Neil Cybart 12/17/24 Neil Cybart 12/17/24

Apple Releases Second Wave of Apple Intelligence, My Initial Thoughts on Visual Intelligence, Image Playground Beats Expectations

With iOS 18.2, iPadOS 18.2, and macOS Sequoia 15.2 now out, the second wave of Apple Intelligence features has gone live for the U.S. and localized English for Australia, Canada, Ireland, New Zealand, South Africa, and the UK.

For many Apple users with supported hardware, this second wave will be the one that truly showcases Apple Intelligence. While Writing Tools and things like notification summaries may have their audiences, this second release phase includes Image Playground, Genmoji, Image Wand, visual intelligence, and ChatGPT integration, among other features.

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Neil Cybart 11/21/24 Neil Cybart 11/21/24

Apple Releases Apple Intelligence Ads, The Controversy Surrounding the Ads, My Verdict

Hello everyone. We are going to shift back to talking product. Today’s update will be focused on Apple Intelligence ads, some of which are causing quite the stir online. The tentative plan for tomorrow is that we will talk screens in the home.

Let’s jump into today’s update.

Apple Releases Apple Intelligence Ads

Over the past two months, Apple has released seven ads for Apple Intelligence.

The first tranche of ads, with actress Bella Ramsey from “Game of Thrones” and “The Last of Us,” came out at the end of September. The ads were from Apple’s ad agency TBWA\Media Arts Lab.

1) iPhone 16 Pro - Email summary. Bella uses email summary to quickly go over an email pitch from her agent that she forgot to look at. The copy attached to the video ad on YouTube includes: “Tap to reveal a summary of a long email in the Mail app and cut to the chase. You can also view summaries of emails right from your inbox.” The video has 5.2M views on YouTube (10K up votes).

2) iPhone 16 Pro - Custom memory movies. Bella helps a Dad trying to eulogize his daughter’s pet fish buried in the backyard by creating a memory movie using photos of the daughter with the fish. “Create a custom memory movie by entering a description in Photos, and Apple Intelligence will find the best photos and videos to craft a storyline with its own narrative arc.” 320K views on YouTube (9K up votes).

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Neil Cybart 10/21/24 Neil Cybart 10/21/24

Thoughts on the Tim Cook Profile in WSJ Magazine

Yesterday, WSJ Magazine published a Tim Cook profile (the piece is available via Apple News+ here) for its annual Innovators issue. Cook, along with a few other recipients, will be recognized at the WSJ's 14th Annual Innovator Awards next week.

Apple smartly used the profile to put the spotlight back on its products.

In today’s update, we go over my thoughts on the profile. In addition to the broader themes found in the profile, we go over a few areas where the WSJ profile was lacking.

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Neil Cybart 6/13/24 Neil Cybart 6/13/24

How Apple Intelligence Was Developed, Ranking Apple Intelligence Features, AAPL’s Wacky Price Action

There is value found in spending time on the details regarding how Apple Intelligence was developed and functions. We will then go over my thoughts on the various Apple Intelligence features, ranking the features from most impressive to most concerning. We will then address AAPL price action.

Happy Thursday. It’s been a very busy week. As a reminder, we still have some WWDC news to go over early next week.

There’s a lot to cover today, so let’s jump right in.

How Apple Intelligence Was Developed

During Apple’s Platforms State of the Union presentation (available to view here), which is aimed at developers, the company went into detail regarding how Apple Intelligence was developed.

Apple Intelligence began with an on-device large language model that Apple built to achieve a certain power/size balance that allowed it run on device yet power the experiences Apple wanted to offer. Apple relied on fine-tuning to “teach” the model certain tasks such as text summarization, proofreading etc. Instead of producing different models with different expertise objectives, Apple relied on adapters which basically gave the foundation model specialization capabilities.

Apple then compressed the model (16-bit per parameter down to 4-bit) with on-device being the goal.

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