New guidelines from China reportedly blocks U.S. chips in government computers

U.S. China trade microchip trade battle

China has reportedly prohibited the use of U.S. processors from both AMD and Intel in government computers and servers. The directive is designed to encourage the use of domestic alternatives.

Chinese government agencies are now required to choose ‘safe and reliable’ domestic alternatives for these chips. The sanctioned list features processors from Huawei and the state supported firm Phytium, both of which face bans in the U.S.

In addition to processors, China is now also restricting Microsoft Windows on government devices, opting instead for domestically produced operating systems.

These guidelines are part of a broader tech trade battles between China and the U.S. While the impact on Intel and AMD remains to be seen, it’s clear that China is taking aggressive steps to reduce reliance on U.S. built technology.

The global tech landscape continues to evolve, and these decisions have far-reaching implications for both countries and the industry as a whole.

U.S. and China trade tensions are unlikely to recede anytime soon.

Water scarcity and its impact on semiconductor production

Water scarcity

Water scarcity is a pressing global issue and has far-reaching consequences across various industries. One sector significantly affected is semiconductor manufacturing.

How does water scarcity pose a threat to the production of essential microchips.

Water in Semiconductor Manufacturing

Ultra-pure water is a critical resource in semiconductor fabrication plants (fabs). It is used for cleaning, cooling, and various processing steps during chip production.

Microchips power our devices—computers, smartphones, sensors, and LEDs—all of which rely on water-intensive manufacturing processes.

Global Water Scarcity

Freshwater availability is unevenly distributed worldwide. While oceans contain 97% of water (mostly saline), accessible freshwater constitutes only a small fraction.

Approximately four billion people experience severe water scarcity for at least one month annually, and half a billion face it year-round.

Taiwan’s Drought and Chip Production

Taiwan, a semiconductor manufacturing hub, faces a severe drought. Over 20% of global microchips are produced there.

Water shortages threaten supply chains, potentially impacting chip production.

Cost and Sustainability

Creating fully self-sufficient local supply chains would cost $1 trillion. Such self-reliance could increase semiconductor costs by up to 65%.

Urgent action is needed to ensure sustainable water management in fabs, as chips control everything from cars to appliances.

In conclusion, water scarcity poses a real danger to semiconductor production. Addressing this challenge requires strategic planning, conservation efforts, and global cooperation.

AI a problem or a solution?

Will the problem of water scarcity exacerbate the uneven distribution of water around the world as the rich have easier access to the precious resource.

Will the explosion of AI tech push the imbalance – water is a basic necessity to maintain human life. Will AI have a hand in controlling the distribution of water – even for its own needs?

Nvidia revenue is up 265% latest figures show and stock gains 15%

AI chip

The excitement surrounding artificial intelligence (AI) technology appears to show few signs of abating

The technology company at the heart of the AI chip boom reported its Q4 earnings after the stock market’s close on Wednesday 21st February 2024, beating expectations for both earnings and sales. The company’s total revenue is up 265% from a year ago.

Investors are looking to Nvidia’s latest quarterly earnings report to see whether the company’s meteoric growth can last.

Nvidia one year share price as at 22nd February 2024

Nvidia one year share price as at 22nd February 2024

AI chips

Nvidia makes powerful computer chips that power popular AI tools like OpenAI’s ChatGPT and Microsoft’s Copilot. High demand for those chips has propelled the company into the exclusive trillion-dollar club.

As of market close on 21st February 2024 the company’s market cap sat at $1.667 trillion, putting it behind Alphabet’s $1.779 trillion market cap. It’s also behind Microsoft and Apple, which hold market caps of $2.988 trillion and $2.819 trillion, respectively.

Nvidia’s stock price has been on an upward trajectory so far this year. Shares have gained by nearly 40% since the beginning of 2024. On top of that, they’ve soared by over 225% in the last 12 months.

Although short-term demand for Nvidia’s AI chips has been strong, major companies such as Microsoft and Meta have indicated interest in buying them from other companies.

If you had invested $1,000 in Nvidia

If you had invested $1,000 in Nvidia five, 10 or 24 years ago, here’s how much your investment would be worth now.

$1,000 in Nvidia five years ago, your investment would have increased by an eye-watering 1,015% and be worth around $17,542 as of 20th February 2024.

If you had invested $1,000 in Nvidia 10 years ago, your investment would have soared by about 22,340% and be worth around $148,226 as of 20th February 2024.

But, if you had invested $1,000 in Nvidia in January 1999, when Nvidia first went public, your investment would have grown by around 277,708% and be worth close to $2,784,065 as of 20th February 2024.

AI has only just started.

Nvidia stock closes at all-time high

AI chip image

Nvidia stock closes at all-time high, a day before earnings

Shares of Nvidia closed up 2.3% at an all-time high of $504 on Monday 20th November 2023. The record comes ahead of the company’s Q3 results due Tuesday 21st November 2023, when analysts are expecting to see revenue growth of over 170%.

And, if that’s not enough, the forecast for Q4, according to some analysts, is likely to show a number close to 200% growth.

