ah yes, the age-old traditional camera square, first pioneered in the year of 2018. truly a bygone era
> **Based on a count of independent hardware security subsystems and components.
That does not seem like a meaningful measure for security.
I had to buy a new phone and I am really happy that Pixel 6 looks promising, otherwise iPhone would have been the only choice. I really wish Samsung would get its act together on software and updates, as they have really compelling hardware. For now, at least from the preview of Verge it looks like I will probably pick up a Pixel 6.
It seems that CPU design for phones and for data centres are quite different problems, or do you see them as facets of the same problem?
At least that's what Apple seems to have done between M1 and A series processors.
(Disc: I work for Google, but not in Cloud nor Pixel)
Still limited by the same TDP. Just as data point and prospective Apple spend more TDP budget on its mobile CPU core than any current ARM Server CPU core.
I am most interested in their choice of GPU. Would it be AMD?
What's the useful advantage to a flush back? I don't really see any. As long as I can hold the phone, and it can lie on a table or stand without wobbling, it seems to do what it needs to.
It's not like you're stacking phones on top of each other the way you do books or magazines. (And heck if you work in repair or provisioning and actually do stack phones, it's easy enough to turn every other one 180°.)
Also I don't know where you're getting "fraction of a millimeter" from. Camera bumps are significantly more than a whole millimeter. And their function is depth, not volume -- you can't redistribute it across the whole case or anything. You'd have to make the entire phone thicker, and then heavier as well if you're putting anything into the new extra space.
As phones they couldn't be more different. The Fold3 aims to completely change the way we experience phones, while compromising on standard phones essentials (camera).
On the other hand, the Pixel6pro looks to be a final evolution of the classical smartphone, maximizing for battery, camera, software-smoothness and hitting all the essentials correctly.
I agree with you, but at this point I'm used to cases anyway. If nothing else, I like being able to flip the phone over on its screenside without the screen touching the surface.
Regardless, I'm sure someone will make a case that mostly flush.
For example, reading over some paper documents, whilst using your phone's calculator.
Guess I shouldn't have gotten my hopes up for a surge of small phones spurred by the iPhone 12 Mini. Which is a real shame, since I'm way overdue for an upgrade but 99% of phones are way too large.
First they have the Nexus 7, Nexus 4, Nexus 10, and then ... Nexus 5, Nexus 6, Nexus 9, ... oh wait they aren't versions, they are number of inches ... -____-
And then they have Google Hangouts, Google Hangouts Meet, google Meet, Google Chat, Google Hangouts Dialer, Google Duo, Google Uno, uh ....
And then now TensorFlow and then Tensor ... is that like TensorFlow without the flow?
(Disc: Work for Google, not on Pixels)
Previous Pixels worked great but then inexplicably lost OS updates after only a few years.
AFAIK it's not inexplicabile, it's just Quallcomm stopping driver support for newer Android versions a few short years down the road, since they're in the business of selling as many chips as possible and can't monetize the users keeping their phone longer like Apple and Google can with their software and services.
Google uses LTS Linux kernels for Android, and once upstream stops supporting a version, the phone usually stops getting support shortly after.
I just wish batteries become replaceable again, my phone is 3.5 years old and the only thing that is noticeably worse is battery life. If we are gunning for longer update cycles, batteries should ideally be replaceable. I sincerely hope some big country takes up this as an environmentally friendly/right to repair thing and forces all manufacturers to do this.
Weirdly my 3.5 year old phone actually has about the same battery life as it started with. As android 3.5 years ago was terrible at battery management, so software updates have compensated for battery degradation.
First they have the Nexus 7, Nexus 4, Nexus 10, and then ... Nexus 5, Nexus 6, Nexus 9, ... oh wait they aren't versions, they are number of inches ... -____- and most people in this world don't even think in inches -_____-
And then they have Google Hangouts, Google Hangouts Meet, google Meet, Google Chat, Google Hangouts Dialer, Google Duo, Google Uno, uh ....
And then now TensorFlow and then Tensor ... is that like TensorFlow without the flow?
> Osterloh did explain that the SoC is an ARM chip designed around a TPU, or Tensor Processing Unit
- slate form factor < 6"; the phone should fit in my damn pocket - no hole punch or notch for the camera on the front (how was this even acceptable to consumers, it looks like shit) - no otherwise irregular protrusions for the back camera or whatever
Is this just impossible now?
Think Galaxy S9, but just with upgraded hardware and maybe smaller bottom bezels.
Looks like getting Qualcomm out of the picture is one motivation.
What is the benefit of having all of the ML bits on device? Can models leverage them post training?
Yes, the whole point is to be able do to things like improve personalized speech recognition on-device, image recognition on-device, translation on-device, etc.
Potentially improved privacy (this is how Apple tries to sell it). Less data has to leave the phone to gain the utility of the ML models.
Improved device performance. Reduced network use and better specialized chips leading to better performance. Either in terms of better battery life or better time to get the result.
On a Google device I would say the potential is reduced to zero!
Yes. The whole point is that you have a slow process train the model offline on very large volumes of sample data, then use that trained model to make actual inferences based on data you find in the field. As those models become bigger and more complex, it takes progressively more computing power to run inference on those models. These ML accelerators are effectively the new GPUs — highly specialised processors designed to more efficiently handle highly specialised workloads.
