AI to give fillip to new industrial revolution

Fast-growing frontier field will apply to wider range of sectors

Artificial intelligence has the potential to revolutionize various industries, and its meteoric rise will spearhead a new technological and industrial revolution, experts said.

The fast-growing generative AI technology will be increasingly applied to a wider range of sectors next year to empower such a transformation and upgrade traditional industries, they added.

Their comments come as major Chinese technology companies ramp up efforts to launch their own AI-powered large language models, which could turn into potential rivals of ChatGPT, an AI chatbot from US-based AI research company OpenAI that has taken the world by storm and triggered a new generative AI wave after it debuted in late 2022.

Generative AI refers to computer algorithms trained with huge amounts of data capable of generating content such as images, text, audio and video. It is the key technology underpinning ChatGPT, an acronym for chat generative pre-trained transformer.

As AI potentially becomes the driving force behind innovation, companies must adapt and invest in AI to stay competitive, the experts said.

The rapid growth in AI spending, the transformation of IT services, and the convergence of AI solutions are just a few of the significant changes foreseen in the technology landscape, they added.

Meanwhile, industry insiders said the commercial use of AI chatbots has raised concerns about how to regulate generative AI.

They called for ensuring responsible use of the technology and promoting its healthy advancement, considering the emergence of a new set of problems including ethics, privacy leakage and data security.

According to a report by global market research company International Data Corp, the announcement of the GPT-3.5 series from OpenAI in late 2022 captured the world's attention and triggered a surge of investment in generative AI, which will reshape the IT industry and the way businesses operate.

IDC expects that worldwide spending on AI solutions will grow to more than $500 billion in 2027, and most enterprises will experience a notable shift in the weight of technology investments toward AI implementation and adoption of AI-enhanced products and services.

The IT industry will feel the impact of AI more than any other industry, as every company races to introduce AI-enhanced products or services and to assist their customers with AI implementations, it said.

The consultancy also said that China's spending on AI will likely hit $38 billion in 2027, and account for about 9 percent of the global market, with a compound annual growth rate of about 25 percent from 2023 to 2027.

Kitty Fok, managing director of IDC China, said Chinese companies respond faster to AI deployments compared to their foreign counterparts.

AI technology is driving digital transformation across industries, including manufacturing, transportation, energy, healthcare and retail, Fok said.

"We are currently in a transitional stage in the application of generative AI," said Zhou Zhengang, vice-president of IDC China.

Zhou estimates that generative AI will speed up its integration with a wider range of sectors and evolve into a productivity tool next year. Meanwhile, an increasing number of industry-specific LLMs will emerge.

LLMs are AI models fed with huge amounts of text data for use in a variety of tasks, ranging from natural language processing to machine translation.

AI chatbots such as ChatGPT leverage machine learning algorithms and show strong capabilities in mimicking humanlike responses and assisting people with tasks such as writing essays and scripts, making business proposals and even checking program bugs, which they do within seconds.

A slew of Chinese tech giants, including Alibaba Group Holding Ltd, Baidu Inc, JD, Tencent Holdings Ltd, and iFlytek Co Ltd have accelerated steps to launch ChatGPT-like products, and bolster the large-scale commercial application of LLMs.

Alibaba Cloud, the cloud computing unit of Alibaba Group, recently unveiled its open-source 72 billion-parameter version of its AI-powered LLM, Tongyi Qianwen.

The LLM, called Qwen-72B, achieves a better performance over GPT-3.5 and GPT-4 in some authoritative LLM evaluation rankings, with enhanced capabilities in understanding English and Chinese, mathematics reasoning and coding. The company has already open-sourced LLMs with 7 billion parameters and 14 billion parameters.

"Building up an open-source ecosystem is critical to promoting the technological advancement and application of LLMs in China," said Zhou Jingren, CTO of Alibaba Cloud.

The company, Zhou said, will invest in open-source LLM, and aspires to build the most open cloud in the era of AI and make generative AI capabilities accessible to everyone.

Zhou said the open-source LLMs will help enterprises simplify the process of model training and deployment, lower thresholds for the application of LLMs and establish their own customized AI models at a faster pace.

Alibaba Cloud has also released a series of industry-specific models to boost productivity across various industries, such as customer support, legal counseling, healthcare, finance and document management.

Robin Li, co-founder and CEO of Baidu, said: "Generative AI and large language models hold immense transformative power in numerous industries, presenting a significant market opportunity for us. To stay ahead of the game, we keep upgrading our models to generate more creative responses while improving training throughput and lowering inference costs."

