As we sail into the era of seamless technological integration, Mirae Asset Management has pioneered the first-ever exchange-traded fund (ETF) centered on on-device artificial intelligence (AI) technology. This fresh investment avenue focuses on the burgeoning ecosystem of on-device AI, allowing investors to tap into the companies spearheading this innovation.
At the heart of this technology lies the capability for artificial intelligence processes to occur directly on user devices, bypassing the need to transmit data to external servers. This not only secures data privacy but also enhances accessibility, allowing AI to evolve into a ubiquitous personal assistant that operates independently of an internet connection.
The ETF, named TIGER Global On-Device AI, zeroes in on firms with a strong global presence in the on-device AI sphere, including those specialized in developing Neural Processing Units (NPUs). NPUs are central to AI operation, pivotal for performing inference calculations essential to AI’s responsiveness.
Anticipation is surging for this ETF as experts predict a skyrocketing demand for semiconductors dedicated to AI inference, potentially accounting for the lion’s share of global semiconductor usage. Leading the charge in the NPU market are tech giants like Apple, Qualcomm, and ARM. This ETF also handpicks top-tier platform companies such as Microsoft, Google, and Meta, all currently competing in the advanced deep learning algorithm space.
To mark the launch of TIGER Global On-Device AI, Mirae Asset Management celebrates with promotional events for trading clients in collaboration with securities firms. The manager of ETF at Mirae Asset, expressed enthusiasm for the ETF’s potential, likening the investment opportunity to that of an early stake in a company on the scale of NVIDIA, given the expected acceleration of the NPU market to cater to everyday AI applications.
Current Market Trends:
There is a significant trend towards investing in technologies related to artificial intelligence (AI), driven by increased usage of AI in various sectors ranging from healthcare to finance and from smart home devices to automotive industry. The development of on-device AI is particularly noteworthy for its ability to process data directly on the device, increasing privacy and reducing latency, making it ideal for applications like smartphones, wearables, and Internet of Things (IoT) devices. Consequently, there is an increasing demand for semiconductor components such as Neural Processing Units (NPUs), which are specialized hardware designed to efficiently run AI algorithms.
Forecasts:
The AI market, including on-device AI, is expected to grow significantly in the coming years. According to research from Gartner or IDC, the AI semiconductor market could see growth rates well above the general semiconductor market. As AI becomes more integrated into consumer electronics and industrial applications, the investment in specialized AI chips, like NPUs, is expected to surge, presenting a substantial opportunity for growth in the ETF market targeting these technologies.
Key Challenges and Controversies:
One challenge facing on-device AI and related investment products like the TIGER Global On-Device AI ETF is the rapid pace of technological change, which can make picking winning companies difficult. Furthermore, there are ongoing controversies regarding data privacy and the ethical use of AI. With on-device AI, while there is increased privacy due to data processing occurring locally, concerns around bias, decision transparency, and regulatory compliance persist. These concerns could lead to regulatory challenges and public skepticism that might impact market perception.
Important Questions:
1. What are the key technologies and companies driving the on-device AI trend?
2. How does on-device AI impact data privacy and security compared to cloud-based AI?
3. What are the potential applications and industries that might benefit from this technology?
4. How does on-device AI contribute to the increasing demand for specialized semiconductors?
Advantages of On-Device AI:
– Increased Privacy: Data is processed locally on the device, reducing the risk of data breaches or misuse.
– Lower Latency: By enabling real-time processing without the need for a network connection, responsiveness is greatly improved.
– Enhanced Accessibility: With AI being able to operate independently of a network, services can be accessed in more locations.
Disadvantages of On-Device AI:
– Device Limitations: On-device AI is limited by the computational power of the device, which may not match that of cloud-based solutions.
– Algorithm Complexity: The complexity of algorithms that can run on a device is limited compared to those that can be processed in a data center.
– Cost: The additional hardware required for on-device AI, such as NPUs, can increase the cost of devices.
Finally, for investors interested in keeping up with financial services and investment opportunities, Mirae Asset Management’s main website can be a helpful resource: miraeasset.com. Please note that investment involves risks, and it’s crucial for investors to perform their own due diligence before investing.
The source of the article is from the blog mgz.com.tw