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As more than 400 speakers took the stages at SEMICON West 2024, sustainability and workforce development stood out as two major focus areas. The second day of this year’s CEO Summit keynote program, themed Seizing the Global Opportunities and Challenges Ahead, featured sessions on both topics. One of the first sessions of the day was the Chief Sustainability Officer (CSO) panel discussion, titled Bracing for the Evolving Global Risk for the Semiconductor Ecosystem, moderated by Vice President of SEMI Global Sustainability Programs, Dr. Mousumi Bhat. Later that morning, Shari Liss, Vice President of SEMI Global Workforce Development Programs and Executive Director of the SEMI Foundation, moderated a fireside chat, Advocating for Real Change: Why Inclusion and Belonging Need to be Everyone’s Concern, with Sandra Mahadwar from KLA Corporation. Bhat and Liss were later interviewed for a podcast by Francoise von Trapp of 3D InCites to share additional insights on sustainability and workforce development, respectively. Bhat was also joined by Paul Kelly, COO of the New York Center for Research, Economic Advancement, Technology, Engineering, and Science (NY CREATES). Creating a More Sustainable Semiconductor Industry During their interview, both Bhat and Kelly emphasized that the industry will need to reduce its use of per and polyfluoroalkyl substances (PFAS) to sustainably innovate at today’s nanometer pace. For this reason, Kelly highlighted the importance of learning to balance current production demands with the health of climate.To achieve this balance, they discussed the efforts of the Semiconductor Climate Consortium (SCC). Much of the SCC’s efforts, they said, will focus on driving the industry toward net zero emissions. SEMI and NY CREATES announced a memorandum of understanding (MOU) at SEMICON West 2024 to promote sustainable practices within the industry, with a focus on PFAS reduction. Kelly pointed to the ability of SCC members to test new materials, gases, and chemicals at NY CREATES’ R D facilities in upstate New York to work toward replacing PFAS with more sustainable alternatives. Bhat also shared that this collaboration helps facilitate prototyping, experimentation, and tests and measurements for newer, more sustainable substances.Dr. Mousumi Bhat of SEMI and Dave Anderson of NY CREATES celebrate their organizations’ sustainability MOU at SEMICON West 2024.“The thought leadership comes from the Consortium, and the support on infrastructure comes from NY CREATES,” said Bhat. “This should become a blueprint to solve some of the challenging problems that we have in our industry.” When it comes to reducing emissions, Bhat mentioned two key objectives. The first, she said, is access to clean energy, and the second is the reduction of greenhouse gases. Bhat cited these as the issues that will take the longest for the industry to solve and pointed to the importance of industry collaboration and partnerships to support the needed experimentation. But while partnerships will bring the industry closer to net zero, both Bhat and Kelly cautioned that it won’t be reached overnight. “Much more needs to be done in the industry to reach that net zero goal,” said Kelly. “New chip technologies, new chemicals, and new processes are very much large leaps to achieving that. But right now, even some of the most advanced will only reduce [emissions] by 70%.” To help bridge this gap, Bhat encouraged others to join and participate in the SCC. “Rather than everybody doing a one-to-one experimentation in their own space and spending those resources, I would like to invite anyone that's not part of the climate consortium,” she said. “And [I invite] those that are part of the climate consortium to engage more actively, so that we are all accelerating the journey toward net zero.” Addressing the Talent Shortage This year’s SEMICON West also featured five keynote sessions dedicated to workforce development, as well as a Workforce Development Pavilion that included several talks around diversity, equity, inclusion, and belonging (DEIB). With the estimated one million jobs the industry will need to fill by 2030, Liss shared that every role is needed – from entry level all the way to Ph.D. researchers. “We need to try and bring in as many people as we can over the next few years,” said Liss. “The talent shortage is a global issue, not just a U.S. one.” Shari Liss of SEMI moderated the fireside chat at SEMICON West 2024 with Sandra Mahadwar from KLA Corporation.To begin to close the talent gap, Liss stressed the importance of educating children about the semiconductor industry. “We are just invisible to kids,” she said. “In every part of the globe, they carry chips in their hands all day every day, and they don’t know. So to me, breaking that barrier and making sure kids know about our work as an industry is going to be so critical to making this successful.” Liss also highlighted differences in workforce development programs across the world, noting that what works in one region may not translate to another. For example, apprenticeships are widely embraced in Europe, she said, but they’re a fairly new practice in the U.S. Conversely, she shared that veteran-focused programs wouldn’t work for some regions, but they’re a “powerful win” in the U.S. Each SEMICON show across the world, she shared, includes similar workforce development and DEIB programming, in addition to targeted sessions for students and HR professionals. Companies can interview for open positions at SEMICON shows as well. To learn more about SEMI’s workforce development initiatives and programming, visit semi foundation.org, or check out this overview of DEIB content at SEMICON West 2024. Samer Bahou is director of Marketing Communications at SEMI.
