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Apple has officially selected Google’s Gemini artificial intelligence model to power the next generation of Siri, a strategic move that briefly pushed Alphabet’s market valuation past the $4 trillion mark. The multi-year agreement, confirmed Monday, allows Apple to integrate advanced generative AI capabilities into its devices immediately while it continues to develop its own proprietary foundation models.
Key Points
- Apple-Google Deal: Apple will utilize the Gemini model to upgrade Siri, a deal reportedly valued at $1 billion annually, serving as an interim solution while Apple builds its internal AI infrastructure.
- Market Milestone: Following the news, Alphabet shares surged, allowing the company to briefly surpass a $4 trillion market capitalization.
- Pharma AI Push: Nvidia and Eli Lilly announced a $1 billion joint investment over five years to build a Silicon Valley laboratory dedicated to AI-driven drug discovery.
- Robotics Breakthrough: 1X Technologies revealed a new AI model for its "Neo" android, enabling the robot to learn physical tasks from scratch without prior data training.
The AI Landscape: Alliances and Market Cap Milestones
The confirmation that Apple has chosen Gemini to run AI-powered features on the iPhone marks a pivotal moment in the generative AI race. According to reports cited by Bloomberg and CNBC, the partnership stabilizes Apple’s AI roadmap, which had faced scrutiny for lagging behind competitors. The deal is viewed by analysts as a "bridge" strategy, involving payments estimated at $1 billion per year, ensuring Apple users access top-tier AI while Cupertino engineers finalize their own foundation models.
The announcement had immediate repercussions on Wall Street. Alphabet’s stock rallied significantly, propelling the company’s market value to $4 trillion, briefly overtaking Apple before gains moderated. This valuation shift underscores the market's premium on AI infrastructure and model dominance.
Denny Fish, a portfolio manager discussing the market implications, noted that the industry is seeing a healthy "leapfrogging effect" among major players like OpenAI, xAI, and Google. However, he emphasized that the massive capital expenditure required for this infrastructure is being scrutinized.
"The deployment of the capital is going to be pretty measured... This is hard. Look at what's going on at Stargate in Texas, trying to put up 10 gigawatts. The labor that's needed. The power, the expertise. It's a heavy lift."
From Digital to Physical AI: Nvidia and Eli Lilly
Beyond the digital assistants, the application of AI in the physical world took a significant step forward with a new partnership between Nvidia and pharmaceutical giant Eli Lilly. The companies plan to invest a combined $1 billion over five years to establish a new laboratory in Silicon Valley.
While Eli Lilly had previously partnered with Nvidia in October to develop an AI supercomputer, this new facility focuses specifically on accelerating drug discovery. According to Eli Lilly’s CFO, the ultimate vision is to utilize AI to identify targets for hard-to-treat diseases, such as those requiring gene therapy.
This move signals a shift in investor focus from purely digital AI applications (like chatbots) to physical manifestations. The goal is to reduce the time and cost associated with bringing new pharmaceuticals to market, a process that traditionally takes a decade and billions of dollars.
Frontier Tech: Robotics and Self-Learning Machines
In the robotics sector, 1X Technologies announced a significant update to its "Neo" humanoid robot. The company introduced a new AI model grounded in physics, which reportedly allows the robot to execute tasks it has never encountered before through a simple prompt.
Unlike traditional robotics that rely on specific programming for every movement, the Neo robot utilizes a "world model" to simulate outcomes. This allows the machine to attempt tasks—such as removing a sticky note from a board—by understanding the physics of the environment rather than relying solely on training data.
"It's all about things just being anything that you don't have in your data set, but still being able to have a sensible approach... Now all you need is the robot teaching itself to do these tasks by experimenting and doing it in the real world."
Bernt Øivind Børnich, CEO of 1X, emphasized that safety remains the priority, noting that the robots are designed to be "soft and compliant" to ensure they can operate safely alongside humans while learning through trial and error.
Policy Headwinds and Global Trade
While technology stocks rallied, the broader market faced political and regulatory pressures. In the automotive sector, the European Union is reportedly weighing minimum price floors on electric vehicles (EVs) imported from China as an alternative to steep tariffs. This potential compromise aims to balance Europe’s climate goals—which rely on affordable EV adoption—with the need to protect domestic manufacturers.
Simultaneously, the U.S. financial sector reacted sharply to policy proposals from President Trump regarding consumer credit. The administration has suggested a temporary 10% interest rate cap on credit cards for one year. The proposal caused volatility for payment processors and fintech lenders like Visa, Affirm, and Klarna, as the industry grapples with the potential revenue impact of such a regulation.
As earnings season approaches, investors will be watching closely to see if the massive capital expenditures in AI infrastructure—estimated by Moody's to reach $3 trillion—begin to yield tangible revenue improvements beyond the hardware suppliers.
