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2. Apple AirPods Pro review: The best gets better [Video] - AOL

   www.aol.com/finance/apple-airpods-pro-review...

   Apple's latest second-generation AirPods Pro get major software improvements and a USB-C charging case, building on the company's best earbuds. ... You can still press once to answer calls, but to ...

3. Over 24,000 people love these 2nd-generation AirPod Pros ...

   www.aol.com/lifestyle/heads-apple-airpods-pro-2...

   Here's the quickest AirPods Pro (2nd generation) review on the internet: Yep, they're a little bit better. OK, that's it, thanks for reading! ... The key is to make sure you get a really good seal ...

4. The 12 best affordable AirPods alternatives — starting at ...

   www.aol.com/article/lifestyle/2020/10/19/best...

   Why break the bank for expensive headphones when these AirPods alternatives are sleek, multi-functional and super affordable? Skip to main content. Sign in. Mail. 24/7 Help. For premium support ...

5. AirPods - Wikipedia

   en.wikipedia.org/wiki/AirPods

   Website. apple .com /airpods. AirPods are wireless Bluetooth earbuds designed by Apple. They were first announced on September 7, 2016, alongside the iPhone 7. Within two years, they became Apple's most popular accessory. [4] [5] AirPods are Apple's entry-level wireless headphones, sold alongside the AirPods Pro and AirPods Max .

6. AirPods Pro - Wikipedia

   en.wikipedia.org/wiki/AirPods_Pro

   AirPods Pro. AirPods Pro are wireless Bluetooth in-ear headphones designed by Apple, initially introduced on October 30, 2019. [5] [6] They are Apple's mid-range wireless headphones, available alongside the base-level AirPods and the highest-end AirPods Max . The first-generation AirPods Pro use the H1 chip, also found in the second-generation ...

7. Reinforcement learning from human feedback - Wikipedia

   en.wikipedia.org/wiki/Reinforcement_learning...

   v. t. e. In machine learning, reinforcement learning from human feedback ( RLHF) is a technique to align an intelligent agent to human preferences. It involves training a reward model to represent human preferences, which can then be used to train other models through reinforcement learning . In classical reinforcement learning, an intelligent ...