Apple Intelligence has been fueled by the company’s silicon initiatives, as highlighted in a recent interview. Notably, these initiatives underwent a significant transformation back in 2017 in anticipation of advancements in AI.
The latest episode of The Circuit podcast features hosts Ben Bajarin and Jay Goldberg interviewing Apple executives Tom Boger and Tim Millet.
The discussion centers around Apple silicon, exploring the interplay between AI and the company’s silicon development efforts.
It’s revealed that the initial Neural Engine was developed as part of Apple’s push into computational photography, which ultimately enabled their AI success.
Here’s a noteworthy excerpt regarding a pivotal decision made in 2017 that set the stage for AI implementation on M1 devices:
We launched [the Neural Engine] in 2017, but something else of interest transpired that year: the release of the paper Attention is All [You Need]. This paper significantly influenced the development of transformer networks… My team took notice. They were engaged with the concepts presented in that paper back in 2017 and realized, wow, this could be very important. We knew we needed to adapt accordingly.
Thus, we began re-architecting our neural engine as soon as we started rolling it out, ensuring that by the time we launched M1 during the transition to Apple silicon in 2020, we could effectively run these networks. So, what did this entail? It allowed us to confidently assert that we could support Apple Intelligence across all Macs equipped with Apple Silicon. Thanks to M1, we prepared ourselves by monitoring trends and making timely innovations, understanding that proper silicon integration takes time.
While Apple Intelligence didn’t exist in 2017, the proactive measures taken by Apple’s silicon teams to enhance the Neural Engine were crucial in enabling 2020 Macs to support the new software today.
The complete interview is available on Apple Podcasts and is definitely worth a listen.
What are your thoughts on the AI insights shared in the interview? We’d love to hear your opinions in the comments.
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