Google, VNG launch Applied AI Lab to accelerate Vietnam’s AI capabilities

Google, VNG launch Applied AI Lab to accelerate Vietnam’s AI capabilities

Representatives from Google, VNG, and VNU-HCM during a working session at VNG Campus.

Google Labs’ AI Futures Fund has teamed up with Saigon AI Hub (SAIH)—an open research initiative set up by VNG Group and Vietnam National University Ho Chi Minh City—to launch an Applied AI Lab, marking the tech giant’s first such collaboration globally.

The partnership underscores a broader push by Google, VNG, and VNUHCM to accelerate Vietnam’s AI capabilities, with a focus on translating research into commercially viable applications. By providing early access to its latest AI models and tools, Google aims to deepen engagement with local researchers and startups, positioning the initiative as a catalyst for ecosystem-wide development.

Under the arrangement, Google Labs will work closely with SAIH’s research teams, offering not only access to advanced technologies but also hands-on technical support from engineers and experts across Google and Google DeepMind.

“By choosing Saigon AI Hub as the inaugural partner for this experimental collaboration model, we are not just providing tools; we are co-creating an environment where Vietnamese researchers can bridge the gap between theoretical research and real-world impact,” said Josh Woodward, VP of Gemini app, Google Labs, and AI Studio. “We believe the solutions developed here will not only benefit Vietnam but will offer valuable insights for the global AI community.” 

Le Hong Minh, founder and chairman of VNG, said the initiative addresses a key bottleneck in Vietnam’s AI landscape. “The biggest barrier to AI research in Vietnam is not a shortage of talent. It is the lack of resources and the right conditions for that talent to perform at its full potential. Through global partnerships like this one with Google Labs, researchers at SAIH and across Vietnam will have the opportunity to work with the same technologies, at the same time, as the world’s leading AI institutions.”

The Applied AI Lab is launching with 10 research groups comprising nearly 60 researchers from universities across Ho Chi Minh City. The teams have been selected based on practical applicability, research strength, and alignment with responsible AI principles, spanning areas such as computational linguistics, computer vision, human-robot interaction, healthcare, and cybersecurity.

Google Labs is the home for AI experiments at Google. AI Futures Fund is an initiative within Google Labs that invests in and works with organisations to accelerate their ambitious ideas. 

Located at VNG Campus, SAIH is building a comprehensive academic AI research ecosystem focused on problems with high applied value for Vietnam’s economy and society.   

VNG on Monday also reported Q1 2026 net revenue of 2.8 trilliondong ($111.4 million), up 32% YoY, while adjusted operating profit jumped 154% to 470 billion dong ($18.8 million). Net profit reached 125 billion dong ($5 million), extending the company’s return to the black, supported by double-digit growth and tighter cost control.

“What is becoming clearer this quarter is how our platforms are starting to scale together, rather than as separate businesses. As monetisation improves and operating discipline strengthens, we are able to reinvest more deliberately into the next layer of growth, especially in areas where data, user base, AI and infrastructure can reinforce each other. That will define how we scale in the next phase”, said Kelly Wong, Chief Executive Officer of VNG Group. 

Games remained the main revenue driver, rising 38% YoY to 1.94 trillion dong($77.5 million), with bookings up 48%. Active users edged up to 60.7 million, while international markets accounted for 17% of bookings.

Digital payments arm ZaloPay was a standout, with revenue more than doubling to 216 billion dong ($98.4 million). GreenNode recorded 170 billion dong ($6.8 million) in revenue, stable on a comparable basis, as the segment transitions toward higher-value AI workloads. 

Edited by: Joymitra Rai

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