AI Industry Review in 2024 Part One: The Wave of Prosperity and Innovation

by Anthony Law    2024-12-08

In this era of rapid technological advancement, artificial intelligence (AI) is undeniably one of the most remarkable fields. As 2024 is drawing to a close, we have initiated a series of reviews of the AI industry in this year. This is the first of the three AI industry reviews, which will focus on the overall development pattern of the global AI industry and deeply analyze the trends presented in various aspects such as technological innovation, industry penetration, and corporate competition.

In 2024, the global AI industry has exhibited a scene of vigorous development and fierce competition. AI technology has continuously penetrated into various industries, ranging from healthcare to financial services, from transportation to manufacturing, almost everywhere. Governments of different countries have regarded AI as a crucial strategic development area and vigorously invested resources to promote their own AI research and applications.

1. Widespread Penetration of AI Technology in Various Industries

In 2024, the global AI industry has presented a picture of booming development and intense competition. AI technology has continuously infiltrated into every industry, from healthcare to financial services, from transportation to manufacturing, it is almost ubiquitous.

Healthcare

AI has made remarkable progress in medical image diagnosis. Through learning and analyzing a large amount of medical image data, AI systems can quickly and accurately identify lesion sites, assist doctors in diagnosis, and improve diagnostic efficiency and accuracy. For example, some AI systems can analyze X-ray, CT and other images to help doctors detect signs of diseases such as tumors more quickly.

Financial Services

Banking and other financial institutions utilize AI for risk assessment, intelligent investment advisory and other businesses. AI systems can more precisely evaluate the credit risk of customers by analyzing multi-dimensional data such as customers' consumption behavior and credit records, providing a scientific basis for loan approval. At the same time, the intelligent investment advisory service can offer personalized investment portfolio suggestions according to customers' investment goals and risk preferences, lowering the investment threshold and enabling more ordinary investors to enjoy professional financial services.

Transportation

Autonomous driving technology is one of the important applications of AI in the transportation field. With the help of deep learning and sensor technology, autonomous vehicles can sense the surrounding environment, make decisions and control the vehicle's driving. In addition, AI is also used for traffic flow prediction and intelligent traffic management. Through real-time analysis of traffic data, it optimizes the control of traffic lights and alleviates traffic congestion.

Manufacturing

The applications of AI in the manufacturing industry include quality inspection, production process optimization, etc. For example, by using computer vision technology, AI systems can quickly detect products on the production line, timely discover defective products, and improve product quality. At the same time, through the analysis of production data, AI can optimize the production process, improve production efficiency and reduce production costs.

2. Emphasis and Investment of Governments in AI

Governments of various countries have regarded AI as a key strategic development area and vigorously invested resources to promote their own AI research and applications.

United States

The US government has introduced a series of policies and plans to support AI research and development. For example, the Defense Advanced Research Projects Agency (DARPA) of the United States has carried out a number of AI-related projects, aiming to promote the application of AI technology in the military field. In addition, the National Science Foundation (NSF) of the United States has also increased its funding for AI basic research and cultivated a large number of AI professionals.

China

The Chinese government attaches great importance to the development of the AI industry and has issued policy documents such as the "New Generation Artificial Intelligence Development Plan", clearly defining the development goals and key tasks of the AI industry. At the same time, the government has also increased its financial investment in AI research and development, supported the establishment of numerous AI industrial parks, formed a good industrial ecological environment, and attracted a large number of enterprises and talents to engage in the AI field.

European Union

The European Commission has released the "Artificial Intelligence Coordination Plan", aiming to promote cooperation and coordination among EU member states in the AI field. The European Union also plans to invest billions of euros in AI research and innovation to promote the application of AI technology in healthcare, transportation, energy and other fields.

3. Innovative Breakthroughs in Core AI Technologies

Deep learning, natural language processing, and computer vision, as core AI technologies, have seen continuous innovation. AI chips in 2024 play a crucial role in facilitating these advancements.

Deep Learning

New neural network architectures like Transformer have enhanced AI systems' intelligence. In 2024, Nvidia's H100 Tensor Core GPU is significant. It boosts computing power and energy efficiency for neural network tasks. AMD's MI300 series also stands out with its innovative design and better memory bandwidth and floating-point computing. Google's TPU v5 is competitive in specific scenarios, optimized for TensorFlow.

In China, Huawei's Ascend AI chips progress. The Ascend AI cloud service, with its full-stack design, offers computing power support. Huawei Cloud's centers across the country provide efficient services. For example, iFLYTEK and SF Technology benefit from Ascend in their model development.

