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We expanded the NVIDIA Agent Toolkit to help developers build agents that use company data to answer questions and make predictions, with controls over what agents can access and do. Watch how Lila Sciences , Siemens and Dassault Systèmes are using AI agents to design potential therapies, plan factory...

18,449 Aufrufe • vor 3 Tagen •via X (Twitter)

16 Kommentare

Profilbild von Ted | unfair.so
Ted | unfair.sovor 2 Tagen

@LilaSciences @Siemens @Dassault3DS agents anstheyring with company data also means anstheyring about competitors. they track how they rank brands:

Profilbild von Harley Lewis Foote
Harley Lewis Footevor 2 Tagen

@LilaSciences @Siemens @Dassault3DS Controls over what they can access is the main thing for me. Agent surfacing company data to the wrong person is every company's nightmare

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Elara AIvor 2 Tagen

@LilaSciences @Siemens @Dassault3DS NVIDIA Agent Toolkit builds enterprise agents

Profilbild von Mark
Markvor 3 Tagen

@LilaSciences @Siemens @Dassault3DS Siemens letting agents plan factory production now, my spreadsheet feels very threatened

Profilbild von Polash Khan
Polash Khanvor 2 Tagen

@LilaSciences @Siemens @Dassault3DS That's awesome! It's great to see how these companies are using AI to push boundaries in design.

Profilbild von Raúl Nogales 🇪🇸🇺🇸
Raúl Nogales 🇪🇸🇺🇸vor 2 Tagen

@LilaSciences @Siemens @Dassault3DS The dividing line will be consequence. Reading company data to answer a question is one risk class, while acting on a prediction in a factory or a lab is another. Approval thresholds should rise with that consequence, not stay flat across tools.

Profilbild von Dharmendra Valiya
Dharmendra Valiyavor 2 Tagen

@LilaSciences @Siemens @Dassault3DS the access controls are the part I'd want to see more of. can you scope an agent to read only on some data and get a log of every query it ran? that's usually what security teams ask first

Profilbild von Aapakari
Aapakarivor 2 Tagen

@LilaSciences @Siemens @Dassault3DS The access controls matter more than another flashy demo. 🔒

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The SI Maximalistvor 2 Tagen

@LilaSciences @Siemens @Dassault3DS I’m glad you’re giving developers control over what agents can read and what they can do 🩷

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BuilderCulturevor 2 Tagen

@LilaSciences @Siemens @Dassault3DS For the access controls, can you publish a test where an agent finds the right answer in a document the requesting user cannot read? The useful score is how often it refuses that answer, not just how often it retrieves the right one.

Profilbild von Kyssta
Kysstavor 2 Tagen

@LilaSciences @Siemens @Dassault3DS every enterprise agent demo: 'it answers questions from your company data,' then it stops exactly where the data governance question starts.

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Max Petrusenkovor 2 Tagen

@LilaSciences @Siemens @Dassault3DS scoped access holds until a narrow-scope worker writes a note that a wider-scope worker reads and obeys

Profilbild von Van0SS
Van0SSvor 2 Tagen

@LilaSciences @Siemens @Dassault3DS can u trace each prediction back to the table it used??

Profilbild von Vision
Visionvor 2 Tagen

@LilaSciences @Siemens @Dassault3DS The access controls are the real product here, the demos are just the trailer

Profilbild von Rock Lambros
Rock Lambrosvor 2 Tagen

@LilaSciences @Siemens @Dassault3DS I'd want both halves. Build-time least privilege limits what the agent can reach, and a check before each tool call limits what it does there. OWASP's Agent Control Standard puts that check in a separate Guardian:

Profilbild von Abenezer Nuro
Abenezer Nurovor 2 Tagen

@LilaSciences @Siemens @Dassault3DS Access controls are the real unlock here. Building the agent is the easy week. Getting approval for what data it can touch is the hard quarter.

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