Alibaba’s research arm Damo Academy has recently published a list of top trends that are likely to shape the technology landscape this year.
Chief among them is the rise of generative AI, which recently set the world abuzz with ground-breaking applications like OpenAI’s ChatGPT, alongside promises of faster and better quality decision-making through the use of machine learning (ML).
Here’s a round-up of top trends from Alibaba, which was put together by analysing public papers and patent filings over the past three years and conducting interviews with nearly 100 scientists, entrepreneurs and engineers around the world.
Generative AI generates new content based on a given set of text, images, or audio files. Currently, Generative AI is mainly used to produce prototypes and drafts and is applied in scenarios like gaming, advertising and graphic design.
As the technology advances and becomes available at a lower cost, generative AI will become an inclusive technology that can enhance the variety, creativity and efficiency of content creation. In the next three years, Alibaba expects business models and the ecosystem around generative AI to emerge and mature, helping people to take on more creative tasks.
Traditional decision-making systems had been limited in that they handled problems with uncertainty and were slow to respond to large-scale problems. As such, academics and the tech industry began to use machine learning to optimise the decision-making process. In future, decision intelligence is expected to make its way into applications aimed at optimising seaport and airport operations, as well as manufacturing processes, among other areas.
Much has been discussed about the rise of cloud-native security as more organisations move their applications and infrastructure to the cloud. Alibaba expects security technologies and cloud computing to become more integrated than before, in tandem with growing adoption of containers, microservices and serverless computing. At the same time, cloud-native security will become more versatile and can adapt more easily to multicloud and hybrid cloud architectures.
Hardware and software integration
From Apple to Oracle, technology suppliers have long touted the benefits of tighter hardware-software integration that promises better performance and user experience. The same is true for cloud services, for which cloud suppliers have started to build chips that can bolster the performance of cloud-based applications.
In that regard, Alibaba has made a bold claim that its Cloud Infrastructure Processor (CIPU) will become the de facto standard for next-generation cloud computing and bring new development opportunities for core software R&D and dedicated chip design.
Cloud network fabric
With compute and networking capabilities converging, the idea of a cloud network fabric comprising cloud-defined protocols, software, chips, hardware, architecture and platforms is expected to replace the traditional TCP-based network architecture. Alibaba expects the cloud network fabric to become part of core networks in next-generation datacentres and cloud backbone networks.
Computational imaging is an emerging interdisciplinary technology. In contrast with traditional imaging techniques, computational imaging makes use of mathematical models and signal processing capabilities, and thus can perform unprecedented in-depth analysis on light field information.
This technology is already used in mobile phone photography, healthcare and autonomous driving. In the future, computational imaging will continue to revolutionise traditional imaging technologies, and give rise to innovative applications such as lens-less imaging, and non-line-of-sight (NLOS) imaging.
Chiplet-based design lets semiconductor manufacturers break down a system on a chip (SoC) into multiple chiplets. The chiplets can be manufactured separately using different processes and integrated into an SoC through interconnects and packaging.
The interconnect standards of chiplets are now being unified, accelerating the industrialisation process. Powered by advanced packaging technologies, chiplets could pave the way for a new wave of change in the R&D of integrated circuits and reshape the chip industry landscape.
Processing in memory (PIM)
PIM technology integrates a CPU and memory on a single chip, allowing data to be directly processed in memory. In future, compute-in-memory chips are projected to be used in more powerful applications such as cloud-based ML inferencing. This will shift the traditional compute-centric architecture towards a data-centric architecture, which will have a positive impact on cloud computing, AI, and the internet of things (IoT).
Large-scale urban digital twins
Urban digital twins have made major progress in areas such as traffic governance, natural disaster prevention and management, carbon peaking and neutrality. In future, Alibaba expects large-scale urban digital twins to become more autonomous and multi-dimensional.