CAMBRIDGE, UK – Artificial Intelligence is transforming the world as we know it; from the success of DeepMind over Go world champion Lee Sedol in 2016 to the robust predictive abilities of OpenAI’s ChatGPT, the complexity of AI training algorithms is growing at a startlingly fast pace, where the amount of compute necessary to run newly-developed training algorithms appears to be doubling roughly every four months. In order to keep pace with this growth, hardware for AI applications is needed that is not just scalable – allowing for longevity as new algorithms are introduced while keeping operational overheads low – but is also able to handle increasingly complex models at a point close to the end-user.

Drawing from the “AI Chips: 2023–2033” and “AI Chips for Edge Applications 2024–2034: Artificial Intelligence at the Edge” reports, IDTechEx predicts that the growth of AI, both for training and inference within the cloud and inference at the edge, is due to continue unabated over the next ten years, as our world and the devices that inhabit them become increasingly automated and interconnected.

The why and what of AI chips

The notion of designing hardware to fulfill a certain function, particularly if that function is to accelerate certain types of computations by taking control of them away from the main (host) processor, is not a new one; the early days of computing saw CPUs (Central Processing Units) paired with mathematical coprocessors, known as Floating-Point Units (FPUs). The purpose was to offload complex floating point mathematical operations from the CPU to this special-purpose chip, as the latter could handle computations more efficiently, thereby freeing the CPU up to focus on other things.

As markets and technology developed, so too did workloads, and so new pieces of hardware were needed to handle these workloads. A particularly noteworthy example of one of these specialized workloads is the production of computer graphics, where the accelerator in question has become something of a household name: the Graphics Processing Unit (GPU).

Just as computer graphics required the need for a different type of chip architecture, the emergence of machine learning has brought about a demand for another type of accelerator, one that is capable of efficiently handling machine learning workloads. Machine learning is the process by which computer programs utilize data to make predictions based on a model and then optimize the model to better fit with the data provided, by adjusting the weightings used. Computation, therefore, involves two steps: Training and Inference.

The first stage of implementing an AI algorithm is the training stage, where data is fed into the model, and the model adjusts its weights until it fits appropriately with the provided data. The second stage is the inference stage, where the trained AI algorithm is executed, and new data (not provided in the training stage) is classified in a manner consistent with the acquired data.

Of the two stages, the training stage is more computationally intense, given that this stage involves performing the same computation millions of times (the training for some leading AI algorithms can take days to complete). As such, training takes place within cloud computing environments (i.e. data centers), where a large number of chips are used that can perform the type of parallel processing required for efficient algorithm training (CPUs process tasks in a serialized manner, where one execution thread starts once the previous execution thread has finished. In order to minimize latency, large and numerous memory caches are utilized so that most of the execution thread’s running time is dedicated to processing. By comparison, parallel processing involves multiple calculations occurring simultaneously, where lightweight execution threads are overlapped such that latency is effectively masked. Being able to compartmentalize and carry out multiple calculations simultaneously is a major benefit for training AI algorithms, as well as in many instances of inference). By contrast, the inference stage can take place within both cloud and edge computing environments. The aforementioned reports detail the differences between CPU, GPU, Field Programmable Gate Array (FPGA) and Application-Specific Integrated Circuit (ASIC) architectures, and their relative effectiveness in handling machine learning workloads.

Within the cloud computing environment, GPUs currently dominate and are predicted to continue to do so over the next ten-year period, given Nvidia’s dominance in the AI training space. For AI at the edge, ASICs are preferred, given that chips are more commonly designed with specific problems in mind (such as for object detection within security camera systems, for example). Digital Signal Processors (DSPs) also account for a significant share of AI coprocessing at the edge, though it should be noted that this large figure is primarily due to Qualcomm’s Hexagon Tensor Processor (which is found in their modern Snapdragon products) being a DSP. Should Qualcomm redesign the HTP such that it strays from being a DSP, then the forecast would heavily skew in favour of ASICs.

