Microsoft Corporation is set to inject $1.5 billion into G42, a leading AI firm based in the UAE, following intricate negotiations with the US government. G42’s agreement to sever ties with China and embrace American technology underpins this landmark investment, positioning it strategically amidst global technological realignments. The deal underscores Washington’s efforts to constrain Chinese access to AI and amplifies the partnership between Microsoft and G42, with Microsoft President Brad Smith slated to join G42’s board.
Behind closed doors, G42 engaged in talks with the US Commerce Department‘s Bureau of Industry and Security, committing to scale back its operations in China or risk punitive measures from Washington. With influential backing from Abu Dhabi’s ruling family, G42 aims to establish itself as a regional AI powerhouse.
This move of US Commerce Department, part of the broader Biden administration’s agenda, reflects a concerted push to counter China’s technological dominance and bolster alliances worldwide.
G42’s agreement with Microsoft secures a substantial investment and paves the way for enhanced collaboration in AI applications, leveraging Microsoft’s Azure cloud infrastructure. Amidst scrutiny over alleged ties to blacklisted Chinese firms, G42 denies any affiliations with Beijing’s government or its military-industrial complex. The deal’s culmination signals a pivotal moment in the tech landscape, driven by strategic realignments and a concerted effort to navigate geopolitical complexities.
OpenAI, supported by Microsoft, has set its sights on Japan, inaugurating its first Asia office in Tokyo. CEO Sam Altman expressed enthusiasm for a long-term collaboration with Japan, envisioning partnerships with government bodies, businesses, and research institutions. With the success of its ChatGPT AI chatbot, OpenAI seeks to expand its revenue streams globally.
Altman and COO Brad Lightcap have been actively engaging Fortune 500 executives in the US and UK, signalling a concerted effort to attract business. Last year’s meeting with Prime Minister Fumio Kishida laid the groundwork for OpenAI’s expansion into Japan, joining its offices in London and Dublin. Japan, aiming to bolster its competitiveness against China, sees AI as pivotal in its digital transformation and addressing labour shortages.
OpenAI is strategically positioned with a tailored model for the Japanese language, led by Tadao Nagasaki, former president of Amazon Web Services in Japan. Despite Japan’s reputation as a technology follower, companies like SoftBank and NTT are investing in large language models. Notable Japanese clients of OpenAI include Toyota Motor, Daikin Industries, and local government entities.
The move aligns with Microsoft’s recent commitment of $2.9 billion over two years to bolster cloud and AI infrastructure in Japan. The investment surge from US tech giants underscores Japan’s growing importance in the global AI landscape and its alignment to maintain a solid place in the race for cutting-edge technology development.
President Biden’s administration has escalated tensions with China by adding more Chinese entities to an export blacklist than any previous US government. This latest move by the Commerce Department brings the total number of entities targeted under Biden to 319, surpassing the count during Trump’s tenure. The decision underscores the increasing use of economic tools to achieve foreign policy objectives, particularly as Biden seeks to limit China’s access to advanced technology, citing national security concerns.
The heightened scrutiny on China comes amidst growing apprehensions in Washington over President Xi Jinping’s assertiveness towards Taiwan, fueling fears of Beijing leveraging American technology to bolster its military capabilities. Both Democrats and Republicans have rallied behind the tough stance on China, reflecting bipartisan consensus on the issue, especially with the upcoming elections looming. Biden has maintained Trump’s tariffs while expanding restrictions on Beijing’s access to cutting-edge innovations, notably in critical sectors like AI.
The entity list serves as a primary mechanism for sanctioning entities on national security grounds and has increasingly become a focal point in US-China relations. Beijing has denounced Washington’s actions as economic coercion and unilateral bullying, vowing to defend the rights and interests of Chinese companies. In a retaliatory move, China imposed sanctions on two US companies, signalling a tit-for-tat escalation in tensions. However, such measures are largely symbolic, with minimal impact on the targeted firms.
