The IT industry has experienced significant transformations since its early days. In the 1990s, Microsoft's Windows operating system revolutionized personal computing, making digital technology accessible to millions. Then, in 2007, Apple introduced the first iPhone, ushering in a new era of mobile computing that reshaped how people interact with technology. Fast forward to 2015, when AlphaGo defeated a top human Go player, marking a major milestone in artificial intelligence. Many experts consider this event as the most impactful moment in the current AI wave.
But what makes AI so powerful? According to Su Jiaxing, a technical marketing manager at NVIDIA, it's not just about games or specific applications. The rapid development of algorithms, the massive data generated by smartphones and the internet, and the exponential growth in computing power have all contributed to AI’s recent breakthroughs. These three factors are key to why AI is now so effective and widely applicable.
During his talk on "Market Opportunities and Challenges of AIoT Embedded Systems," Su Jiaxing emphasized that AI is one of the most transformative technologies in IT. He pointed out that the number of participants at the GPU Technology Conference (GTC) has surged over the years, and the usage of CUDA, NVIDIA’s software development platform, has grown fivefold in just five years. This growth highlights the increasing demand for GPU-based processing, which is essential for AI applications. The popularity of GTC and the success of CUDA clearly reflect the booming AI industry.
Su Jiaxing also noted that the current wave of AI applications is primarily driven by vertical industries, aligning closely with the Internet of Things (IoT). IoT systems collect vast amounts of data through sensors, providing critical input for AI platforms. The integration of large-scale data and high-performance computing units creates an AIoT architecture that enables smarter, more efficient systems.
For instance, in smart cities, it's projected that by 2020, there will be over a billion surveillance cameras worldwide. These cameras generate massive visual data that can be used for traffic monitoring, accident detection, and even criminal investigations. Traditionally, such tasks required human intervention, but with the sheer volume of data, manual processing has become impractical.
Thanks to technological advancements, AI systems are now capable of handling these tasks more efficiently than humans. In 2015, AI achieved a recognition rate of 97%, surpassing human accuracy of 95%. Whether in speed or precision, AI is proving to be a superior solution for these complex tasks.
Beyond smart cities, IoT systems across various sectors—such as manufacturing, healthcare, and agriculture—generate diverse data that requires robust computing platforms. These platforms must combine high-performance hardware and optimized software. NVIDIA offers solutions in both areas: GPUs for hardware and the CUDA platform for software development. With CUDA, developers can design efficient AIoT architectures tailored to their specific needs, using the right GPU for their application.
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