AI as a driver for semiconductor manufacture

Chips for AI training are typically manufactured at the most leading-edge nodes (where nodes refer to the transistor technology used in semiconductor chip manufacture), given how computationally intensive the training stage of implementing an AI algorithm is. Intel, Samsung, and TSMC are the only companies that can produce 5 nm node chips. Out of these, TSMC is the furthest along with securing orders for 3 nm chips. TSMC has a global market share for semiconductor production that is currently hovering at around 60%. For the more advanced nodes, this is closer to 90%. Of TSMC’s six 12-inch fabs and six 8-inch fabs, only two are in China, and one is in the USA. The rest are in Taiwan. The semiconductor manufacture part of the global supply chain is therefore heavily concentrated in the APAC region, principally Taiwan.

Such a concentration comes with a great deal of risk should this part of the supply chain be threatened in some way. This is precisely what occurred in 2020 when a number of complementing factors (discussed further in the “AI Chips: 2023 – 2033” report) led to a global chip shortage. Since then, the largest stakeholders (excluding Taiwan) in the semiconductor value chain (the US, the EU, South Korea, Japan, and China) have sought to reduce their exposure to a manufacturing deficit, should another set of circumstances arise that results in an even more exacerbated chip shortage. This is shown by the government funding announced by these major stakeholders in the wake of the global chip shortage.These government initiatives aim to spur additional private investment through the lure of tax breaks and part-funding in the way of grants and loans. While many of the private investments displayed pictorially below were made prior to the announcement of such government initiatives, other additional and/or new private investments have been announced in the wake of them, spurred on as they are by the incentives offered through these initiatives.

A major reason for these government initiatives and additional private spending is the potential of realizing advanced technology, of which AI can be considered. The manufacture of advanced semiconductor chips fuels national/regional AI capabilities, where the possibility for autonomous detection and analysis of objects, images, and speech are so significant to the efficacy of certain products (such as autonomous vehicles and industrial robots) and to models of national governance and security, that the development of AI hardware and software has now become a primary concern for government bodies that wish to be at the forefront of technological innovation and deployment.

Growth of AI chips over the next decade

Revenue generated from the sale of AI chips (including the sale of physical chips and the rental of chips via cloud services) is expected to rise to just shy of USD$300 billion by 2034, at a compound annual growth rate of 22% from 2024 to 2034. This revenue figure incorporates the use of chips for the acceleration of machine learning workloads at the edge of the network, for telecom edge, and within data centers in the cloud. As of 2024, chips for inference purposes (both at the edge and within the cloud) comprise 63% of revenue generated, with this share growing to more than two-thirds of the total revenue by 2034.

This is in large part due to significant growth at the edge and telecom edge, as AI capabilities are harnessed closer to the end-user. In terms of industry vertical, IT & Telecoms is expected to lead the way for AI chip usage over the next decade, with Banking, Financial Services & Insurance (BFSI) close behind, and Consumer Electronics behind that. Of these, the Consumer Electronics industry vertical is to generate the most revenue at the edge, given the further rollout of AI into consumer products for the home. More information regarding industry vertical breakout can be found in the relevant AI reports.

For more information regarding key trends and market segmentations with regards AI chips over the next ten years, please refer to the two reports: “AI Chips: 2023–2033” and “AI Chips for Edge Applications 2024–2034: Artificial Intelligence at the Edge”.

FARNBOROUGH, UK – Gen3, Global leader in SIR, CAF, Solderability, Ionic Contamination & process optimisation equipment, is excited to announce its participation in the Southern Manufacturing & Electronics Expo, taking place Feb. 6-8, 2024 at the Farnborough International Exhibition Centre. GEN3 will be exhibiting a range of innovative products, including MEK's JDz650 inline and Desktop Verispector AOI systems, MBTech's N29 SA4 Stencil Cleaning Equipment, and the GEN3 AutoSIR2+ and NEW CM Series.

MEK JDz650 and Desktop Verispector AOI Systems: MEK's iSpector JDz AOI systems, featuring a 5-megapixel camera, offer advanced inspection capabilities for both SMT and THT solder joints. The JDz utilizes a Z-axis for maximum flexibility in THT and sandwiched SMD inspection, allowing inspection of objects at different height levels. The VeriSpector AOI system is a cost-effective solution for inspecting THT components before they enter the wave or selective soldering machine, providing real-time assembly and placement inspection with short inspection times of under 5 seconds.