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In the long unfolding arc of technology innovation, artificial intelligence (AI) looms immense. In its quest to mimic human behavior, the technology touches energy, agriculture, manufacturing, logistics, healthcare, construction, transportation and nearly every other imaginable industry – a defining role that promises to fast track the fourth Industrial Revolution. And if the industry oracles have it right, AI growth will be nothing shy of explosive.“The gains these days are not incremental,” said Ajit Manocha, SEMI president and CEO, said to a gathering in July of the Chinese American Semiconductor Professional Association (CASPA) for its Summer Symposium at SEMI’s headquarters in Milpitas. “They are hockey stick – exponential – with AI semiconductors growing in market size from $4 billion this year to $70 billion in 2025.”Manocha left little doubt that AI is remaking the semiconductor industry and, in the process, the world at large. Internet of Things (IoT) and 4G/5G, both key AI enablers, will account for more than 75 percent of device connections by 2025.“Today, 30 billion devices worldwide are connected,” Manocha said, citing an Applied Materials prediction that the number of connected devices globally will grow to between 500 billion and 1 trillion by 2030. Those devices will generate stunning amounts of data collected, interpreted and used to reason, solve problems, learn and plan, leading to the holy grail of autonomous machine behavior.To process this colossal amount of data central to the promise of AI, the industry must break through the limits of a key technology: memory. Memory a Critical AI BottleneckThe challenge for memory starts with performance. Historically, every decade gains in compute performance have outpaced improvements in memory speed by 100 times, and over the past 20 years that gap has grown, said Steven Woo, a fellow and distinguished inventor at Rambus, presenting at the symposium. The upshot is that memory has bottlenecked compute and, in turn, AI performance. The industry has responded with new ways to implement memory systems on AI chips. Each is suited to unique performance requirements and, of course, comes with trade-offs. Among the frontrunners: On-chip memory delivers the highest bandwidth and power efficiency but is limited in capacity. HBM (High Bandwidth Memory) offers both very high memory bandwidth and density. GDDR balances trade-offs among bandwidth, power efficiency, cost and reliability. Since 2012, AI training capability has grown 300,000 times, besting Moore’s law by 25,000 times in doubling every 3.5 months, a blistering pace compared to the 18-month doubling cycle of Moore’s law, Woo said. The staggering improvements have been driven by parallel computing capacity and new application-specific silicon like Google’s Tensor Processing Unit (TPU).These specialized silicon architectures and parallel engines are key to sustaining future gains in compute performance and combatting the slowing of Moore’s Law and the end of power scaling, Woo said. By rethinking the way processors are architected for certain markets, chipmakers can develop dedicated hardware capable of operating with 100 to 1,000 times greater energy efficiency than general purpose processors to overcome another big limiter to scaling compute performance – power.For its part, the memory industry can improve performance by signaling at higher data rates and using stacked architectures like HBM for greater power efficiency and performance, and by bringing compute closer to the data.Memory scaling for AIA key challenge is scaling memory for AI. Demand for better voice, gesture and facial recognition experiences and more immersive virtual reality and augmented reality interactions is tremendous, said Bill En, senior director at AMD, speaking at the symposium. These capabilities require more processing power across both high-performance computing (HPC) for big data analytics and machine learning as it relies on AI and machine intelligence to generate meaningful insights. Emerging machine learning applications include classification and security, medicine, advanced driver assistance, human-aided design, real-time analytics and industrial automation. And with 75 billion IoT-connected devices – all generating data – expected by 2025, there will be no shortage of data to analyze, En said. The wings alone of a new Airbus A380-1000 feature some 10,000 sensors.Mountains of this data are stored in massive data centers on magnetic hard drives, then transferred to DRAM before moving to SRAM within the CPU for the handoff to the compute hardware for analysis.With data growing at an exponential clip, the question is how to make sure all other memory systems can handle the flood of data. AMD’s answer is a chiplet architecture featuring eight smaller chips around the edge that drive the compute and a large chip in the center that doubles the IO interface and memory capability to in turn double chip bandwidth.AMD has also moved from a legacy GDDR5 memory chip configuration to HBM to bring memory bandwidth closer to the GPU for more efficient processing of AI applications. The HBM provides much higher bandwidth while reducing power consumption. Compared to DRAM, AMD’s HBM delivers a much faster data rate and far greater memory density, En said.Over the next decade, look for more performance improvements from multi-chip architectures, innovations in memory technology and integration, aggressive 3D stacking and streamlined system-level interconnects, he said. The industry will also continue to drive performance gains in devices, compute density and power through technology scaling.Michael Hall is a global marketing communications manager at SEMI.
