Introduction to AI Accelerators
Amazon Web Services has scored another major win for its custom AWS Trainium accelerators after striking a deal with AI video startup Decart. The partnership will see Decart optimize its flagship Lucy model on AWS Trainium3 to support real-time video generation, and highlight the growing popularity of AI accelerators over Nvidia’s graphics processing units.
What is Decart and How Does it Use AWS Trainium?
Decart is essentially going all-in on AWS, and as part of the deal, the company will also make its models available through the Amazon Bedrock platform. Developers can integrate Decart’s real-time video generation capabilities into almost any cloud application without worrying about underlying infrastructure. The distribution through Bedrock increases AWS’s plug-and-play capabilities, demonstrating Amazon’s confidence in growing demand for real-time AI video. It also allows Decart to expand its reach and grow adoption among the developer community. AWS Trainium provides Lucy with the extra processing grunt needed to generate high-fidelity video without sacrificing quality or latency.
Why All the Fuss Over AI Accelerators?
Custom AI accelerators like Trainium provide an alternative to Nvidia’s GPUs for AI workloads. While Nvidia still dominates the AI market, its GPUs processing the vast majority of AI workloads, it’s facing a growing threat from custom processors. AWS Trainium isn’t the only option developers have. Google’s Tensor Processing Unit (TPU) product line and Meta’s Training and Inference Accelerator (MTIA) chips are other examples of custom silicon, each having a similar advantage over Nvidia’s GPUs – their ASIC architecture (Application-Specific Integrated Circuit).
How Do ASICs Work?
As the name suggests, ASIC hardware is engineered specifically to handle one kind of application and do so more efficiently than general-purpose processors. While central processing units are generally considered to be the Swiss Army knife of the computing world due to their ability to handle multiple applications, GPUs are more akin to a powerful electric drill. They’re vastly more powerful than CPUs, designed to process massive amounts of repetitive, parallel computations, making them suitable for AI applications and graphics rendering tasks. If the GPU is a power drill, the ASIC might be considered a scalpel, designed for extremely precise procedures.
The Trainium Advantage
Decart chose AWS Trainium2 due to its performance, which let Decart achieve the low latency required by real-time video models. Lucy has a time-to-first-frame of 40ms, meaning that it begins generating video almost instantly after prompt. By streamlining video processing on Trainium, Lucy can also match the quality of much slower, more established video models like OpenAI’s Sora 2 and Google’s Veo-3, with Decart generating output at up to 30 fps. Decart believes Lucy will improve. As part of its agreement with AWS, the company has obtained early access to the newly announced Trainium3 processor, capable of outputs of up to 100 fps and lower latency.
Comparison with Nvidia
Nvidia might not be too worried about custom AI processors. The AI chip giant is reported to be designing its own ASIC chips to rival cloud competitors’. Moreover, ASICs aren’t going to replace GPUs completely, as each chip has its own strengths. The flexibility of GPUs means they remain the only real option for general-purpose models like GPT-5 and Gemini 3, and are still dominant in AI training. However, many AI applications have stable processing requirements, meaning they’re particularly suited to running on ASICs.
Conclusion
The rise of custom AI processors is expected to have a profound impact on the industry. By pushing chip design towards greater customization and enhancing the performance of specialized applications, they’re setting the stage for a new wave of AI innovation, with real-time video at the forefront.
FAQs
- What is AWS Trainium?
AWS Trainium is a custom AI accelerator designed by Amazon Web Services to support AI workloads. - What is Decart and how does it use AWS Trainium?
Decart is an AI video startup that uses AWS Trainium to support real-time video generation. - What is the advantage of using ASICs over GPUs?
ASICs are engineered specifically to handle one kind of application and do so more efficiently than general-purpose processors, making them suitable for applications with stable processing requirements. - Will ASICs replace GPUs completely?
No, ASICs aren’t going to replace GPUs completely, as each chip has its own strengths and GPUs remain the only real option for general-purpose models.
