Inventec, a global leader in high-powered servers headquartered in Taiwan, is launching its cutting-edge C805G6 server for data centers based on AMD's newest 4th Gen EPYC platform—a major innovation in computing power that provides double the operating efficiency of previous platforms. These innovations are timely, as the industry worldwide faces converse challenges—on one hand, a growing need to reduce carbon footprints and power consumption, while, on the other hand, the push for ever higher computing power and performance for AI. In fact, in 2022 MIT found that improving a machine learning model tenfold will require a 10,000-fold increase in computational requirements.

Addressing both pain points, George Lin, VP of Business Unit VI, Inventec Enterprise Business Group (Inventec EBG) notes that, "Our latest C805G6 data center solution represents an innovation both for the present and the future, setting the standard for performance, energy efficiency, and security while delivering top-notch hardware for powering AI workloads."

TrendForce reports that the HBM (High Bandwidth Memory) market's dominant product for 2023 is HBM2e, employed by the NVIDIA A100/A800, AMD MI200, and most CSPs' (Cloud Service Providers) self-developed accelerator chips. As the demand for AI accelerator chips evolves, manufacturers plan to introduce new HBM3e products in 2024, with HBM3 and HBM3e expected to become mainstream in the market next year.

The distinctions between HBM generations primarily lie in their speed. The industry experienced a proliferation of confusing names when transitioning to the HBM3 generation. TrendForce clarifies that the so-called HBM3 in the current market should be subdivided into two categories based on speed. One category includes HBM3 running at speeds between 5.6 to 6.4 Gbps, while the other features the 8 Gbps HBM3e, which also goes by several names including HBM3P, HBM3A, HBM3+, and HBM3 Gen2.

Pixelworks, Inc., a leading provider of innovative visual processing solutions, today announced the official launch of its new IRX gaming experience brand. As a brand targeted at smartphone users, IRX is grounded on Pixelworks' mobile visual processing solutions and coupled with in-depth game tuning services. This combination leverages Pixelworks' expertise to achieve ultra-smooth gaming experience and the highest picture quality for different types of games on mobile devices. In addition, it exercises effective control of power consumption, latency and other performance variables to ensure stable and long-lasting gaming with optimal visual performance, providing end users with unparalleled mobile gaming experiences.

The IRX gaming experience is enabled by a portfolio of technology advantages and product application experiences based on the Company's innovative distributed rendering architecture. More specifically, Pixelworks' ultra-low latency MotionEngine technology, low power super-resolution technology, AI Always-on HDR and other technologies bring optimized rendering capabilities to smartphones that exceed what can be achieved by a traditional chipset. Together with Pixelworks' profound tuning experience for different games on various mobile devices the result is a meaningfully enriched visual experience for smartphone users, which is the core foundation for the IRX gaming experience.

Dell Technologies introduces new offerings to help customers quickly and securely build generative AI (GenAI) models on-premises to accelerate improved outcomes and drive new levels of intelligence. New Dell Generative AI Solutions, expanding upon our May's Project Helix announcement, span IT infrastructure, PCs and professional services to simplify the adoption of full-stack GenAI with large language models (LLM), meeting organizations wherever they are in their GenAI journey. These solutions help organizations, of all sizes and across industries, securely transform and deliver better outcomes.

"Generative AI represents an inflection point that is driving fundamental change in the pace of innovation while improving the customer experience and enabling new ways to work," Jeff Clarke, vice chairman and co-chief operating officer, Dell Technologies, said on a recent investor call. "Customers, big and small, are using their own data and business context to train, fine-tune and inference on Dell infrastructure solutions to incorporate advanced AI into their core business processes effectively and efficiently."

NVIDIA has been raking in lots of cash this year and hit a major milestone back in late May, with a trillion dollar valuation—its stock price doubled thanks to upward trends in the artificial intelligence market, with growing global demand for AI-hardware. Business Insider believes that Team Green will continue to do very well for itself over the next couple of years: "Mizuho analyst Vijay Rakesh has given NVIDIA's stock price another 20% upside to run—and even this new target of $530 is "conservative," according to a Sunday client note seen by Insider. Rakesh's previous price target for NVIDIA was $400. NVIDIA shares closed 0.7% higher at $446.12 apiece on Monday. The stock has surged 205% so far this year."

