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keyword:P.K Tseng6 result(s)

Press Releases
TrendForce Says with Cloud Companies Initiating AI Arms Race, GPU Demand from ChatGPT Could Reach 30,000 Chips as It Readies for Commercialization


Emerging Technologies

The recent arrival of ChatGPT has generated a lot of buzz across the industry sectors related to cloud computing and artificial intelligence (AI) Tech giants such as Microsoft, Google, and Baidu have all built products and services derived from “generative AI” technologies According to TrendForce’s latest report “Trends and Challenges in Development of AI Applications as Seen from AI Generated Content (AIGC)”, this new wave of interest is expected to bring benefits to the participants across the supply chain for GPUs and AI chips These participants include NVIDIA, TSMC, Unimicron, AIChip, etc However, there are challenges pertaining to the adoption and function-related optimization of products and services that powered by generative AI Furthermore, user experience is at the core of an AI-based technology and involves the protection personal information and the accuracy of the responses to content requests Therefore, regulatory issues will likely emerge as generative AI moves to the next phase of its development TrendForce says generative AI represents an integration of different types of algorithms, pre-trained models, and multimodal machine learning Notable ones include Generative Adversarial Network (GAN), Contrast Language-Image Pre-Training (CLIP), Transformer, and Diffusion Generative AI searches for patterns in the existing data or batches of information and efficiently outputs content that is suitable for scenarios such as data collection and analysis, social interactions, copywriting, etc There are already many apps powered by generative AI in the market right now, and the most common kinds of output from them include texts, images, music, and software codes To Capture AI-Related Opportunities, Major Providers of Cloud Services First Need to Strengthen Their Own Search Engines Data, computing power, and algorithms are the three indispensable factors that drive the development of generative AI Also, while AI-based products and services are relatively easy to build, optimizing them is much more difficult In this respect, the major cloud companies are in a more advantageous position since they possess huge amounts of the essential resources From the perspective of the developers of these products, the existing chat robots such as ChatGPT are able to not only converse with users in the natural language but also somewhat meet the demand for “comprehending” users’ input Hence, having a better capability to understand what users need or desire can, in turn, provide further suggestions to users’ inquiries and responses And since using an internet search engine is pretty much a habit for the majority of people worldwide, the most urgent task of the major cloud companies is to keep optimizing their own search engines TrendForce’s latest investigation finds that Google remains the absolute leader in the global market for internet search engines with a market share of more than 90% Microsoft with its Bing now has a market share of just 3% and will unlikely pose a significant threat in the short term However, Bing is gaining more users that can contribute to its data feedback and model optimization cycle Therefore, Google has to be on guard against the chance of Microsoft creating differentiation in search-related services and perhaps capture certain kinds of opportunities in the area of online advertising Taiwan’s AIchip and eMemory Are Expected to Profit from Rising Demand for GPUs and AI-Related Chips Generative AI requires a huge amount of data for training, so deploying a large number of high-performance GPUs helps shorten the training time In the case of the Generative Pre-Trained Transformer (GPT) that underlays ChatGPT, the number of training parameters used in the development of this autoregressive language model rose from around 120 million in 2018 to almost 180 billion in 2020 According to TrendForce’s estimation, the number of GPUs that the GPT model needed to process training data in 2020 came to around 20,000 Going forward, the number of GPUs that will be needed for the commercialization of the GPT model (or ChatGPT) is projected to reach above 30,000 Note that these estimations use NVIDIA’s A100 as the basis for calculations Hence, with generative AI becoming a trend, demand is expected to rise significantly for GPUs and thereby benefit the participants in the related supply chain NVIDIA, for instance, will probably gain the most from the development of generative AI Its DGX A100, which is a universal system for AI-related workloads, delivers 5 petaFLOPS and has nearly become the top choice for big data analysis and AI acceleration Besides NVIDIA, AMD has also successively launched the MI00, MI200, and MI300 series of server chips that are widely adopted for AI-powered applications Regarding Taiwan-based companies in the related supply chain, TSMC will continue to play a key role as the premier foundry for advanced computing chips Nan Ya PCB, Kinsus, and Unimicron are the island’s suppliers for ABF substrates that could take advantage of this emerging wave of demand As for developers of AI chips from Taiwan, examples include GUC, AIchip, Faraday Technology, and eMemory Products and Services Powered by Generative AI Will Face Regulatory Challenges Due to Concerns About Personal Data and Fake Content  ChatGPT has taken off to become the leader among AI-related products and services because it enables consumers to use the technology in a very convenient and interactive manner In the future, TrendForce anticipates that generative AI in its early phase of development will mainly enter applications such as voice customer service, voice assistant, gaming, and retail Since the major players in this market are still optimizing their products, the smaller players are also limited in their efforts to build new products TrendForce believes the continuing growth of generative AI depends on whether the next-generation of products and services will be regarded by consumers as being both innovative and practical Apart from product development, the industries that are involved in generative AI will be facing challenges pertaining to regulations and training resources for machine learning There are already concerns about whether companies that offer products and services such as ChatGPT will be able to protect the data privacy of users and ensure that certain types of content such as news are “accurate” or “authentic” In addition to these issues, there is also the matter of compliance with local laws and regulations Turning to training resources, effective optimization of AI models hinges on whether providers of knowledge platform services do a good job in sorting, filtering, and integrating the various types of data that are then handed to developers of AI models for training For additional insights from TrendForce analysts on the latest tech industry news, trends, and forecasts, please visit our blog at https://insidertrendforcecom/

