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Last week at the Amazon Web Services annual re:Invent conference, the company announced the rollout of two new custom computing chips—and, according to AWS, they’re cheaper, better, faster, stronger.
Quick recap: AWS, Amazon’s hyper-successful cloud computing unit—responsible for two-thirds of the company’s operating income last year—spends the big bucks on data-center chips capable of handling all sorts of machine learning. Then, it rents out that compute to its clients.
- AWS has been working on bringing that chip manufacturing “in-house” since 2015, when it purchased an Israeli semiconductor startup for a rumored ~$350 million. On Tuesday, it announced the chip’s newest generation.
The new goods
First up is the Gravitron 3, an Arm–based chip that AWS says is 25% faster for general workloads than the previous version, and 3x faster for typical machine learning tasks—plus, the company claims it saves 60% of the energy. Its chief competitors: chips from Intel and AMD.
Then there’s Trn1, a new AWS “instance”—i.e., a virtual server that allows people to connect and run applications using Amazon’s cloud infrastructure. With bandwidth up to 800 gigabytes/second, according to Amazon, it’s 2x faster than what’s currently available.
- That’s partly because Trn1 is powered by Trainium, the buzzy chip AWS debuted last year to—as its name suggests—supercharge the training of deep learning models.
- AWS says Trn1 is especially created for AI tasks like image recognition, forecasting, fraud detection, and natural language processing. And that it’ll train models for ~40% less $$ than Nvidia’s leading chip.
But, but, but: Despite the cost and performance comparisons AWS is floating, it still has to maintain a healthy working relationship with key competitors like Nvidia, which AWS is currently working with to bring Android game streaming to mobile devices.
So AWS is treading lightly: Execs told Reuters that the new chip rollouts are all in the name of healthy market competition and bringing performance costs down.