Nvidia is still by far the market leader in GPUs for AI, but high prices and competition are fast becoming an issue.

Can Nvidia continue the AI ride and hold this remarkable market share position?

Nvidia stock falls after restrictions placed on AI chip exports from U.S.

AI microchip

The U.S. reportedly announced new restrictions on exports of advanced chips to China, including two made-for-China chips from Nvidia.

U.S. chip stocks fell as the curbs also hit Advanced Micro Devices and Intel.

Loopholes

The curbs are aimed at closing loopholes that became apparent after the U.S. announced export curbs on microchips in October 2022. The restrictions are designed to prevent China’s military from importing advanced semiconductors or equipment.

Nvidia has said in a filing that the new export restrictions will block sales of two high-end artificial intelligence chips it created for the Chinese market – A800 and H800. It said that one of its gaming chips will also be blocked.

Nvidia Corp one month chart – closed at 439.38 17th October 2023

Although the curbs also affect other chip makers, analysts believe Nvidia will be hit the hardest because China accounts for up to 25% of its revenues from data centre chip sales. Nvidia’s shares, which are considered a star stock, fell by as much as 4.7% in the wake of the announcement.

Semiconductor Industry Association

The Semiconductor Industry Association, which represents 99% of the U.S. semiconductor industry by revenue, said in a statement that the new measures are ‘overly broad‘ and ‘risk harming the U.S. semiconductor structure without advancing national security as they encourage overseas customers to source elsewhere’.

China reacts

A spokesperson for the Chinese embassy also said that it ‘firmly opposes‘ the new restrictions, which also target Iran and Russia and go into effect in 30 days.

Nvidia stock falls after restrictions on AI chip exports from U.S. to China

Two months ago, China retaliated by restricting exports of two materials, gallium and germanium, which are key to the semiconductor industry.

China is by far the biggest player in the global supply chain of gallium and germanium. It produces 80% of the world’s gallium and 60% of germanium.

The materials are ‘minor metals‘, meaning that they are not usually found on their own in nature, and are often the by-product of other processes. It’s not only the U.S., Japan and the Netherlands – which is home to key chip equipment maker ASML – have also imposed chip technology export restrictions on China.

Fallout

The constant ‘fall-out’ between the world’s two biggest economies has raised concerns over the rise of so-called ‘resource nationalism‘ – a practice where governments hoard critical materials to exert influence over other countries.

Nvidia’s stock at record high after Google AI deal

AI microchip

Nvidia shares rose 4.2% Tuesday 29th August 2023 to close at a record high, after the company announced a partnership with Google that could expand distribution of its artificial intelligence technology (AI).

The stock’s bountiful run continued, now up 234% in 2023, making it by far the best performer in the S&P 500. Facebook parent Meta is second in the index, up 148% so far this year.

The record close comes less than a week after the company said quarterly revenue doubled from a year earlier and gave a forecast indicating that sales this period could rise 170% on an annual basis. The day after the better-than-expected earnings report, the stock climbed to a record intraday high of $502.66 before declining later in the afternoon.

Nvidia’s business is booming because its graphics processing (GPU’s) are being gobbled up by cloud companies, government agencies and startups to train and deploy generative AI models like the technology deployed in OpenAI’s ChatGPT as fasta as Nvidia can make them.

NVIDIA stock chart

Nvidia announcment

On Tuesday 29th August 2023, Nvidia CEO Jensen Huang appeared at a Google conference to announce an AI agreement between the two companies.

Through the partnership, Google’s cloud customers will have greater access to technology powered by Nvidia’s powerful H100 GPUs.

‘Our expanded collaboration with Google Cloud will help developers accelerate their work with infrastructure, software and services that supercharge energy efficiency and reduce costs’, the Nvidia CEO reportedly said in a blog post.

Nvidia’s GPUs are also available on competing cloud platforms from Amazon and Microsoft.

Nvidia blasts off into AI superstardom

AI rocket

Technology giant Nvidia reports its sales have hit a record after more than doubling as demand for its artificial intelligence (AI) chips take off!

It figures

The company says revenue jumped to above $13.5bn (£10.6bn) for the three months to the end of June. Nvidia also expects sales to perform very well in the current quarter and plans to buy back $25bn of its stock. The firm’s shares rose by more than 6.5% in extended trading in New York, adding to their huge gains this year. Nvidia also said it expects revenue of around $16bn for the three months to the end of September 2023.

That is substantially higher than Wall Street expected and would equate to a rise of around 170%, compared to the same time last year.

Even before 23rd August’s figures, Nvidia’s stock price had more than tripled for the year, making it the top performer in the S&P 500. It’s share price jumped to around $500 after hours, a level that would mark a record if it closes there on 24th August 2023. Its prior closing high was $474.94 on 18th July 2023.

‘A new computing era has begun’, Nvidia’s chief executive, Jensen Huang, said in a statement. ‘Companies worldwide are transitioning from general-purpose to accelerated computing and generative AI’, he reportedly added.

Strong performance

The strong performance was driven by Nvidia’s data centre business, which includes AI chips.

