EDITOR'S PICKS
THE FACES OF DEEP TECH
FuriosaAI and the coming break in the AI hardware order
The future of finance is transparent: How Summit is rewriting the rules of finance automation
AI, abundance and the age of adaptation: A conversation with futurist and former OpenAI executive Zack Kass
Interview with Pexx CEO Marcus Lim: Stablecoins are about transferring value, not speculation
The sum and substance of trust: Sumsub’s strategy to outwit synthetic fraud and scale for growth in APAC
Stablecoins, settlements and Southeast Asia: StraitsX CEO Tianwei Liu charts the next evolution in digital payments
The time dividend thesis: Why AppliedAI CEO sees enterprise AI as a liberation of work
Beyond the AI hype: How ASEAN’s MSMEs can turn intelligence into impact
AI’s forgotten problem: Plaud’s Nathan Xu on building AI that remembers what matters
Liquidity reimagined: How Riverchain is building the financial railroads for APAC’s construction economy
Ping Identity: Malicious AI agents could pose significant threat to APAC enterprises
From coordinates to consciousness: Auki Labs and the dawn of spatial intelligence
From green dye to smart surgery: How UltraGreen is reimagining healthcare with vertical AI
Using AI to build better companies: A conversation with Prof. Hyunjin Kim on AI venture creation
FEATURED VIDEOS
Establishing trust in agentic finance
Dr Bo Bai explains why finance may need a “Know Your Agent” or KYA framework comparable to KYC requirements. Such a framework would establish who owns and controls an AI agent, verify the parties behind it and enable institutions to monitor how it interacts with financial systems. It would also support anti-money-laundering controls, accountability and human intervention when autonomous systems make consequential decisions. Dr Bai argues that stronger AI capabilities alone will not bring agentic finance into the mainstream. In a regulated industry where mistakes can carry serious financial consequences, robust governance, security and human oversight must come first.
What will AI get wrong by 2030?
As AI models become faster and more economical, the next challenge is not simply scaling their use but ensuring that AI agents deliver reliable outcomes without compromising security, privacy or trust. Val Bercovici, Chief AI Officer at WEKA, explains why organisations need to define the results they expect from AI, allocate sufficient resources for quality output and establish strong guardrails before deploying agents at scale. He also examines the risks of using powerful models indiscriminately, the role of security and privacy scanning, and why governments may eventually need international agreements governing the development and proliferation of advanced AI.
The AI reality check for banks
As banks accelerate their adoption of AI, the bigger challenge is no longer whether to embrace the technology, but how and where to deploy it effectively. Durga Prasad Uppu from Bank Negara Indonesia (BNI) speaks to Deeptech Times about moving AI from experimentation into real banking operations, the security questions that follow and why meaningful transformation must begin with a clearly defined business problem.
The Next Now: Retail's deep tech revolution begins in APAC
What does the future of retail actually look like when AI, robotics, automation and deep tech move beyond experimentation and into real-world deployment? Ryf Quail shares why APAC is emerging as one of the world’s most important battlegrounds for retail innovation, and how technologies once viewed as futuristic are now transforming stores, supply chains and customer experiences across the region. We also dive into the theme behind the NRF 2026 APAC show: “The Next Now” and why the future of retail is no longer a distant vision, but an operational reality unfolding across APAC today.
Why Java is quietly powering the enterprise AI revolution
AI may dominate technology headlines, but what powers the infrastructure behind AI systems? In this interview, Dean Vaughan, vice president for APAC at Azul, shares insights from the 2026 State of Java Survey & Report and explains why Java is becoming increasingly critical in the enterprise AI era. He also highlights how enterprises are optimising their infrastructure by adopting high-performance Java platforms that can significantly reduce compute requirements and improve application efficiency.
