Meta Platforms, the parent company of Facebook and Instagram, is pushing forward with an ambitious plan to design its own artificial intelligence chips in-house starting in September, joining a growing list of technology giants seeking to reduce their dependence on Nvidia and gain more control over their AI infrastructure costs.
According to the New York Post, Mark Zuckerberg’s initiative, known internally as “Iris,” centers on developing custom silicon to supercharge the AI systems behind Facebook and Instagram. Meta, which expects to spend up to $145 billion on AI infrastructure this year, is working with Palo Alto-based Broadcom on design and Taiwan Semiconductor Manufacturing on production.
The move has significant implications for New York’s tech ecosystem, where Meta maintains a substantial workforce and where the AI industry’s infrastructure investments have become an increasingly important part of the local economy. Meta’s New York offices house thousands of employees, many working on AI and related technologies.
Meta joins Amazon, Google, and Microsoft, all of which have in-house chip programs. OpenAI recently introduced its first custom inference chip with Broadcom, while Anthropic is reportedly in talks with Samsung about developing its own chip. The proliferation of custom silicon projects reflects a fundamental shift in how the largest technology companies are approaching their hardware infrastructure.
Even as companies launch their own chip development efforts, the semiconductor industry remains under tremendous demand strain. AI companies’ efforts to become more autonomous provide no silver bullet to the supply chain conundrum. Demand for manufacturing, packaging, and other chip production resources continues to outpace supply, while several specialized chip-making processes are controlled by a small number of companies already operating at capacity.
Meta’s latest project builds on a long-running effort to develop its own chips. Its Training and Inference Accelerators program, launched more than five years ago, has focused on in-house chip development, though progress has been slow. Development of the new Iris chip has reportedly moved much more rapidly. Testing took just six weeks and faced no major problems, according to Reuters.
Meta plans to introduce a new chip roughly every six months through 2027, compared with the typical annual-or-longer release cycle for AI chips. The accelerated timeline reflects the urgency of the AI arms race and the financial pressures of relying on a single supplier for critical infrastructure.
The custom product is intended to complement the large number of graphics processing units, or GPUs, that Meta buys from Nvidia and AMD for AI workloads. But bringing the newest GPUs online at Meta’s scale “has been a heavy lift, and it has cost us time,” according to a company memo reviewed by Reuters. Developing custom chips can potentially lower costs and diversify supply chains.
“I want something in my pocket when I’m sitting across the table from Jensen negotiating,” Bernstein senior analyst Stacy Rasgon told Axios, referring to Nvidia CEO Jensen Huang. The comment captures the strategic calculus driving the custom chip trend: leverage in negotiations with the dominant supplier.
The trend has implications beyond the technology companies themselves. The semiconductor supply chain involves a global network of manufacturers, designers, and equipment suppliers. Apple announced this week that it plans to spend more than $30 billion with Broadcom over the next five years, helping the chipmaker expand a manufacturing facility in Fort Collins, Colorado. Samsung manufactures advanced chips for both its own products and outside customers, while Intel is working to expand its contract manufacturing business.
Showing the complexity of attaining chip autonomy, those manufacturers rely on lithography equipment from Dutch company ASML, the only supplier of the most advanced machines used to produce AI chips. This bottleneck in the supply chain means that even companies designing their own chips remain dependent on a limited number of manufacturing partners and their equipment suppliers.
For New York’s tech sector, the expansion of custom chip programs could bring both opportunities and challenges. The city has been working to establish itself as a hub for AI innovation, and the growing investment in custom silicon design creates demand for specialized engineering talent. However, chip design and manufacturing have historically been concentrated in Silicon Valley and other tech corridors, and New York faces competition from regions with deeper semiconductor industry roots.
Meta’s announcement also comes amid broader debates about the concentration of power in the AI industry and the massive capital investments being made by the largest technology companies. With Meta spending up to $145 billion on AI infrastructure in a single year, the scale of investment raises questions about market competition and whether smaller companies can keep pace.
As the custom chip race accelerates, the competitive dynamics of the AI industry are likely to be reshaped, with implications for everyone from the largest technology platforms to the consumers who use their products every day.
The trend also has significant implications for New York’s financial markets. Semiconductor and AI-related stocks have been among the most heavily traded securities on the New York Stock Exchange and Nasdaq, and the acceleration of custom chip programs is likely to drive increased trading activity and investment in the sector. Analysts at major Wall Street firms have been closely tracking the custom silicon trend, with several issuing research notes about its potential impact on Nvidia’s market dominance.
For New York-based AI startups and research institutions, the proliferation of custom chip programs could create both opportunities and challenges. On one hand, a more diverse chip ecosystem could lower barriers to entry for companies developing AI applications, as competition among chip suppliers drives down costs and increases availability. On the other hand, the massive capital investments required to develop custom silicon could further concentrate AI capabilities in the hands of the largest technology companies, potentially widening the gap between industry leaders and smaller competitors.
The city’s academic institutions, including Columbia University and NYU, have been expanding their AI and semiconductor research programs in recent years. The growing demand for custom chip design talent could create opportunities for these institutions to partner with technology companies and attract research funding, strengthening New York’s position in the AI ecosystem even as Silicon Valley remains the center of chip development.