Despite the Biden administration’s firm stance, there have been occasional concessions, such as withdrawing a Chinese government laboratory from the entity list to address the fentanyl crisis. Nonetheless, the recent additions to the list signal a continuation of the US strategy to maintain its technological edge, particularly in dual-use technologies. As Washington tightens controls on exports to Chinese firms involved in military modernisation efforts, the stage is set for further friction in the already strained US-China relationship.
Amazon CEO Andy Jassy unveiled the company’s substantial investments in generative AI technology in his annual shareholder letter, released on Thursday. With the growing significance of AI in driving business growth, companies like Amazon are making significant financial commitments to develop and deploy AI products and services.
Jassy outlined Amazon’s GenAI stack, which comprises three layers for various aspects of AI development and deployment. The bottom layer focuses on facilitating model training and prediction, with Amazon investing in custom AI chips to lower customer costs. The middle layer caters to companies seeking to customise foundational models using their data, enhancing security and scalability for generative AI applications. At the top layer, Amazon builds AI applications for its consumer businesses, such as the AI-powered shopping assistant ‘Rufus’ and the Amazon Web Services application ‘Amazon Q.’
Amazon’s shift towards AI represents a strategic pivot, expanding beyond its core cloud computing businesses through AWS and e-commerce. Adding Andrew Ng, an AI expert, to Amazon’s board further emphasises its commitment to AI innovation. As Amazon diversifies its offerings, cost optimisation remains critical, focusing on logistics network efficiency and exploring new revenue streams, such as advertising within Prime Video.
The complexity of Amazon’s growth strategy stems from its diverse business portfolio, spanning industries like satellite internet and healthcare. Jassy aims to position Amazon as a leading innovator, continually experimenting with tech-enabled solutions to address customer needs. As investors await Amazon’s upcoming quarterly earnings report, scheduled for 25 April, the company’s AI investments and broader growth trajectory will be closely monitored.
Japan is positioning itself as a promising destination for American investment in emerging tech sectors, with Prime Minister Fumio Kishida directly appealing to US executives during a lunch event in Washington. Kishida emphasised Japan’s openness to collaboration in critical areas like AI, semiconductors, and clean energy, highlighting the mutual benefits such investments would bring. His visit preceded a summit with President Joe Biden, which was focused on enhancing defence and economic ties between the two nations.
Japanese foreign direct investment in the US has exceeded $750 billion, making Japan the largest foreign investor in America and contributing to creating over 1 million jobs. Microsoft recently announced a substantial $2.9 billion investment to bolster its cloud computing and AI infrastructure in Japan, marking its largest-ever investment in Asia’s second-largest economy. This move underscores the increasing business ties between the US and Japan, coinciding with efforts to modernise their political and military alliance.
As the global geopolitical landscape undergoes significant shifts, Japan and the US are intensifying collaboration, particularly in areas like semiconductor technology. Rapidus, a Tokyo-backed chipmaker, is partnering with IBM to advance chip technology in Japan, aiming to regain ground in an industry once dominated by Japan but now led by competitors like TSMC, Intel, and Samsung. Japan’s efforts to revitalise its semiconductor sector align with Washington’s tightening restrictions on chip sales to China, reflecting broader tech rivalry between the two economic giants.
Prime Minister Kishida also addressed concerns about Japan’s economy, expressing optimism for a resurgence after years of deflationary pressures. With recent moves like ending negative interest rates and initiating the first rate hike in 17 years, Japan aims to break free from deflationary sentiments and foster growth in the coming years. These economic reforms signal Japan’s determination to regain its economic strength and reaffirm its position as a key player in the global market.
Texas students face a new era in standardised testing as the state rolls out an AI-powered scoring system to evaluate open-ended exam questions. The Texas Education Agency (TEA) is implementing an ‘automated scoring engine’ employing natural language processing technology akin to chatbots like OpenAI’s ChatGPT. With plans to replace a majority of human graders, TEA anticipates annual savings of $15–20 million, reducing the need for temporary scorers from 6,000 in 2023 to under 2,000 this year.
