04-24-2026Price:

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AI & TECH

Apple's chips position it to dominate AI agents

Friday, April 24, 2026 · from 3 podcasts
  • Apple's privacy model and M-series chips make it the top platform for on-device AI.
  • New CEO John Ternus, a hardware expert, signals a strategic pivot from cloud AI.
  • Apple's strategy avoids the costly cloud war, creating a powerful hardware moat.

Apple spent a year looking like an AI laggard. Its slow, hardware-focused approach is now positioning it to become the dominant platform for autonomous AI agents. The recent "Mac mini renaissance" among open-source developers wasn't an accident; it was a signal.

Aravind Srinivas argued on This Week in AI that Apple's most underrated asset is its silicon. While competitors burn billions on server farms, Apple has secured production for two-nanometer chips designed to run AI agents locally. This moves compute from the cloud to the device, solving the privacy and latency problems that plague cloud-based models when handling sensitive data like emails and health records.

This strategy gives context to the recent leadership change. On The Intelligence, Tom Lee Devlin framed the appointment of hardware chief John Ternus as CEO as a deliberate choice. He's not there to build a better cloud model; he's there to build the AI-native devices - smart glasses and wearables - that make local AI indispensable. After 15 years of Tim Cook's operational focus, which grew the company's value to $4 trillion, the shift is clear.

The contrast with rivals is stark. Google is scrambling, with Sergey Brin reportedly leading a "strike team" to improve Gemini's agentic execution. Amazon is committing $25 billion to Anthropic in an equity-for-compute deal just to keep AWS relevant. They are fighting an expensive war in the cloud.

Apple is fighting on its own turf. On The AI Daily Brief, Nathaniel Whittemore noted that Apple’s perceived inaction now looks like a clever, profitable strategy. By licensing Google's Gemini - a move seen as a dependency just months ago - Apple saved billions in R&D while waiting for its hardware advantage to become undeniable.

The company may not need the smartest model. It just needs to be the best and safest place to run everyone else's. By controlling the on-device orchestration layer, Apple is setting the terms for the agentic era.

Source Intelligence

- Deep dive into what was said in the episodes

Aravind Srinivas & Edwin Chen: The $1B Bootstrap, Apple's AI Edge, and Benchmarks | TWiAI E10Apr 23

  • Aravind Shavas, CEO of Perplexity AI, confirmed the company's revenue grew to $500 million recently, driven primarily by Perplexity Computer's success in simplifying agent orchestration for users.
  • Perplexity Computer provides an intuitive interface for orchestrating multiple AI agents without API keys or complex setup, offering access to various models and connectors for tasks like research, browser automation, and data analysis.
  • Serge AI, which has never raised venture capital, has approximately 130 employees and 50,000 expert contractors, providing services to major AI labs including OpenAI, Google, Anthropic, Microsoft, and Meta.
  • Apple's M-series chips are an underrated asset for local LLM inference, outperforming DGX Spark benchmarks, and the company has already secured two-nanometer chip fab capacity for next year, positioning it for future local AI processing.
  • Aravind Shavas envisions Apple enabling local agent loops to run on devices, preserving user privacy for personal data like photos and messages, believing Apple is uniquely positioned to profit from this due to its chips, OS, and ecosystem.
  • For model evaluation, Edwin Chen advocates measuring real-world human usage and practical helpfulness, rather than contrived benchmarks, ensuring models produce creative and useful outputs that truly benefit users.
  • Aravind Shavas developed Perplexity's 'Model Council' at Jensen Huang's suggestion, allowing users to query multiple models simultaneously, compare their responses, and receive a synthesized analysis highlighting agreements and disagreements.
  • Jason Calacanis praises Whisper Flow for its superior speech-to-text accuracy, especially when combined with a foot pedal for dictating long, detailed prompts, which significantly improves model responses.
  • Aravind Shavas is impressed by the improved Grok integration within X, particularly the 'Explain Grok' button for contextualizing tweets, and by the Gemini 3 Flash model for its exceptional speed and intelligence.
Also from this episode: (8)

Models (5)

  • Edwin Chen, founder and CEO of Serge AI, clarified his company's role as 'AI teaching' rather than simple 'data labeling,' employing highly educated experts to cross-examine and instill values, wisdom, and taste into frontier models.
  • Edwin Chen believes AI models will not be commodified due to their distinct personalities and specializations, arguing users will naturally prefer different models based on their mood or the specific task, similar to choosing friends.
  • Edwin Chen describes LM Arena as a 'terrible cancer on AI,' leading models to prioritize 'pretty formatting' over correctness due to companies optimizing for its visible yet flawed benchmarks, making models ultimately worse.
  • Edwin Chen highlights Claude Design for its well-designed and opinionated interface, which enables non-designers to rapidly prototype new interfaces and landing pages, accelerating product development.
  • Edwin Chen and Jason Calacanis share experiences where AI models, like those analyzing blood work results or personalized health trackers (e.g., Whoop), provided more effective and tailored health recommendations than human doctors.

VC (1)

  • Edwin Chen criticizes the trend of raising excessive AI capital, arguing it incentivizes volume over quality, diverts CEO focus from product to fundraising, and can lead to models prioritizing engagement over genuine usefulness.

Startups (1)

  • Aravind Shavas advises founders to be disciplined capital allocators, maintaining a 'bootstrap founder' mentality even after raising substantial funds, and suggests Perplexity AI aims for profitability without significant increases in payroll or infrastructure.

