And you can’t tell when something is active/focused or not because every goddamn app and web site wants to use its own “design language”. Wish I had a dollar for every time I saw two options, one light-gray and one dark-gray, with no way to know whether dark or light was supposed to mean “active”.

I miss old-school Mac OS when consistency was king. But even Mac OS abandoned consistency about 25 years ago. I’d say the introduction of “brushed metal” was the beginning of the end, and IIRC that was late 90s. I am old and grumpy.

Say all you want about hallucinations, but AI will never be able to outperform humans at bullshitting, so sales and marketing is safe.

Wait, isn’t it the other way around? You should arrive in NY earlier than you left London, since NY is 5 hours behind London. So if you leave at 8:30 and arrive 1.5 hours later, it should only be 5AM when you arrive.

You might need a third breakfast before your elevenses in that case.

Interesting read, thanks! I’ll finish it later, but already this bit is quite interesting:

Without access to gender, the ML algorithm over-predicts women to default compared to their true default rate, while the rate for men is accurate. Adding gender to the ML algorithm corrects for this and the gap in prediction accuracy for men and women who default diminishes.

We find that the MTEs are biased, signif-icantly favoring White-associated names in 85.1% of casesand female-associated names in only 11.1% of case

If you’re planning to use LLMs for anything along these lines, you should filter out irrelevant details like names before any evaluation step. Honestly, humans should do the same, but it’s impractical. This is, ironically, something LLMs are very well suited for.

Of course, that doesn’t mean off-the-shelf tools are actually doing that, and there are other potential issues as well, such as biases around cities, schools, or any non-personal info on a resume that might correlate with race/gender/etc.

I think there’s great potential for LLMs to reduce bias compared to humans, but half-assed implementations are currently the norm, so be careful.

Being factually incorrect about literally everything you said changes nothing? Okay.

More importantly, humans are capable of abstract thought. Your whole argument is specious. If you find yourself lacking the context to understand these numbers, you can easily seek context. A good starting place would be the actual paper, which is linked in OP’s article. For the lazy: https://www.nature.com/articles/s41598-020-61146-4

It’s 14,000 to 75,000, not millions.

Microplastics are in the range of one micrometer to five millimeters, not nanometers.

They link to the full source paper: https://www.nature.com/articles/s41598-020-61146-4

That seems more like your problem than OP’s.

After all these years, I’m still a little confused about what Forbes is. It used to be a legitimate, even respected magazine. Now it’s a blog site full of self-important randos who escaped from their cages on LinkedIn.

There’s some sort of approval process, but it seems like its primary purpose is to inflate egos.

It was an SEO hellhole from the start, so this isn’t surprising.

Do Forbes next!

It says:

Available Architectures
aarch64, x86_64

And it uses Android Translation Layer. Interesting. I’ll give it a shot on my desktop later.

I claim ownership of the microorganisms in and on my body. I am not merely human; I am a glorious amalgamation of trillions of distinct beings, working in harmony to bring you shitposts!

As a begrudging Comcast customer myself, allow me to explain. They are the least shitty option because the only alternatives in my area are 5G and Verizon DSL. Verizon DSL has a max download speed less than 1mbps.

So yeah, I use Comcast. And I hate it.

However, it is still comparatively easy for a determined individual to remove a watermark and make AI-generated text look as if it was written by a person.

And that’s assuming people are using a model specifically designed with watermarking in the first place. In practice, this will only affect the absolute dumbest adversaries. It won’t apply at all to open source or custom-built tools. Any additional step in a workflow is going to wash this right out either way.

My fear is that regulators will try to ban open models because the can’t possibly control them. That wouldn’t actually work, of course, but it might sound good enough for an election campaign, and I’m sure Microsoft and Google would dump a pile of cash on their doorstep for it.

Who thought it was a good idea to let an internet ad company control our internet client?

It seemed a lot more reasonable 15 years ago. The default on Windows at the time of Chrome’s rise was Internet Explorer.

I am watching Ladybird with great interest. The world needs a new-from-the-ground-up browser.

simply logging out or using an alt account

It is increasingly difficult to use X without an account. Not sure what the signup process is like nowadays. IIRC it used to require phone number verification in the Twitter days, but perhaps Musk relaxed the requirements in order to better pad the usage stats with spambots?

Yeah, AMD is lagging behind Nvidia in machine learning performance by like a full generation, maybe more. Similar with raytracing.

If you want absolute top-tier performance, then the RTX 4090 is the best consumer card out there, period. Considering the price and power consumption, this is not surprising. It’s hardly fair to compare AMD’s top-end to Nvidia’s top-end when Nvidia’s is over twice the price in the real world.

If your budget for a GPU is <$1600, the 7900 XTX is probably your best bet if you don’t absolutely need CUDA. Any performance advantage Nvidia has goes right out the window if you can’t fit your whole model in VRAM. I’d take a 24GB AMD card over a 16GB Nvidia card any day.

You could also look at an RTX 3090 (which also has 24GB), but then you’d take a big hit to gaming/raster performance and it’d still probably cost you more than a 7900XTX. Not really sure how a 3090 compares to a 7900XTX in Blender. Anyway, that’s probably a more fair comparison if you care about VRAM and price.

Basically the only thing that matters for LLM hosting is VRAM capacity

I’ll also add that some frameworks and backends still require CUDA. This is improving but before you go and buy an AMD card, make sure the things you want to run will actually run on it.

For example, bitsandbytes support for non-CUDA backends is still in alpha stage. https://huggingface.co/docs/bitsandbytes/main/en/installation#multi-backend

Assuming nominal voltage of 3.7, that’s about 60Wh. For comparison, the 14" MacBook has a 70Wh battery.

That’s not good battery life but it depends on what kind of usage they’re assuming with that 7H number. I’m not sure a MacBook runs that long under high load. If it’s 7H on a heavy load, that’s respectable.

Edit: not sure what class of device is the best comparison here. Laptop? Tablet? Phone? 🤷