In this talk, Sam Fok, Co-Founder and CEO of femtoAI, shares how ultra-efficient AI inference is enabling intelligence to run directly on embedded and edge devices. Drawing from real-world experience at the intersection of silicon and software, he explains why efficiency—not scale alone—will define the next wave of AI, how co-design unlocks major gains in power and cost, and what it takes to move edge AI from research prototypes into scalable, deployable systems.

In this talk, Laura Swan, General Partner at Silicon Catalyst Ventures, shares a clear and practical view of what it takes to scale semiconductor startups from early concepts to real-world impact. Drawing on decades of engineering and venture experience, she explains why hardware and semiconductors scale differently from software, how founders should think about timing, capital, and ecosystem support, and why Taiwan’s semiconductor supply chain is critical in helping startups

In this talk, Janis Skriveris, Principal and Deeptech Lead at Plug and Play Ventures, breaks down what it really takes to scale semiconductor and deep-tech startups from early innovation to global impact. Drawing on years of experience running accelerator programs and investing in frontier technologies, he explains how ecosystems, corporate partnerships, and cross-border collaboration—especially between Silicon Valley and Taiwan—enable startups to move beyond prototypes into

In this talk, Andy Lombard, Founder and Managing Partner of Tesoro Venture Capital, shares a candid look at what it truly takes to scale AI and semiconductor startups. Drawing on decades of experience as a serial founder, investor, and former Motorola executive, he explains why deep-tech companies face fundamentally different challenges than software startups—and how global supply chains, capital strategy, and cross-border partnerships, especially between Silicon Valley and T

Hosted by Sparknify on behalf of the Taipei Computer Association, this high-energy gathering brought together 400+ founders, investors, accelerators, and deep-tech leaders to explore how Taiwan is emerging as a global launchpad for semiconductor and AI innovation. Featuring insights from top VCs, accelerators, and startup founders, the event showcased how capital, manufacturing, and ecosystem support converge to help startups scale from prototype to global impact.

AI is entering a new phase. The focus is no longer on models that talk or generate images, but on AI agents that plan, decide, and act inside real systems. These agents promise autonomy across industries, from software to manufacturing. Yet beneath the excitement lies a less discussed constraint that will determine whether AI agents become real infrastructure—or remain impressive demos.

Many “AI-first” startups don’t fail because their models are weak—they fail when intelligence meets the physical world. Manufacturing constraints, reliability debt, and deployment realities quietly overwhelm promising demos, exposing blind spots that traditional investor diligence often misses. This article examines why models are not products, why execution determines survival, and how founders and investors can rethink risk before reality does it for them.

Most hardware startups make their first critical mistake with their first hire. By over-indexing on ML or firmware talent, early teams often overlook systems thinking, manufacturing reality, and long-term reliability. This article examines why early hardware teams become demo-optimized instead of product-ready, what the right first hires actually look like, and how founders can build teams capable of surviving real-world constraints—before costly mistakes are locked in.

Most hardware startups don’t fail because their ideas are wrong—they fail after the demo, when real-world constraints appear. Manufacturing assumptions collapse, suppliers misalign, thermal issues surface, and certification delays quietly drain runway. This article explores the “prototype trap,” where promising startups stall between proof and production, and explains how early engagement with Taiwan’s manufacturing ecosystem and programs like ICTGC can help founders turn fra

Edge AI is becoming the next major frontier as companies shift intelligence from the cloud into devices, robots, vehicles, and sensors. Rising cloud costs, strict latency demands, and increasing privacy regulations are driving this transition. For startups, the opportunity is huge—but success requires mastering hardware constraints, co-designing systems, and partnering with the right manufacturing ecosystem.

Silicon Valley is quietly shifting toward a new frontier: analog AI chips that bring intelligence out of the cloud and into everyday devices. For early-stage founders, the moment is thrilling and uncertain—demand is rising for real-time, low-power AI, but the old rules no longer apply. The teams that embrace local intelligence now will shape the next decade of hardware innovation.

Across China’s industrial heartland, factory floors once crowded with workers are now lit by the cool glow of automation. Assembly lines hum in perfect sync, robotic arms dance in silence, and production runs 24 hours a day without human fatigue. It’s a glimpse of a near-future world where machines, not men, drive the rhythm of industry.

Silicon Valley’s long-held belief that software dominates innovation is shifting. As AI systems mature and demand physical embodiments to act in the real world, hardware is experiencing a major resurgence. Robotics, autonomous machines, and AI-native devices are rapidly rising, driven by changes in global supply chains, manufacturing economics, and evolving venture investment priorities.

Taiwan—the “Silicon Island”—is the world’s center for advanced chip fabrication powering the AI revolution. On January 13, 2026, Sparknify will host “Bridging Silicon Valley and Taiwan: Semiconductor & AI Synergies” on behalf of the Taipei Computer Association (TCA) at Startup Island Taiwan – Silicon Valley Hub in Palo Alto. The event connects global founders, researchers, and investors with Taiwan’s world-class semiconductor and hardware ecosystem.