time to time I have to perform quantitative code analyses in our so called enterprise repositories. And the results are shocking every time. I have found an extremely poor SQL code block to type cast many columns in hundreds of projects. It was simply copied again and again even though the casting was no longer necessary.
The training base should be sufficiently qualified (and StackOverflow ranking is obviously not enough).
But unfortunately it's probably too late for that now. Now inexperienced programmers are undercutting themselves with poor AI output as training input for the next generation of models.
Not using Claude but this behaviour comes not from the model itself. Basically the model does not now what it provided in the other iterations of your for loop. Ask for 20 different profiles. Or, even better: ask for different types of cancers and iterate this list.
I have tried this even with all ranges of temperature (0 to 1) ... it produces the SAME profile over and over ... Since I couldn't get to format the code here, I have put it on pastebin -- https://pastebin.com/fCu3Ji6n
Any chance someone can try this out ? I am pretty sure it will be the same, something is odd (maybe it is too harmless with patient profile?)
Interesting approach to load the model direct. But no explanation on the video or on the company page[1] about the processing units itself. The numbers from the page (2.3x faster, 1/2 the power) are plausible for top notch FPGAs.
[1] https://github.com/Infini-AI-Lab/Sequoia/tree/main/Engine