Enterprise (1)

  • Aravind Shavas argues that value in AI accrues at the application layer, as pure API model companies struggle to maintain a significant lead for long; the performance gap between frontier models typically shrinks to months.

How Apple's AI Strategy Changes with a New CEOApr 21

  • OpenAI released "Chronicle" for Codex, a memory feature using background screen captures to understand user workflows and improve interactions, though it consumes tokens and raises privacy concerns.
  • Anthropic's new "live artifacts" feature for Cowork enables users to build dynamic dashboards and trackers from live data feeds, demonstrated for personalized briefings and mission control.
  • AI development platform Vercel disclosed a security incident where Shiny Hunters, a sophisticated criminal group, accessed systems via compromised employee credentials and exfiltrated user data; Guillermo Rauch suspects AI accelerated the attack.
  • TSMC reported a 35% revenue boost and forecasts over 30% growth but faces capacity limits, with ASML unable to supply lithography machines. Nikkei Asia predicts memory chip shortages until at least 2027, meeting only 60% of demand.
  • Apple initially appeared to lag in AI, but Nathaniel Whittemore notes a "Mac mini renaissance" for open-source agents, and commentators like Ejaz suggest Apple's inaction, licensing Google's Gemini, proved a clever, profitable strategy.
  • Tim Cook is stepping down after 15 years as Apple CEO, having grown the company from $350 billion to $4 trillion. Polymath notes Apple's 11x market cap increase under Cook lagged other major tech companies during the same period.
  • Incoming Apple CEO John Ternus faces the "daunting task" of defining Apple's AI strategy, especially after Tim Cook's "lack of decisiveness" marred previous efforts, according to Mark Gurman's sources, despite Apple's hardware strength.
  • Google established a "strike team," involving Sergey Brin, to improve AI coding and agentic execution, focusing on training models on Google's internal codebase to close the gap with Anthropic's 100% AI-written code.
  • Amazon expanded its Anthropic partnership with a $25 billion investment, providing 5 gigawatts of compute, including Tranium 3 chips, to resolve Anthropic's inference shortage and ensure Claude's availability via AWS.
  • Meta is reportedly planning 10% layoffs impacting approximately 8,000 workers, but also launched "Level Up," a free four-week program with CBRE to train fiber technicians for data center construction, addressing an acute labor shortage.
Also from this episode: (3)

Models (2)

  • Dario Amodei met with White House officials, including Susie Wiles and Scott Bessett, to discuss Mythos' cybersecurity implications, a meeting seen by Nathaniel Whittemore as a potential detente after recent hostile rhetoric.
  • Axios reported the NSA is actively using Anthropic's Mythos preview model, despite the Department of Defense classifying Anthropic as a supply chain risk, indicating cybersecurity needs may outweigh inter-agency disputes.

Startups (1)

  • DeepSeek is seeking its first outside investment of $600 million for a $10 billion valuation, while Cursor aims for $2 billion in funding at a $50 billion valuation, with Andreessen Horowitz leading and NVIDIA potentially participating.

Mac daddy: Apple’s new bossApr 21

  • Apple announced John Ternus, its head of hardware engineering, will succeed Tim Cook as CEO in September, leading the company through the AI era. Tom Lee Devlin notes this choice is consequential, despite Cook remaining executive chairman.
  • John Ternus, who led iPhone successes and developed the first iPad and AirPods, spent almost half his life at Apple and considers Tim Cook his mentor. He shares Cook's understated and unflappable qualities.
  • Tim Cook's 15-year tenure saw Apple's market value rise over 40% to more than $4 trillion in the past year, with profits and annual sales quadrupling. His share price grew nearly 2,000% under his operational leadership.
  • Tom Lee Devlin observes that Apple has lagged its big tech peers in AI, with its 'Apple intelligence' foray perceived as a flop, and will rely on Google's Gemini models for future AI features.
  • Lee Devlin argues Apple's core competitive advantage lies in innovative hardware, not software, making the choice of hardware chief John Ternus strategic. The company hopes Ternus will create next-generation AI-native products like smart glasses.
Also from this episode: (7)

Society (2)

  • Moika Iida reports that women are disproportionately leaving rural Japan for cities due to economic and cultural factors, straining local industries and public services. A 2014 government report warned nearly 900 municipalities could face extinction.
  • Japanese towns are implementing gender equality initiatives, like workshops and anti-sexism manga, to retain women, but Moika Iida notes a tension. Towns often combine these efforts with government-backed matchmaking to encourage marriage and childbirth.

Labor (1)

  • Koyasu Miwa cites Japan's large gender pay gap, especially in rural areas, and a lack of appealing jobs as economic reasons for women's exodus. Deep-seated patriarchal norms also pressure women regarding marriage and family.

History (1)

  • Catherine Nixey states that boredom emerged as a new disease in 18th-century Britain, blamed for social ills and causing lethargy. The word 'bored' first appeared in English in 1768, the same year as 'interesting.'

Psychology (3)

  • Søren Kierkegaard called boredom the 'root of all evil,' and by the 1840s, it reached epidemic proportions in Britain. Scientists have found bored individuals are more prone to binge drinking and sadistic acts.
  • In a Science study, researchers found many participants preferred electric shocks over being alone with their thoughts. This highlights the unpleasantness of solitude and is cited by Catherine Nixey as evidence of boredom's depth.
  • Catherine Nixey observes a modern anxiety about the scarcity of boredom in Britain, now described as an 'endangered state.' Indirect evidence includes declining rates of drinking, reading, and sex among young Britons.