I understand the myopic that makes this happen. Amazon gets a marquee event, and supposedly boosts its stature and hopefully drives viewership. Everything a corporate vice president wants. The Emmy organization gets the most money, that they use for⦠whatever. Win-win right?

Well, no. Viewership will drop because now people have to get an Amazon prime subscription as opposed to simply having basic cable, or (gasp!) an antenna. They wonâ(TM)t even know when it happens because they wonâ(TM)t see the ads for it on a competing network. And so what used to be yearly appointment viewing cultural touchstone dies.

See also: Apple and the Charlie Brown specials.

Look, I use HEIC, but JPEG-XL is just better.

* Royalty-free
* Lossless transcoding of legacy JPEGs to immediately reduce their sizes by ~20% (fast enough that you can have webservers do it in realtime)
* Better fine detail / high frequency data representation for the same bitrate. HEIC was designed for video and simply is not as good at stills.
* Faster decoding
* MUCH faster compression
* True progressive decoding - and not old-school blocky progressive decoding, but using a smart algorithm that restores coarse detail (particularly focusing on parts of the image that the eyes immediately focus on) first, then progressively adding in finer detail that the eyes take more time to notice later.
* Vastly better lossless compression
* Better colour depth and native HDR (up to 32 bit per channel)
* Up to 1B x 1B pixel images (again, useful for scientific and engineering applications), with efficient loading (don't have to load and decode the whole 1B x 1B image at full resolution to view it)
* Arbitrary colour spaces - you can even use it for scientific hyperspectral imaging. You can include e.g. alpha, depth maps, thermal data, selection masks, etc etc.

It's just a better format for stills. It's annoying that it's taken this long to get support to take off (because it takes ages for most people to update their browsers), but I'm really glad that it's starting to.

The need for them came from relativity, but the atomic clocks needed to be able to handle such fine corrections are based on the hyperfine transition of 133Cs. You're not getting very far on atomic clocks without particle physics

Okay Felicia.

Sounds like Newton. Long tradition, I guess

"Okay, nuclear power. Yeah. Yeah, they did give us that. That's true. "

"And industrial-scale superconducting magnets!"

"Don't forget GPS satellite relativistic corrections!"

"And radioisotope therapy!"

"Electron beam therapy?"

"World Wide Web, wasn't that created by particle physicists?"

"Yeah, they did do that."

"Capacitative touchscreens too, you know."

"All right, all right, FAIR ENOUGH! But APART from computers, telecommunications, nuclear power, PET scans, MRIs, satellite communications, superconductors, radioisotope therapy, electron beam therapy, heat-shrink tubing, cargo and baggage screening, smoke detectors, muon tomography, capacitative touchscreens, and the World Wide Web, WHAT HAS PARTICLE PHYSICS EVER DONE FOR US?!"

"Synchrotron light sources for drug discovery?"

"Oh, drug discovery?! GROW UP!"

Yeah, what has a better understanding of particle physics ever done for US, huh??? ... ...

_ ...........

if this were true it would not be possible for the system to read the watermark.

You confuse "invisible to humans" with "invisible to statistical analysis". Humans can't, for example, see the difference between metameric colours. Statistical analysis can. Humans can't see minor drift at scales where Brownian motion dominates. Statistical analysis can. Humans can't see the difference between background disease rates and new rising threats. Statistical analysis can. On and on. Statistical analysis is a far more powerful tool than human perceptual abilities.

this is also a lie. Identical thoughts must be expressed identically, otherwise they are, in fact, *different* thoughts.

I literally gave an example above. If you saw "picked a mango", "selected and picked a mango", "from within the tree, picked a mango", you would never think there was anything going on in the choice, and it isn't going to change the story one iota.

("It actually makes RAM needs worse" -> "MoEs actually make RAM needs worse")

It actually makes RAM needs worse than a dense model, for a given quality.

That said, inference techniques like FreeToken are improving MoE swapping performance, so it's not as bad as it once was. Honestly, I would not be at all surprised if we start doing training in a swap-aware manner, where expert cache misses count as loss and models can queue experts to start loading before they're needed. Could even train in two tiers of loading - RAM and disk. Wouldn't that be great? Could run multi-terabyte models on consumer hardware. Training would tend to tend to concentrate key logic and reasoning on small number of very active experts, mixed reasoning/knowledge on less common experts that are usually kept in RAM, and rarer knowledge on experts that usually remain on-disk until needed.

There are well known, reputable abliterators on HuggingFace.

Also, censorship usually (not always) is something you care about for chats, not agentic work.

A .safetensors or .gguf model cannot run code unless you let it. No agentic framework = all it can do is write text. It can't hurt you directly. At worst, it can only lie to you.

It's big, but not good for its size. They're using tricks to pretend that they're better than they are. For example, compare the numbers that they list for the competion on DeepSWE up against the actual DeepSWE scores.

Not cool, Mistral.

Artificial Analysis is overrated, but yes, Mistral is playing fast and loose with their claims.