Software Alternatives, Accelerators & Startups

Pacifica VS Apple Core ML

Compare Pacifica VS Apple Core ML and see what are their differences

Pacifica logo Pacifica

Stress and anxiety relief through beautiful CBT tools

Apple Core ML logo Apple Core ML

Integrate a broad variety of ML model types into your app
  • Pacifica Landing page
    Landing page //
    2023-07-21
  • Apple Core ML Landing page
    Landing page //
    2023-06-13

Pacifica videos

2017 Chrysler Pacifica - Review and Road Test

More videos:

  • Review - Is the 2020 Chrysler Pacifica a GOOD minivan to BUY over a Toyota or Honda?
  • Review - 2019 Chrysler Pacifica, one year review!

Apple Core ML videos

IBM Watson & Apple Core ML Collaboration - What it means for app development

Category Popularity

0-100% (relative to Pacifica and Apple Core ML)
Health And Fitness
100 100%
0% 0
Developer Tools
0 0%
100% 100
Meditation
100 100%
0% 0
AI
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apple Core ML seems to be more popular. It has been mentiond 7 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Pacifica mentions (0)

We have not tracked any mentions of Pacifica yet. Tracking of Pacifica recommendations started around Mar 2021.

Apple Core ML mentions (7)

  • Ask HN: Where is Apple? They seem to be left out of the AI race?
    On the machine learning side of AI, they have CoreML. You can drag-and-drop images into Xcode to train an image classifier. And run the models on device, so if solar flares destroy the cell phone network and terrorists bomb all the data centers, your phone could still tell you if it's a hot dog or not. https://developer.apple.com/machine-learning/ https://developer.apple.com/machine-learning/core-ml/... - Source: Hacker News / 4 months ago
  • The Magnitude of the AI Bubble
    Apple has actually created ML chipsets, so AI can be executed natively, on-device. https://developer.apple.com/machine-learning/. - Source: Hacker News / 6 months ago
  • Does anyone else suspect that the official iOS ChatGPT app might be conducting some local inference / edge-computing? [Discussion]
    For your reference, Apple's pages for Machine Learning for Developers and for their research. The Apple Neural Engine was custom designed to work better with their proprietary machine learning programs -- and they've been opening up access to developers by extending support / compatibility for TensorFlow and PyTorch. They've also got CoreML, CreateML, and various APIs they are making to allow more use of their... Source: about 1 year ago
  • Apple to occupy 90% of TSMC 3nm capacity in 2023
    > It’d be one thing if Apple actually worked on AI softwares a bit and made it readily available to developers. * Apple Silicon CPUs have a Neural Engine specifically made for fast ML-inference * Apple supports PyTorch (https://developer.apple.com/metal/pytorch/) * Apple has its own easily accessible machine-learning framework called Core-ML (https://developer.apple.com/machine-learning/) So it would be inaccurate... - Source: Hacker News / about 1 year ago
  • The iPhone 13 is a pitch-perfect iPhone 12S
    This is the developer documentation where they advertise the APIs - https://developer.apple.com/machine-learning/. Source: almost 3 years ago
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What are some alternatives?

When comparing Pacifica and Apple Core ML, you can also consider the following products

Headspace - Meditation made simple. Brilliant things happen in calm minds.

Amazon Machine Learning - Machine learning made easy for developers of any skill level

Synctuition Meditation Program - Synctuition Meditation Program is a world’s most leading meditation app that comes with brand new 3D sounds that enhance the quality of sleep significantly.

TensorFlow Lite - Low-latency inference of on-device ML models

Calm - Calm.com can help you reduce stress and increase calm.

Roboflow Universe - You no longer need to collect and label images or train a ML model to add computer vision to your project.