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.
Elon Musk announced plans to discuss a $5 billion investment in his AI startup, xAI, with Tesla’s board. This potential move, preceded by a poll launched on social medial platform X, has sparked concerns about a conflict of interest, as Musk launched xAI to compete with Microsoft-backed OpenAI. A recent social media poll showed strong public support for the investment, with over two-thirds of respondents in favor.
Tesla recently reported lower-than-expected second-quarter results, with declining automotive gross margins and profits. Musk highlighted the potential benefits of integrating xAI’s technologies with Tesla, including advancements in full self-driving and new data centre development. However, critics argue that the investment might not be in the best interest of Tesla shareholders.
xAI, launched by Musk last year, has already raised $6 billion in funding, attracting major investors such as Andreessen Horowitz and Sequoia Capital. Despite Musk’s ambitious plans for xAI, his past ventures have faced scrutiny over conflicts of interest, including the controversial acquisition of SolarCity by Tesla in 2016.
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.
Alphabet’s Google has revealed two innovative AI systems, AlphaProof and AlphaGeometry 2, which demonstrate significant advancements in solving complex mathematical problems. These systems tackled abstract math more effectively than previous AI models, showcasing enhanced reasoning capabilities.
DeepMind, Google’s AI unit, reported that these models managed to solve four out of six questions at the 2024 International Math Olympiad. AlphaProof, which integrates the Gemini language model with the AlphaZero system, solved three problems, including the most challenging one, while AlphaGeometry 2 solved another.
These achievements mark the best performance by an AI system in the competition to date, with some problems solved in minutes and others taking up to three days. Meanwhile, Microsoft-backed OpenAI is developing a similar project known as ‘Strawberry,’ raising concerns among its staff about its potential impact on humanity.
As per the Financial Times report, JPMorgan Chase has started deploying an in-house generative AI tool, claiming that its proprietary version of OpenAI’s ChatGPT can perform the task of a research analyst. As per an internal memo accessed by Financial Times, the company has granted its asset and wealth management employees access to the language model platform, LLM Suite. The rollout represents one of Wall Street’s major LLM applications.
The memo described the LLM suite as a ‘ChatGPT-like product’ intended for general productivity, complementing its other applications handling private financial information called Connect Coach and SpectrumGPT. Earlier this year, JPMorgan began rolling out the LLM Suite to select bank areas, and currently, approximately 15% of the workforce has access to the tool.
JPMorgan CEO Jamie Dimon told shareholders that the use of AI has the potential to augment virtually every job and impact our workforce composition. It may reduce certain job categories or roles, but it may create others as well. It is worth noting that so far, the company has not disclosed the number of research analysts it employs.
SK Hynix, the world’s second-largest memory chip maker and a key Nvidia supplier, will invest 9.4 trillion won ($6.8 billion) for its inaugural chip plant in South Korea. Kim Young-sik, the company’s head of manufacturing technology, explained that this is a strategic investment for the company in response to the surge in demand for AI semiconductors. The ambitious project will involve building four state-of-the-art semiconductor plants near Seoul. The construction is expected to start in March next year, and its completion is slated for May 2027.
The site will span 4.2 million square meters and will house four cutting-edge chip plants and over 50 local firms in the semiconductor sector. The facility will also boast a ‘mini-fab’ research centre for processing 300-mm silicon wafers, offering local chip materials and equipment manufacturers a realistic environment to test their innovations.
Why does it matter?
It is worth noting that this new fab will be set in the Yongin Semiconductor Cluster near Seoul, where the government aims to build a large-scale chip operations complex. As such, SK Hynix’s investment will help supplement the South Korean government’s efforts to sustain its leadership in-memory technology, which is crucial for AI applications.
