Discus Fish of Cobo and Samuel Tse of Animoca Brands discuss how AI agents, digital identity and blockchain could change the way money moves.
Updated
November 2, 2026 12:03 PM
The Agentic Economy Summit at CVCF 2026 explores how AI agents and digital assets could shape the future of business and finance. IMAGE: CYBERPORT
For an AI agent to manage money on someone’s behalf, it needs more than the ability to follow instructions. It must be able to establish whom it represents, access funds and transact within agreed limits.
These are among the questions informing the discussion of AI and digital assets at Cyberport Venture Capital Forum (CVCF) 2026. Ahead of the forum, Discus Fish, CEO and Co-founder of Cobo, and Samuel Tse, Head of Investment and Corporate Finance at Animoca Brands, shared their views on how this convergence could develop—and where they see opportunities for businesses.
Discus Fish points to a longstanding challenge: blockchain can be difficult for everyday users to navigate, but AI agents may find it easier to interact with these networks.
“Blockchains have always been hard for ordinary people to use. AI agents may be better users: the chain is fully transparent and every record is traceable, which suits agents well.”
His outlook comes with a qualification. Both the agents and the networks they would use still need to develop.
“Agents aren’t capable enough yet, and chains are still adapting. But once agents truly run on-chain, the number of users and what’s possible will grow by an order of magnitude.”
Discus Fish says blockchain could reshape how financial assets are issued, traded and settled over the next five years. He also notes that institutional adoption has progressed faster than Cobo initially expected, with individual users no longer leading the shift. “Since 2017, we have believed blockchain will become part of the financial infrastructure of the future. We expected individual users to lead, but institutions moved faster.”
For Fish, the next stage involves a broader range of assets and financial clients.
“What gets redefined next is how assets are issued, traded, and settled. As traditional assets like US equities come on-chain, a much wider range of financial clients will follow.”
Samuel Tse, Head of Investment and Corporate Finance at Animoca Brands, focuses on investment opportunities across digital assets and agentic AI. He sees digital identity as essential to allowing AI agents to act on behalf of people while keeping transactions within the permissions they set.
He believes users should set clear rules for what an AI agent can do, allowing it to complete transactions without requiring approval for each one.
“Once agents can prove who they represent, hold digital assets, and move value under clear rules, the economy stops being click-by-click. You set the policy once—who, how much, for what—and the agent transacts inside it.”
He describes applications ranging from everyday payments and transfers to subscriptions, swaps and earning returns on idle funds. “That’s agentic transactions: payments, transfers, subscriptions, swaps, even chasing a better rate on idle cash. Identity is the trust layer. Assets and credentials are the spending authority—always accountable to the human who granted permission.”
In Tse’s account, the human remains the source of that authority. The agent acts within the permissions granted to it.
To illustrate how AI agents, digital identity and digital assets might work together, Tse offers a hypothetical Hong Kong parent's weekday.
“A Hong Kong parent’s weekday: top up the child’s Octopus, book a weekend football slot, translate a school notice for the helper, check weather before pickup, restock milk at the member price, and keep leftover budget earning until tomorrow.”
At present, he says, completing these tasks requires navigating services that often operate separately.
“Today that means many apps that don't talk to each other, and rails that struggle with micro payments.”
His proposed alternative brings the tasks together under instructions established by the user.
“With an agent, they set the rules once and let it decide what to do. Identity unlocks trust and member prices without oversharing. Digital assets fit the money—per-use fees, hard limits, yield until spend.”
For Tse, this combination could create opportunities across payments, merchants, identity providers and digital-asset platforms. He compares the potential scale of agentic commerce to an earlier change in how consumers accessed services.
“The iPhone in 2007 rewired how people buy and use services for 20 years. We are just at the beginning of a similar paradigm shift, with outcomes we can barely imagine.”
Discus Fish and Samuel Tse offer two perspectives on the emerging agentic economy, from the blockchain infrastructure enabling transactions to the digital identity and permissions that allow AI agents to act on people's behalf. At CVCF 2026, these ideas will become part of a wider conversation with the leaders building and investing in this evolving space.
Be part of the conversation. Join industry leaders, founders and investors at CVCF 2026 on 4–5 November and explore the technologies and opportunities shaping the next phase of business.
Exclusive for Ventureport readers: Use code cvcf26vp to access a Full Access Pass for HK$300, subject to confirmation by the organiser.
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A new AI model replaces months of simulation with near-instant predictions, changing how spacecraft operations are prepared
Updated
August 10, 2026 5:56 PM
Northrop Grumman Stargaze serves as the mother ship for the Pegasus, an air-launched orbital rocket. PHOTO: UNSPLASH
Flexcompute, a startup that builds software to simulate real-world physics, is working with Northrop Grumman to change how space missions are prepared. Together, they have developed an AI-based system that can predict how spacecraft respond during critical manoeuvres such as docking—when one spacecraft moves in and connects with another in orbit. These steps have traditionally taken months of preparation.
At the centre of this work is a long-standing problem in space operations. When a spacecraft fires its thrusters, the exhaust plume interacts with nearby surfaces. These interactions can affect movement, temperature and stability. Because these effects are difficult to test in real conditions, engineers have relied on large volumes of computer simulations to estimate outcomes before a mission. That process is slow and resource-intensive.
The new system replaces much of that workflow with a trained AI model. Instead of running millions of simulations, the model learns patterns from physics-based data and can make predictions in seconds. It also provides a measure of uncertainty, which helps engineers understand how reliable those predictions are when making decisions.
"At Northrop Grumman, we're pioneering physics AI to accelerate design and solve complex simulation and modelling problems like plume impingement—critical for station keeping, rendezvous and space robotics. Simply put: we're pushing the boundaries of advanced space operations", said Fahad Khan, Director of AI Foundations at Northrop Grumman. "Partnering with Flexcompute and NVIDIA, we're accelerating innovation and mission timelines to deliver superior space capabilities for customers at the speed they need".
The system is built using technology from NVIDIA, which provides the computing framework behind the model. Flexcompute has adapted it to handle the specific challenges of spaceflight, including how gases expand and interact in a vacuum. The result is a tool that can simulate complex scenarios much faster while maintaining the level of accuracy needed for mission planning.
By shortening preparation time, the model changes how engineers approach spacecraft design and operations. Faster predictions mean teams can test more scenarios and adjust plans more quickly. It also helps improve fuel use and extend the lifespan of spacecraft.
"Northrop Grumman's confidence reflects what sets Flexcompute apart", said Vera Yang, President and Co-Founder of Flexcompute. "We are able to take the most accurate and scalable physics foundations and evolve them into highly trained, customized Physics AI solutions that engineers can rely on. This work shows how we are transforming the role of simulation, not just speeding it up, but expanding what engineers can confidently solve and how quickly they can act".
The collaboration points to a broader shift in how engineering problems are being handled. Instead of relying only on detailed simulations that take time to run, companies are beginning to use AI systems that can approximate those results quickly while still reflecting the underlying physics.
"The industry's most ambitious space missions now demand a level of speed and precision that traditional engineering cycles can no longer sustain", said Tim Costa, vice president and general manager of computational engineering at NVIDIA. "By integrating NVIDIA PhysicsNeMo, Northrop Grumman and Flexcompute are transforming complex simulations like plume impingement from days of compute into seconds of insight, drastically accelerating the path from mission concept to orbit".
What emerges from this work is a shift in how missions are prepared. When prediction cycles move from months to seconds, testing and decision-making can happen faster. For space operations, where timing and precision are closely linked, that change could reshape how systems are built and run.