Press Releases
Abetted by Green Factories, Global Smart Manufacturing Market Estimated to Reach US$620 Billion by 2026, Says TrendForce


Emerging Technologies

According to TrendForce research, companies are moving actively on energy conservation and carbon reduction In the short term, the introduction of automation as an intelligent foundation will attract increasing attention from the industry and emerging market demands such as remote operations, virtual reality, and simulation operations will become more practical in the medium term This stage of development is expected to solve the dilemma posed by the slow progress of Industry 40, accelerate the development of related technologies, and drive the global smart manufacturing market to reach US$620 billion by 2026 According to TrendForce, there are quite a variety of ways for the manufacturing industry to move towards sustainable operation Looking at the common man-machine-material law in factory management, design of low-carbon machinery and equipment, selection of packaging materials, circular economy business model, use of renewable energy, and even the use of green construction facilities are all tools and means Considering cost and benefit, production process improvement and overall environmental monitoring are key areas of current Industry 40 greening technology Take the Sustainability Lighthouses selected by the World Economic Forum as an example, these smart factories utilize a plethora of Industry 40 technologies and focus on energy conservation and carbon reduction Compared with manufacturers focusing on energy optimization in 2021, the 2022 selection is more comprehensive with Western Digital, Schneider Electric, and Johnson & Johnson Janssen improving overall efficiency and migrating to green factories through technical tools such as digital twin unmanned factories, IIoT real-time energy management and control systems, and AI process management Looking further at overseas business opportunities for Taiwanese green factories, manufacturers with an existing overseas foundation will hold a relatively potential advantage and also be pressed to move their products and services closer in line with energy conservation and carbon reduction, such as Tongtai Machine & Tool forging green machine tools to maintain overseas competitiveness through strategies such as visual monitoring, digital twinning, and carbon inventory to reduce its carbon footprint, and using lightweight, innovative materials and power-saving motors in its designs TECO developed equipment systems that can reduce material loss and convert waste heat into green electricity HIWIN's intelligent ballscrew can identify the best lubrication timing to reduce lubricant use/waste and carbon emissions Delta Electronics uses low-carbon industrial automation as an entry point to focus on renewable energy power generation and energy storage systems, motor inverters, etc Since carbon neutrality cannot be achieved overnight, even if the use of intuitive green products and services or renewable energy are adopted, related supporting measures are still required to maximize benefits Therefore, more manufacturers are expected to accelerate their digital transformation and introduce industrial automation to lay green foundations in 2023, which will also become the main driving force for annual growth in the market In the medium and long term, companies can obtain data through automation to improve quality and then reduce waste and connect entire plants through digital virtualization Finally, companies can use the least resource intensive, environmentally friendly production process with integrated energy management, while maintaining market competitiveness and building a decarbonized business model for a circular economy Under the interlinked and multi-linear automatic, virtual, and low-carbon development framework, the critical core of a glorious decade for the smart manufacturing industry will be built with green manufacturing as a goal For additional insights from TrendForce analysts on the latest tech industry news, trends, and forecasts, please visit our blog at https://insidertrendforcecom/

Press Releases
Wi-Fi 6/6e Expected to Become Mainstream Technology with Close to 60% Market Share in 2022, Says TrendForce



