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Apple announced a new feature for developers today called Create ML. Since machine learning is a commonly used tool in the developer kit these days, it makes sense that Apple would want to improve the process. But what it has here, essentially local training, doesn’t seem particularly useful.
The most important step in the creation of an machine learning model, like one that detects faces or turns speech into text, is the “training.” That’s when the computer is chugging through reams of data like photos or audio and establishing correlations between the input (a voice) and the desired output (distinct words).
Part - Process - Orders - Magnitude - Power
This part of the process is extremely CPU-intensive, though. It generally requires orders of magnitude more computing power (and often storage) than you have sitting on your desk. Think of it like the difference between rendering a 3D game like Overwatch and rendering a Pixar film. You could do it on your laptop, but it would take hours or days for your measly four-core Intel processor and onboard GPU to handle.
That’s why training is usually done “in the cloud,” which is to say, on other people’s computers set up specifically for the task, equipped with banks of GPUs and special AI-inclined hardware.
Create - ML - PC - Briefly - Stage
Create ML is all about doing it on your own PC, though: as briefly shown on stage, you drag your data onto the interface, tweak some stuff, and you can have a model ready to go in as little as 20 minutes if you’re on a maxed-out iMac Pro. It also compresses the model so you can more easily include it in apps (a feature already included in Apple ML tools, if I remember correctly). This is mainly possible because it’s applying Apple’s own vision and language models, not building new ones from scratch.
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