Samsung Electronics is making strides in developing memory chips essential for the AI market, narrowing the gap with rival SK Hynix. The company has recently received approval from Nvidia for its HBM3 memory chips and anticipates approval for its next generation, HBM3E, within months. The advancement follows months of setbacks, including development challenges and replacing the head of its semiconductor division.
Samsung’s efforts come as the demand for high-bandwidth memory (HBM) is expected to soar, driven by AI advancements. The HBM market is projected to grow from $4 billion in 2022 to $71 billion by 2027. Nvidia’s approval is crucial for Samsung to capitalise on this booming market and improve its revenue and market share despite still trailing SK Hynix.
Why does this matter?
The company has faced significant engineering challenges, particularly with the thermal management of the stacked DRAM chips used in HBM. Under the leadership of Jun Young-hyun, Samsung has focused on resolving these issues and enhancing its technology. The company has also reorganised its HBM team to boost innovation and collaboration.
As Samsung progresses, it aims to ramp up production and meet the growing demand for AI memory chips. With its financial resources and production capacity, the company is well-positioned to address market shortages and secure a significant share of the lucrative AI memory market.
The United Arab Emirates recently cancelled meetings between US Congressional staffers and the Emirati AI firm G42 following US lawmakers’ concerns about the potential transfer of US AI technology to China. The intervention was personally handled by the UAE Ambassador to the US, who stopped the meetings involving the House Select Committee on China.
The cancelled meetings suggest diplomatic tension as US lawmakers, particularly those wary of China, examine the implications of the AI technology transfer to the Middle East. The US State Department has not commented, while a G42 spokesperson directed questions to the Emirati government. The UAE embassy’s spokesperson cited a miscommunication around the visit since the embassy officials were only made aware of the staff delegation shortly before it was about to arrive.
The staffers’ visit was intended to discuss the transfer of advanced chips from companies like Nvidia to the UAE and Saudi Arabia and the broader US-China tech competition. Amidst these concerns, the Biden administration has defended the G42-Microsoft deal, noting that it led to G42 cutting ties with China’s Huawei.
Meta Platforms announced the launch of AI Studio, a tool enabling users to create and design personalised AI chatbots. The new feature allows Instagram creators to develop AI characters to manage direct messages and story replies, enhancing user interaction on the platform. These AI characters can be shared across Meta’s various platforms and are built using Meta’s Llama 3.1 model. This latest version of Meta’s AI model is available in multiple languages and competes with other advanced models like OpenAI’s.
Why does this matter?
Meta’s initiative follows OpenAI’s confidential project, code-named ‘Strawberry,’ aiming to showcase advanced reasoning capabilities. Introducing AI Studio marks Meta’s effort to offer cutting-edge AI tools to its vast user base, leveraging its Llama 3.1 model to provide powerful AI-driven features for content creators and users alike.
According to a recent research paper, Apple has opted to use Google-designed chips instead of Nvidia’s for two crucial components of its AI software infrastructure. This choice is noteworthy as Nvidia is widely regarded as the leading provider of AI processors. The paper detailed that Apple employed Google’s tensor processing units (TPUs) in large clusters, specifically 2,048 TPUv5p chips for AI models on devices like iPhones and 8,192 TPUv4 processors for server models.
The research paper did not mention any use of Nvidia chips, despite Nvidia dominating about 80% of the AI processor market through its graphics processing units (GPUs). Unlike Nvidia, which sells its GPUs directly, Google offers TPUs through its Google Cloud Platform, requiring customers to use Google’s platform for access.
Why does this matter?
Apple has begun introducing parts of its new AI suite, Apple Intelligence, to beta users. This recent publication only disclosed the full extent of Apple’s reliance on Google hardware, despite earlier reports hinting at this partnership.
Apple’s engineers noted the potential for even larger, more sophisticated AI models using Google’s chips. However, Apple’s stock saw a minor decline of 0.1% to $218.24 following the research paper’s release.
Amazon.com is pushing forward with the development of its own AI chips, aiming to reduce its dependence on Nvidia and lower costs for its customers. Engineers in Amazon’s Austin, Texas, chip lab are currently testing a new server design packed with these proprietary AI chips. Rami Sinno, director of engineering for Amazon’s Annapurna Labs, highlighted the increasing demand for more affordable alternatives to Nvidia’s products.
Amazon acquired Annapurna Labs in 2015 and has since focused on creating processors that can handle complex calculations and large data sets more economically. As competitors like Microsoft and Alphabet also develop their own AI processors, Amazon’s initiative is a strategic move to maintain its edge in the AI cloud business, which is the main growth driver for Amazon Web Services (AWS).
Amazon’s new AI tools are also part of its broader strategy to tackle misinformation and enhance service offerings. This development comes as Nvidia adapts to tightening US export controls by creating China-specific AI chips.
The National Institute of Standards and Technology (NIST) has re-released Dioptra, a tool designed to measure AI model risks, particularly from data poisoning attacks. The modular, open-source web-based tool, originally launched in 2022, aims to help companies and individuals assess and analyse AI risks. It can be used for benchmarking, researching models, and exposing them to simulated threats, offering a common platform for these activities.
NIST has positioned Dioptra to support government agencies and businesses in evaluating AI system performance claims. The tool’s release coincides with new documents from NIST and the AI Safety Institute that outline ways to mitigate AI-related dangers, including the generation of non-consensual pornography. This effort is part of a broader US-UK partnership to advance AI model testing, which was announced at the UK’s AI Safety Summit last year.
