A step forward that could influence how smart contracts are designed and verified.
Updated
January 8, 2026 6:32 PM
ChainGPT's robot mascot. IMAGE: CHAINGPT
A new collaboration between ChainGPT, an AI company specialising in blockchain development tools and Secret Network, a privacy-focused blockchain platform, is redefining how developers can safely build smart contracts with artificial intelligence. Together, they’ve achieved a major industry first: an AI model trained exclusively to write and audit Solidity code is now running inside a Trusted Execution Environment (TEE). For the blockchain ecosystem, this marks a turning point in how AI, privacy and on-chain development can work together.
For years, smart-contract developers have faced a trade-off. AI assistants could speed up coding and security reviews, but only if developers uploaded their most sensitive source code to external servers. That meant exposing intellectual property, confidential logic and even potential vulnerabilities. In an industry where trust is everything, this risk held many teams back from using AI at all.
ChainGPT’s Solidity-LLM aims to solve that problem. It is a specialised large language model trained on over 650,000 curated Solidity contracts, giving it a deep understanding of how real smart contracts are structured, optimised and secured. And now, by running inside SecretVM, the Confidential Virtual Machine that powers Secret Network’s encrypted compute layer, the model can assist developers without ever revealing their code to outside parties.
“Confidential computing is no longer an abstract concept,” said Luke Bowman, COO of the Secret Network Foundation. “We've shown that you can run a complex AI model, purpose-built for Solidity, inside a fully encrypted environment and that every inference can be verified on-chain. This is a real milestone for both privacy and decentralised infrastructure”.
SecretVM makes this workflow possible by using hardware-backed encryption to protect all data while computations take place. Developers don’t interact with the underlying hardware or cryptography. Instead, they simply work inside a private, sealed environment where their code stays invisible to everyone except them—even node operators. For the first time, developers can generate, test and analyse smart contracts with AI while keeping every detail confidential.
This shift opens new possibilities for the broader blockchain community. Developers gain a private coding partner that can streamline contract logic or catch vulnerabilities without risking leaks. Auditors can rely on AI-assisted analysis while keeping sensitive audit material protected. Enterprises working in finance, healthcare or governance finally have a path to adopt AI-driven blockchain automation without raising compliance concerns. Even decentralised organisations can run smart-contract agents that make decisions privately, without exposing internal logic on a public chain.
The system also supports secure model training and fine-tuning on encrypted datasets. This enables collaborative AI development without forcing anyone to share raw data—a meaningful step toward decentralised and privacy-preserving AI at scale.
By combining specialised AI with confidential computing, ChainGPT and Secret Network are shifting the trust model of on-chain development. Instead of relying on centralised cloud AI services, developers now have a verifiable, encrypted environment where they keep full control of their code, their data and their workflow. It’s a practical solution to one of blockchain’s biggest challenges: using powerful AI tools without sacrificing privacy.
As the technology evolves, the roadmap includes confidential model fine-tuning, multi-agent AI systems and cross-chain use cases. But the core advancement is already clear: developers now have a way to use AI for smart contract development that is fast, private and verifiable—without compromising the security standards that decentralised systems rely on.
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Examining how robots are moving from demonstrations to daily use.
Updated
January 8, 2026 6:22 PM
An industrial robotic arm capable of autonomous welding. PHOTO: ADOBE STOCK
CES 2026 did not frame robotics as a distant future or a technological spectacle. Instead, it highlighted machines designed for the slow, practical work of fitting into human systems. Across the show floor, robots were no longer performing for attention but being shaped by real-world constraints—space, safety, fatigue and repetition.
They appeared in factories, homes, emergency settings and industrial sites, each responding to a specific kind of human limitation. Together, these four robots reveal how robotics is being redefined: not as a replacement for people, but as infrastructure that quietly takes on work humans are least meant to carry alone.
Hyundai Motor unveiled its electric humanoid robot, Atlas, during a media day on January 5, 2026, at the Mandalay Bay Convention Center in Las Vegas as part of CES 2026. Developed with Boston Dynamics, Hyundai’s U.S.-based robotics subsidiary, Atlas was presented in two forms: a research prototype and a commercial model designed for real factory environments.
