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The example is not ideal for showcasing a graph analytics database because they could have used a traditional relational database to answer the same query, Which of my contacts work at Google?
This will make it super easy for me to add LLM functionality to existing webxr spaces, and I'm excited to see how an intelligent avatar or convo between them will play out. This is, very likely, the thing that will make this possible :)
If anyone wants to collab, or contribute in some way, I'm open to ideas and support. Search for 'exeud' to find more info
Earlier quoted context omitted.
This is really cool, but I'm super anxious about entering my personal data, especially LinkedIn connections. Is there some other demo you could do with public graph data? It'd be just as cool of a demo, but with less fear of information misuse. I'm even more anxious about leaking information about my professional connections as I am leaking my own data.
Your concern makes sense, but in the demo we show, all your private data AND the graph database AND the LLM (basically, everything) is confined to your client session in the browser, and no data actually ever leaves your machine. That's the whole point of Wasm! The graph that you build is more for your own exploration and not for sharing with the outside world.
imo, privacy shouldn't be the driver but the kicker, because it's so inflammatory.
I absolutely love this. I make VR experiences that run on the ICP, which delivers wasm modules as smart contracts - I've been waiting for a combo of node-friendly, wasm deployable tools and webLLM. The ICP essentially facilitates self-hosting of data and provides consensus protocols for secure messaging and transactions. This will make it super easy for me to add LLM functionality to existing webxr spaces, and I'm ex…
I think I like the idea but I don't think I fully understand what it is that you're doing :) But I love everything VR.
I absolutely love this. I make VR experiences that run on the ICP, which delivers wasm modules as smart contracts - I've been waiting for a combo of node-friendly, wasm deployable tools and webLLM. The ICP essentially facilitates self-hosting of data and provides consensus protocols for secure messaging and transactions. This will make it super easy for me to add LLM functionality to existing webxr spaces, and I'm ex…
Why the Blockchain there? I don't really see the value. But maybe I misunderstand. It's just that I tend to be pretty dismissive of products mentioning blockchain. Mostly from the time when this tech was severely overhyped. Like Metaverse after it and now of course AI. I do know there's some usecases for it, I just wonder what they are and why you chose it. I think I like the idea but I don't think I fully understand…
Blockchain has taken a weird path. It started with Bitcoin offering something genuinely new - a Byzantine fault-tolerant mechanism for decentralized value exchange without trusted intermediaries. But the industry has drifted toward "web3" hype where the technology often isn't necessary.
Companies pick tech stacks for all sorts of reasons beyond technical merit - vendor relationships, development velocity, legacy system compatibility, and UX considerations all factor into these decisions.
Truth is, most blockchain companies today are solving problems that could be handled just fine with traditional databases and APIs. The industry is shifting toward abstraction layers that hide the consensus mechanisms anyway, focusing on user experience instead.
The project mentioned probably doesn't actually need a blockchain backend for what it's doing, except maybe for tradable collectibles on an ERC standard.
Earlier quoted context omitted.
Your concern makes sense, but in the demo we show, all your private data AND the graph database AND the LLM (basically, everything) is confined to your client session in the browser, and no data actually ever leaves your machine. That's the whole point of Wasm! The graph that you build is more for your own exploration and not for sharing with the outside world.
Still, using non-personal example would mean the user wouldn't have to consider whether to trust you on that point (or do the analysis), and would make the technology demo friction-free. imo, privacy shouldn't be the driver but the kicker, because it's so inflammatory.
Could someone please explain in-browser inference to me? So in the context of OpenAI usage (WebLLM github), this means I will send binary to OpenAI instead of text? And it will lower the cost and run faster?
> Full OpenAI Compatibility
> WebLLM is designed to be fully compatible with OpenAI API.
It means that WebLLM exposes an API that is identical in behaviour with the OpenAI one, so any tools that build against that API could also build against WebLLM and it will still work.
WebLLM by the looks of it runs the inference purely in the browser. None of your data leaves your browser.
WebLLM does need to get a model from somewhere, with the demo linked here getting Llama3.1 Instruct 8B model{1}.
1: https://huggingface.co/mlc-ai/Llama-3.1-8B-Instruct-q4f32_1-...