Natural Language Processing

Natural language processing has advanced in speech, translation, and text generation. Google's AI assistant is smarter. OpenAI's GPT models are powerful. In 2024, AI chips for this field speed up text processing and support large models. A startup's NLP-Chip1 is five times faster than general chips in long-text tasks.

Domestic Cambricon explores here. Its chips perform well in specific natural language tasks, aiding domestic development.

Computer Vision

Computer vision has breakthroughs in image recognition and more. It's used in security and driving. In 2024, AI chips with specialized units improve image processing. Intel's Mobileye EyeQ5 is excellent in autonomous driving, handling sensor data well.

Chinese HiSilicon and Cambricon's chips have wide use. HiSilicon's chips enhance machine vision, cutting costs and improving accuracy.

On December 3, 2024, the Artificial Intelligence Chip Working Group of the National Integrated Circuit Standardization Technical Committee was established in Beijing, which is a milestone for China's AI chip standardization, promoting industry growth and innovation.

4. Integration Trend of AI and Other Advanced Technologies

At the same time, the integration trend of AI with other advanced technologies such as the Internet of Things (IoT), big data, and cloud computing has become increasingly evident.

Integration of AI and IoT

By combining AI technology with IoT devices, intelligent interconnection and collaborative work among devices can be realized. For example, a smart home system can use AI technology to achieve intelligent control of household appliances, automatically adjusting temperature, lighting and other environmental parameters according to users' habits and needs.

Integration of AI and Big Data

Big data provides rich data resources for AI, enabling AI systems to learn and train better. At the same time, AI technology can also be used for the analysis and mining of big data to discover the potential value in the data. For example, enterprises can use AI technology to analyze customer data, understand customer needs and optimize marketing strategies.

Integration of AI and Cloud Computing

Cloud computing provides powerful computing power support for AI, enabling AI systems to train and infer more quickly. At the same time, AI technology can also be used for resource management and optimization of cloud computing to improve the efficiency and performance of cloud computing. For example, cloud service providers can use AI technology to dynamically allocate server resources and automatically adjust resource configurations according to users' needs.

5. Competition of Global Tech Giants in the AI Field

The competition among global tech giants in the AI field has reached an intense level, with major players making significant strides in research and development.

Google: Leading the Charge in AI Innovation

Google has made substantial investments in AI research and development, positioning itself at the forefront of voice recognition and intelligent interaction. Its AI assistant excels in these areas and has achieved remarkable results in natural language processing and computer vision, exemplified by innovations like the BERT model.

Microsoft: Transforming Productivity with AI

Microsoft has seamlessly integrated AI into its suite of office software, enhancing productivity across the board. Features like the intelligent writing assistant in Word and advanced data analysis tools in Excel streamline workflows and improve efficiency. Additionally, Microsoft is exploring critical areas such as cloud computing and AI ethics, ensuring its technologies are not only effective but also responsible.

Amazon: Optimizing Logistics with AI

Amazon leverages AI to enhance logistics and supply chain management, utilizing predictive analytics to forecast inventory needs and optimize delivery routes, ultimately reducing operational costs. The company has also launched a range of AI-driven products and services in smart home technology and voice recognition, such as the popular Amazon Echo.

China's Tech Giants: Innovating at Breakneck Speed

In China, tech giants are making remarkable advancements in the AI sector.

Baidu: Pioneering Autonomous Driving

Baidu's Apollo autonomous driving platform is continuously evolving through collaborations with automobile manufacturers to accelerate commercialization. The company's voice recognition technology is widely used in smart speakers and other devices. Baidu has also achieved breakthroughs in natural language processing and image recognition, bolstering its search business and various intelligent applications.

Alibaba: Revolutionizing E-Commerce with AI

Alibaba capitalizes on its strengths in e-commerce and cloud computing by integrating AI into its intelligent logistics system. This integration optimizes warehouse management and delivery route planning, significantly improving efficiency. Additionally, Alibaba's intelligent customer service operates 24/7, enhancing user experience while actively developing a smart home ecosystem.

Tencent: Enhancing User Experience through AI

Tencent applies AI extensively within its core businesses of gaming and social networking. In gaming, AI enhances graphics rendering, designs intelligent non-player characters (NPCs), and combats cheating to improve player experiences. On social platforms, Tencent utilizes AI for personalized content recommendations, friend matching, and relationship analysis. Furthermore, it strengthens risk prevention measures to ensure secure payment transactions in fintech.

