1. De-identify your data before you send it to AI. 2. Run AI in an enclave with no external network. The idea of AI in an enclave is that "no-one is around to watch it"; No one CAN watch it. + w/ attestation you can cryptographically verify that code hasn't been modified.

👇🏼 great read on how @capeprivacy lets folks use LLMs while preserving privacy "The Cape API runs entirely within a secure enclave, so no human can see what’s being processed (including the humans at Cape and AWS)"

This was a very fun chat with Gavin Uhma CTO of @capeprivacy on security and privacy in LLMs . Very interesting insights topic thaat should be top of mind in the foundation model space open.substack.com/pub/thesequenc… #TheSequence #LLMs #MachineLearning #GenerativeAI

New pricing for @capeprivacy powered by Tier.run! CapeChat is free. CapeChat+ is $20/month. The Cape API is entirely usage based, priced per token. capeprivacy.com/pricing/

The first fully confidential LLM!!

Looking to use an LLM but concerned about the sensitivity of your data? The Cape API keeps your data private while using the LLM of your choice. Here's how you can get started:

Nobody can compete with OpenAI. If you want to integrate a Large Language Model with your application, OpenAI wins every day. But the problem is that companies can't justify using OpenAI's API with their customer's private information. Here is a solution: The @capeprivacy

“Nobody can compete with Open AI” 👀 Very bold statement at this stage. As for @capeprivacy - great product and fantastic work here. Forward outlook will be that many organizations in Healthcare, Finance and Insurance will want to implement. 💡

Imagine if as you were typing a reply X would show you similar replies. It might lead to deeper discussions on popular threads rather than people making the same gut reaction over and over.

Wondering what eBPF is, why Next.js is all over Twitter, how Intel's Secure Enclaves or AWS Nitro is used? SSB Pod #20 is a brain trust chat covering new tech w/ Alex Mackenzie & Ian Livingstone Apple: podcasts.apple.com/us/podcast/20-… Spotify: open.spotify.com/episode/7xskFT…

What data is your organization dropping into LLMs? Many teams just want to know this. Is it email addresses, SSNs, passwords, health numbers, etc. Our new dashboard provides a simple way to measure this. And of course it only collects the classifications not the actual data.

I hear a lot of folks in our AI community complain about openAI -- they don't publish, don't release models, maximum-for-profit, etc., so they are more like closedAI rather than openAI. This is true, but you have to give it to those guys -- they showed the true potential of LLMs

We need your help! Many of you might have heard of the 6.8 magnitude earthquake in Morocco last week that killed 2,900 people and left thousands more injured and hundreds of thousands unsheltered with their lives in ruin. While this likely feels like it is a world away, for one

These are good predictions. I'd add fine tuning for gpt-3.5 16k as well. Although that's pretty easy because they said it's coming in the fall with gpt-4 fine tuning. I'd love to see them move from 30 day to zero data retention, but that requires rethinking moderation.

With Cape’s Knowledge Retrieval #ai capabilities, get the most personalized user experience that integrates to all of your #datasources and use #llms to securely search through troves of disparate enterprise documents and sites to accelerate and optimize your business.📈

We are #hiring! If you are an experienced technical engineer looking for a challenging role, working with a great #team and the latest #ai technologies, please take a look at our open positions! lnkd.in/eHTznXUX

With Cape’s #ai, one of our #financialservices #banking customers integrated internal client data to leverage private #LLMs to implement 1:1 personalized automated email #marketing campaigns, with an estimated time savings down from 27 days to 5 mins per campaign!

We need a new Voyager spacecraft that has just a GPT and a keyboard for aliens to ask any question about us.

Fully Homomorphic Encryption (FHE) ensures data confidentiality, but not integrity: Clients have no way to verify whether the results are correctly computed. While Zero-Knowledge Proofs can solve this problem, they come at a high cost—up to 10,000x more expensive than FHE.

🤖 As we @versiononevc spend time & invest in robotics, I’m sharing how our thinking has evolved since our last update wrt to: 1) Commoditization of software & hardware 2) Task-specific robots vs. generalized humanoids 3) Understanding the need for automation 4) Business model