Despite the emergence of competing hardware from the likes of AMD and Intel, Rakesh predicts that NVIDIA will maintain a dominant position in the AI chip market until at least 2027: "With demand for generative AI accelerating, we see significant opportunities for hardware suppliers powering the higher compute needs for large-language models, particularly AI powerhouse NVIDIA. Insider reports that the company: "could generate around $300 billion in AI-specific revenue by 2027 with a 75% market share of AI server units...That's 10 times his projection of $25 billion to $30 billion in AI revenues this year." Rakesh has reportedly stuck with a $140 buy rating and price target for AMD shares.

Intel Corporation today reported second-quarter 2023 financial results. "Our Q2 results exceeded the high end of our guidance as we continue to execute on our strategic priorities, including building momentum with our foundry business and delivering on our product and process roadmaps," said Pat Gelsinger, Intel CEO. "We are also well-positioned to capitalize on the significant growth across the AI continuum by championing an open ecosystem and silicon solutions that optimize performance, cost and security to democratize AI from cloud to enterprise, edge and client."

David Zinsner, Intel CFO, said, "Strong execution, including progress towards our $3 billion in cost savings in 2023, contributed to the upside in the quarter. We remain focused on operational efficiencies and our Smart Capital strategy to support sustainable growth and financial discipline as we improve our margins and cash generation and drive shareholder value." In the second quarter, the company generated $2.8 billion in cash from operations and paid dividends of $0.5 billion.

IBM has launched a new tool to help enterprises track greenhouse gas (GHG) emissions across cloud services and advance their sustainability performance throughout their hybrid, multicloud journeys. Now generally available, the IBM Cloud Carbon Calculator - an AI-informed dashboard - can help clients access emissions data across a variety of IBM Cloud workloads such as AI, high performance computing (HPC) and financial services.

Across industries, enterprises are embracing modernization by leveraging hybrid cloud and AI to digitally transform with resiliency, performance, security, and compliance at the forefront, all while remaining focused on delivering value and driving more sustainable business practices. According to a recent study by IBM, 42% of CEOs surveyed pinpoint environmental sustainability as their top challenge over the next three years. At the same time, the study reports that CEOs are facing pressure to adopt generative AI while also weighing the data management needs to make AI successful. The increase in data processing required for AI workloads can present new challenges for organizations that are looking to reduce their GHG emissions. With more than 43% of CEOs surveyed already using generative AI to inform strategic decisions, organizations should prepare to balance executing high performance workloads with sustainability.

IBASE Technology Inc. (TPEx: 8050), a leading provider of industrial computing solutions, unveils the SI-624-AI industrial AI computer, which won the Embedded Computing Design's Embedded World 2023 Best in Show Award in Germany. This recognition highlights the exceptional performance and innovation of the rugged system in the field of AI deep learning.

The SI-624-AI is designed to meet the demands of high-speed multiple tasks for artificial neural network applications. Powered by the 12th Gen Intel Core CPU and incorporating the NVIDIA Ampere Architecture MXM GPU, this cutting-edge system delivers image processing capabilities that enable real-time analysis of visual data, enhancing automation, quality control, and overall production efficiency for AIoT applications in smart factory, retail, transportation or medical fields. It is suitable for use as a digital signage control system in mission-critical control rooms in transportation networks, smart retail, healthcare, or AI education where remote AI data analysis capabilities are required.

NVIDIA DGX Cloud - which delivers tools that can turn nearly any company into an AI company - is now broadly available, with thousands of NVIDIA GPUs online on Oracle Cloud Infrastructure, as well as NVIDIA infrastructure located in the U.S. and U.K. Unveiled at NVIDIA's GTC conference in March, DGX Cloud is an AI supercomputing service that gives enterprises immediate access to the infrastructure and software needed to train advanced models for generative AI and other groundbreaking applications.