The State of Texas Assessments of Academic Readiness (STAAR) exams, revamped last year to include fewer multiple-choice questions, now feature up to seven times more open-ended inquiries. TEA’s director of student assessment, Jose Rios, cites the time-intensive nature of scoring these responses as a driving factor behind the shift. Despite initial training using 3,000 human-graded exam responses and implemented safety nets, including human rescoring for a quarter of computer-graded results and ambiguous AI-confounding answers, concerns linger among educators.
While TEA is optimistic about cost savings, some educators, like Lewisville Independent School District superintendent Lori Rapp, remain cautious. Rapp notes a ‘drastic increase’ in zero-scored constructed responses during the system’s limited trial, raising questions about test question integrity versus automated scoring accuracy. The move towards AI-driven grading aligns with a broader trend in education, with AI essay-scoring engines already in use across 21 states, albeit with mixed success. TEA emphasises distinctions between its ‘closed system’ scoring engine and broader AI, highlighting the importance of transparency and accountability in its implementation.
Why does it matter?
As Texas students navigate this new grading landscape, concerns about fairness and accountability emerge. With generative AI tools already raising issues of academic integrity and equity, questions arise about the consistency and impartiality of AI grading. As the rollout progresses, stakeholders will be watching closely to assess the impact of AI on standardised testing and its implications for education policy and practice.
Meta is gearing up for the next leap in AI chip technology, promising enhanced power and faster training for its ranking models. The Meta Training and Inference Accelerator (MTIA) aims to optimise training efficiency and streamline reasoning tasks, particularly for ranking and recommendation algorithms. In a recent announcement, Meta emphasised MTIA’s pivotal role in its long-term strategy to fortify AI infrastructure for current and future technological advancements, aligning with existing technology setups and forthcoming GPU developments.
Today, we’re introducing the next generation of Meta’s custom-made chips, part of our growing investment in AI infrastructure.https://t.co/Vlev4wF2yU
The company’s commitment to custom silicon extends beyond computational power, encompassing memory bandwidth, networking, and capacity enhancements. Initially unveiled in May 2023 with a focus on data centres, MTIA v1 was slated for a 2025 release. However, Meta was surprised by revealing that both MTIA iterations are already in production, indicative of accelerated progress in their chip development roadmap.
While MTIA currently specialises in training ranking and recommendation algorithms, Meta envisions expanding its capabilities to include generative AI training, such as with its Llama language models. The forthcoming MTIA chip boasts significant upgrades, featuring 256MB memory on-chip and operating at 1.3GHz, compared to its predecessor’s 128MB and 800GHz configuration. Early performance tests indicate a threefold improvement across evaluated models, reflecting Meta’s strides in chip optimisation.
Why does it matter?
Meta’s pursuit mirrors a broader trend among AI companies, with players like Google, Microsoft, and Amazon venturing into custom chip development to meet escalating computing demands. The competitive landscape underscores the need for tailored solutions to efficiently power AI models. As the industry witnesses unprecedented growth in chip demand, market leaders like Nvidia stand poised for substantial valuation, highlighting the critical role of custom chips in driving AI innovation.
Three major players in the AI field, OpenAI, Google, and Mistral, have unveiled new versions of their cutting-edge AI models within 12 hours, signalling a burst of innovation anticipated for the summer. Meta’s Nick Clegg hinted at the imminent release of Meta’s Llama 3 at an event in London, while Google swiftly followed with the launch of its Gemini Pro 1.5, a sophisticated large language model with a limited free usage tier. Shortly after, OpenAI introduced its milestone model, GPT-4 Turbo, which, like Gemini Pro 1.5, supports multimodal input, including images.
