"Artificial Intelligence Rated as the Most Destructive Technology Over the Next Decade"
By Qian Tongxin
Every year, Gartner's emerging technology maturity curve, commonly referred to as the Hype Cycle, captures the attention of investors and serves as a compass for businesses making significant investment decisions. This tool helps organizations evaluate the visibility of new technologies and decide whether to adopt them based on their position along a timeline and level of media exposure.
The Most Disruptive Technology of the Next Ten Years
In 2017, Gartner's emerging technology curve highlighted three major trends: ubiquitous artificial intelligence (AI), transparent and immersive experiences, and digital platforms. Among these trends, Gartner emphasized four key technology areas that decision-makers should prioritize: commercial ecosystem extension technologies like blockchain, fusion technologies such as brain-computer interfaces, commercial automation technologies like delivery drones, and security-focused technologies like software-defined security, which promise a more secure digital world.
The brightest star on the 2017 Hype Cycle was artificial intelligence. Gartner predicted that AI would become the most disruptive technology over the next decade, thanks to advancements in computational power, vast datasets, and deep neural networks. With the "wings" of AI, humans can solve problems unimaginable before, leveraging data in unprecedented ways.
In the realm of AI, Gartner noted that intelligent robots were nearing the peak of their rapid growth phase. Expectations around intelligent robots were expected to continue expanding in the coming years. Examples included Amazon Robotics' plan to deploy 10,000 robots to handle customer orders, Google's acquisitions of several robotics companies, and Rethink Robotics' launch of Baxter and Sawyer, robots capable of working alongside human employees. Additionally, hotels like Hilton and Westin began using service robots.
Machine learning also reached the apex of rapid growth. Gartner suggested that machine learning would find applications across numerous industries, from automating processes to drug discovery, enhancing customer relationships, optimizing supply chains, predicting maintenance needs, improving operational efficiency, combating fraud, advancing autonomous driving, and optimizing resources.
Virtual assistant technology, driven by tech giants like Google, Amazon, Apple, Microsoft, and Facebook, also gained traction globally. Virtual assistants became one of the first practical applications of AI accessible to everyday users.
Gartner's report highlighted how thousands of vendors explored deep learning applications in areas such as computer vision, conversational systems, and bioinformatics. Researchers continued to publish groundbreaking papers on the subject. Hardware manufacturers raced to deliver high-performance algorithms trained on deep neural networks. By 2018, it was estimated that 80% of data scientists would use deep learning as their standard tool.
Microsoft Shifts Focus to AI
Sheng Linghai, Vice President of Research at Gartner, explained to the First Financial reporter: "Companies will base their investment decisions on the maturity and positioning of these technologies." Companies generally fell into three categories: A, B, and C. Large corporations like Intel would explore new technologies early, influencing the broader technology landscape. Type B firms, like Huawei and Lenovo, adopted a cautious approach initially but quickly followed suit during the speculative peak. Type C firms, representing smaller entities, preferred waiting until the technology matured before investing.
Leading tech companies worldwide had already embraced AI, including Apple, Amazon, Google, and Facebook. Microsoft joined this race relatively late but with significant momentum. In Microsoft's latest annual financial report, AI was listed among the company's top priorities, marking a shift from its previous focus on mobile and cloud services.
Microsoft's financial report now mentions six items related to AI, none of which appeared in last year's report. The company stated: "Our strategic vision is to compete and grow by building premier platforms and productivity services for intelligent clouds, embedding intelligence into AI." This marked a departure from Microsoft's previous emphasis on mobile and cloud services.
Despite cloud services remaining Microsoft's primary revenue driver, it's evident that CEO Satya Nadella has prioritized AI. Microsoft acquired AI startups like Maluuba and Swiftkey and established a formal AI research group focused on future-oriented R&D in infrastructure, services, applications, and search.
Last month, Microsoft announced plans to develop AI chips for its new HoloLens AR device. Its next step involves enabling cloud users to accelerate AI tasks like image recognition, processing large datasets, and predicting customer buying patterns using machine learning algorithms.
Doug Burger, a distinguished engineer at Microsoft Research, stated: "We're aggressively advancing AI. Our goal is to lead in the field of AI cloud."
IBM's Watson Faces Challenges?
In response to Microsoft's entry into the AI arena, Sheng Linghai told the First Financial reporter: "If Microsoft can establish its hardware as an industry standard, its subsequent software algorithms and AI cloud services will stabilize. Microsoft's hardware platform could serve as a gateway for future software cloud services like AI, promoting various new technologies and services."
It remains unclear whether Microsoft can "catch up," but it might not be the first to reach the finish line. IBM, one of the earliest players in AI, bet heavily on Watson, expecting it to commercialize in fields like healthcare.
Last January, IBM CEO Ginni Rometty announced at CES that IBM would transition into a cognitive solutions cloud platform company, with Watson as its centerpiece. However, IBM's transformation seems to have hit a snag, as the company reported declining revenue for 21 consecutive quarters.
James Kisner, an analyst at Jefferies, commented after IBM's financial release: "While Watson is one of the most comprehensive platforms currently, IBM has fallen behind competitors in AI."
IBM's investments in Watson, including acquisitions like Explorys, Phytel, Truven, and Merge Healthcare, totaled over $4 billion, nearly double IBM's quarterly net profit. Despite these efforts, Watson's commercial ventures faced setbacks, prompting market reflection on AI. This also highlights the importance of timely involvement in emerging technologies. Forrester noted: "IBM's greatest challenge now is better leveraging synergies between AI and infrastructure, data integration, and professional services."
IBM specifically mentioned Watson in its second-quarter earnings report, stating: "Watson continues to expand globally, and cognitive intelligence presents opportunities worldwide, not just in major cities like New York, Boston, or Silicon Valley."
Coincidentally, China recently released its "New Generation Artificial Intelligence Development Plan." In response, Li Yonghui, IBM's Distinguished Engineer and Chief Technology Officer for Greater China's Hardware Systems Division, told CBN: "Many people mistakenly believe only research companies will benefit from AI. Infrastructure providers like GPU and FPGA companies, IoT firms, cloud computing service providers, and traditional companies offering AI solutions for products and services will also gain. Startups will also profit. Throughout this process, the Chinese government will benefit from the overall industry's progress."
Sheng Linghai told the First Financial reporter: "AI is still in its infancy. IBM once sold processes, services, and consultations, appealing to many corporate clients. Entering the AI era changes everything. We believe AI offers small companies an opportunity. Those providing AI cloud services will see substantial demand since small firms won't build their own high-performance AI computers. That's why both Google and IBM are developing new chips."
According to Sheng Linghai, Google's TPU chips primarily serve machine learning acceleration services for AI companies, while IBM develops neural network computing chips. He added: "New chip architectures can handle more complex AI training. But where does the data come from? Alibaba, Google, and similar companies are major players in this space."
Flat Wire Power Inductors,Flat Copper Wire Inductors,Flat Coil High Current Inductors,Flat Wire High Power Inductors
Shenzhen Sichuangge Magneto-electric Co. , Ltd , https://www.scginductor.com