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13" MacBook Pro (M2) 'core' question???


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If you dig into the tech specs, you’ll find that four of those cores are „Performance“ cores, and four are „Efficiency“ cores. 
 

In other words, four of them are super-low-power, intended for keeping basic idle tasks and system processes running without having to keep the heavy-iron performance cores fired up all the time. 
 

All of the heavy lifting is done on the other four cores, which are only powered up when the need arises. 
 

This is one of the reasons these machines achieve such insane battery life. 

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58 minutes ago, analogika said:

If you dig into the tech specs, you’ll find that four of those cores are „Performance“ cores, and four are „Efficiency“ cores. 
 

In other words, four of them are super-low-power, intended for keeping basic idle tasks and system processes running without having to keep the heavy-iron performance cores fired up all the time. 
 

All of the heavy lifting is done on the other four cores, which are only powered up when the need arises. 
 

This is one of the reasons these machines achieve such insane battery life. 

Very good to know. Also, battery life is amazing on this computer. Thanks for explaining!!! 👍

What does Apple mean by 16-core neural engine? 

Edited by deckard1
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41 minutes ago, conanthewarrior said:

I am really behind with the times, but what is "machine learning"?

 

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Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks.[1] It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so.[2] Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.

https://en.wikipedia.org/wiki/Machine_learning

It's a very useful tool that's letting computers do some incredible things, so having dedicated silicon speeds these processes up significantly...

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A fairly simple example of "machine learning" is – thanks to a one "Dr. Kurzweil," whose name you might recall from music synthesizers – the present ability of your phone to "take dictation," instead of requiring you to manually type-in your text messages.  You may have also noticed that it magically seems to adapt to the various words and phrases that you commonly use, "becoming more accurate with time."

Many decades ago, a too-well funded defense project for "Russian-to-English translation" (back when we had no available computer-power whatsoever ...) produced the following now-comical result:  "The spirit is willing but the flesh is weak" ... became ... "The wine is acceptable but the meat has spoiled."

The conundrum of the computer programmers of that time, aside from the fact that they possessed far less computing power than you could expect from a cigarette lighter today, is that there was no (known) if...then...else strategy to get from one place to the other.

Edited by MikeRobinson
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