On the Brink of the Future: How the Connector Industry Shapes the AI Revolution

In a world rapidly advancing towards AI technologies, we find ourselves at a turning point in electrical engineering, especially in the connector industry. As an Interconnect Specialist, I want to share my insights on how our market needs to adapt and evolve in the face of the AI revolution.

With the emergence of AI technologies, particularly following the breakthrough of ChatGPT, tech giants like Microsoft, Google, and Apple have adjusted their strategies. Over the past three years, major computer companies had focused on VR. The rapid advances in AI technology caught many by surprise. Many computer manufacturers have had, and continue to have, to quickly adjust their strategies. Microsoft has already responded, taking a strong position through investments in AI. Google, completely taken aback, had something up its sleeve and quickly rolled out its own AI. Apple is at risk of becoming the big loser here. Maybe Apple will turn the tables, but only if they deviate from their company philosophies and indeed prioritize processing voice commands in the cloud. Tough times are ahead for Apple. The next two years will show whether they have missed the connection or can still catch up. Microsoft had, not without reason, temporarily surpassed Apple as the world's most valuable company. But let's get to the main topic, as this development underscores the need for the connector and semiconductor industry to adapt to new challenges.

Chip Shortage and AI Chips: Despite significant advances in chip development, exemplified by OpenAI's strategic decision to develop its own AI chips, the general chip shortage remains a central challenge. This particularly affects the availability of AI-specific chips essential for the ongoing implementation of AI technologies.

Focus on Automotive and Industry 4.0: The connector industry has thus far focused on complex applications in the automotive industry and Industry 4.0. Keyword: SPE. The same focus has been on fast data connectors for the automotive and transportation industries. For example, many suppliers in the agriculture sector are currently developing new future-proof ECUs designed for the future of agriculture. High-resolution camera systems, real-time soil composition analysis, and autonomous driving are just a few keywords. The automotive sector is also evolving into a playground for tech enthusiasts and people who want to be constantly connected. Industry 4.0, automotive, and transportation are the markets that connector developers have focused on for data transmission. Here, developments are being utilized that are already ten years old in some cases. The automotive industry and Industry 4.0 have been prioritized. Major connector manufacturers have invested more here. Detailed specifications and validations have been developed. A focus on very simple data connectors with enormous performance, primarily for use in server farms, has been overlooked. For cloud applications, vibrations do not need to be considered. The issue of tightness can also be neglected. And more importantly, connectors are needed now! Investment is now flowing into AI applications. In short: The topic of "simple," yet powerful connectors for server farms and cloud applications has been neglected.

Lack of Infrastructure for AI: The early phases of AI development are accompanied by a lack of infrastructure, underscoring the need for efficient connectors for the rapidly growing server farms.

What does this mean?

AI technology is competing with smart appliance devices, medical market devices, Industry 4.0, and of course, the automotive industry with its transformation to e-mobility. The topic of renewable energies will also continue to be decisive. Now AI is added to the mix. What can connector manufacturers do? Connector manufacturers should form an AI Task Force to develop products that meet these new requirements. But not a task force for how to use AI themselves, but what products they can contribute. Questions like "What should connectors for AI applications look like?", "Are existing solutions overdesigned?" or "Are large working groups slowing me down and preventing innovation?" need to be clarified. The larger manufacturers are certainly better positioned as they have the resources. But now is the time for specialists, and this offers an opportunity. Major automotive specialists such as TE, Aptiv, Amphenol, and Luxshare should continue to focus on automotive. Molex, Rosenberger, Amphenol, TE, Harting, Phoenix should not lose sight of the industry. But what about the others? Here lie opportunities. Of course, the top 10 and probably many more have enough resources to dance at all weddings. But specialists in data connectors, and of course, the top 10 would do well to quickly bring rudimentary, functional, and affordable data connectors for AI models to market. Manufacturers should work together with us distributors and our customers to develop a strategy. Who knows the market better than we and our customers? This includes many contract manufacturers.

In summary:

1. Development of rudimentary, functional data connectors: Simpler and more cost-effective connectors are needed for AI applications. Here lies an opportunity for specialists and smaller manufacturers.
2. Collaboration with distributors and customers: Developing a joint strategy with distributors and customers can provide valuable market insights and lead to more effective solutions.
3. Specialization vs. Diversification: While large manufacturers should continue to focus on automotive and Industry 4.0, others should specialize in simple data connectors for AI models.

Conclusion: The AI revolution requires rapid adaptation and innovation in the connector industry. With the right strategy and collaboration, we can develop efficient solutions for the challenges of the AI era. It's time to use our expertise to master this new technological wave.