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Right now, when you send a query to an LLM, it gets decrypted on the server. The LLM sees your data in plain text. Prof. Ajay Joshi (BU, CipherSonic AI ) on fully homomorphic encryption, which may be key for the future of AI privacy: how we can compute...

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Cerebras

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Fully homomorphic encryption was invented in the 1980s. Why wasn't it adopted sooner? A 100,000x slowdown, driven by memory boundedness. Ajay Joshi from CipherSonic AI explains how his team got it down to less than 2x. (if this pattern sounds familar... LLM inference is memory-bound too. It's why wafer-scale exists.)
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Fully homomorphic encryption was invented in the 1980s. Why wasn't it adopted sooner? A 100,000x slowdown, driven by memory boundedness. Ajay Joshi from CipherSonic AI explains how his team got it down to less than 2x. (if this pattern sounds familar... LLM inference is memory-bound too. It's why wafer-scale exists.)

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Yes, your data is encrypted in transit and at rest. But nobody talks about this. It still gets decrypted server-side, actually, to process it, even with all the safeguards. FHE lets you compute on encrypted data without ever decrypting it. Wild. Is it 1000x slower rn? Yeah, Will it work for everything? Maybe not, but for medical records, financial data, proprietary code? This is the future. Explained! Enjoy.
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