"Generative AI has made the rapid adoption of AI a business imperative for leading companies in every industry, driving many enterprises to seek more accelerated computing infrastructure," said Pat Moorhead, chief analyst at Moor Insights & Strategy. Generative AI could add more than $4 trillion to the economy annually, turning proprietary business knowledge across a vast swath of the world's industries into next-generation AI applications, according to recent estimates by global management consultancy McKinsey.

Somewhat out of the blue, Silicon Box has announced the opening of its US$2 billion semiconductor assembly plant in Singapore. The "startup" is founded by several of Marvell's founders, suggesting the company has the right pedigree to compete in what is sure to be a very competitive market over the next few years. Silicon Box is not a foundry and will at least at this point in time, not be involved in foundry services, but instead the company will focus on advanced chip packaging technologies, focusing on chiplets.

The company is promising "faster time-to-market, lower new device design cost" on its very rudimentary website, something the company has yet to prove to be capable of. However, its new plant in Singapore covers 73,000 square metres and is said to feature state of the art production equipment for turning chiplets into chips. The factory is said to create some 1,200 jobs in Singapore, suggesting that this is a company that means business. According to a comment by company founder and CEO BJ Han to Reuters, "customers had been lining up" since before the completion of the assembly plant. Silicon Box is expecting to have several AI chipset companies as its customers, including Tenstorrent, which so far is the only officially mentioned client. Time will tell if Silicon Box can compete with established chip packaging businesses and if they can deliver on their promise to be faster and cheaper than the competition.

Cerebras Systems, the pioneer in accelerating generative AI, and G42, the UAE-based technology holding group, today announced Condor Galaxy, a network of nine interconnected supercomputers, offering a new approach to AI compute that promises to significantly reduce AI model training time. The first AI supercomputer on this network, Condor Galaxy 1 (CG-1), has 4 exaFLOPs and 54 million cores. Cerebras and G42 are planning to deploy two more such supercomputers, CG-2 and CG-3, in the U.S. in early 2024. With a planned capacity of 36 exaFLOPs in total, this unprecedented supercomputing network will revolutionize the advancement of AI globally.

"Collaborating with Cerebras to rapidly deliver the world's fastest AI training supercomputer and laying the foundation for interconnecting a constellation of these supercomputers across the world has been enormously exciting. This partnership brings together Cerebras' extraordinary compute capabilities, together with G42's multi-industry AI expertise. G42 and Cerebras' shared vision is that Condor Galaxy will be used to address society's most pressing challenges across healthcare, energy, climate action and more," said Talal Alkaissi, CEO of G42 Cloud, a subsidiary of G42.

Mark Papermaster, AMD's Chief Technology Officer and Executive Vice President of Technology and Engineering announced: "Over the past 50 years, Ethernet has grown to dominate general networking. One of its key strengths is flexibility - the ability to adapt to different workloads, scale and computing environments. One of the places that it hasn't been well-known, though, is in high-performance networking environments.

Now, the Ultra Ethernet Consortium (UEC) was formed by leading technology companies to focus on tuning the Ethernet foundation for high-performance Artificial Intelligence, Machine Learning, and High-Performance Computing (AI/ML/HPC) workloads. This includes work at the Physical, Link, Transport, and Software layers with robust security and congestion protections.

Qualcomm Technologies, Inc. and Meta are working to optimize the execution of Meta's Llama 2 large language models directly on-device - without relying on the sole use of cloud services. The ability to run generative AI models like Llama 2 on devices such as smartphones, PCs, VR/AR headsets, and vehicles allows developers to save on cloud costs, and to provide users with private, more reliable, and personalized experiences.

As a result, Qualcomm Technologies plans to make available on-device Llama 2-based AI implementations to enable the creation of new and exciting AI applications. This will allow customers, partners, and developers to build use cases, such as intelligent virtual assistants, productivity applications, content creation tools, entertainment, and more. These new on-device AI experiences, powered by Snapdragon, can work in areas with no connectivity or even in airplane mode.

