Apple is now manufacturing roughly a quarter of its iPhones in India, reaching a milestone that analysts at JPMorgan projected in 2022 as the company gradually reduces its reliance on China as its primary manufacturing hub.

According to a report by Bloomberg, about 55 million iPhones produced last year came from India, out of an estimated 220 million to 230 million units manufactured globally. The figure indicates that Apple has quickly scaled production in the country, turning India into one of the most important pillars of its global supply chain.

The expansion is part of a broader strategy by the company to spread manufacturing across multiple countries, limiting exposure to geopolitical tensions, supply disruptions, and shifting trade policies that have complicated operations in China in recent years.

Apple has accelerated its manufacturing shift over the past year. The company produced the entire iPhone 17 lineup in India ahead of its global launch in September, marking a significant development in Apple’s production strategy. Previously, the earliest batches of new iPhone models were almost exclusively assembled in China, with other countries joining the production cycle later.

Speaking about the company’s evolving supply chain strategy, Apple chief executive Tim Cook said the majority of iPhones sold in the United States are now supplied from India-based manufacturing facilities. That shift indicates that India has rapidly moved from a secondary assembly location to a central manufacturing base.

Industry analysts say the transformation of Apple’s supply chain has been years in the making. The COVID-19 pandemic first exposed the risks of heavy dependence on Chinese manufacturing when lockdowns disrupted operations at major iPhone assembly plants. Since then, Apple has steadily expanded production partnerships in India with key contract manufacturers.

The pace of diversification increased in 2025 as uncertainty grew around U.S. tariff policies affecting Chinese imports. The shifting trade environment has prompted companies with global supply chains to reassess production locations and build redundancy into manufacturing networks.

The issue has also drawn political attention. At a business summit in Doha in May, U.S. President Donald Trump reportedly warned Cook against accelerating Apple’s manufacturing expansion in India, highlighting how the company’s supply chain strategy intersects with wider economic and trade priorities.

On the other hand, Apple’s expansion represents a major win in India’s effort to position itself as a global electronics manufacturing hub. The country has introduced a range of incentives under its production-linked incentive (PLI) scheme to attract large-scale technology manufacturing investments from companies seeking alternatives to China.

Apple’s contract manufacturing partners — including large electronics assemblers — have significantly expanded factory capacity in India in recent years, allowing production of newer iPhone models to begin earlier in the product cycle. The shift has also coincided with rapid growth in Apple’s presence in the Indian consumer market, which the company increasingly views as one of its most promising long-term growth opportunities.

According to data from analyst firm Counterpoint Research, Apple shipped about 14 million iPhones in India last year, representing a 9% increase from the previous year. That growth reflects the gradual expansion of Apple’s customer base in a country long dominated by lower-cost Android devices.

In revenue terms, the market has become increasingly significant. Bloomberg reported that iPhone sales in India exceeded $9 billion last year, highlighting how rising incomes and expanding premium smartphone demand are reshaping the market.

Apple has also been steadily increasing its retail footprint in the country. The company opened its sixth Apple Store in India last month, adding to the flagship outlets launched earlier in major cities as part of its push to strengthen direct engagement with customers.

The company is also exploring ways to deepen its ecosystem presence in the country. Apple is reportedly in discussions to launch its digital payments service, Apple Pay, in India later this year, a move that would expand its services portfolio in one of the world’s fastest-growing digital payments markets.

Analysts say the parallel expansion of manufacturing and consumer sales in India gives Apple a strategic advantage. Producing devices locally not only helps the company diversify supply chains but also reduces import costs and improves its ability to compete in a price-sensitive market.

At the same time, the growing scale of production in India illustrates how the global electronics supply chain is slowly evolving away from a single-country manufacturing model toward a more distributed network spanning multiple regions.

That shift could prove essential for Apple as geopolitical tensions, trade disputes, and regulatory pressures continue to reshape the global technology industry.

Nvidia is developing an open-source platform for artificial intelligence agents called “NemoClaw,” positioning itself to capitalize on the explosive growth of agentic AI tools, according to a Wired report, citing anonymous sources familiar with the matter.

The company has begun pitching the platform to major enterprise software providers, including Salesforce, Cisco, Google, Adobe, and CrowdStrike, in hopes of securing partnerships that would integrate NemoClaw into their ecosystems. Neither Nvidia nor the named companies immediately responded to requests for comment on the report.

Sources indicated that no formal partnerships have been finalized, though early access to the platform is expected to be offered in exchange for contributions to the open-source project. Because NemoClaw will be fully open source, partners would gain free usage rights, with Nvidia aiming to build a broad, collaborative ecosystem around agent development and deployment.

The platform is designed to enable companies to deploy AI agents that perform complex, multi-step tasks for employees — such as automating workflows across CRM, security, collaboration, and productivity tools — while incorporating built-in security and privacy controls. A key feature is hardware-agnostic access: companies can use NemoClaw regardless of whether their infrastructure runs on Nvidia GPUs, lowering barriers to adoption and positioning the platform as a neutral, foundational layer for enterprise agentic AI.

Nvidia’s Push into Agentic AI

Nvidia’s move denotes a deliberate shift from its core strength in AI training and inference hardware toward software and ecosystem layers that drive end-user adoption. The company has released several foundational models optimized for agentic use cases in recent months, including:

• Nemotron — a family of open models focused on reasoning, planning, and tool use.
• Cosmos — a multimodal agent framework designed for real-world task execution.

