A brief history of ARM

Arm micro hip

Brief ARM history

Arm is a British semiconductor and software design company that is known for its Arm processors, which are widely used in smartphones, tablets, laptops, and other devices. Arm was founded in 1990 as a joint venture between Acorn Computers, Apple Computer, and VLSI Technology. The company was originally called Advanced RISC Machines, but later changed its name to Arm Ltd in 1998.

In 1985, the first Arm silicon chip was created by Acorn engineers Sophie Wilson and Steve Furber, who designed a 32-bit processor with a simple and elegant instruction set.

In 1990, Arm was spun off from Acorn as a separate company, with Apple as a major investor. Arm’s first product was the ARM6 processor, which was used in Apple’s Newton personal digital assistant.

Impression of the Apple Newton PDA device

In 1993, Arm introduced the ARM7 processor, which became one of the most successful embedded processors in history. It was used in devices such as the Nokia 6110 mobile phone, the Nintendo Game Boy Advance, and the Lego Mindstorms robotics kit.

In 1994, Arm launched the ARM9 processor family, which offered higher performance and lower power consumption than previous generations. The ARM9 was used in devices such as the Sony PlayStation Portable, the Palm Treo smartphone, and the Amazon Kindle e-reader.

In 1997, Arm introduced the ARM10 processor family, which featured a superscalar architecture and a floating-point unit. The ARM10 was used in devices such as the Apple iPod, the Samsung Galaxy S smartphone, and the Raspberry Pi computer.

In 1998, Arm changed its name from Advanced RISC Machines to Arm Ltd, reflecting its global expansion and recognition.

In 1999, Arm launched the ARM11 processor family, which featured a vector floating-point unit and a TrustZone security extension. The ARM11 was used in devices such as the iPhone 3G, the Nintendo DS, and the Raspberry Pi Zero.

In 2000, Arm became a public company, listing on the London Stock Exchange and the Nasdaq. The company raised £213 million in its initial public offering.

In 2001, Arm introduced the Cortex processor family, which offered a range of performance, power, and cost options for different applications. The Cortex processors are used in devices such as the Samsung Galaxy S10, the Apple Watch, and the Tesla Model 3.

In 2005, Arm acquired Artisan Components, a provider of physical intellectual property (IP) for chip design. This enabled Arm to offer a complete solution for system-on-chip (SoC) development.

In 2006, Arm announced the Mali graphics processing unit (GPU) family, which complemented its CPU offerings with high-performance graphics capabilities. The Mali GPUs are used in devices such as the Huawei Mate 20 Pro, the Oculus Quest, and the Samsung Smart TV.

Artistic image of ARM chip

In 2009, Arm partnered with IBM, Samsung, Texas Instruments, and others to form the Linaro consortium, which aimed to improve the Linux software ecosystem for Arm-based devices.

In 2010, Arm unveiled the Cortex-A15 processor, which was the first Arm processor to support virtualization and big.LITTLE technology. The Cortex-A15 was used in devices such as the Google Nexus 10, the LG G3, and the Nintendo Switch.

In 2011, Arm announced the Cortex-M0+ processor, which was the world’s most energy-efficient microcontroller. The Cortex-M0+ was used in devices such as the Arduino Nano 33 IoT, the Fitbit Flex 2, and the Nest Thermostat.

In 2012, Arm launched the Cortex-A53 and Cortex-A57 processors, which were the first Arm processors to support the 64-bit ARMv8 architecture. The Cortex-A53 and Cortex-A57 were used in devices such as the iPhone 6s, the Samsung Galaxy S6 Edge+, and the Microsoft Surface Pro X.

In 2013, Arm acquired Geomerics, a developer of real-time lighting technology for video games. This enhanced Arm’s graphics portfolio with dynamic illumination and global illumination effects.

In 2014, Arm introduced the Cortex-A72 processor, which delivered a 50% performance improvement over the previous generation. The Cortex-A72 was used in devices such as the Huawei P9, the Xiaomi Mi 5s Plus, and the Amazon Fire HD 10.

In 2015, Arm announced the Cortex-A35 processor, which was the most efficient Arm processor for smartphones and tablets. The Cortex-A35 was used in devices such as the Nokia 2.1, the Samsung Galaxy J2 Core, and the Lenovo Tab M7.

In 2016, Arm was acquired by SoftBank Group for £24.3 billion, becoming a subsidiary of the Japanese conglomerate. The deal was motivated by SoftBank’s vision of investing in technologies that would drive the future of artificial intelligence (AI), internet of things (IoT), and smart cities.