The company launched the latest version of its LLM, Ernie 4.0, in October, saying its capabilities are on par with those of OpenAI's most advanced GPT-4 model. The newest version boasts enhanced capacities in understanding, generation, reasoning and memory compared with previous models.

Li said Baidu is committed to building new growth momentum for generative AI and LLMs to drive sustainable long-term development.

He highlighted that the company is working hard to build Ernie-powered applications and solutions for different industries and scenarios, and empower more enterprises to create industry-specific AI models and applications.

Chinese e-commerce giant JD has unveiled its LLM, ChatRhino, which could be used in a wide range of fields, including retail, logistics, finance and health, as the company aims to bolster digital transformation and upgrade various industries by using AI.

Xu Ran, CEO of JD, said the company has accumulated huge amounts of data and knowledge from extensive industrial scenarios, and it will strengthen cooperation with industry partners to promote technological innovation.

Tencent rolled out its foundation LLM, Hunyuan, in September.

The LLM supports a wide array of functions spanning creation of images, copy writing, text recognition, and customer service.

Chinese enterprises can access Hunyuan via Tencent's public cloud platform and fine-tune it to specific needs, the company said.

Critical juncture

Global consultancy Accenture said in a report that Chinese enterprises are at a crucial juncture of breakthroughs in AI, as generative AI and other rapidly evolving technologies usher in a future for business where the physical and digital worlds are inextricably linked.

According to the report, 91 percent of the business executives surveyed in the country agreed that AI foundation models will play an important role in their organization's strategies over the next three to five years.

"As generative AI will have far-reaching impact, business leaders must act immediately and scale up investments in data, talent and customized AI models to meet the unique needs of enterprises," said Yu Yi, technology lead for Accenture Greater China.

Most Chinese executives agreed that generative AI will spark significant creativity and innovation and usher in a new era of enterprise intelligence, Yu said.

They also pointed out that their companies expect quick large-scale analytical abilities and accelerated innovation as the two major benefits from the use of AI models.

Pan Helin, co-director of the Digital Economy and Financial Innovation Research Center at Zhejiang University's International Business School, said although LLMs have significant potential for applications in a wide range of sectors like culture, retail, healthcare and education, their real value comes from the consumer market, and the ultimate goal of LLMs in industrial applications is to benefit the general public.

Noting that the process of training large AI models necessitates higher requirements for computing capacity, algorithms and quality of data, Pan said, "Chinese AI companies should increase investment in basic scientific research, including mathematics, statistics and computer science, to gain a competitive edge in the global AI chatbot race."

Moreover, the commercial use of the revolutionary AI chatbot has triggered controversy and concern about how to promote the healthy development of generative AI.

Chinese authorities issued a 24-point guideline for managing generative AI services in August. The country encourages the innovative development of generative AI and supervises the technology using methods compatible with innovation and development.

These measures support use of the technology in various fields to produce positive and high-quality content, and encourage the independent innovation of basic technologies, including generative AI algorithms, frameworks, chips and software platforms.

A group of Chinese companies and research institutions have opened their AI-powered LLMs to the public after receiving approval from the authorities on Aug 31.

"Making LLMs available to the public will boost iterations and upgrades, and promote technological advances as well as their large-scale commercial use," said Lu Yanxia, research director at IDC China.

Lu said Chinese tech companies' continual advancements in AI models will further promote the popularization of LLMs among the public, and bring about fresh business opportunities for domestic AI servers, cloud computing and chip companies.

The LLMs also necessitate a higher demand for data and knowledge in professional fields, and for talent that can fine-tune specialized models based on diverse industrial demands, she said.

Global consultancy Boston Consulting Group said generative AI will replace human beings in doing a large number of repetitive, simple and basic tasks, thus reducing costs and improving operational efficiency.

Although AI brings new development opportunities, challenges abound as data security tops in priority, and more efforts are needed to ensure that the technology is used safely and responsibly.

"It is important for banks to establish a responsible AI system and ensure fairness, accountability, transparency, privacy and security in the application of generative AI," said Sun Wei, partner of BCG and core leader of the BCG financial institutions practice.

She also called for greater efforts to formulate a code of conduct for employees who use generative AI tools, guide them to reasonably judge and use the content output by machines, and establish management mechanisms concerning risk control and liability affirmation.