What’s Driving the Next Wave of Tech: AI, Chiplets, Cloud‑Native Security and More

Multimodal Pre‑training Large Models

Multimodal pre‑training large models aim to achieve unified representation of text, images, and audio, becoming fundamental AI infrastructure. They enhance cross‑modal semantic alignment, enabling models to understand and generate across modalities. Recent breakthroughs include CLIP (image‑text matching) and BEiT‑3 (general multimodal foundation model).

Chiplet

Chiplet technology decomposes a traditional SoC into multiple silicon‑level modules that are fabricated separately and later integrated through advanced packaging. This modular approach reduces cost, enables heterogeneous process technologies, and supports IP reuse. With the formation of the UCle alliance in March 2022, chiplet interconnect standards are converging, accelerating industrial adoption and reshaping the entire chip development flow.

Compute‑in‑Memory (存算一体)

Compute‑in‑Memory integrates computation directly within storage units, eliminating data movement overhead and dramatically improving efficiency. Driven by AI workloads that require high memory bandwidth and parallelism, such solutions—based on SRAM, DRAM, or Flash—are entering verification for low‑power edge devices like smart homes, wearables, and robotics, and may later revolutionize cloud‑scale inference architectures.

Cloud‑Native Security

Cloud‑native security tightly couples security technologies with cloud infrastructure, creating a platform‑level, intelligent protection system. Security and compliance become intrinsic to cloud products, enabling automatic risk detection and self‑healing capabilities.

Soft‑Hard Integrated Cloud Computing Architecture

The next‑generation cloud architecture shifts from CPU‑centric to CIPU‑centric designs, combining software‑defined solutions with hardware acceleration. This integration accelerates cloud applications while preserving elasticity, and defines new service standards for future cloud ecosystems.

Predictable Fabric (端网融合的可预期网络)

Predictable Fabric is a cloud‑defined, high‑performance network that tightly couples servers and networking to enable scalable compute clusters. It supports both emerging high‑performance computing scenarios and general workloads, promising to replace traditional TCP‑based data‑center networks.

Dual‑Engine Intelligent Decision

Combining operations‑research optimization with machine‑learning models creates a dual‑engine decision system that addresses large‑scale, dynamic resource allocation problems. This approach improves solution speed and quality for applications such as power grid dispatch, port throughput, airport scheduling, and manufacturing process optimization.

Computational Optical Imaging

Computational optical imaging merges optics with signal‑processing algorithms to capture multidimensional light‑field information (angle, polarization, phase). It surpasses traditional imaging limits and is already applied in smartphones, medical imaging, and autonomous driving, with future prospects in lens‑free and non‑line‑of‑sight imaging.

Large‑Scale City Digital Twin

City digital twins have evolved from 2D models to large‑scale, three‑dimensional, autonomous, and global representations. Recent advances enable massive dynamic sensing, real‑time rendering, and joint simulation, supporting applications in traffic management, disaster response, and carbon‑neutral initiatives.

Generative AI

Generative AI (AIGC) creates new content from existing text, audio, or images. Recent breakthroughs include diffusion models (e.g., DALL·E‑2, Stable Diffusion) for image generation, GPT‑3.5‑based ChatGPT for NLP, and GitHub Copilot for code. As the technology matures, it will become a ubiquitous foundation for digital content creation.