Apple is significantly broadening its custom silicon horizons, with new processors reportedly under development for its first foray into smart glasses, the next generations of powerful Mac computers, and a pivotal move into dedicated AI server chips, according to detailed reporting from Bloomberg.
This expansive strategy underscores Apple’s commitment to deepening hardware-software integration across its entire product line, bolstering its artificial intelligence capabilities, and directly engaging with competitors in nascent markets like smart eyewear while reinforcing its strength in personal computing and AI processing. For users and the tech industry, this signals Apple’s long-term vision for a more intelligent, interconnected, and power-efficient ecosystem, driven by its own meticulously crafted silicon.
The most strategically significant development may be Apple’s push into AI server chips, reportedly under the codename ‘Baltra’ and potentially involving collaboration with Broadcom. These server-grade chips, expected to be completed around 2027 are designed to handle the demanding backend processing for Apple Intelligence features.
The initiative appears to be an evolution of an earlier effort known as Project ACDC (Apple Chips in Data Center), which aimed to create custom AI accelerators. By developing its own server chips, Apple could reduce its current reliance on third-party infrastructure, such as AWS’s Trainium2 chips which Apple presently uses for some AI model pretraining, and potentially achieve greater performance, cost efficiency, and enhanced privacy for its AI services.
Another key area of innovation is the development of specialized, ultra-low-power chips for smart glasses, a project codenamed N401. Drawing inspiration from Apple Watch processors, these chips are engineered for optimal power efficiency and will manage multiple cameras and AI-driven user assistance features, writes Bloomberg.
Mass production with TSMC, Apple’s long-standing chip manufacturing partner is reportedly targeted for late 2026 or 2027, suggesting a potential product launch within the next two to three years. This move would place Apple in direct competition with Meta’s Ray-Ban smart glasses, which, as have sold approximately 2 million units since 2023, and that expect significant AI powered improvements like facial recognition. Apple CEO Tim Cook is reportedly determined to make a significant impact in this emerging wearable category and already working on their own smart glasses.
Next-Generation Silicon For Macs And Wearables
Apple’s relentless pursuit of performance and efficiency continues with its Mac silicon roadmap. Following the M4 series, which included the powerful M4 Max that set new performance benchmarks, Apple is reportedly developing the M5 chip, anticipated for iPad Pro and MacBook Pro models by the end of 2025.
Beyond that, future generations codenamed M6 (Komodo), M7 (Borneo), and an even more advanced Mac system-on-chip (SoC) known as ‘Sotra’ are in the works, according to Bloomberg. This dedication to in-house Mac chip development builds on successes like the M3 Ultra, which Johny Srouji, Apple’s Senior Vice President of Hardware Technologies, described in an Apple official statement as “the pinnacle of our scalable system-on-a-chip architecture, aimed specifically at users who run the most heavily threaded and bandwidth-intensive applications.”
Apple’s silicon ambitions also extend to its broader wearable lineup. New chips are reportedly being designed for future camera-equipped AirPods (codenamed Glennie) and Apple Watches (codenamed Nevis), with an estimated completion around 2027, according to Bloomberg. This comprehensive chip strategy is supported by Apple’s substantial $500 billion investment in U.S. manufacturing, AI data centers, and semiconductor partnerships.
As part of this investment, a new AI server manufacturing facility is planned for Houston, Texas, expected to be operational in 2026, building upon Apple’s previous $430 billion U.S. investment announced in 2021. Tim Cook emphasized this commitment, stating, “We are bullish on the future of American innovation, and we’re proud to build on our long-standing U.S. investments with this $500 billion commitment to our country’s future,”.
Strategic Rationale And Navigating Challenges
The drive to develop custom silicon across such a wide array of products offers Apple numerous advantages. In-house server chips like Baltra could provide tailored performance for Apple Intelligence, potentially surpassing the capabilities of current solutions that adapt Mac chips for server tasks. As Data Center Dynamics (DCD) noted, “While Apple currently does AI processing on high-performance chips originally designed for Macs, those chips were not expressly designed for that purpose and therefore aren&t as fast or energy efficient as those that have been, posing a challenge for the company as it plans to continue rolling out and scaling up its AI features and services.”
Custom chips also align with Apple’s strong emphasis on privacy and security, a point Craig Federighi, Apple’s SVP of Software Engineering, highlighted at a past WWDC when he said, “We’re investing in both on-device intelligence and cloud-based AI to deliver better user experiences while maintaining our commitment to privacy.” Furthermore, this vertical integration could reduce reliance on third-party chipmakers like Nvidia, especially in the competitive AI hardware space.
However, Apple’s ambitious roadmap faces several potential obstacles. The significant U.S. investment is reportedly tied to securing government incentives, including CHIPS Act funding, which involves ongoing negotiations. The tech giant also competes for a limited pool of highly skilled semiconductor engineers and AI specialists.
Moreover, supply chain complexities, such as key manufacturing partner Foxconn’s extensive commitments to Nvidia for its AI superchips, could introduce delays or capacity constraints for Apple’s new chip production. Bloomberg previously reported that Apple’s AI technology itself needs to ‘vastly improve’ before it can deliver truly compelling AI-centric devices, a challenge that underpins the necessity of these advanced chip developments.