The development of Dioptra aligns with President Joe Biden’s executive order on AI, which mandates comprehensive AI system testing and the establishment of safety and security standards. Companies developing AI models, such as Apple, are required to notify the federal government and share safety test results before public deployment.
Despite its capabilities, Dioptra has limitations. It only works with models that can be downloaded and used locally, such as Meta’s expanding Llama family. Models that are accessible only via an API, like OpenAI’s GPT-4, are currently not compatible. Nonetheless, NIST proposes that Dioptra can highlight which types of attacks might degrade an AI system’s performance and quantify their impact.
Shanghai has announced a massive $13.8 billion investment to bolster its integrated circuit, biomedicine, and AI industries. The biggest city in China is making a significant push to solidify its position as a global tech leader.
The AI sector will benefit significantly, with investments directed towards intelligent chips, software, autonomous driving, and intelligent robots. The following initiative is part of Shanghai’s broader strategy to foster innovation and build a competitive edge in the global market.
Funds will support original innovation, enhancing Shanghai’s technological capabilities. This move is expected to accelerate the development of globally competitive enterprises within the city, driving growth and attracting talent.
By focusing on these key sectors, Shanghai aims to solidify its reputation as a leading commercial hub. The strategic investment underscores the city’s commitment to advancing technological innovation and economic development.
Microsoft investors are keenly awaiting Tuesday’s earnings report, focusing on whether the Azure cloud-computing business has shown sufficient growth to justify the massive investment in AI infrastructure. With Microsoft being a leader in monetising AI through its collaboration with ChatGPT creator OpenAI, Azure’s growth is expected to remain steady at around 31% from April to June, aligning with forecasts. However, investors are looking for a more significant boost from AI contributions in the fiscal fourth quarter, following its 7% contribution to Azure’s growth in the prior quarter.
Microsoft’s capital spending is projected to have surged by 53% year-over-year to $13.64 billion, up from $10.95 billion in the previous quarter. Concerns over high spending on data centres with short-term gains have affected the US stock market, particularly after Alphabet’s recent report of capital expenditures exceeding estimates and only modest revenue boosts from AI integrations, causing a selloff in major tech stocks. Analysts emphasise the importance of Microsoft’s ability to accelerate AI-related revenue growth to meet investor expectations and justify continued high capital expenditures.
The increased spending has enabled Microsoft to attract more enterprise clients by expanding its AI cloud services and introducing features like the 365 Copilot assistant for Word and Excel. Despite half of the Fortune 500 companies using the $30-per-month Copilot service, Microsoft still needs to disclose its revenue contribution. Analysts expect the impact of Copilot to be more evident in the latter half of 2024. The company’s strategic focus on enterprise AI applications positions it well to capitalise on its extensive client base.
Microsoft shares have risen about 13% this year, adding over $350 billion to its market value, though the stock has recently dipped by nearly 9% amid a tech selloff. The company is expected to report a 14.6% increase in overall revenue for the April-June period, a slowdown from the 17% growth in the previous quarter, primarily due to slower growth in its personal computing segment, which includes Windows and Xbox. The productivity segment, which houses Office apps, LinkedIn, and 365 Copilot, is anticipated to grow by about 10%.
Apple’s upcoming AI features will be released later than initially expected, missing the launch of the new iPhone and iPad software updates. The AI features, called Apple Intelligence, are set to roll out by October, a few weeks after the scheduled release of iOS 18 and iPadOS 18 in September. These new features will first be available to developers for testing with the beta versions of iOS 18.1 and iPadOS 18.1.
In June, Apple highlighted its commitment to AI with new device enhancements, aiming to boost declining sales. Apple Intelligence is designed to generate text, images, and other content on demand. It will be compatible with the iPhone 15 Pro, iPhone 15 Pro Max, and devices with the M1 chip and later. The MacOS Sequoia update will allow iPhone screens to be mirrored on Mac computers for interaction.
Why does it matter?
The delay follows Apple’s decision in June to postpone the launch of three AI features due to the EU regulations. The rules mandate that Apple ensures compatibility with rival products and services.
The tech giant continues to push its AI initiatives despite the challenges posed by international regulations as it seeks to remain competitive in the evolving AI field.
The International Olympic Committee (IOC) has unveiled the Olympic AI Agenda, the third in a series of strategic documents under President Thomas Bach, focusing on the transformative impact of AI on sports. The agenda follows the Olympic Agenda 2020, launched in December 2014, and the Olympic Agenda 2020+5, introduced in March 2021, reflecting the accelerating digital revolution and the increasing potential of AI to reshape various aspects of life, including sports.
AI presents a groundbreaking opportunity to enhance global accessibility to sports, aligning with the IOC’s mission of promoting solidarity and inclusivity. The Olympic AI Agenda aims to establish a governance and oversight framework to identify and mitigate risks while leveraging insights from a diverse panel of experts, including AI pioneers, academics, athletes, and technology company representatives. This panel, convened by the IOC in 2023, has conducted a comprehensive review of AI’s applications in sports, focusing on high-impact areas where the IOC can lead and inspire AI integration.
Recognising that the future of AI in sports is a collaborative effort, the IOC invites stakeholders across the Olympic Movement, such as athletes, International Federations, National Olympic Committees, and the International Paralympic Committee, to join this transformative journey. By working together, they aim to unlock AI’s full potential to promote solidarity, enhance digitalisation, improve sustainability and resilience, and reinforce the role of sports in society, ultimately building a better world through sports.
