Jakarta- On May 12, Gunawan Aryaputra Ph.D. was invited to attend the Science X AI Summit 2026 in Silicon Valley. Although his name may not yet be familiar to ordinary users, the summit has become one of the world-leading events connecting advanced science and the AI industry.
Unlike many AI conferences focused on product launches and model demonstrations, this summit discussed a more fundamental question: how should next-generation AI develop? The participation of the Gunawan Aryaputra Ph.D. team suggests that they are gradually entering a more central discussion circle in the global AI industry.
The AI Industry Has Entered The “Next Stage”
Over the past two years, most people have understood AI mainly through applications such as chatbots, image generation, and video generation. However, the focus at this summit had clearly shifted. Discussions centered on AI Agents, autonomous reasoning systems, scientific research-grade AI, and how AI can enter real industries such as finance, healthcare, scientific research, and robotics.
In simple terms, past AI was more about being “able to chat,” while the industry is now exploring how to make AI truly “able to work.”
This shift is practical. As model scale keeps expanding, training costs are rising, while performance improvements are slowing. Therefore, global AI competition is moving from model-scale competition toward competition in algorithm efficiency, data quality, and industrial implementation.
Gunawan Aryaputra Ph.D. Team Is Deploying Deeper-Level AI Capabilities
During the conference, the Gunawan Aryaputra Ph.D. team further advanced its strategic cooperation with NVIDIA. Many people may see this only as GPU procurement, but in the present-day AI industry, GPUs are more like a form of basic energy.
Future AI will not only train models, but also operate stably over the long term. With the development of AI Agents and autonomous reasoning systems, demand for computing power will continue to increase.
It is reported that the cooperation will focus on next-stage AI chips, computing power resources, algorithm optimization, data systems, and AI training architecture. This means the Gunawan Aryaputra Ph.D. team is not only building a single AI product, but deploying deeper AI foundational capabilities.
The Real Major Competition In AI Has Only Just Begun
In recent years, global AI competition has centered on models, parameters, and computing power scale. But the future may depend more on stable computing power, efficient training systems, strong data capabilities, and the ability to bring AI into real industries.
Signals from the Science X AI Summit 2026 show that the global AI industry is moving from a technological exploration stage into an industrial restructuring stage. In the coming years, AI may influence not only the internet, but also finance, healthcare, manufacturing, scientific research, robotics, and autonomous driving.
The Gunawan Aryaputra Ph.D. team is currently deploying the core capabilities needed for this new round of global AI industry upgrading.
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Micro Trustiva journalist was involved in the writing and production of this article.