The computing problem of our time: Moving data

• Celestial AI's Photonic Fabric technology can deliver up to 700 terabits per second of bidirectional bandwidth per chip package.
• The start-up has recently raised $100 million in funding.

The size of AI models that implement machine learning continue to grow staggeringly fast.

Such AI models are used for computer vision, large language models such as ChatGPT, and recommendation systems that rank items such as search results and music playlists.

David Lazovsky

The workhorse silicon used to build such AI models are graphics processing units (GPUs). GPU processing performance and their memory size may be advancing impressively but AI model growth is far outpacing their processing and input-output [I/O] capabilities.

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Habana Labs unveils its AI processor plans

Start-up Habana Labs has developed a chip architecture that promises to speed up the execution of machine-learning tasks. 

The Israeli start-up came out of secrecy in September to announce two artificial intelligence (AI) processor chips. One, dubbed Gaudi, is designed to tackle the training of large-scale neural networks. The chip will be available in 2019. 

Eitan MedinaGoya, the start-up’s second device, is an inference processor that implements the optimised, trained neural network.

The Goya chip is already in prospective customers’ labs undergoing evaluation, says Eitan Medina, Habana’s chief business officer.

Habana has just raised $75 million in a second round of funding, led by Intel Capital. Overall, the start-up has raised a total of $120 million in funding. 

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