Supermicro, Inc., a Total IT Solution Provider for Cloud, AI/ML, Storage, and 5G/Edge, is announcing several new servers to its already broad application optimized product line. These new servers incorporate the new AmpereOne CPU, with up to 192 single-threaded cores and up to 4 TB of memory capacity. Applications such as databases, telco edge, web servers, caching services, media encoding, and video gaming streaming will benefit from increased cores, faster memory access, higher performance per watt, scalable power management, and the new cloud security features. Additionally, Cloud Native microservice based applications will benefit from the lower latencies and power usage.

"Supermicro is expanding our customer choices by introducing these new systems that incorporate the latest high core count CPUs from Ampere Computing," said Michael McNerney, vice president of Marketing and Security, Supermicro. "With high core counts, predictable latencies, and up to 4 TB of memory, users will experience increased performance for a range of workloads and lower energy use. We continue to design and deliver a range of environmentally friendly servers that give customers a competitive advantage for various applications."

Announced today, Ultra Ethernet Consortium (UEC) is bringing together leading companies for industry-wide cooperation to build a complete Ethernet-based communication stack architecture for high-performance networking. Artificial Intelligence (AI) and High-Performance Computing (HPC) workloads are rapidly evolving and require best-in-class functionality, performance, interoperability and total cost of ownership, without sacrificing developer and end-user friendliness. The Ultra Ethernet solution stack will capitalize on Ethernet's ubiquity and flexibility for handling a wide variety of workloads while being scalable and cost-effective.

Ultra Ethernet Consortium is founded by companies with long-standing history and experience in high-performance solutions. Each member is contributing significantly to the broader ecosystem of high-performance in an egalitarian manner. The founding members include AMD, Arista, Broadcom, Cisco, Eviden (an Atos Business), HPE, Intel, Meta and Microsoft, who collectively have decades of networking, AI, cloud and high-performance computing-at-scale deployments.

Today, U.S. Deputy National Security Advisor Anne Neuberger, Chairwoman of the Federal Communications Commission (FCC) Jessica Rosenworcel, and Laurie Locascio, Director of the National Institute of Standards and Technology (NIST) unveiled the U.S. national IoT security label at the White House.

Infineon Technologies AG supports this action to address the growing need for IoT security. The new label supports the IoT security requirements under NISTIR 8425, which resulted from an Executive Order to improve the nation's cybersecurity. This label will recognize products that meet these requirements by permitting them to display a U.S. government label and be listed in a registry indicating that these products meet U.S. cybersecurity standards.

Phison Electronics, a global leader in NAND controllers and storage solutions, announced today the expansion of its IMAGIN+ service to include AI computational models and AI services solutions. Phison's aiDAPTIV+ utilizes Phison's innovative integration of SSDs into the AI computing framework and expands NAND storage solutions in the AI application market. Phison has been a global leader deeply engaged in NAND controller innovations for more than 23 years. In recent years, the company has developed and integrated AI and machine learning technologies into NAND controllers and algorithms in order to enhance the computational performance and reliability of the company's NAND storage solutions.

Additionally, Phison has established a data science team, developed and deployed relevant AI technologies, and created a world-class validation laboratory. These efforts have accelerated the adoption of Phison's storage solutions in various applications, including PCs, mobile phones, automobiles, gaming platforms, enterprise data center & edge applications, supply chain logistics, and more. With the recent rise of large-scale generative AI models such as ChatGPT, the possibilities for artificial intelligence to assist both businesses and individuals in the future are significant. The rapid growth of AI models has also led to a significant increase in the hardware infrastructure cost associated with providing AI services.

DEEPX, a leading AI semiconductor technology company, aims to drive innovation in the rapidly evolving edge AI landscape with its state-of-the-art, low-power, high-performance AI chip product lineup. With a focus on revolutionizing application areas such as smart cities, surveillance, smart factories, and other industries, DEEPX unveiled its latest AI semiconductor solutions at the 2023 Samsung Foundry Forum (SFF), under the theme of "For AI Everywhere."

Recognizing the importance of collaboration and technological partnerships, DEEPX leveraged Samsung Electronics' foundry processes, harnessing the power of 5 nm, 14 nm, and 28 nm technologies for its semiconductor chip designs. As a result, the company has developed a suite of four high-performance, energy-efficient AI semiconductor products: DX-L1, DX-L2, DX-M1, and DX-H1. Each product has been specifically engineered to cater to the unique demands of various market segments, from ultra-compact sensors with minimal data processing requirements to AI-intensive applications such as robotics, computer vision, autonomous vehicles, and many others.

