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First noticed by developer Steve Troughton-Smith, the leaked firmware provides a few interesting tidbits.
First, HomePod is listed as an iPhone SE in the iTunes store; curious because it has an A8 SoC, while the 5 SE proper has an.
But, the HomePod does run a full client, so that may be 5 reason for the designation, at least this early on.
A slim bezel encompasses the screen, which is only interrupted by a sliver up top which we assume will house the speaker, camera and new sensors.
Those sensors will be used for facial recognition, another feature confirmed with these leaks.
Changes to — but not significant ones.
It will likely allow developers to simply utilize it and let the API itself do the heavy lifting of figuring out which method of biometric security the device https://csgoup.ru/100/akkumulyatornaya-batareya-ventura-hr-1234w-9-ach.html 5 again, Touch ID may still be in play in the Pro.
But what about the Home нажмите чтобы прочитать больше 5 the Home button isand there are no indications that iOS 11 will make any concessions on this front.
Whether it be facial recognition, fingerprints or eye scanning, BiometricKit would be a good home for all of it.
It may also loop in eye scanning, перейти на страницу could be complimentary or a second form of authentication.
Either way, light code changes will be necessary.
If the new iPhone has facial scanning and not Touch ID, reverting to passwords will be clumsy for users.
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Where 5 this estimate come from?
Dice predicts salary ranges based on the job title, location, and skills listed in individual job descriptions.
Our proprietary machine-learning algorithm uses more than 600,000 data points to make its predictions.
To get the most accurate prediction of the salary you might earn, customize the prediction in your Dice profile.
Actual salary offered by employer may vary.
How was this salary estimate calculated?
Dice's predictive salary model is a proprietary machine-learning algorithm.
Unlike many other salary tools that require a critical mass of reported salaries for a given combination of job title, location and experience, the Dice model can make accurate predictions on even uncommon combinations of job factors.
The model does this by recognizing patterns in the more than 600,000 salary data points to infer how much each factor - job title, location, experience, education, and skills - will impact the salary.
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Nate has written for 5 like SlashGear and The Next Web.