Hey everyone,
I am just wondering if anyone could explain why my kernel_task is using ~20% cpu and 1.2GB of ram in the background. All I am doing at the moment is watching a youtube video in chrome and writing this in another tab.
For reference I only just received my Macbook Pro about 7 hours ago and have just finished setting it up. Clean install, nothing transferred to it aside from two photos from dropbox. Installed Photoshop and Adobe Bridge, Microsoft Office 360, Java (which I quickly removed since I decided that I did not need it as my Java tasks can be met on my other machine), and Spotify.
All the installers have been removed, there is nothing else on my machine at the moment, it is as fresh as one can be basically.
I have 2 empty folder's in documents and one with the two photos in it, everything else on the machine is listed above.
Thank you
Also was wondering if anyone could tell me what these files are in spotlight search when I search for "java" as I thought I had gotten rid of everything. Photo also attached:
I am just wondering if anyone could explain why my kernel_task is using ~20% cpu and 1.2GB of ram in the background. All I am doing at the moment is watching a youtube video in chrome and writing this in another tab.
For reference I only just received my Macbook Pro about 7 hours ago and have just finished setting it up. Clean install, nothing transferred to it aside from two photos from dropbox. Installed Photoshop and Adobe Bridge, Microsoft Office 360, Java (which I quickly removed since I decided that I did not need it as my Java tasks can be met on my other machine), and Spotify.
All the installers have been removed, there is nothing else on my machine at the moment, it is as fresh as one can be basically.
I have 2 empty folder's in documents and one with the two photos in it, everything else on the machine is listed above.
Thank you
Also was wondering if anyone could tell me what these files are in spotlight search when I search for "java" as I thought I had gotten rid of everything. Photo also attached:
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