Intel has responded to the high demand for advanced chips in mainland China by bringing its processor, the Gaudi2, to the market. This move comes as the country grapples with US export restrictions, leading to a thriving market for smuggled NVIDIA GPUs. At a press conference in Beijing, Intel presented the Gaudi2 processor as an alternative to NVIDIA's A100 GPU, widely used for training AI systems. Despite US export controls, Intel recognizes the importance of the Chinese market, with 27 percent of its 2022 revenue generated from China. NVIDIA has also tried to comply with restrictions by offering modified versions of its GPUs, but limited supplies have driven the demand for smuggled GPUs. Intel's Gaudi2 aims to provide Chinese companies with various hardware options and bolster their ability to deploy AI through cloud and smart-edge technologies. By partnering with Inspur Group, a major AI server manufacturer, Intel plans to build Gaudi2-powered machines tailored explicitly for the Chinese market.

China's AI ambitions face potential challenges as the US government considers restricting Chinese companies access to American cloud computing services. This move could impede the utilization of advanced AI chips by major players like Amazon Web Services and Microsoft for their Chinese clients. Additionally, there are reports of a potential expansion of the US export ban to include NVIDIA's A800 GPU. As China continues to push forward with its AI development projects, Intel's introduction of the Gaudi2 processor helps country's demand for advanced chips. Balancing export controls and technological requirements within this complex trade landscape remains a crucial task for both companies and governments involved in the Chinese AI industry.

Artificial intelligence (AI) has emerged as a transformative force in chip design, with recent examples from China and the United States showcasing its potential. Jensen Huang, CEO of Nvidia, believes that AI can empower individuals to become programmers, while Lisa Su, CEO of AMD, predicts an era where AI dominates chip design. During the 2023 World Artificial Intelligence Conference (WAIC) in Shanghai, Su emphasized the importance of interdisciplinary collaboration for the next generation of chip designers. To excel in this field, engineers must possess a holistic understanding of hardware, software, and algorithms, enabling them to create superior chip designs that meet system usage, customer deployment, and application requirements.

The integration of AI into chip design processes has gained momentum, fueled by the AI revolution catalyzed by large language models (LLMs). Both Huang and Mark Papermaster, CTO of AMD, acknowledge the benefits of AI in accelerating computation and facilitating chip design. AMD has already started leveraging AI in semiconductor design, testing, and verification, with plans to expand its use of generative AI in chip design applications. Companies are now actively exploring the fusion of AI technology with Electronic Design Automation (EDA) tools to streamline complex tasks and minimize manual intervention in chip design. Despite limited data and accuracy challenges, the "EDA+AI" approach holds great promise. For instance, Synopsys has invested significantly in AI tool research and recently launched Synopsys.ai, the industry's first end-to-end AI-driven EDA solution. This comprehensive solution empowers developers to harness AI at every stage of chip development, from system architecture and design to manufacturing, marking a significant leap forward in AI's integration into chip design workflows.

TrendForce reports that continued production cuts by DRAM suppliers have led to a gradual quarterly decrease in overall DRAM supply. Seasonal demand, on the other hand, is helping to mitigate inventory pressure on suppliers. TrendForce projects that the third quarter will see the ASP for DRAM converging towards a 0~5% decline. Despite suppliers' concerted efforts, inventory levels persistently remain high, keeping prices low. While production cutbacks may help to curtail quarterly price declines, a tangible recovery in prices may not be seen until 2024.

PC DRAM: The benefits of consolidated production cuts on DDR4 by the top three suppliers are expected to become evident in the third quarter. Furthermore, inventory pressure on suppliers has been partially alleviated due to aggressive purchasing by several OEMs at low prices during 2Q23. Evaluating average price trends for PC DRAM products in 3Q23 reveals that DDR4 will continue to remain in a state of persistent oversupply, leading to an expected quarterly price drop of 3~8%. DDR5 prices—influenced by suppliers' efforts to maintain prices and unmet buyer demand—are projected to see a 0-5% quarterly decline. The overall ASP of PC DRAM is projected to experience a QoQ decline of 0~5% in the third quarter.

