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I don’t know what dialect this is written in, but can anybody translate it to engineer? What type of problem are they trying to solve and how are they going abo

I don’t know what dialect this is written in, but can anybody translate it to engineer? What type of problem are they trying to solve and how are they going about it? (Is this DRM for AIs?)

jasonsb 2y ago
Had to use bullshitremover dot com for this one. This is the translation: > Blah blah, AI is the future, trust it, crypto, governance, auditing, safer AI.
- lawlessone 2y ago
  yeah is that what "Hedera Consensus Platform" is? Wonder what happens if that fails.
  - ramoz 2y ago
    You lose some benefits around decentralized trust & temporal anchoring. But not all. DLT are established in software supply chains and are being adapted to AI supply chain (see below). It's not indicative of a "crypto" play. "Sigstore’s public signing ledgers form the foundation of trust for SLSA provenance" - https://storage.googleapis.com/gweb-research2023-media/pubtools/pdf/b2573d2ddfbfc551d216db1ac4668097f0a0f3e1.pdf https://storage.googleapis.com/gweb-research2023-media/pubto... https://docs.sigstore.dev/logging/overview/ https://docs.sigstore.dev/logging/overview/ https://github.com/sigstore/rekor https://github.com/sigstore/rekor
    - mistrial9 2y ago
      software developer's rule #32 - "you are not Google"
- aftbit 2y ago
  I got: > Verifiable Compute is a new AI framework that uses hardware-based crypto to verify AI models and data. It lets companies audit and control their AI systems to make them more secure and compliant. Intel and Nvidia are supporting it.
ben_w 2y ago
Allow me: "Are you running the AI that you thought you were running, or a rip-off clone that will sneakily insert adverts for Acme, your one-stop-shop for roadrunner-related explosives, traps, and fake walls, into 1% of outputs? Here's how you can be sure."
- ramoz 2y ago
  Allow me to help extract the general value: (your case is not the direct point, but the measures are a part of strengthening the supply chain[1]. Other application include strengthening privacy [2]) Verifiability measures are designed to transform privacy and security promises from mere assurances into independently checkable, technical guarantees. _Generally achieving_: verification of claims (from governance/regulation, to model provenance), cryptographic attestation ensuring code integrity, enforceable transparency through append-only logs and tooling, no blind trust-but verifiable trust, a structured environment for ongoing scrutiny and improvement. [1] https://www.rand.org/pubs/research_reports/RRA2849-1.html https://www.rand.org/pubs/research_reports/RRA2849-1.html [2] https://security.apple.com/blog/private-cloud-compute/ https://security.apple.com/blog/private-cloud-compute/
  - fc417fc802 2y ago
    [dead]
drak0n1c 2y ago
People are starting to worry about generative AI/LLM training data - copyright, bias, knowledge gaps, bad/outdated info. They are also worried about the black box of hardcoded "alignment" layers on top - which can and has introduced similar issues. Cryptographic proof of a model's training data provenance and its compute would be reassuring to large enterprises, governments, and conscientious users who are hesitant to embrace AI. You don't want to accidentally use part of a biased social media chat LLM to summarize legislation or estimate results of a business plan.
th0ma5 2y ago
Some have speculated they want to command regulations so complex that only they can adhere to them.

I don’t know what dialect this is written in, but can anybody translate it to engineer? What type of problem are they trying to solve and how are they going about it? (Is this DRM for AIs?)

jasonsb 2y ago

Had to use bullshitremover dot com for this one. This is the translation: > Blah blah, AI is the future, trust it, crypto, governance, auditing, safer AI.

lawlessone 2y ago
yeah is that what "Hedera Consensus Platform" is? Wonder what happens if that fails.
- ramoz 2y ago
  You lose some benefits around decentralized trust & temporal anchoring. But not all. DLT are established in software supply chains and are being adapted to AI supply chain (see below). It's not indicative of a "crypto" play. "Sigstore’s public signing ledgers form the foundation of trust for SLSA provenance" - https://storage.googleapis.com/gweb-research2023-media/pubtools/pdf/b2573d2ddfbfc551d216db1ac4668097f0a0f3e1.pdf https://storage.googleapis.com/gweb-research2023-media/pubto... https://docs.sigstore.dev/logging/overview/ https://docs.sigstore.dev/logging/overview/ https://github.com/sigstore/rekor https://github.com/sigstore/rekor
  - mistrial9 2y ago
    software developer's rule #32 - "you are not Google"
aftbit 2y ago
I got: > Verifiable Compute is a new AI framework that uses hardware-based crypto to verify AI models and data. It lets companies audit and control their AI systems to make them more secure and compliant. Intel and Nvidia are supporting it.

ben_w 2y ago

Allow me: "Are you running the AI that you thought you were running, or a rip-off clone that will sneakily insert adverts for Acme, your one-stop-shop for roadrunner-related explosives, traps, and fake walls, into 1% of outputs? Here's how you can be sure."

ramoz 2y ago
Allow me to help extract the general value: (your case is not the direct point, but the measures are a part of strengthening the supply chain[1]. Other application include strengthening privacy [2]) Verifiability measures are designed to transform privacy and security promises from mere assurances into independently checkable, technical guarantees. _Generally achieving_: verification of claims (from governance/regulation, to model provenance), cryptographic attestation ensuring code integrity, enforceable transparency through append-only logs and tooling, no blind trust-but verifiable trust, a structured environment for ongoing scrutiny and improvement. [1] https://www.rand.org/pubs/research_reports/RRA2849-1.html https://www.rand.org/pubs/research_reports/RRA2849-1.html [2] https://security.apple.com/blog/private-cloud-compute/ https://security.apple.com/blog/private-cloud-compute/
- fc417fc802 2y ago
  [dead]

drak0n1c 2y ago

People are starting to worry about generative AI/LLM training data - copyright, bias, knowledge gaps, bad/outdated info. They are also worried about the black box of hardcoded "alignment" layers on top - which can and has introduced similar issues. Cryptographic proof of a model's training data provenance and its compute would be reassuring to large enterprises, governments, and conscientious users who are hesitant to embrace AI. You don't want to accidentally use part of a biased social media chat LLM to summarize legislation or estimate results of a business plan.

th0ma5 2y ago

Some have speculated they want to command regulations so complex that only they can adhere to them.