By 2025, the AI market is expected to exceed $6 trillion.
Bitcoin technology has been instrumental in the development of artificial intelligence.
Content sponsored by PlatON Network
When the popularization of computers began 70 years ago, we could never have imagined the level of digitization that the world is experiencing today. With the advent of the metaverse and the development of artificial intelligence (AI), it is becoming increasingly difficult to distinguish between the physical and the digital.
On the other hand, data has become a valuable resource in the digital age. Generated from recording the characteristics and behaviors of observed objects, the data can take many forms, including words, numbers, graphics, audio, and video.
According to Statista, it is estimated that connected devices worldwide will number 30.9 billion units by 2025. These devices generate massive data. IDC predicts that by the same year, the global data circle will expand to 163ZB (1 trillion GB), which is ten times the 16.1ZB of data generated in 2016.
How can we harness the value of data at such a scale? Artificial intelligence may be the answer.
60 years ago artificial intelligence appeared on the map
During a six-month seminar at Dartmouth College in the summer of 1956, a group of young scientists, including Minsky, coined the term “artificial intelligence.” Since then, machine learning algorithms based on big data and a great computing power have made advances in various fields of artificial intelligence.
Today, most people are familiar with artificial intelligence. This technology has been integrated into our daily lives. From online shopping to industrial production, we see the convenience and progress that artificial intelligence brings.
Deloitte’s White Paper on the global development of artificial intelligence in 2019, predicted that The global AI market is expected to exceed $6 trillion by 2025with a compound growth rate of 30% from 2017 to 2025. A research report published by PwC suggests that global GDP will be 14% higher by 2030 as a result of AI adoption, contributing an additional $15.7 trillion to the World economy.
Over the last 60 years, the field of artificial intelligence has flourished. As we move into the fourth industrial revolution, the technological revolution, the power of this technology has become increasingly evident.
Data privacy: an obstacle for artificial intelligence?
For artificial intelligence to become the core technology, three elements are indispensable: data, algorithms, and computing power.
The widespread adoption of the mobile Internet has contributed to the incredible growth of global data. This data provides the “production material” for the AI. Although we cannot deny the great advance of artificial intelligence, there are still obstacles to overcome for its mass adoption.
The first challenge is the pressure of data governance and privacy. In 2018, the European Union introduced the General Data Protection Regulation (GDPR). In 2021, China’s Data Security Law and Personal Information Protection Law came into effect. All these stricter regulations on privacy and personal data seek to effectively prevent the misuse of data.
Furthermore, data privacy pressure also comes from within. Companies face a big dilemma: while sharing data and interacting with other companies clearly improves the performance of AI algorithms, they must also ensure that their data is not disclosed as such.
Further, developing artificial intelligence is expensive. Some institutions believe the cost of training next-generation AI models could increase by a factor of 100 by 2025, from around $1 million today to more than $100 million.
Faced with challenges such as data privacy, high costs, and the centralization of technologies, how can artificial intelligence overcome these obstacles and move forward? The research and application of certain cutting-edge technologies have paved the way.
Blockchain comes to the rescue
The emergence of blockchain and computing to preserve privacy has inspired AI. The ingenious fabric of data has catalyzed the interplay between blockchain, privacy-preserving computing, and AI in different ways. When these technologies are combined, data processing reaches a new level.
For example, Blockchain consensus algorithms help complete subject collaboration tasks in AI systems. At the same time, its technical characteristics allow data recovery. That way, you can incentivize the addition of a broader range of data, algorithms, and computing power to build more efficient AI models.
There are a variety of platforms developed to preserve privacy. AntChain Morse MPC and Baidu MesaTEE are an example. Howevermost of these platforms provide their services to other companies. The reason is simple: inter-company data business is the most fundamental business need, which solves the basic contradiction between companies for data sharing, interaction, and AI algorithm improvement.
Business services are just the beginning of what AI can achieve so far. In the foreseeable future, data ownership will eventually be returned to individuals.
Recently, a product launched by a company that focuses on cutting-edge technology has shown users and the market a new direction in the application of Universal Artificial Intelligence (UAI).
A solution to the problem of data privacy
A network innovatively designed to integrate the three elements of artificial intelligence (computing power, algorithm, and data) is PlatON Privacy-preserving Computation Network (tentative name). Is a network of decentralized computing infrastructure to share data and preserve privacy.
Plato It is not only useful for companies, but also for individuals. Individuals and institutions can add data and participate in the computing tasks posted on the platform, as well as provide computing power on the platform to complete the computing tasks of others. Individual AI developers can develop their desired AI algorithms and computing tasks completed with their algorithms will also generate profit for them.
This innovative approach enables effective ownership identification, pricing and data protection, as well as privacy-preserving asset creation.
The network has multiple measures to preserve data privacy. Secure collaborative computing, zero-knowledge proof, homomorphic encryption, verifiable computing, federal learning, and other cryptographic technologies protect data well.
Besides, the computational results, such as the trained AI models, are also protected against leaks. The products can efficiently run smart contracts and popular deep learning frameworks seamlessly, ensuring their versatility, compatibility and high availability.
PlatON is undergoing closed beta testing, and such a large and complex platform will inevitably face challenges. How to price data by multiple parties? How to accurately capture and apply data as it flows between various parties? How to attract AI developers to provide basic algorithms?
It is evident that this is an amount of data never seen before. The integration and application of new technologies takes time, but Plato has already taken a step forward in the commercialization of data.