Undoubtedly, 2023 has been the year of generative AI, and Google is marking its end with even more AI developments. The company has announced the creation of its most powerful TPU (formally known as Tensor Processing Units) yet, Cloud TPU v5p, and an AI Hypercomputer from Google Cloud. “The growth in [generative] AI models — with a tenfold increase in parameters annually over the past five years — brings heightened requirements for training, tuning, and inference,” Amin Vahdat, Google’s Engineering Fellow and Vice President for the Machine Leaning, Systems, and Cloud AI team, said in a release.
The Cloud TPU v5p is an AI accelerator, training and serving models. Google designed Cloud TPUs to work with models that are large, have long training periods, are mostly made of matrix computations and have no custom operations inside its main training loop, such as TensorFlow or JAX. Each TPU v5p pod brings 8,960 chips when using Google’s highest-bandwidth inter-chip interconnect.
The Cloud TPU v5p follows previous iterations like the v5e and v4. According to Google, the TPU v5p has two times greater FLOPs and is four times more scalable when considering FLOPS per pod than the TPU v4. It can also train LLM models 2.8 times faster and embed dense models 1.9 times faster than the TPU v4. 
Then there’s the new AI Hypercomputer, which includes an integrated system with open software, performance-optimized hardware, machine learning frameworks, and flexible consumption models. The idea is that this amalgamation will improve productivity and efficiency compared to if each piece was looked at separately. The AI Hypercomputer’s performance-optimized hardware utilizes Google’s Jupiter data center network technology.
In a change of pace, Google provides open software to developers with “extensive support” for machine learning frameworks such as JAX, PyTorch and TensorFlow. This announcement comes on the heels of Meta and IBM’s launch of the AI Alliance, which prioritizes open sourcing (and Google is notably not involved in). The AI Hypercomputer also introduces two models, Flex Start Mode and Calendar Mode. 
Google shared the news alongside the introduction of Gemini, a new AI model that the company calls its “largest and most capable,” and its rollout to Bard and the Pixel 8 Pro. It will come in three sizes: Gemini Pro, Gemini Ultra and Gemini Nano. This article originally appeared on Engadget at https://www.engadget.com/google-announces-new-ai-processing-chips-and-a-cloud-hypercomputer-150031454.html?src=rss

Undoubtedly, 2023 has been the year of generative AI, and Google is marking its end with even more AI developments. The company has announced the creation of its most powerful TPU (formally known as Tensor Processing Units) yet, Cloud TPU v5p, and an AI Hypercomputer from Google Cloud. “The growth in [generative] AI models — with a tenfold increase in parameters annually over the past five years — brings heightened requirements for training, tuning, and inference,” Amin Vahdat, Google’s Engineering Fellow and Vice President for the Machine Leaning, Systems, and Cloud AI team, said in a release.

The Cloud TPU v5p is an AI accelerator, training and serving models. Google designed Cloud TPUs to work with models that are large, have long training periods, are mostly made of matrix computations and have no custom operations inside its main training loop, such as TensorFlow or JAX. Each TPU v5p pod brings 8,960 chips when using Google’s highest-bandwidth inter-chip interconnect.

The Cloud TPU v5p follows previous iterations like the v5e and v4. According to Google, the TPU v5p has two times greater FLOPs and is four times more scalable when considering FLOPS per pod than the TPU v4. It can also train LLM models 2.8 times faster and embed dense models 1.9 times faster than the TPU v4. 

Then there’s the new AI Hypercomputer, which includes an integrated system with open software, performance-optimized hardware, machine learning frameworks, and flexible consumption models. The idea is that this amalgamation will improve productivity and efficiency compared to if each piece was looked at separately. The AI Hypercomputer’s performance-optimized hardware utilizes Google’s Jupiter data center network technology.

In a change of pace, Google provides open software to developers with “extensive support” for machine learning frameworks such as JAX, PyTorch and TensorFlow. This announcement comes on the heels of Meta and IBM’s launch of the AI Alliance, which prioritizes open sourcing (and Google is notably not involved in). The AI Hypercomputer also introduces two models, Flex Start Mode and Calendar Mode. 

Google shared the news alongside the introduction of Gemini, a new AI model that the company calls its “largest and most capable,” and its rollout to Bard and the Pixel 8 Pro. It will come in three sizes: Gemini Pro, Gemini Ultra and Gemini Nano. 

This article originally appeared on Engadget at https://www.engadget.com/google-announces-new-ai-processing-chips-and-a-cloud-hypercomputer-150031454.html?src=rss …Read More

Leave a Reply