But it's $1600 Apple. Not the cheapest Mac book air.
this post was submitted on 09 Nov 2023
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I still hate that they killed the mid-range model. Your option is the lower end MacBook Air with no fan, or the higher-end MacBook Pro. There is no in between.
I absolutely love the snappiness of the m1 chip in my current 2020 MBP, and how much more efficient ARM is compared to x86, but it seems really hard to justify going an extra 300$ in the future.
I really just wish they would bring back the original MacBook (with no suffixes at the end)
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Ridiculous.
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With the launch of Apple's M3 MacBook Pros last month, a base 14-inch $1,599 model with an M3 chip still only gets you 8GB of unified DRAM that's shared between the CPU, GPU, and neural network accelerator.
In a show of Apple's typical modesty, the tech giant's veep of worldwide product marketing Bob Borchers has argued, in an interview with machine learning engineer and content creator Lin YilYi, that the Arm-compatible, Apple-designed M-series silicon and software stack is so memory efficient that 8GB on a Mac may equal to 16GB on a PC – so we therefore ought to be happy with it.
With that said, macOS does make use of several tricks to optimize memory utilization, including caching as much data as it can in free RAM to avoid running to and from slower storage for stuff (there's no point in having unused physical RAM in a machine) and compressing information in memory, all of which other operating systems, including Windows and Linux, do too in their own ways.
Given a fast enough SSD, the degradation in performance associated with running low on RAM can be hidden to a degree, though it does come at the expense of additional wear on the NAND flash modules.
We'd hate to say that Apple has designed its computers so that they perform stunningly in the shop for a few minutes, and work differently after a few months at home or in the office.
His comment is also somewhat ironic in that much of the focus of YilYi's interview with Borchers centered around the use of Apple Silicon in machine-learning development, which you don't do in a store.
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