MBTech N29 SA4 Stencil Cleaning Equipment: The N29 SA4 Stencil Cleaning Equipment from MBTech boasts stainless steel construction, automation with PLC, ultrasonic cleaning system, closed-loop water-based process with patented filtration, rinsing with filtered cleaning liquid, and water-free operation. This state-of-the-art equipment is designed for high-precision cleaning of stencils, ensuring efficiency, low power consumption, and superior results.

GEN3 AutoSIR2+: GEN3's AutoSIR2+ system represents a significant advancement in SIR (Surface Insulation Resistance) testing. With shielded precision electronics, it allows state-of- the-art accuracy resistance measurements up to 10^14Ω. The system can monitor up to 256 x 2-point test patterns or 78 x 5- point test patterns, providing a full picture of electrochemical reactions on a circuit assembly. The frequent monitoring capability enables early trend analysis, saving considerable test time and money.

NEW CM Series: GEN3 will introduce the NEW CM Series with redesigned software and hardware for an enhanced user experience. The system offers accelerated testing cycles, completing within 3 minutes, without compromising accuracy.

The CM Series optimizes measurement capability, delivering better accuracy and stability. GEN3 will also represent other key principles in the UK and Ireland market, including Finetech, Hirox, and Nordson.

Visit GEN3 at Stand C100 during the Southern Manufacturing & Electronics Expo to explore these cutting-edge solutions and gain insights into the future of electronics manufacturing.

For more information about Gen3 and its innovative testing solutions, visit www.gen3systems.com 

BEWHOLME, UK – Bentec is pleased to announce that GPS Technologies GmbH, a leading supplier of electronics manufacturing solutions in Central Europe, now represents Prey by Detech’s cutting-edge Universal Product Inspector (UPI) in the region. As a company at the forefront of integrated manufacturing solutions, GPS Technologies is set to enhance its customer offerings by incorporating the versatile and user-friendly UPI into its product portfolio.

With strategic partnerships spanning Europe, the USA, and Asia, GPS Technologies has established itself as a key player in the electronics manufacturing sector. The company’s commitment to providing real added value and a competitive advantage to its customer base aligns seamlessly with the innovative features and capabilities of the Prey UPI.

GPS Technologies specializes in delivering manufacturing and process solutions tailored to the specific needs of the automotive, industrial electronics, and EMS sectors. The comprehensive product range includes laser marking systems, stencil printers, dispensers, soldering systems, inspection systems (SPI, AOI, AXI), board handling systems, process materials, software solutions (NPI/MES), autonomous transport systems, collaborative robot solutions, and more.

The collaboration with Prey by Detech introduces the Universal Product Inspector (UPI) as the latest equipment development to further strengthen GPS Technologies’ position in the market. The UPI leverages years of vision and software expertise to provide a cost-effective, versatile visual inspection system. “The Prey UPI is a game-changer in the realm of automated final product inspection. We are excited to bring this cutting-edge technology to our customers, offering them a universal solution that is user-friendly, accurate, flexible, and repeatable across diverse industries," said Andreas Gerspach, General Manager at GPS Technologies GmbH.

The UPI addresses a longstanding challenge in the industry by automating the final inspection process, which has traditionally relied on human operators. This versatile system finds application in various industrial sectors where consistent and high-quality final product assessment is crucial. The UPI can inspect a wide range of items, examining both sides of an assembly in less than 4 seconds. Additionally, it is designed to identify missed/damaged connector pins, barcode and label placement, scratches, lead connections, and several other tasks that are currently manually inspected.

GPS Technologies remains committed to providing future-oriented process solutions for electronics manufacturing, focusing on scalability, flexibility, and ease of integration. The addition of the Prey UPI to its product lineup further strengthens the company's dedication to helping businesses increase productivity, reduce costs, lower energy consumption, and enhance overall safety.

Prey By Detech is a British designed and manufactured product line. Based in Yorkshire, England, the company has been involved in producing inspection technologies for many years, which has led to the development of the Universal Product Inspector (UPI). The company has its own software, design, and manufacturing, resulting in fast reactions to customer requirements. The Prey UPI will soon be available as an inline for customers needing this high-volume capability. The platform also allows itself for customization to fulfil customer requirements.