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Five young dancers bathed in a striking rainbow of colors with their silhouettes cast in the background dazzled SEMICON Japan 2018 attendees at the opening ceremony in mid-December. Gone were the standard opening keynotes and ribbon cutting, replaced by live performance and media art set against a dramatic black backdrop. There was no mistaking the wide-eyed looks of wonder in the audience.In its sheer vibrance, the opening ceremony thrilled with an excitement that seemed to embody the extraordinary growth expectations for the global semiconductor supply chain over the next five years, with the industry poised to double sales from $2 trillion to a staggering $4 trillion – a phenomena SEMI president and CEO Ajit Manocha has called The Rebirth of the Semiconductor Industry. Driving this unprecedented growth will be SMART applications that are transforming industries and applications worldwide, powered by artificial intelligence (AI) and Internet of Things (IoT) technologies.The dramatic scene at SEMICON Japan 2018 was staged by Rhizomatiks, a media arts company that produced the Rio Olympic Games closing ceremony and is famous for its pop music spectacles. The company’s CTO, Motoi Ishibashi, the event’s first keynote speaker, described his team’s development of drones and vehicles guided by motion and precision-control technologies. It was some of these SMART vehicles that maneuvered the opening ceremony performers from the dance company Elevenplay onstage. Only Rhizomatiks, Ishibashi said, has this capability. In its mission to enrich people’s lives through new media arts, Rhizomatiks uses the latest virtual and mixed-reality technologies to orchestrate not only dance performances but music videos, commercials, fashion shows and festivals.Toru Nishikawa, the second keynote speaker and CEO at Preferred Networks, a leading Japan-based developer of deep learning software programs, surprised the SEMICON Japan audience with his discussion of his company’s work to develop a specialized chip for deep learning processing, joining technology giants Apple, Google, Alibaba and Microsoft in chip design. As more IT and software companies develop specialized, differentiated chips, the devices are quickly becoming the heartbeat of SMART technologies. The company’s approach has taken hold. Only four years old, Preferred Networks is enjoying rapid growth by working with global powerhouses including Toyota, NTT, Panasonic, Fanuc, NVIDIA, Intel and Microsoft. Ishibashi’s and Nishikawa’s fresh visions and the media arts extravaganza reflected the success of SEMICON Japan, held again at Tokyo Big Sight: The event’s 1,881 booths – filled by 727 exhibitors from 14 regions – was the highest count in six years. With Japan home to companies that supply about 40 percent of semiconductor equipment and materials worldwide, top suppliers historically have occupied the largest spaces on the SEMICON Japan show floor.According to IDC, personal computers and smartphones, long the largest revenue sources for the semiconductor industry, will remain top revenue drivers in the coming years. But revenue from new SMART technologies for applications such as automotive and factory automation is growing, a trend expected to continue with a 2018-2022 CAGR of 9.5 percent for automotive and 5.2 percent for manufacturing, compared to 1.1 percent for PCs and 2.9 percent for smartphones.SEMICON Japan’s new SMART Applications zone highlighted these and other new market opportunities for semiconductor growth with product and technology exhibits from companies including Bosch, IBM, Microsoft, NEC, Preferred Networks, Sony, SAS, Siemens, Tesla and Toyota. But the zone wasn’t all work and no play. The ROBOT SQUARE and SPORTS x IOT robot exhibits took visitors back to their school days, with robot anime – from Astro Boy to Gundam and Evangelion – that they could ride and control! As the World Gets Smarter, So Must SEMICON and the IndustryWe all agree the world is getting smarter at a fast pace. New cars are easier to drive – some models are almost fully autonomous on highways and streets. Your SMART speaker has gone well beyond an audio playback device and is more like a home AI platform. Almost all storefronts are equipped with video cameras. Your workplace, whether an office or a factory, is driven by automation. The reliance of these environments and devices on semiconductors is driving exponential chip and changing the world. Businesses need to adapt and so do SEMICON events. We’re doing just that as SEMICON Japan 2018 demonstrated – from an opening ceremony enabled by technology innovation to new faces of the industry to the SMART Application zone. As the SEMICON Japan presidents’ reception concluded the first day of the show, a robot from the ROBOT SQUARE suddenly appeared in the reception hall in front of about 250 executives from the global industry. Everyone at the reception was impressed and stepped forward to the stage, reflecting the overall excitement about SEMICON Japan, which for many years showcased only chip manufacturing equipment and materials. This year, to keep pace with the changing world, it was much more than that.SEMICON Japan 2019 will again take place in December at Tokyo Big Sight. However, organizers of the Tokyo Olympics will be using the East Exhibit Hall usually occupied by SEMICON Japan to prepare for the games. As a result, SEMICON Japan will be held in the West and South Halls instead. Look for more changes to the event. I hope to see you next year!Jim Hamajima is president of SEMI Japan.
