14,665 karma · joined April 8, 2012
[1] https://seranking.com/blog/health-ai-overviews-youtube-vs-me...
https://hackernoon.com/the-long-now-of-the-web-inside-the-in...
Like smartphones, AI chips also have a replacement cycle. AI chips depreciate quickly -- not because the old ones go bad, but because the new ones are so much better in performance and efficiency than the previous generation. While smartphones aren't making huge leaps every year like they used to, AI chips still are -- meaning there's a stronger incentive to upgrade every cycle for these chips than smartphone processors.
It's the same programming with LLMs. Through experience, you build up intuition and rules of thumb that allow you to get good results, even if you don't get exactly the same result every time.
If you refuse to work with AI, however, you're already significantly limiting your opportunities. And at the pace things are going, you're probably going to find yourself constrained to a small niche sooner rather than later.
EDIT: Doing the math on the sponsor list, it's probably around $1M in ARR now.
I hear this a lot, but the most comprehensive study I've seen found the opposite -- that retail electricity prices tend to decrease as load (from datacenters and other consumers) increases [1].
The places where electricity prices have increased the most since 2019 (California, Hawaii, and the Northeast) are not places where they're building a lot of new datacenters.
[1] https://www.sciencedirect.com/science/article/pii/S104061902...
For a long time, it was thought this might be the optimal shape, but it was never proven. And it couldn't have been because it turns out that you can do better: the Gerver sofa (1992) is a more complicated shape, composed of 18 curve segments and has A=2.2195.
Nobody knew whether there might be an even better shape until now (assuming the proof holds up).
At the end of the day, the best option is to use an attorney who knows the right procedures and would also run the risk of professional consequences if they submitted false claims.
60 * 445 / 216.276 = 123.453365145
60 * 445 / 216.282 = 123.449940356
Not the other way around. And since the timing is only given with millisecond accuracy, the bpm should be rounded to the same number of significant digits: 60 * 445 / 216.276 = 123.453
60 * 445 / 216.282 = 123.450
So, it's the YouTube version that's 123.45 bpm to within the rounding error.Has it occurred to you that perhaps what they want is to be the CxO of a big tech company? There’s a lot of power, prestige, and impact on society that you can’t easily have if you quit. Maybe they really enjoy the work itself too.
At the moment it's "We don't need more contributors who aren't programmers to contribute code," which is from a reply and isn't representative of the original post.
The HN guidelines say: please use the original title, unless it is misleading or linkbait; don't editorialize.
[1] https://github.com/apple/ml-sharp/blob/main/LICENSE
[2] https://fedoraproject.org/wiki/Licensing/Apple_MIT_License
- https://www.cnbc.com/2024/04/03/apple-investigates-app-store...
- https://www.macrumors.com/2023/02/23/app-store-apple-music-a...
- https://www.the-sun.com/tech/4944089/apple-maps-down-icloud-...
- https://www.macrumors.com/2019/05/08/itunes-and-app-stores-s...
- https://www.macrumors.com/2018/03/27/app-store-outage/
- https://www.cnbc.com/2016/06/02/apple-reporting-outages-for-...
- https://www.cnbc.com/2015/03/11/some-apple-services-sufferin...
https://news.ycombinator.com/item?id=46193412
As of right now, it seems to have been flagged into oblivion by the anti-AI crowd. I found both posts to be interesting, and it's unfortunate that one of them is missing from the conversation.
Why? NVIDIA is better positioned to produce faster and more efficient ML ASICs any of their huge customers (except possibly Google). And on top of that, the fact that there is a huge library of CUDA code that will run out of the box on NVIDIA hardware is a big advantage.
Arguably, this shift has already happened. Modern NVIDIA datacenter GPUs, like the H100, only bear a passing resemblance to a GPU -- most of the silicon is dedicated to accelerating ML workloads.
The dash key is right between the "0" and the "="
Press it twice and just about every word processing program in existence will turn it into an emdash.
> For this invention will produce forgetfulness in the minds of those who learn to use it, because they will not practice their memory. Their trust in writing, produced by external characters which are no part of themselves, will discourage the use of their own memory within them. You have invented an elixir not of memory, but of reminding; and you offer your pupils the appearance of wisdom, not true wisdom, for they will read many things without instruction and will therefore seem to know many things, when they are for the most part ignorant and hard to get along with, since they are not wise, but only appear wise.
I, for one, am glad we have technologies -- like writing, the internet, Google, and LLMs -- that let us expand the limits of what our minds can do.
[1] https://www.perseus.tufts.edu/hopper/text?doc=Perseus%3Atext...