Google made a small but important change to their privacy policy over the weekend that effectively lays claim to anything you post publicly online for use to train their AI models. The original wording of the section of their privacy policy claimed that public data would be used for business purposes, research, and for improving Google Translate services. Now however the section has been updated to read the following:

Google uses information to improve our services and to develop new products, features and technologies that benefit our users and the public. For example, we use publicly available information to help train Google's AI models and build products and features like Google Translate, Bard, and Cloud AI capabilities.

Further down in the policy text Google has another section which exemplifies the areas of "publicly available" information they seek to scrape,

For example, we may collect information that's publicly available online or from other public sources to help train Google's AI models and build products and features like Google Translate, Bard, and Cloud AI capabilities. Or, if your business's information appears on a website, we may index and display it on Google services.

Last week a small-time developer (who releases titles on Steam) kicked up a lot of fuss about AI-generated content being banned, blocked or removed by Valve. They claim that their game has been rejected repeatedly by Steamworks supervisors due to the presence of "fairly obviously AI-generated" material. The incensed dev took to the r/aigamedev subbreddit to chronicle their experience, and share how their latest and greatest "waifu" mini-game got blocked for a second time (for not owning the necessary rights): "It took them over a week to provide this verdict, while previous games I've released have been approved within a day or two, so it seems like Valve doesn't really have a standard approach to AI generated games yet, and I've seen several games up that even explicitly mention the use of AI. But at the moment at least, they seem wary, and not willing to publish AI generated content, so I guess for any other devs on here, be wary of that. I'll try itch.io and see if they have any issues with AI generated games."

Eurogamer has contacted Valve about this matter, and a company spokesperson responded, albeit with the caveat that Steam's policy on AI-generated content is still a "work in progress." They stated: "Our priority, as always, is to try to ship as many of the titles we receive as we can," but the process is further complicated by not knowing whether the developer has "sufficient rights in using AI to create assets, including images, text, and music." There are many legal grey areas when dealing with this type of content: "it is the developer's responsibility to make sure they have the appropriate rights to ship their game."

The AI hype continues to push hardware shipments, especially for servers with GPUs that are in very high demand. Another example is the latest feat of AI startup, Inflection AI. Building foundational AI models, the Inflection AI crew has secured an order of 22,000 NVIDIA H100 GPUs and built a supercomputer. Assuming a configuration of a single Intel Xeon CPU with eight GPUs, almost 700 four-node racks should go into the supercomputer. Scaling and connecting 22,000 GPUs is easier than it is to acquire them, as NVIDIA's H100 GPUs are selling out everywhere due to the enormous demand for AI applications both on and off premises.

Getting 22,000 H100 GPUs is the biggest challenge here, and Inflection AI managed to get them by having NVIDIA as an investor in the startup. The supercomputer is estimated to cost around one billion USD and consume 31 Mega-Watts of power. The Inflection AI startup is now valued at 1.5 billion USD at the time of writing.

In a bid to prepare its ISV ecosystem for emerging technologies with future processor microarchitectures, Intel periodically releases instruction-set reference guides. The latest of these was leaked to the web, making their first references to the upcoming "Arrow Lake" and "Lunar Lake" client processor microarchitectures. From the looks of it, Intel is planning a massive push into the client AI acceleration space, starting with the upcoming "Meteor Lake" architecture that debuts later this year. The processor is expected to feature hardware acceleration for AI, with the new AI Boost feature.

The company could build on AI Boost with even more capabilities in the subsequent "Arrow Lake" and "Lunar Lake" microarchitectures. Among the instruction sets relevant to AI deep-learning neural net building and training, are AVX VNNI with INT8, AVX VNNI with INT16, AVX-IFMA, and AVX-NE Convert. There are several new security-relevant instructions, including SHA512, SM3, and SM4. "Lunar Lake" will introduce TSE-PBNDKB (total storage encryption). The ISA Reference Guide can be accessed here.