Shown under the theme “AI Robotics, Beyond the Lab to Life: Partnering Human Progress,” Atlas is designed to work alongside humans rather than replace them. The premise is straightforward—robots take on physically demanding and repetitive tasks such as sorting and assembly, while people focus on work requiring judgment, creativity and decision-making.
Built for industrial use, the commercial version of Atlas is designed to adapt quickly, with Hyundai stating it can learn new tasks within a day. Its adult-sized humanoid form features 56 degrees of freedom, enabling flexible, human-like movement. Tactile sensors in its hands and a 360-degree vision system support spatial awareness and precise operation.
Atlas is also engineered for demanding conditions. It can lift up to 50 kilograms, operate in temperatures ranging from –20°C to 40°C and is waterproof, making it suitable for challenging factory settings.
Looking ahead, Hyundai expects Atlas to begin with parts sorting and sequencing by 2028, move into assembly by 2030 and later take on precision tasks that require sustained physical effort and focus.
Widemount’s Smart Firefighting Robot is designed to operate in environments that are difficult and dangerous for humans to enter. Developed by Widemount Dynamics, a spinout from the Hong Kong Polytechnic University, the robot is built to support emergency teams during fires, particularly in enclosed and smoke-filled spaces.
The robot can move through buildings and industrial facilities even when visibility is near zero. Rather than relying on cameras or GPS, it uses radar-based mapping to understand its surroundings and determine a safe path forward. This allows it to continue operating when smoke, heat or debris would normally restrict access.
As it approaches a fire, the robot analyses the burning object. Its onboard AI helps identify the material involved and selects an appropriate extinguishing method. Sensors simultaneously assess flame intensity and send real-time updates to command centres, giving responders clearer situational awareness.
When actively fighting a fire, the robot can aim directly at the source and deploy extinguishing agents autonomously. The system continuously adjusts its actions based on incoming sensor data, reducing the need for constant human intervention during high-risk situations.
At CES 2026, LG Electronics offered a glimpse into how household work could gradually shift from people to machines. The company introduced LG CLOiD, an AI-powered home robot designed to manage everyday chores by working directly with connected appliances within LG’s ThinQ ecosystem.
Designed for indoor living spaces, CLOiD features a compact upper body with two articulated arms, a head unit and a wheeled base that enables steady movement across floors. Its torso can tilt to adjust height, allowing it to reach items placed low or on kitchen counters. The arms and hands are built for careful handling, enabling the robot to grip common household objects rather than heavy tools. The head also functions as a mobile control unit, housing cameras, sensors, a display and voice interaction capabilities for communication and monitoring.
In practice, CLOiD acts as a task coordinator. It can retrieve items from appliances, operate ovens and washing machines and manage laundry cycles from start to finish, including folding and stacking clothes. By connecting multiple devices through the ThinQ system, the robot turns separate appliances into a single, coordinated workflow.
These capabilities are supported by LG’s Physical AI system. CLOiD uses vision to recognise objects and interpret its surroundings, language processing to understand instructions and action control to execute tasks step by step. Together, these systems allow the robot to follow routines, respond to user input and adjust task execution over time.
Doosan Robotics introduced Scan & Go at CES 2026, an AI-driven robotic system designed to automate large-scale surface repair and inspection. The solution targets environments with complex, irregular surfaces that are difficult to pre-program, such as aircraft structures, wind turbine blades and large industrial installations.
Scan & Go operates by scanning surfaces on site and building an understanding of their shape in real time. Instead of relying on detailed digital models or manual coding, the system plans its movements based on live data. This enables it to adapt to variations in size, curvature and surface condition without extensive setup.
The underlying technology combines 3D sensing with AI-based motion planning. The system interprets surface data, generates tool paths and refines its actions as work progresses. In practical terms, this reduces manual intervention while maintaining consistency across large work areas.
By handling surface preparation and inspection tasks that are time-consuming and physically demanding, Scan & Go is positioned as a support tool for industrial teams operating at scale.
Taken together, these robots signal a clear shift in how machines are being designed and deployed. Across factories, homes, emergency sites and industrial infrastructure, robotics is moving beyond demonstrations and into practical roles that support human work.
The unifying theme is not replacement, but relief—robots taking on tasks that are repetitive, hazardous or physically demanding. CES 2026 suggests that robotics is evolving from spectacle to utility, with a growing focus on systems that adapt to real environments, respond to genuine constraints and integrate into everyday workflows.