Amid AI and tech startups, Eastseabrother proved the power of demand and trust.
Updated
January 23, 2026 10:41 AM
Cats having a jolly good time with a can of tuna. PHOTO: UNSPLASH
At a Silicon Valley pitch event crowded with AI, SaaS and deep-tech startups, the company that stood out was not selling software or algorithms. It was selling pet treats.
Eastseabrother, a premium pet food brand from South Korea, ranked first at a Plug and Play–hosted investor pitch competition in Sunnyvale. The product itself is simple: single-ingredient pet treats made from wild-caught seafood sourced from Korea’s East Sea. The company follows a principle it calls “Only What the Sea Allows”, working directly with regional fishermen while avoiding overfishing. With no additives and minimal processing, what sets Eastseabrother apart is not novelty, but control—over sourcing, supply chains and consistency.
That clarity helped the company walk away with both Best Product and Best Potential. “Investors asked detailed questions about repeat purchase rates and customer feedback, not just our technology or supply chain”, said Eunyul Kim, CEO of Eastseabrother. “That told us the market is shifting—real consumer trust now carries as much weight as a compelling tech narrative”.
What truly caught investors’ attention was not an ambitious vision of the future, but concrete evidence of traction today. Eastseabrother has already secured shelf space in specialty pet stores across California, New York and North Carolina, including an exclusive partnership with EarthWise Pet, a national specialty retail chain. At a consumer showcase at San Francisco’s Ferry Building, the brand recorded the highest on-site sales among all participating companies.
At its core, the pitch was built on simplicity: one ingredient, clear sourcing and a defined customer need. In a market saturated with complex products and abstract claims, that focus and transparency stood out.
The judges’ decision also reflects a broader shift in venture capital thinking. Not every successful startup is built on complex software or high-tech innovation. In categories like pet care—where trust, quality and transparency shape buying behavior—execution and credibility can matter more than technical sophistication.
Today, Eastseabrother has extended its reach beyond the U.S., expanding into Singapore and Hong Kong, with additional plans to grow further in North America as demand for premium pet food rises. And the broader takeaway from this pitch is not that consumer brands are overtaking tech startups. It is that investors are increasingly focused on fundamentals: who is buying, why they are returning and whether the business can sustain itself beyond the pitch deck.
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AI growth is increasingly becoming a manufacturing, packaging and deployment challenge — not just a computing one.
Updated
May 26, 2026 5:28 PM
Taipei 101 and Taipei Nan Shan Plaza, viewed from Elephant Mountain. PHOTO: UNSPLASH
As AI companies continue scaling larger models and data centers, the pressure is no longer falling only on chip design. Manufacturing capacity, advanced packaging and infrastructure deployment are becoming equally important parts of the AI race. AMD’s latest investment announcement reflects how quickly that shift is accelerating.
The US chipmaker announced plans to invest more than US$10 billion across Taiwan’s semiconductor and manufacturing ecosystem to support next-generation AI infrastructure. The investment focuses on expanding partnerships and increasing advanced packaging capacity needed for future AI systems.
The announcement highlights a growing reality across the AI industry. Building powerful AI chips is no longer enough on its own. Companies now also need the manufacturing networks, packaging technologies and supply chain coordination required to deploy AI infrastructure at global scale.
AMD’s investments center heavily around advanced chip packaging, an area becoming increasingly critical as AI systems demand higher performance and greater power efficiency. Traditional chip architectures are struggling to keep pace with the size and complexity of modern AI workloads. Advanced packaging helps connect processors, memory and computing systems more efficiently while managing power and cooling limitations inside large-scale AI environments.
The company said it is working with Taiwan-based partners including ASE, SPIL and PTI to develop next-generation packaging technologies for its upcoming 6th Gen AMD EPYC processors, codenamed “Venice.” AMD also said it had qualified what it described as the industry’s first 2.5D panel-based EFB interconnect technology alongside PTI.
At the center of the broader strategy is AMD Helios, the company’s rack-scale AI infrastructure platform scheduled for deployment beginning in the second half of 2026. The platform combines AMD Instinct MI450X GPUs, 6th Gen EPYC CPUs, networking systems and AMD’s ROCm software stack into integrated AI infrastructure systems designed for hyperscale deployment.
Rather than selling individual processors alone, companies are increasingly building complete AI infrastructure platforms that combine hardware, software, cooling systems and power management into unified deployments. That transition is reshaping how AI infrastructure is designed, manufactured and delivered.
Taiwan is also becoming more deeply embedded in that process. AMD’s investment spans not only semiconductor packaging companies but also manufacturing and system integration partners including Sanmina, Wiwynn, Wistron and Inventec. The partnerships reflect Taiwan’s growing role as one of the operational centers of the global AI infrastructure economy.
Dr. Lisa Su, Chair and CEO of AMD, said: “As AI adoption accelerates, our global customers are rapidly scaling AI infrastructure to meet growing compute demand. By combining AMD leadership in high-performance computing with the Taiwan ecosystem and our strategic global partners, we are enabling integrated, rack-scale AI infrastructure that helps customers accelerate deployment of next-generation AI systems”.
Power efficiency is becoming another major challenge shaping AI infrastructure decisions. As AI workloads consume more electricity and generate more heat, infrastructure providers are increasingly being forced to rethink cooling systems, interconnect technologies and deployment economics.
AMD’s announcement signals how the AI competition is evolving beyond model development and raw computing power. The next stage may depend just as heavily on who can manufacture, package and deploy AI infrastructure fast enough to support global demand.