Exponential demand growth for remote and unmanned terminals in smart home, logistics, manufacturing and other end-user applications has driven iterative updates in Wi-Fi technology Among the current generations of technologies, Wi-Fi 5 (80211ac) is mainstream while Wi-Fi 6 and 6E (80211ax) are at promotional stages, according to TrendForce’s investigations In order to meet the connection requirements of industry concepts such as the Metaverse, many major manufacturers have trained their focus on the faster and more stable next generation 80211be Wi-Fi standard amendment, commonly known as Wi-Fi 7 Considering technical characteristics, maturity, and product certification status, Wi-Fi 6 and 6E are expected to surpass Wi-Fi 5 to become mainstream technology in 2022, with global market share expected to reach 58% TrendForce states, in common residential applications of Wi-Fi, Wi-Fi 6E supports 6GHz and expands bandwidth by at least 1200MHz, delivering higher efficiency, throughput, and security than Wi-Fi 6, and can optimize remote work, VR/AR, and other user experiences Moreover, in terms of the vertical IoT sector with the highest output value, smart manufacturing still mostly employs Ethernet and 4G/5G mobile networks as the central communication technologies in current smart factories However, as early as 2019, major British aerospace equipment manufacturer, Mettis Aerospace, and the Wireless Broadband Alliance (WBA) conducted phased testing of the practicality of Wi-Fi 6 in factories, and they believe that Wi-Fi 6 can be widely adopted for manufacturing Market not yet mature, practical application of Wi-Fi 7 must wait until the end of 2023 at the earliest TrendForce believes that the introduction of Industry 40 technology tools will become more common and the degree of digitalization within companies will increase in the post-pandemic era, with 5G and Wi-Fi expected to bring complementary and synergistic effects to the manufacturing field The primary reason for this is that 5G characteristics include wide connection, large bandwidth, and low latency In addition, multi-access edge computing (MEC) and standalone (SA) network slicing can improve computing power and flexibility, all of which significantly upgrade smart manufacturing tools Although the transmission range of Wi-Fi is small, it resists interference and enhances the physical penetration of wireless signals at smart manufacturing locations Wi-Fi also reduces the cost of 5G distributed antennas and small base stations while extending communications range and improving equipment battery life Looking forward to next generation Wi-Fi 7, companies such as MediaTek, Qualcomm, and Broadcom, are already laying the groundwork for their forays into this standard TrendForce believes, even though focus is currently shifting to Wi-Fi 7, scheduled application of Wi-Fi 7 is expected to fall between the end of 2023 and the beginning of 2024 Challenges remain in terms of overall development and issues such as equipment investment, spectrum usage, deployment cost, and terminal equipment penetration must all be overcome in order to demonstrate the technical benefits of Wi-Fi 7 For additional insights from TrendForce analysts on the latest tech industry news, trends, and forecasts, please visit our blog at https://insidertrendforcecom/

Press Releases
Industrial Metaverse Expected to Propel Global Smart Manufacturing Revenue to US$540 Billion by 2025, Says TrendForce


Emerging Technologies

In light of the metaverse’s ability to satisfy the demands of WFH, virtual reality, and simulations, the smart manufacturing industry will also likely capitalize on the rise of the metaverse and undergo an accelerated growth of related technologies, according to TrendForce’s latest investigations Global smart manufacturing revenue is expected to increase at a 1535% CAGR across the 2021-2025 period and surpass US$540 billion in 2025 This growth can primarily be attributed to several factors First, industrial applications take place in closed environments, and companies that utilize such applications have generally made good progress in terms of digital transformation Furthermore, by utilizing simulation technologies, companies are able to significantly cut down on their labor costs, project time, and wasted resources Simulation technologies, if developed as an industry 40 application, also serve as the backbone of CPS (cyber-physical systems) TrendForce therefore expects the smart manufacturing industry to be perfectly positioned with innate advantages and motivations as one of the main enablers of the metaverse Regarding the diverse mainstream smart manufacturing tools, digital twins, which major adopters believe to be a significant application of industry 40, empower the simulation of the physical world through digital data, bridge the virtual world with the real world, and subsequently serve as a key technology shaping the metaverse during its infancy In particular, Microsoft has included digital twins in its metaverse technology stack due to their ability to generate rich digital models It should be pointed out that the vast majority of digital twins currently used for industrial applications deliver digital simulations for either a single product or a single production line primarily because the reliability of simulated models requires a database containing sufficient data from the modeled product itself Some examples of digital twins in action include Boeing utilizing digital twins to build engines, Unilever using simulated production lines to cut down on waste production, and Siemens Energy and Ericsson respectively leveraging Nvidia’s Omniverse platform to operate power plants and perform predictive maintenance as well as simulating equipment allocations for 5G networks Digital twin technologies will progress towards wider deployments and deeper operations in response to the rise of the metaverse and to the growing complexity of digital simulation models used for constructing products Hence, relevant digital twin technologies will also begin to emerge in the market In terms of width of deployment, digital twins need to model more comprehensive and extensive virtual objects and spaces that form the operating environment in the metaverse in order to achieve better predictive accuracy Relevant technologies include 5G, WiFi 6, cloud and edge computing, smart sensors, as well as more resilient communication environments/computing platforms, and more diverse sensors In terms of depth of operation, developments in technologies used for industrial drones, cobots, and machine vision feature improved precision and operability that enable AI-based decisions made in the virtual space to be applicable to decision-making scenarios in the real, physical world On the whole, taking into account the rapid development of AR/VR and HMI technologies, as well as other factors including economic outcomes, feasibility of operation, and the overall industrial environment, TrendForce believes that the direction of metaverse-based digital twin application development for industrial purposes will focus on human resource training, remote diagnostics, energy monitoring, and predictive maintenance in the short and medium terms For instance, Rockwell, Siemens, ABB, Advantech, Ennoconn, and Delta are some of the companies that have made good progress in this area In the long term, on the other hand, individual companies will likely be able to construct virtual factories in the collaborative industrial metaverse and thereby connect their various factory locations or even engage in cross-industrial collaborations With regards to long-term applications, then, companies that are competent in industry 40 development and possess various lighthouse factories and vast databases will likely to be pioneers in the industry; leading examples include Bosch, Schneider Electric, Haier, and Foxconn For additional insights from TrendForce analysts on the latest tech industry news, trends, and forecasts, please visit our blog at https://insidertrendforcecom/