These models complement Nvidia’s existing NeMo platform, which provides end-to-end tools for building, customizing, deploying, monitoring, and optimizing AI agents — from data curation and fine-tuning to safety alignment and performance evaluation.

The NemoClaw name appears to be a deliberate nod to the viral success of OpenClaw (originally Clawdbot, then Moltbot), the open-source AI agent project that burst into mainstream awareness in late January 2026. Created by an Australian developer who was quickly acquired by OpenAI, OpenClaw demonstrated the power of lightweight, locally runnable agents that perform sequential tasks via natural-language interfaces on messaging apps (WhatsApp, Telegram, Discord).

Nvidia CEO Jensen Huang called OpenClaw “the most important software release probably ever,” underscoring the company’s view that agentic AI represents the next major wave beyond large language models.

Security and Enterprise Readiness

While OpenClaw’s consumer success has been dramatic, experts have repeatedly flagged security risks — especially for enterprise use cases. Agents with broad access to email, calendars, documents, codebases, and internal tools can introduce vulnerabilities ranging from data leakage and prompt injection to unintended actions with real-world consequences.

Nvidia’s NemoClaw is expected to address these concerns head-on with enterprise-grade features:

• Fine-grained access controls and permission boundaries.
• Audit logs and behavioral monitoring.
• Built-in safeguards against prompt injection and jailbreaking.
• Compliance tooling aligned with SOC 2, ISO 27001, and GDPR requirements.

By offering these controls natively, Nvidia aims to make agentic AI palatable to risk-averse Fortune 500 companies and regulated industries — sectors that have so far been cautious about adopting consumer-grade agent tools.

Developer Conference & The Market

Wired report arrives just one week before Nvidia’s annual GTC developer conference (March 17–20, 2026) in San Jose, where CEO Jensen Huang is expected to deliver a major keynote. GTC has historically been the venue for Nvidia’s most significant hardware and software announcements, including new GPU architectures (Blackwell in 2024, Rubin expected in 2026) and ecosystem expansions.

Industry watchers anticipate that NemoClaw — or at least a preview of its capabilities — could feature prominently, alongside updates to NeMo, Nemotron, Cosmos, and Nvidia’s broader AI software stack (NIM microservices, Blueprints, etc.). The conference is also likely to include announcements on partnerships with enterprise software vendors, potentially confirming some of the companies named in the Wired report.

Nvidia’s agentic push comes amid fierce competition:

• OpenAI has aggressively expanded ChatGPT’s agent capabilities (e.g., GPT-4o with tool use, custom GPTs, and enterprise connectors).
• Anthropic’s Claude has surged in enterprise adoption after refusing unrestricted Pentagon use, emphasizing safety and constitutional AI principles.
• Google has integrated Gemini deeply into Workspace (with Gemini for Gmail, Docs, Sheets, Meet) and is rolling out agentic features across Google Cloud.
• Microsoft has embedded Copilot agents throughout its 365 suite and Azure ecosystem.

Nvidia’s hardware-agnostic approach with NemoClaw — combined with its dominant position in AI training/inference chips — gives it unique leverage: it can court developers and enterprises regardless of which model they prefer, while ensuring that Nvidia GPUs remain the preferred compute backend.

The announcement (if confirmed at GTC) could reinforce Nvidia’s narrative as the “picks and shovels” provider of the AI era — not just selling GPUs but enabling the entire agentic software stack. Shares have been volatile in recent months amid concerns over AI spending sustainability, U.S.-China tensions, and emerging competition from Chinese AI chipmakers.

A successful agent platform launch could bolster investor confidence in Nvidia’s software moat and long-term ecosystem dominance. For OpenAI, Anthropic, Google, and others, Nvidia’s move is both an opportunity (easier integration with enterprise data) and a competitive threat (a neutral platform could reduce dependence on any single model provider).

Only in America can a company raise over $1 billion without a balance sheet, powered largely by a vision articulated in a pitch deck. That is the depth of the American innovation capital market.

Artificial intelligence startup Advanced Machine Intelligence announced that it has raised $1.03 billion at a $3.5 billion pre-money valuation, even though the company is still early in its development journey. The round was co-led by Cathay Innovation, Greycroft, Hiro Capital, HV Capital, and Bezos Expeditions, the investment vehicle of Jeff Bezos.

The company was founded by renowned AI scientist Yann LeCun, who previously served as chief AI scientist at Meta Platforms. The financing marks one of the largest early-stage investments in an AI startup and positions AMI as a high-profile experiment in LeCun’s long-standing view that today’s large language models alone cannot produce truly intelligent machines.

What investors are funding here is not revenue or proven financials. They are funding a narrative of possibility, a belief that the company’s focus on reasoning, planning, and “world models” could represent the next frontier of AI.

This is how the American technology ecosystem works. Capital flows aggressively toward credible founders, big ideas, and technological inflection points. Investors are not waiting for proof; they are positioning themselves ahead of potential paradigm shifts.

In many parts of the world, investors demand a balance sheet before writing checks. In Silicon Valley, the order is often reversed: capital arrives first to enable the balance sheet to exist later.

That structural difference explains why the United States continues to dominate frontier innovation. It is not just about talent or technology. It is about risk capital willing to fund the future before it becomes visible.

And when legends pitch bold ideas in that ecosystem, billion-dollar checks can follow. Good luck Yann LeCun.