[0] https://www.sciencealert.com/a-strange-phrase-keeps-turning-...

In the nicest way possible I'm saying this form of preference testing is ultimately useless, primarily due to a base of dilettantes with more free time than knowledge parading around as subject matter experts and secondarily due to presumed malfeasance. The latter is more apparent to more of the masses (that don't blindly believe any leaderboard they see) now that access to the model itself is more widespread and people are seeing the performance doesn't match the "revolution" promised [0]. If you're still confused why selecting a model based on a glorified Hot or Not application is flawed, perhaps ask yourself why other evals exist in the first place (hint: some tests are harder than others.)

[0](One such instance of someone competent testing it and realizing it's not even close to the "best" model out) https://www.youtube.com/watch?v=WVpaBTqm-Zo

As someone who's been fortunate enough to be fit and able to work out their entire life, not sure how there are people like you who shun and shame those trying to gain a semblance of control over their weight in a world where it does have a real impact whether they get serious medical attention or not. Your likely skewed thoughts on vanity be damned, bigger people are treated worse across the board and GLP-1 is a genuine salve.

Instead of assuming my comment is a generalized view on how businesses should operate as whole (and not the subject of the piece), perhaps take a moment to consider how the magnitude of buybacks--in the face of stiff competition, that have now leapfrogged them--is directly correlated to the mismanagement and dysfunction within Intel that leaves them unable to rise to the challenge the country demands.

During Gemini's initial release the language surrounding nano was that it was only the Pro initially, and I was happy to wait. The complete inability to run it, when the new Samsung phones can (including the model with 8GB as reported above) feels not only like a bait-and-switch/false-advertising, but a constraint based solely on driving sales. It does demand a clear explanation.

I care less about another potential Pixel class action, and more that I have to get another phone to test and deploy my apps to a smaller audience to.

After reading (and attempting to quickly implement the models ensembles within) both the RealFill[0] and Break-A-Scene[1] papers published from Google researchers just prior to the Pixel 8 launch I was expecting either a leap in their G3 tensor core akin to 2013 Moto X NLP+contextual awareness cores[2] (which provided better implementations of Active Display, gesture recognition, and voice recognition in loud environs than 95% of current mobile devices) or the Coral[3], the edge TPU they developed that got shockingly amazing inference performance from (though HW production handed off to ASUS in 2022--thanks to the chip shortage, the general arbitrary nature of the company, and their wholesale divestment from IoT) I expected more.

All that to say this: your assumptions of inference performance on >$1000 hardware are fundamentally flawed (the fact that you reach for the buzzy "generative" prefix suggests they're erroneously informed by twitter influencers and attempting to deploy current LLMs.)

Custom hardware can and has been developed in the past (on mobile devices) that could've been tailored to the task at hand. If they failed to meet performance, power draw, or processing time requirements, they should've reframed their pitch instead of exposing themselves to what is likely going to be yet another class action suit focusing on their hardware.

[0] https://realfill.github.io/ [1] https://omriavrahami.com/break-a-scene/static/paper/Break-A-... [2] https://en.wikipedia.org/wiki/Moto_X_(1st_generation)#Hardwa... [3] https://coral.ai/