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Lightly AI VS Apple Machine Learning Journal

Compare Lightly AI VS Apple Machine Learning Journal and see what are their differences

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Lightly AI logo Lightly AI

Improve your machine learning models by using the right data

Apple Machine Learning Journal logo Apple Machine Learning Journal

A blog written by Apple engineers
  • Lightly AI Landing page
    Landing page //
    2023-04-21
  • Apple Machine Learning Journal Landing page
    Landing page //
    2022-12-13

Category Popularity

0-100% (relative to Lightly AI and Apple Machine Learning Journal)

Lightly AI

Apple Machine Learning Journal

AI
26 26%
AI
74% 74
Developer Tools
26 26%
Developer Tools
74% 74
Analytics
100 100%
Analytics
0% 0
Data Science And Machine Learning
22 22%
Data Science And Machine Learning
78% 78

User comments

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Social recommendations and mentions

Based on our record, Apple Machine Learning Journal seems to be more popular. It has been mentiond 6 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.

Lightly AI mentions (0)

We have not tracked any mentions of Lightly AI yet. Tracking of Lightly AI recommendations started around Jul 2021.

Apple Machine Learning Journal mentions (6)

  • 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
  • Which papers should I implement or which Projects should I do to get an entry level job as a Computer vision engineer at MAANG ?
    We even host annual poster sessions of those PhD intern’s work while at our company, and it’ll give you an idea of the caliber of work. It may not be as great as Nvidia, Stryker, Waymo, or Tesla (which are not part of MAANG but I believe are far more ahead in CV), but it’s worth of considering. Source: about 1 year ago
  • Apple’s secrecy created engineer burnout
    They have something for ML: https://machinelearning.apple.com. - Source: Hacker News / about 2 years ago
  • [D] Is anyone working on open-sourcing Dall-E 2?
    They're more subtle about it, I think. https://machinelearning.apple.com/ Some of the papers are pretty good. I don't disagree with your sentiment in aggregate, though. Source: about 2 years ago
  • How does Apple achieve both secrecy and quality for a release?
    Siri is not where it needs to be because Apple refuses to mine user data to enrich it. They also are very hesitant to allow researchers to publish their breakthroughs which makes recruitment very hard. Although this is changing https://machinelearning.apple.com/. - Source: Hacker News / about 2 years ago
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What are some alternatives?

When comparing Lightly AI and Apple Machine Learning Journal, you can also consider the following products

Evidently AI - Open-source monitoring for machine learning models

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

Dioptra - Dioptra is a data centric platform to automate continuous model improvement.

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

JarvisLabs.ai - Let's make AI simple

Lobe - Visual tool for building custom deep learning models

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