Mint Explainer: Will US’s $500 billion Stargate plan help Trump’s China?

What is the Stargate Project?
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Announced Tuesday, it’s a new company that intends to invest $500 billion over the next four years to build new artificial intelligence (AI)-focused data centers across the US.
The joint venture between Openai, Oracle Corp., SoftBank Group Corp., and MGX, which will begin deploying $100 billion immediately, aims to strengthen the country’s AI infrastructure, create 100,000 jobs and take on China in AI development. Have to increase your competition.
Masayoshi’s son will be the president.
Why is America supporting this?
America has a good reason to be antsy in the AI space.
It currently has the strongest AI ecosystem in the world, leading significantly across key metrics, according to Stanford University’s Global AI Vibrancy Tool, which ranks countries on AI research output, economic activity and infrastructure.
By November 2024, the US is producing high-quality AI research, building notable machine learning (ML) models, private investments, AI-related mergers/acquisitions, job postings, and newly funded AI startups.
However, China-based Baidu Inc. China’s Ernie Bot can’t catch up to Openai’s Chatgate China ranks second in AI and is providing credible competition, with $67.2 billion in AI-related private investment in 2023 compared to $7.8 billion in 2023 Is attracting. According to the Stanford report, for the US.
China produced more notable ML models (61 vs. 15) and led in AI-related patents.
Furthermore, China continues to innovate in space, which is worrying the US.
Chinese AI lab DeepSeq, for example, is making headlines with its new DeepSeq-R1, an open-source reasoning model that rivals OpenAI’s O1. This model is trained using Reinforcement Learning (RL) with unsupervised fine-tuning (SFT).
The innovation is important because it avoids reliance on pre-labeled datasets, allowing models to independently explore solutions and adapt to new challenges. The company claims that using this method, DeepSeq-R1 outperformed O1’s API (Application Programming Interface) cost ($0.14 vs. $7.50 per million inputs). During math, code and logic tasks are performed with Openai-O1.
Moreover, while the US hosts Nvidia Corp, the world’s largest AI company, most of the latter’s chips are manufactured by Taiwan Semiconductor Manufacturing Co Ltd (TSMC).
Since China considers Taiwan a breakaway province, navigating these complexities will shape the U.S. semiconductor and AI landscape for years to come.
What are its implications for the global AI race?
Governments around the world are turning their attention to AI data centers equipped to host advanced AI workloads since the latter guzzles computing power. This sample: While a 30-megawatt (MW) data center used to be considered large, a 200-MW is now considered “normal,” according to McKinsey & Company.
Consultancy Firm estimated Even if all currently known plans are delivered on time, there could still be a data center supply deficit of more than 15 gigawatts (GW) in the US alone by 2030.
McKinsey analysis suggested that demand for A-ready data center capacity is expected to grow at an average annual rate of 33% from 2023 to 2030. By that year, approximately 70% of the total data center capacity demand will be for facilities equipped to handle the data. Advanced AI workloads.
The fastest growing advanced AI use case, generative AI (GenE), is projected to account for approximately 40% of this demand. Cloud service providers (CSPs) such as Amazon Web Services (AWS) Inc., Google Cloud Platform, Microsoft Azure, and Baidu are the companies fueling much of today’s incremental demand for A-ready data centers.
What are other countries doing?
UK ranked third in Global AI Vibrancy Ranking 2023. India ranked fourth, followed by the United Arab Emirates (UAE), which is investing heavily in AI research through institutions such as the Institute of Technology Innovation.
The UK government has announced a substantial expansion of data centers to attract AI firms. The initiative aims to remove planning barriers to facilitate private sector investments in AI infrastructure. Additionally, the European Union (EU) is actively investing in AI infrastructure.
What does India stand for?
India, too, has launched several important schemes to enhance its AI infrastructure. Rackbank Datacenters Pvt. Ltd. has announced its 80MW AI-centric data center with 60,000 GPU (Graphics Processing Unit) capacity in Madhya Pradesh.
There are currently about 150 data centers in the country, including those from large companies – also known as hyperscalers because of their size – such as AWS, Microsoft Azure, Google Cloud, NTT Data Group Corp, Sify Technologies Ltd, and Ctrls Datacenters Ltd, and new entrants such as Yotta Infrastructure, Digital Connexion and Lumina Cloudinfra Pvt. Ltd.
They are all rapidly expanding their capabilities to accommodate increasing digitalization, demand for AI and GenY projects, nationwide rollouts of 5G, laws mandating certain data must be stored locally, and The need for edge computing that allows data processing on the devices themselves.
Additionally, Microsoft Corp. recently announced a $3 billion investment to expand its cloud and AI services in India over the next two years, aiming to accelerate AI innovation and equip 10 million people with AI skills by 2030 .
Additionally, the Government of India has launched the IndiaAI Mission, a comprehensive national level initiative with a budget outlay of ₹10,371.92 crore (about $1.25 billion), which focuses on enhancing computing infrastructure, supporting deep-tech startups, and developing data platforms to promote AI development in various sectors.
To be sure, India boasts of a strong and cost-effective talent pool in software engineering, integrated circuits (IC) and manufacturing device design, with 2,000 semiconductor chip design engineers. Leading semiconductor firms including Intel Corp, Texas Instruments Inc, Nvidia Corp, Advanced Micro Devices Inc, and Qualcomm Technologies Inc have set up design, research and development centers in the country.
India is also stepping up its semiconductor manufacturing capabilities. It has approved four major projects ₹1.5 trillion, which includes ventures by Micron Technology Inc and a partnership between Tata Electronics and Taiwan’s Powerchip Semiconductor Manufacturing Corp (PSMC). These initiatives aim to produce 180,000 wafers monthly upon completion.
Additionally, Adani Group, in collaboration with Israel’s Tower Semiconductor Ltd., is planning a $10 billion fab in Panvel, Maharashtra, setting up a foundation for local chip-making and providing services for design, manufacturing and ATMP (assembly , which has a complete semiconductor value chain, including testing, marking and packaging). India has also set aside a $10 billion fund to attract global chipmakers.
India has also inked semiconductor agreements with the US, Singapore and the EU, signaling its intention to strengthen its global position in a sector challenged by raw material shortages and geopolitical tensions. Its focus on producing 28nm and higher chips is strategic, balancing cost efficiency with longer shelf life. However, swift execution of these projects is essential for success.
What challenges does India need to address?
The National Mission for AI further outlines India’s ambitions, with plans to build infrastructure using 10,000 GPUs through a public-private partnership, supported by A. 10,000 crore investment. However, India must address restrictions on US AI chip exports, which were tightened under the Biden administration, to ensure access to critical technology.
Stargate shows the US’s “serious intention” to take control of AI and all large language models (LLMS), said Ajai Chaudhary, founder of HCL (Hindustan Computer Limited) and chairman of the Epic Foundation and India’s National Quantum Mission.
Dubbing Stargate as the “weaponization of tech”, he said India needs to create its own “AI theory” by controlling its own data and domestic hardware for data centres.
Geopolitics, as we see, is again an important factor.
(T) AI Data Center
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