To find out more about GPS Technologies, visit the company at https://gps-tec.eu. For further information about Prey UPI, visit www.bentec-int.com/prey-upi/ or contact the company at Detech Europe Limited, The Farm Office, Model Farm, Atwick Road, Bewholme, East Riding of Yorkshire, YO25 8DT, United Kingdom; +44 (0)1262 409944; E-mail: sales@detech-europe.com.

BLAUBEUREN, GERMANY – Rehm Thermal Systems is showcasing innovative solutions in vapor phase soldering, coating, and dispensing systems at the IPC APEX EXPO in Anaheim, USA. The IPC APEX EXPO 2024 is the largest electronics manufacturing event in North America, featuring a cutting- edge technological conference, professional training courses by industry experts, and inspiring networking opportunities.

Rehm Thermal Systems is presenting the ProtectoXP dispensing system and the CondensoXC vapor phase soldering system at booth 1848 in the Anaheim Convention Center from April 9 to 11, 2024.The Rehm experts on-site are available to answer questions about dispensing various materials for assembly processes, as well as for potting and securing components. At booth 1848, you can witness live demonstrations of the ProtectoXP dispensing system, showcasing its diverse applications and the new integrated 3D height sensor and learn everything about the injection principle in vapor phase soldering with the CondensoXC.

Innovative production line concepts with the ProtectoX series

Smart factory concepts and line integration are key focus areas in the industry. The demands on the new generation of manufacturing systems have grown steadily. Today, it's not just about individual machines but about line solutions, with "turnkey" being the keyword. Whether it's a new or existing process, deep expertise is required to consider all eventualities. If the entire coating process is new to manufacturing, the complexity increases. The integration of a completely new line requires a thorough technological understanding to coordinate and implement the necessary tests and evaluations.

For Rehm Thermal Systems, the conception of a turnkey solution focuses not only on the equipment but especially on the complete dispensing process. This involves determining whether additional sealing, bonding, and dispensing applications should be included in addition to the painting process. Explore the diverse possibilities of our Conformal Coating and Dispensing portfolio with our experts on-site. The systems feature numerous features that simplify the painting process and ensure its success.

A height sensor with Z-position ensures optimal compensation during the dispensing of assemblies that are not planar due to their nature. Since the height must remain constant, automatic height adjustment is essential for a secure process. Another advantage is the 2D programming on 3D objects. Programming is done in 2D, the height sensor scans the adhesive path of the component being dispensed on, and automatically generates the height contour. This automatically creates the appropriate program for this component.

With the ViCON Protecto system software, only a few steps separate the assembly layout from the final coating. Meet our experts on-site and also discover the new integrated 3D height sensor of this coating and dispensing system.

Resource-efficient vapor phase soldering with the Condenso series

In the world of vapor phase soldering systems, vacuum soldering has been a proven technique for decades to significantly reduce air inclusions in solder joints. Rehm has employed a future-proof, sustainable solution from the beginning with the integrated Closed-Loop System for the injected medium Galden® in the vapor phase soldering systems of the Condenso series.

The principle is both efficient and resource efficient. After soldering, the vacuum and/or cooling process begins. Simultaneously, the process gas is suctioned and cleaned. The suction creates a vacuum, ensuring rapid drying of the solder and the process chamber, minimizing losses when ejecting the products.

The suctioned Galden® is filtered and cleaned of impurities using granules. Approximately 99.9% of the medium can be recovered. The cleaned liquid is stored at room temperature in a container and made available for further processes. This eliminates evaporative losses and energy losses. The hermetic isolation of the process chamber (simultaneously vacuum chamber) also eliminates "evaporation loss" during soldering. In addition to minimal maintenance, operating costs are reduced due to lower Galden® consumption.

Innovative M2M communication for board-flow management in SMT assembly lines

The Hermes Standard provides a manufacturer-independent, overarching protocol for Machine-to-Machine (M2M) communication in assembly manufacturing. The goal is to improve or simplify board-flow management, traceability, and electrical wiring across all stations of an SMT line. Modern communication technology and standardized data formats for M2M communication (TCP/IP and XML-based protocol) are extensively utilized.

As a next-generation technology, the Hermes Standard is officially recognized and derived from the IPC-SMEMA-9851 standard. In the long term, "The Hermes Standard" is designed to replace the existing SMEMA interface. With IPC recognition, The Hermes Standard Initiative has achieved a significant milestone in the digitization of electronics manufacturing.