In 2017, Arm launched Project Trillium, a suite of machine learning (ML) solutions that included an ML processor , an object detection processor , and an open-source software framework. The Project Trillium products aimed to enable low-power and high-performance ML applications on edge devices.

In 2018, Arm unveiled the Cortex-A76 processor , which offered a 35% performance boost over its predecessor. The Cortex-A76 was used in devices such as the OnePlus 7T, the Huawei MateBook D14, and the Acer Chromebook Spin 13.

In 2019, Arm announced the Cortex-A77 processor , which improved on its predecessor with a higher clock speed, a larger cache, and better branch prediction . The Cortex-A77 was used in devices such as the Samsung Galaxy S20, the Asus ROG Phone II, and the Lenovo Yoga C940.

In 2020, Arm introduced the Cortex-X1 processor , which was its most powerful CPU design to date. The Cortex-X1 was designed to deliver peak performance for premium device , such as flagship smartphones, laptops and gaming consoles. The Cortex-X1 was used in devices such as the Samsung Galaxy S21 Ultra, the Xiaomi Mi 11, and the Google Pixel 6.

In 2021, Arm launched the Cortex-A78C processor , which was optimized for high-performance computing (HPC) applications. The Cortex-A78C featured up to eight CPU cores , a larger L3 cache, and support for ECC memory. The Cortex-A78C was used in devices such as the Samsung Galaxy Book Pro, the HP Elite Folio , and the Acer Chromebook Spin 513.

Microchip

In 2022, Arm unveiled the Cortex-A710 processor, which was its first big core to support the Armv9 architecture. The Cortex-A710 offered a 30% energy efficiency improvement over its predecessor, as well as enhanced security and ML features. The Cortex-A710 was used in devices such as the OnePlus 10 Pro, the Huawei MatePad Pro 2, and the Microsoft Surface Laptop Studio.

In 2023, Arm announced the Immortalis GPU family , which was its next-generation graphics solution that included hardware-based ray-tracing and variable rate shading capabilities . The Immortalis GPUs aimed to deliver realistic and immersive graphics for gaming, VR and AR applications on mobile devices . The Immortalis GPUs were used in devices such as the Samsung Galaxy S22 Ultra , the Sony Xperia 1 IV, and the Oculus Quest 3.

Powerful world presence

Arm is a leading semiconductor and software design company that has revolutionized the computing industry with its innovative and efficient processor architectures. Arm’s processors power billions of devices across various domains, such as mobile, IoT, AI, HPC, and gaming. Arm has been at the forefront of technological advancements for over three decades, delivering performance, energy efficiency, and security to its customers and partners.

Arm is a subsidiary of SoftBank Group and has a massive global presence.

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…

What China’s new stance in microchip battle means

Gallium and Germanium

Gallium and germanium

No, nor me – never heard of them, but they are extremely important elements needed in microchip manufacturing and China is the world’s largest producer.

Germanium and gallium are two elements that are used in the production of semiconductor chips, which are essential for various electronic devices and technologies. They have different properties and applications, and they are both considered critical materials.

Germanium

Germanium is a metalloid, which means it has properties of both metals and non-metals. It is a shiny, hard, gray-white element that is brittle and can be cut easily with a knife. It has a high melting point of 938°C and a low boiling point of 2830°C. It is mainly obtained as a by-product of zinc production, but it can also be extracted from coal.

Germanium is used in, solar cells, fibre optic cables, infrared lenses light-emitting diodes (LEDs), and transistors. It is also used in some alloys to improve their strength and hardness. Germanium is essential for the defence and renewable energy sectors, as well as for space technologies. It can resist cosmic radiation better than silicon, and it can enhance the performance and efficiency of some semiconductors.

Gallium

Gallium is a metal that has a very low melting point of 29.8°C, which means it can melt in your hand. It is a soft, silvery-white element that can be easily cut with a knife. It has a high boiling point of 2403°C.  It is mainly obtained as a by-product of processing bauxite and zinc ores.

Gallium and Germanium considered critical elements required in the production of microchips

Gallium is used in the electronics industry to produce heat-resistant semiconductor wafers that can operate at higher frequencies than silicon-based ones. It is also used in LEDs, solar panels, microwave devices, sensors, and lasers. Gallium is important for the development of new technologies such as electric vehicles, high-end radio communications, and Blu-Ray players. It can also improve the power consumption and reliability of some semiconductors.

China the largest producer

China is the largest producer and exporter of both germanium and gallium, accounting for about 60% and 80% of the global supply. However, China has recently announced new export restrictions on these two elements, requiring special licences for exporters. This move is seen as a response to the western sanctions on China’s access to advanced microchip technology. 

The export curbs could affect the global supply chain of semiconductor chips and have implications for various industries and markets