Press Releases
Global Smart Manufacturing Revenue for 2021 Expected to Reach US305 Billion Thanks to Increased Digital Transformation and WFH Demand, Says TrendForce


Emerging Technologies

The global smart manufacturing market is expected to welcome a golden period of growth across five years, starting with an annual revenue of US305 billion in 2021 and surpassing US450 billion in annual revenue in 2025 at a 105% CAGR, according to TrendForce’s latest investigations This growth can be attributed to several factors, including the accelerating digital transformation efforts from enterprises, the increased demand from industrial automation and WFH applications, and the emergence of 5G, advanced AI technologies, and other value-added services Looking ahead to 2022, TrendForce believes that the outlook of smart manufacturing has evolved from such conservative strategies as improving the resilience of the manufacturing industry itself, to increasing the industry’s production capacity as well as efficiency while reducing both energy expenditure and carbon emissions These advantages are expected to serve as the main drivers propelling the growth of the smart manufacturing market next year Smart manufacturing development will revolve around 5G, edge computing, and carbon footprint reduction going forward The core feature of smart manufacturing lies in its ability to deliver instant feedback through the integration of virtual data and real, physical equipment Hence, low latency, high security, and fast computing power have become increasingly important for smart manufacturing development, which will revolve around edge computing and 5G applications, including AR/VR, machine vision, digital twins, and predictive maintenance, all of which will experience considerable upgrades in functionality thanks to smart manufacturing Furthermore, as the issue of global warming gains more and more media coverage, 137 countries have now committed to achieving carbon neutrality This pursuit of environmentally friendly outcomes is also reflected in the current state of industry 40 development For instance, companies including Henkel, Johnson & Johnson, Siemens, and Tata Steel all operate manufacturing facilities that qualify them for membership in WEF’s Global Lighthouse Network The aforementioned companies have ensured their facilities operate with optimized energy consumption, highly effective manufacturing processes, and reduced carbon emissions through the adoption of computer simulation/modeling and smart management TrendForce expects the future design of smart manufacturing equipment and factories to center on the use of environmentally friendly IoT technologies Taiwanese manufacturers are likely to seize shares in the niche market in light of the rise of domestic micro-factories It should be pointed out that the Taiwanese manufacturing industry possesses certain competitive advantages in the global market, including a highly consolidated supply chain, a relatively comprehensive smart manufacturing value chain, and the ability to deliver highly customized solutions In particular, various Taiwanese manufacturers specialize in full-service, integrated smart solutions that feature equipment health monitoring and machine vision functionalities, thereby significantly lowering the barrier for adoption Assuming that the domestic industry is able to continue leveraging their existing competitive advantages and furthering their current developments, TrendForce expects micro-factories to become the key factor through which Taiwanese companies can find commercial success in the global smart manufacturing industry Although the smart manufacturing value chain has historically had its various verticals spread throughout the world, recent trends such as a return of domestic manufacturing and tectonic shifts in the manufacturing industry have resulted in the rise of shortened supply chains as well as localized operations These developments have led to the recent surge of micro-factories TrendForce’s investigations indicate that, in addition to their high degree of automation and analytical accuracy, micro-factories deliver improved manufacturing outcomes while minimizing resource consumption and yielding such benefits as a flexible supply chain, lean human resources, and low initial cost Micro-factories have already seen widespread usage in the global automotive and electronics industries in light of these benefits Likewise, TrendForce believes that Taiwanese manufacturers of bicycle chains, steel nuts/bolts/screws, and suitcases will likely succeed in their respective niche markets by upgrade their manufacturing operation with micro-factories For additional insights from TrendForce analysts on the latest tech industry news, trends, and forecasts, please visit our blog at https://insidertrendforcecom/

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