The power of Nvidia’s AI microchips

Revenue for that unit came in at more $10.3bn, a rise of more than 170% from year ago, as cloud computing service providers and large consumer internet companies snapped up its next-generation processors.

This year, Nvidia’s stock market value has jumped to more than $1 trillion as its shares more than tripled in value, mking it the fifth publicly traded U.S. company to join the so-called ‘Trillion dollar club’, along with Apple, Amazon, Alphabet and Microsoft.

AI ‘mania’ helps Nvidia

Nvidia have been making micro chips for a long time and it’s only really been in the last couple of years that the market has caught on.

Nvidia was originally known for making the type of computer chips that process graphics, particularly for computer games. They have been making chips for a long time and have now become the leader in AI chip design and manufacture.

Now Nvidia’s hardware is the foundation for most AI applications, with one report suggesting it had cornered 95% of the market for machine learning.

ChatGPT which generates human-like responses to user queries within seconds was trained using 10,000 of Nvidia’s graphics processing units clustered together in a supercomputer belonging to Microsoft.

AI products are expected to dramatically change how we use computers and the role they play in our lives.

Amazon – leading or competing?

The power of AI

Amazon is one of the leading companies in the field of artificial intelligence (AI) and has been developing its own custom chips to power its AI applications and services.

Amazon’s AI chips are designed to perform tasks such as natural language processing, computer vision, speech recognition, and machine learning inference and training.

AI chips created by Amazon

  • AZ2: This is a processor built into the Echo Show 15 smart display and powers artificial intelligence tasks like understanding your voice commands and figuring out who is issuing those commands. The AZ2 chip also enables features such as visual ID, which can recognize faces and display personalized information on the screen.
  • Inferentia: This is a high-performance chip that Amazon launched to deliver low-cost and high-throughput inference for deep learning applications. Inferentia powers Amazon Elastic Compute Cloud (EC2) Inf1 instances, which are optimized for running inference workloads on AWS. Inferentia also powers some of Amazon’s own services, such as Alexa, Rekognition, and SageMaker Neo.
  • Trainium: This is a chip that Amazon designed to provide high-performance and low-cost training for machine learning models. Trainium will power Amazon EC2 Inf2 instances, which are designed to train increasingly complex models, such as large language models and vision transformers. Trainium will also support scale-out distributed training with ultra-high-speed connectivity between accelerators.

Despite advancements is Amazon chasing to keep up?

Amazon is racing to catch up with Microsoft and Google in the field of generative AI, which is a branch of AI that can create new content or data from existing data. Generative AI can be used for applications such as natural language generation, image and video synthesis, text summarization, and personalization.

AI models from Amazon

  • Titan: This is a family of large language models (LLMs). Titan models can generate natural language texts for various domains and tasks, such as conversational agents, document summarization, product reviews, and more. Titan models are trained on a large and diverse corpus of text data from various sources, such as books, news articles, social media posts, and product descriptions.
Power of AI
Powerful chips for artificial intelligence (AI)
  • Bedrock: This is a service that Amazon created to help developers enhance their software using generative AI. Bedrock provides access to pre-trained Titan models and tools to customize them for specific use cases. Bedrock also allows developers to deploy their generative AI applications on AWS using Inferentia or Trainium chips.

Generative AI

Amazon’s CEO, Andy Jassy in the past said he thought of generative AI as having three macro layers: the compute, the models, and the applications. He said that Amazon is investing heavily in all three layers and that its custom chips are a key part of its strategy to provide high-performance and low-cost compute for generative AI. He also said that Amazon is not used to chasing markets but creating them, and that he believes Amazon has the best platform for generative AI in the world.

Inferentia and Trainium, offer AWS customers an alternative to training their large language models on Nvidia GPUs, which have been getting difficult and expensive to procure. 

‘The entire world would like more chips for doing generative AI, whether that’s GPUs or whether that’s Amazon’s own chips that we’re designing’, Amazon Web Services CEO Adam Selipsky is reported to have said. ‘I think that we’re in a better position than anybody else on Earth to supply the capacity that our customers collectively are going to want’.

Fast actors

Yet others have acted faster, and invested more, to capture business from the generative AI boom. When OpenAI launched ChatGPT in November 2022, Microsoft gained widespread attention for hosting the chatbot, and investing a reportedly whopping $13 billion in OpenAI. It was quick to add the generative AI models to its own products, incorporating them into Bing in February 2023. 

That same month, Google launched its own large language model, Bard, followed by a $300 million investment in OpenAI rival Anthropic. 

Chat Bot
AI Chat Bot robot

It wasn’t until April 2023 that Amazon announced its own family of large language models, called Titan, along with a service called Bedrock to help developers enhance software using generative AI.

Amazon is not used to chasing markets. Amazon is used to creating markets. And for the first time for some time, they find themselves on the back foot and working to play catch up.

And Meta?

Meta also recently released its own LLM, Llama 2. The open-source ChatGPT rival is now available for people to test on Microsoft’s Azure public cloud.

The AI battle continues…