Could someone knowledgeable please explain why an AI-focused CPU is superior to a GPU-based solution with an ARM CPU driving the high-level operations, please, especially when the RAM isn't on-chip?
I know that for GPU's the model weights have to be transferred over the bus initially, but that only has to occur once for inference use cases, so is the Fujitsu system more about training scenarios? Or is the focus more about efficiency, as these are ARM-based cores with AI additions?
Honestly I think this is an HPC CPU that has been AI-washed. Then you might ask why not use GPUs for HPC and I think the simple answer is that Fujitsu just doesn't want to take on the effort of building a GPU.
Yeah, this very much gives the vibe that the original plan was to design a CPU, then suddenly AI AI AI happened, and they squeezed some matmul units into the design at the last minute in order to please the higher ups.
"...working together to bring Mistal’s scientific innovations to consumers around the world"
A quick proof-read wouldn't have gone amiss here.
I also fail to see how privacy is enhanced by sending private browsing data to a cloud service which then forwards it to an LLM, in addition to storing 'memories' and dredging through my browser history.
No, the model has answered correctly. Your question is poorly phrased (possibly deliberately).
Your question would correctly classify the user's input as requesting a human support agent, but at an indeterminate time.
If you wanted to determine whether the user wants to speak to a human support agent immediately, you would have to correctly qualify your question, e.g. "Does the user want to speak to a human support agent now?". You could have another question which is "Is the user requesting a call-back from a human support agent?". Or you could have a multiple choice query which would filter the conversation into one of a number of pre-written possibilities.
This is nothing to do with accuracy or hallucination. It's a different method of interacting with the model where you are relied upon to be precise.
Her playing at Glastonbury here in the UK only seems like the other day, but I just checked and it's been _12 years_! She played her most popular songs and the audience treated her like the star she was. What an incredible, talented, kind-hearted woman. An inspiration to so many for all the best reasons.
I agree with removing the obvious dopamine-related signals, but removing timestamps is a mistake, as they are vital for technical and news-based posts. They're a valuable relevance signal in many cases, not 'noise'. At least make them available on-hover or as a user option. Yes, you could try with a 'limit to historical posts' option, but that's going to be difficult as some topics move a lot faster than others, e.g. current affairs versus web standards.
This sort of unilateral action-before-asking is imo not a great signal to send out if you're trying to grow a platform. If you're going to run experiments, let people know first.
Could I also suggest making the comment text size larger (it's smaller than CSS 'small'), changing the typeface to be proportional, and most importantly making sure the contrast between foreground and background elements is WCAG-compliant? Most of the text is less than 3:1. Currently the site may be quite challenging to access for a visitor with visual impairments, and I think many such users would enjoy a site such as this if it were more accessible. Thanks.
Re: timestamps, feel free to vote[0] on the matter!
Re: design, a lot of people seem to like it the defaults. If you make an account you can customize theme, color scheme, font face/size, and more. If we’re missing a more contrasty theme it should be easy to add.
Your default should be WCAG-compliant. That's the whole point! A visually-impaired user shouldn't have to customise your site for it to be readable. Your site will be failing some accessibility metrics until you do that, and that will affect your search ranking etc. Plus it's generally a good audience-friendly thing to do.
I was aware of the poll, but putting that up after the fact and it being only about the timestamp is a bad signal, too. It says that you're willing to pull the rug on whole sets of features at a whim and just because _you_ think it's the right thing to do. If you're trying to foster a community, I'd argue that this is not the best approach. These sorts of things could be reversible experiments - such as a banner at the top of the page saying "We're trying out removing timestamps and counters like likes! Click here to give us feedback or to switch back to the old UI." And then you keep track of everyone who switched back or re-enabled the feature you're fiddling with. Or you let people switch for a while and give their opinion after the test period.
One would hope that you change minds and differentiate yourself through the strength of your argument, rather than the anfractuosity of your prose or a propensity for sesquipedalian verbiage.
Clarity does not equate to genericity. I am regularly struck by clear writing that is both lucid and powerful without resorting to ten-dollar words or tortured syntax.
The fact that AI text is often so easily spotted is a clear sign that so-called 'slop' is not the same as a writing style focused on brevity and understanding over florid meanderings.
Many people without dementia show amyloid plaques in their brains in autopsies. It's becoming more accepted now that there are multiple interrelated causes after decades pursuing the simplistic amyloid plaque theory.
They aren't equal, as the faster version does an unconditional memory write instead of only writing to the array if the condition is satisfied. The compiler is strictly forbidden from turning a conditional write into an unconditional one.
The Linux kernel had problems years ago when gcc started to do exactly that in certain cases (because it screwed things up with task switches, interrupts, and SMP). It fairly quickly afterwards either stopped doing it entirely or got a switch that would stop it from doing it. Don't remember which.
Large organisations have advocacy, support and friendship groups for many underrepresented or protected groups, such as those for religions, mental health issues, physical disabilities etc. I imagine this is simply one of those internal group's organisational repos.
I know that for GPU's the model weights have to be transferred over the bus initially, but that only has to occur once for inference use cases, so is the Fujitsu system more about training scenarios? Or is the focus more about efficiency, as these are ARM-based cores with AI additions?
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