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Artificial intelligence (AI) is on the verge of transforming entire industries as it gears up to power semiconductor industry innovation and growth, thrusting the technology to front and center at SEMICON Japan 2019, December 12-14 at the Tokyo Big Sight (Tokyo International Exhibition Center).The SMART Technology Forum at SEMICON Japan will highlight the latest AI developments and trends. Supported by U.S. Commercial Service in Japan, the forum will feature Yutaka Matsuo of the University of Tokyo. An authority on AI, Matuso will give an overview of both AI business and technology. His presentation will be followed by an AI outlook from Microsoft Japan, Amazon Web Services and DefinedCrowd.A number of Japanese startups are on leading edge of AI innovation in machine and deep learning. One is Preferred Networks Inc., a company that applies cutting-edge deep learning technology to Internet of Things (IoT) applications across transportation, manufacturing and healthcare.In his opening day keynote at SEMICON Japan, Toru Nishikawa, president and CEO of Preferred Networks, Inc., will highlight the latest developments and promise of using deep learning for industrial applications. Nishikawa will unpack how AI companies jockeying for competitive advantage will win by harnessing technologies to process massive amounts of data efficiently and quickly.Following is look at Preferred Networks, Inc. and five other Japanese startups that are driving AI innovation. Within Japan's world of AI, machine learning, and deep dearning, Preferred Networks is likely the most well-known Japanese company. The parent company, Preferred Infrastructure, was founded in March 2006 by Toru Nishikawa and Daisuke Okanohara, who focused on search engine development before turning to machine learning and establishing Preferred Networks to commercialize the technology.Preferred Networks established itself as one of the world’s top providers of machine learning technology with the development of Chainer – an open source deep learning framework that has been offered free of charge since June 2015 and was released before TensorFlow, Google’s renowned Deep Learning framework. Established in 2012, ABEJA is thought to be Japan’s first venture company to specialize in deep learning. ABEJA's core technology is its AI platform ABEJA Platform. Based on this platform, the company offers various solutions to more than 100 client companies. ABEJA also offers ABEJA Insight, a specialized package service for the retail and distribution, manufacturing, and infrastructure industries. Data analytics provider BrainPad Inc. was the first Japanese AI venture listed on the Tokyo Stock Exchange. Established in 2004, before the advent of big data, BrainPad Inc. cultivated a vision of analyzing vast amounts of data in increase the competitiveness of Japanese companies. LeapMind Inc. aims to offer deep learning technology that uses fewer computing resources and draws less power. Both are important capabilities since deep learning requires considerable computing resources to perform image and speech recognition. The company’s answer to this deep learning challenge is a small form factor FPGA with low power consumption.In April 2018, LeapMind started offering the tool DeLTA-Lite to support model construction for Deep Learning. The tool simplifies the development of deep learning design models, eliminating the need for model design, hardware, and software expertise. Hacarus Inc.’s HACARUS-X AI technology, which combines sparse modeling and machine learning technology, features low power consumption and small devices such as FPGAs. In collaboration with semiconductor trading company PALTEK, Hacarus is integrating HACARUS-X algorithms with Xilinx's FPGA Zynq UltraScale + MPSoC. Both companies area also implementing HACARUS-X algorithms in a box computer.Sparse modeling is gaining attention as a modeling method by which humans can understand the judgment process of AI by extracting features from a small amount of learning data. With expertise in life science fields such as medical and biology and image processing technology, LPixel, Inc. develops image analysis systems with original algorithms and machine learning techniques. It has developed a cloud-based AI image analysis platform and an AI medical image diagnosis support technology that streamlines the review of large amounts of research data and detects image fraud in research papers and other documents for the medical and biology fields, freeing researchers to devote more time to their core work. Yoichiro Ando is a marketing director at SEMI Japan.
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