ByteDance: Harnessing AI for Content Creation

ByteDance showcases strong AI capabilities across its product lineup. Douyin (the Chinese version of TikTok) employs sophisticated algorithms to deliver personalized video recommendations based on user preferences. Its creative tools assist users with copywriting and video editing, fostering creativity while simplifying content creation. Additionally, ByteDance's cloud services integrate AI to offer intelligent solutions for enterprise customers.

Xiaomi: Building a Smart Ecosystem

Xiaomi is focused on developing its intelligent voice assistant, Xiao AI, which can accurately perform various tasks. The company also leverages AI to enhance mobile photography capabilities while striving to create a comprehensive smart hardware ecosystem. Through device collaboration powered by AI, Xiaomi expands its influence in the consumer-level AI market.

Huawei: Powering AI with Advanced Chips

Huawei's Ascend series chips provide robust computing power for AI applications across multiple scenarios. In telecommunications, Huawei employs AI to optimize 5G networks while exploring applications in intelligent security and industrial manufacturing to drive industry-wide upgrades.

6. The Rise of AI Start-ups

In addition to tech giants, a large number of start-ups have emerged like bamboo shoots after a spring rain. However, in 2024, AI start-ups face many new challenges and changes.

On the one hand, the sharp rise in the development cost of AI models has led to a wave of mergers and acquisitions. Training large-scale AI models, such as the GPT series models, requires a huge amount of computing resources and data. According to industry research reports, developing an advanced AI model may involve an investment of millions of dollars or more, including hardware procurement, data labeling, algorithm research and development, and professional talent recruitment. Most start-ups, without a stable profit model, find it difficult to bear such high costs continuously. For example, some start-ups focusing on natural language processing face a tight capital chain when trying to develop similar large-scale language models, forcing them to seek acquisition or cooperation with other enterprises to obtain more resource support.

On the other hand, the huge pressure faced by start-ups is not something that every scientific research talent can or is willing to bear. In large tech enterprises, scientific research talents can often focus on technological research and development, enjoy relatively favorable treatment and a relatively stable working environment. They can use the large-scale computing facilities, rich data resources and professional team collaboration provided by the enterprise to deeply explore the frontier fields of AI technology without having to worry too much about corporate operation management, market expansion and capital raising. For example, in the AI research laboratories of Microsoft or Google, scientific research personnel can devote themselves to conquering complex technical problems such as the combination of quantum computing and AI under a good academic atmosphere and sufficient resource guarantee, publish high-level research results, and have a relatively clear career promotion path. In contrast, scientific research personnel in start-ups may need to take on multiple roles, not only being responsible for technological innovation, but also participating in marketing, customer liaison and even financial management, which is a huge test for their comprehensive abilities and psychological endurance.

Despite facing numerous difficulties, there are still many AI start-ups showing strong vitality and potential in specific fields.

AI Medical Image Diagnosis Field

Some start-ups focus on using AI technology for medical image diagnosis, such as Infervision. These enterprises have developed AI systems with high-precision diagnostic capabilities through the analysis and mining of a large amount of medical image data, providing auxiliary diagnostic tools for doctors and improving the efficiency and accuracy of medical diagnosis.

AI Educational Auxiliary Tools Field

Some start-ups are committed to developing AI educational auxiliary tools, such as Squirrel AI. These enterprises provide personalized learning plans and tutoring services for students through the analysis and mining of students' learning data, improving students' learning effects and interests.

Other Fields

In addition, in fields such as autonomous driving, financial technology, and intelligent manufacturing, many excellent AI start-ups have emerged. These enterprises have occupied a place in the global AI market with their innovative technologies and flexible business models and have also injected new vitality into the entire industry.

Conclusion

In 2024, the global AI industry has shown a booming development trend. The widespread penetration of AI technology in various industries, the emphasis and investment of governments, the innovative breakthroughs in core AI technologies, the integration of AI with other advanced technologies, and the competition and rise of tech giants and start-ups have all promoted the rapid development of the AI industry. However, the AI industry also faces many problems during its development, such as technological interpretability, data security and privacy, ethics and morality, and global regulatory differences. In the future, the global AI industry needs to continuously promote in aspects such as technological innovation, competition among giants and the rise of start-ups and technology integration, while focusing on solving these problems to achieve sustainable development and make this great technology better benefit human society.