In France, Mistral, a startup founded by former Meta AI team members, debuted Mixtral 8x22B, a frontier AI model released as a 281GB download file, following an open-source philosophy. While this approach is criticised for potential risks due to a lack of oversight, it reflects a trend towards democratising access to AI models beyond the control of tech giants like Meta and Google.
Experts caution that the prevailing approach centred on large language models (LLMs) might be reaching its limitations. Meta’s chief AI scientist, Yann LeCun, challenges the notion of imminent artificial general intelligence (AGI) and emphasises the need for AI systems capable of reasoning and planning beyond language manipulation. LeCun advocates for a shift towards ‘objective-driven’ AI to achieve truly superhuman capabilities, thereby highlighting the ongoing evolution and challenges in the AI landscape.
Google unveiled its latest proprietary chip, Axion, demonstrating a willingness to reduce reliance on major chipmakers and bolster its position in the competitive AI landscape. Axion is tailored to manage vast datasets crucial for AI applications and can be grouped into clusters of thousands of chips to enhance performance significantly. According to Google, Axion CPUs outperform existing ‘general-purpose’ chips by about 30%, a move aimed at supporting AI applications within its data centres. Unlike chips aimed at specific business segments, Axion marks Google’s first foray into AI-centric chips for data centre operations.
While customers of Alphabet’s subsidiary will access Axion through Google’s cloud services later this year, the chip won’t be directly purchasable. Google’s vice president, Amin Vahdat, who oversees proprietary chips, emphasised a collaborative approach, avoiding direct competition with longtime partners like Intel and Nvidia. Vahdat views Google’s entry into the chip market as an opportunity to grow the industry collectively, aiming to expand the market rather than capture a share directly from competitors.
In response to Google’s announcement, semiconductor giants like Intel and Nvidia are intensifying their AI chip offerings. Intel recently introduced Gaudi 3, which is expected to be available by the third quarter, focusing on AI applications like training large language models such as ChatGPT. On the other hand, Nvidia plans to launch its latest generation of its H100 chip later this year. Despite Nvidia’s stock decline following Google’s chip reveal, the company has seen substantial growth driven by demand for its powerful chips, now facing heightened competition from rivals like Google in the AI chip market.
Following the news of Axion, Alphabet’s stock rose by 2.4% initially, reflecting investor optimism about Google’s strategic move into AI chips. However, gains moderated later in the day, with Alphabet’s stock closing up 1.28% at approximately $158. Google’s entry into the chip market signals a pivotal shift in its AI strategy, poised to influence the broader semiconductor landscape and competition among major players like Intel and Nvidia.
Meta has confirmed its imminent release of Llama 3, the next iteration of its large language model set to power generative AI assistants. The announcement at an event in London aligns with reports speculating on Meta’s impending launch, indicating a strategic move to enhance its AI offerings.
According to Nick Clegg, Meta’s president of global affairs, the rollout of Llama 3 is slated to begin within the next month. Meta’s Chief Product Officer, Chris Cox, stressed the need to integrate Llama 3 across multiple Meta products, marking a significant step in expanding its AI capabilities.
Meta’s endeavours in AI have been influenced by the success of OpenAI’s ChatGPT, prompting the company to intensify efforts to catch up with competitors. Llama 3, described as broader in scope compared to its predecessors, aims to address criticisms of previous versions regarding limitations in functionality. The new model is expected to offer improved accuracy in answering questions and handle various, including potentially controversial ones, to engage users effectively.
Why does it matter?
While Meta embraces an open-source approach with its Llama models, signalling with developer preferences, it remains cautious in other aspects of generative AI. The company refrains from releasing Emu, its image generation tool, citing concerns about latency, safety, and usability. Despite the company’s advancements in AI technology, notable figures within Meta express scepticism about the future of generative AI, favouring alternative approaches like joint embedding predicting architecture (JEPA) championed by Yann LeCun, Meta’s chief AI scientist.
