### Summary
The UK government plans to spend £100m on computer chips used for artificial intelligence (AI) in order to establish a national resource for AI in Britain. However, industry insiders believe the investment is insufficient compared to other countries' investments.
### Facts
- 📌 The UK government will spend £100m to develop computer chips for AI.
- 📌 The funds will be used to order key components from major chipmakers Nvidia, AMD, and Intel.
- 📌 The government plans to order up to 5,000 graphics processing units (GPUs) from Nvidia.
- 📌 Industry and Whitehall officials fear that the government's investment may be too low to compete globally.
- 📌 The UK accounts for only 0.5% of global semiconductor sales.
- 📌 The US has committed $52bn to the Chips Act, while the EU offers €43bn in subsidies.
- 📌 Delays in progress due to weak investment could leave the UK vulnerable amidst geopolitical tensions over AI chip technology.
- 📌 The UK government aims to establish shared standards for technology through an AI summit in the autumn.
- 📌 UK Research and Innovation (UKRI) is leading the effort to secure orders with major chip manufacturers.
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### Summary
British Prime Minister Rishi Sunak is allocating $130 million to purchase computer chips to power artificial intelligence and build an "AI Research Resource" in the United Kingdom.
### Facts
- 🧪 The United Kingdom plans to establish an "AI Research Resource" by mid-2024 to become an AI tech hub.
- 💻 The government is sourcing chips from NVIDIA, Intel, and AMD and has ordered 5,000 NVIDIA graphic processing units (GPUs).
- 💰 The allocated $130 million may not be sufficient to match the ambition of the AI hub, leading to a potential request for more funding.
- 🌍 A recent report highlighted that many companies face challenges deploying AI due to limited resources and technical obstacles.
- 👥 In a survey conducted by S&P Global, firms reported insufficient computing power as a major obstacle to supporting AI projects.
- 🤖 The ability to support AI workloads will play a crucial role in determining who leads in the AI space.
### Summary
Nvidia's weakened processors, designed for the Chinese market and limited by US export controls, are still more powerful than alternatives and have resulted in soaring Chinese orders worth $5 billion.
### Facts
- The US imposed restrictions to limit China's development of AI for military purposes, including blocking the sale of advanced US chips used in training AI systems.
- Despite being deliberately hobbled for the Chinese market, the latest US technology available in China is more powerful than before.
- Chinese internet companies have placed $5 billion worth of orders for Nvidia's chips, which are used to train large AI models.
- The global demand for Nvidia's products is likely to drive its second-quarter financial results.
- There are concerns that tightening export controls by the US may make even limited products unavailable in the future.
- Bill Dally, Nvidia's chief scientist, anticipates a growing gap between chips sold in China and those available elsewhere in the world, as training requirements for AI systems continue to double every six to 12 months.
- Washington set a cap on the maximum processing speed and data transfer rate of chips sold in China.
- Nvidia responded by creating processors with lower data transfer rates for the Chinese market, such as the A800 and H800.
- The H800 chips in China have a lower transfer rate of 400GB/s compared to 600GB/s set by the US, but they are still more powerful than chips available elsewhere.
- The longer training times for AI systems using these chips increases costs and energy consumption.
- Chinese tech companies rely on Nvidia's chips for pre-training large language models due to their efficiency.
- Nvidia's offering includes the software ecosystem with its computing platform, Cuda, which is part of the AI infrastructure.
- Analysts believe that Chinese companies may face limitations in the speed of interconnections between the chips, hindering their ability to handle increasing amounts of data for AI training and research.
Main Topic: Opportunities for semiconductor startups in the AI chip market
Key Points:
1. Nvidia is currently the leading provider of AI accelerator chips, but it cannot keep up with demand.
2. Startups focusing on AI acceleration in the data center and edge computing have the opportunity to compete with Nvidia.
3. Established companies like Cerebras Systems and Tenstorrent are gaining traction in the market with their unique AI hardware solutions.
The US has expanded export restrictions on Nvidia's artificial intelligence chips, impacting countries in the Middle East and escalating efforts to curtail China's AI capabilities.
Vietnam is emerging as a potential hub for chip makers, with companies like Microsoft, Nvidia, Amkor, Synopsys, and Marvell announcing plans to invest in the region, while chip stocks experienced a slump in the market.
Nvidia's record sales in AI chips have deterred investors from funding semiconductor start-ups, leading to an 80% decrease in US deals, as the cost of competing chips and the difficulty of breaking into the market have made them riskier investments.
The United States and Vietnam have entered into business deals and partnerships worth billions of dollars to advance cooperation in AI technologies and other critical sectors, marking an "upgrading" of their relationship and a focus on building a resilient semiconductor supply chain.
Despite the challenges faced by startups in China, companies like vrch.io are focusing on the application level of AI technology due to high costs and regulatory concerns, opting to target overseas markets before entering the Chinese market.
Intel's AI chips designed for Chinese clients are experiencing high demand as Chinese companies rush to improve their capabilities in ChatGPT-like technology, leading to increased orders from Intel's supplier TSMC and prompting Intel to place more orders; the demand for AI chips in China has surged due to the race by Chinese tech firms to build their own large language models (LLMs), but US export curbs have restricted China's access to advanced chips, creating a black market for smuggled chips.
OpenAI is considering developing its own artificial intelligence chips or acquiring a chip company to address the shortage of expensive AI chips it relies on.
OpenAI, a well-funded AI startup, is exploring the possibility of developing its own AI chips in response to the shortage of chips for training AI models and the strain on GPU supply caused by the generative AI boom. The company is considering various strategies, including acquiring an AI chip manufacturer or designing chips internally, with the aim of addressing its chip ambitions.
Nvidia's upcoming AI chips will drive rapid innovation and provide a boost for investors, according to BofA Global Research.
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