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.
- 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.
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…