Apple Machine Learning Journal Reviews

LaunchDarkly Reviews

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

LaunchDarkly mentions (37)

• How to Add Paid Features to Your SaaS Apps

  This kind of goes without saying since it's the opposite of the first don't I listed, but it's worth restating and giving some examples. Using tools from third parties means taking advantage of what they have done so you don't have to do that work. This means you are free to build things that make your app special. I like to use feature flag tools for this. Some examples are LaunchDarkly, Split, and AWS App... - Source: dev.to / about 2 months ago

• Pivoting a million dollar DevTool startup

  Taplytics is a broad A/B testing platform for marketing teams. While DevCycle is a feature flagging tool built for developers. Taplytics actually has feature flagging, but DevCycle is much more focused and plans to compete directly with incumbents like LaunchDarkly by building a better developer experience (more on how later). But with Taplytics they built so many features and every customer was using them in a... - Source: dev.to / 6 months ago

• Arc Update - 1.20.1 (43987)

  I had a custom rule added to Little Snitch that blocked the following domains: launchdarkly.com, clientstream.launchdarkly.com, mobile.launchdarkly.com. Source: 7 months ago

• Feature flags implementation in Nest.js 😻

  There are however Saas to implement directly a feature management system. Several solutions exist like LaunchDarkly, Flagsmith or Unleash.io. Using a SaaS (Software as a Service) feature flagging solution offers the advantage of a faster and more straightforward implementation process. These services are readily available and can be quickly integrated into your project. - Source: dev.to / 10 months ago

• Boost DX, Enhance UX, and Skyrocket Profits! Dive into a sub-50ms world with Edge Feature Flags 🚀

  Currently, there are numerous feature flag systems available. Options include our own company's open-source system, "Bucketeer", and the renowned SaaS "LaunchDarkly" among others. When comparing these, the following considerations might come into play:. - Source: dev.to / 10 months ago