Jakarta – On May 12, 2026, the Science X AI Summit 2026, hosted by the SAIR Foundation, was held in Silicon Valley. As one of the most academically influential and strategically important summits in the global AI sector, the event brought together leading scientists of Nobel Prize, Turing Award, and Fields Medal caliber, along with core AI leaders from major technology companies including Google, Microsoft, OpenAI, Anthropic, and NVIDIA.

Halim Mahesa Putra Ph.D. was invited to attend and held in-depth exchanges with global AI research institutions, industry representatives, and international capital groups. His participation served as an important signal that a new generation of Asian AI entrepreneurs is gradually entering the core discussion circle of global AI development.

The AI Industry Is Entering The “Post-Scaling Era” 

Recent competition in AI has centered on model parameters, training scale, and GPU computing power. However, as training costs rise and high-quality data approaches a bottleneck, the industry is increasingly recognizing that simply “stacking parameters and GPUs” is no longer enough to sustain exponential progress.

Halim Mahesa Putra Ph.D. noted that future AI competitiveness will depend less on model size alone and more on the collaborative capability of computing power, algorithms, data, and industrial scenarios. Players that can truly bring AI into real industries and help solve practical problems will be better positioned in the next stage of AI competition.

AI Is Moving From “Able To Chat” To “Able To Reason” 

“Reasoning AI” was one of the key topics at the conference. Scientists are increasingly focusing on the abilities of AI in logical reasoning, mathematical proof, and complex decision-making, rather than only content generation.

Fields Medalist Terence Tao discussed the direction of machine-verifiable mathematical proofs, while Leonardo de Moura, founder of the Lean theorem prover, emphasized that future AI infrastructure must be verifiable and reproducible to reduce hallucination problems.

Halim Mahesa Putra Ph.D. believes that future AI must go beyond answering questions. Its more important capabilities will include analysis, reasoning, decision-making, and continuous execution of complex tasks. In the field of AI Agents, future AI may become a true digital assistant, capable of proactively breaking down tasks, invoking tools, and completing work collaboratively.

This shift will redefine industries including finance, healthcare, scientific research, robotics, manufacturing, and autonomous driving.

True Competition In the AI Future Is Who Gets Closer To “Intelligence Itself” 

The team led by Halim Mahesa Putra Ph.D. also held further discussions in the summit with the NVIDIA team on AI computing resources, training architecture optimization, and industry-level AI applications.

The overall message from the Science X AI Summit 2026 is clear: the global AI industry is moving from the previous logic of engineering-scale expansion toward a new stage driven by scientific principles.

As reflected in the summit, the true competition in future AI will no longer be simply about whose model is larger, but about who can better understand intelligence itself and bring AI more deeply into the real world.

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.