End Of Day 1: The Keynote And Platforms State Of The Union Those give a good overview of what to concentrate on for the rest of the week. My plan for the day is to watch the keynote live, and then to watch the Platforms State of the Union. It’s just a list of things I wanted to use in 2017 but found them underpowered or too hard for me to get started with, and was hoping Apple would make some improvements. On the morning of WWDC, I tweeted this: My tweet describing what I was hoping for from WWDC 2018 ( Large preview) But in the meantime, I hoped for increased spatial accuracy.įinally, I love Xcode Playgrounds and iPad Playground books, but they need to to be a lot faster and stable, so I was hoping for something there too.

It was a long-shot, but for AR, the next step is a device. For Siri, I wanted to see many more intents and possibly some indication that intents would be a thing that would be added year round.

Specifically, as an iOS developer, I wanted to see many more Core ML models, spanning more than just image classification and more help in making models. With all of this in the back of my mind, I personally was hoping to hear that Apple was going to make some major improvements in AR, ML, and Siri. The introduction of HomePod last year only highlighted Siri’s woes, and a widely reported customer satisfaction survey showed 98% satisfaction with iPhone X but only a 20% satisfaction with Siri. One issue I explored was how Siri’s emphasis on pre-defined intents limits its range but hasn’t produced the promised accuracy that you might get from a bounded focus. There doesn’t seem to be a lot of energy around exploring wildly different applications (even though we all know the ML is at the core of self-driving cars and whiz-bang demos like Google Duplex).Īnother way Apple uses ML is in Siri, and earlier this year, I wrote about SiriKit and mentioned its perceived and real deficiencies when compared to Alexa and Google. But from the outside, Core ML seems mostly to have one obvious use: image classification. In the Apple/ML space, Swift creator, Chris Lattner, is taking a different approach with Swift for TensorFlow. Apple did not add to its initial library of Core ML downloadable models after the Core ML announcement.Īpple did release Turi Create and Lobe released a new interesting Core ML model maker last month. ARKit has spawned some interest, but no killer app (perhaps Pokemon Go, but that was popular before ARKit).

It was refreshing to see Apple focus on Machine Learning (ML), but there wasn’t much follow up in the rest of 2017. Last year, I wrote that ARKit and Core ML were two of the big highlights. It’s the morning of June 4th, and I’m reviewing my notes from WWDC 2017. Even though the weather is cool and rainy this week in NYC, I’m in a summer mood and looking forward to the renewal that summer and WWDC promise. The traditional boundaries of summer in the US are Memorial and Labor Day, but iOS developers mark the summer by WWDC and the iPhone release. Lou Franco watched this year’s event and shares his notes and references in case you missed out. Since 1987, the Apple Worldwide Developers Conference (WWDC) has been taking place annually and keeping iOS developers on their toes.

Apple keynote summary 2018