New GPU virtualization solution raises $2 million in funding. How will this technology change on-chain computing?

Question

【Crypto World】A project focused on next-generation GPU and AI computing infrastructure, AGGX (Adaptive GPU Mesh Sharding), recently announced good news — it has raised a total of $2 million in its latest round of strategic financing.

This round of funding features a strong lineup, including Ternary LEC Fund, EF Investment & Partners, Spacebar Venture, and two other strategic investors. In simple terms, a group of institutions optimistic about GPU computing have all placed their bets.

How is AGGX’s core technology? The team consists of PhDs and university professors in the US AI field. Their GPU sharding solution is quite interesting — it can virtualize a single GPU into more than 30 on-chain nodes. It sounds simple, but in reality, it addresses a significant challenge.

For the ecosystems of Web2 and Web3, GPU-intensive workloads have always been a bottleneck. AGGX’s solution offers scalable, low-latency computing services while significantly reducing costs. In other words, it allows more tasks to run with fewer hardware resources. This directly benefits on-chain applications, AI inference, data processing, and related scenarios.

PermabullPete · Accepted Answer

GPU sharded into more than 30 nodes? If it can truly run stably, the on-chain computation costs will be cut in half.

Wait, is the funding scale a bit small? Is 2 million really enough to benchmark infrastructure projects?

MetaMaximalist · Answer

gpu virtualization hitting different ngl... but 30 nodes from one chip? that's the kind of infrastructure play most people sleep on until it's already priced in. respect the team composition tho, actual phds not just twitter engineers lmao

BanklessAtHeart · Answer

2 million USD is not a small amount, but can this GPU virtualization really break through? It still seems to depend on actual implementation capability.

A bunch of major institutions have entered, indicating that the track indeed has potential, but whether AGGX's solution can withstand high concurrency is the key.

Splitting one GPU into more than 30 nodes sounds impressive, but I'm worried it might just be on paper, with actual performance falling short.

Fast financing for this kind of infrastructure project is a good thing, but the real focus should be on when the mainnet launches and truly solves Gas or computational bottlenecks.

gas_fee_trauma · Answer

2 million dollars in funding, turning GPU sharding into 30 nodes? Sounds impressive, but actual implementation is the real key.

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Both AI and GPU—everyone's playing this combo now.

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It's funny—virtualizing one GPU into over 30 nodes, how efficient can that really be...

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Ternary and EF have both bet on it? That definitely means it's not just hype.

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On-chain computing bottlenecks have always been an issue; it's good if someone actually solves it.

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The endorsement from the American PhD team is decent, but the project still depends on actual performance benchmarks.

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I've heard similar things about GPU virtualization before, but there hasn't been much news afterward.

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If Web3 can really make use of this, can gas fees be reduced?

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Honestly, this funding amount seems a bit low. Is the competition for Web3 GPU solutions really that fierce?

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30 on-chain nodes—how will the computing power be allocated? Will it be balanced?

CodeSmellHunter · Answer

2 million in funding is indeed substantial, but can GPU virtualization really be implemented? I feel like there are too many projects that are just theoretical.

Splitting one GPU into over 30 nodes reduces costs, but can the performance keep up? It's a bit hard to imagine.

This is a good direction; it just depends on who can truly lower the computing costs. For now, it's still in the early stages.

Haha, institutions are starting to bet on new tracks again. GPU computing is bound to become popular sooner or later.

Sharding has been around in Web3 for a while; it seems like GPU virtualization might also be a trap.

I'm more concerned about whether there will be real application scenarios in the future. Funding is just the beginning, everyone.

RatioHunter · Answer

2 million in funding isn't a lot, and with how competitive this field is, being able to raise money shows there's definitely potential.

GPU virtualization into over 30 nodes? If it can run stably, on-chain computing costs could be cut in half.

But it depends on the actual deployment results; a beautiful paper and a usable product are two different things...

The funding team sounds decent, but where are the ecological applications?

Another team of PhDs and professors—can we stop just talking on paper?

Infrastructure projects like this require a long-term view; short-term hype isn't very valuable.

New GPU virtualization solution raises $2 million in funding. How will this technology change on-chain computing?

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