Lemur Labs

Adoption + Clarity = Turning protocol complexity into user conviction via research-grade education and launch-ready comms. DMs welcome.

[Lemur Labs @lemur_labs]

Are ChatGPT, Perplexity, and Gemini recommending you or the competition?
Our AI SEO shows you how you stack up against your top 3 competitors. If they're showing up and you're not, we can change that.

Google/Meta ads will drain your budget to little avail, because your target audience is asking AI for solutions, not search engines.

Comment "interested" below, and we'll get the ball rolling for you.

[Hellas @hellasdotai]

CatGrad is built around a simple idea.
A model should not be a black box where users hope the provider ran it correctly.

It should be fully specified, from the high-level model structure down to the exact computation.
That is how AI inference becomes verifiable.

[Lemur Labs @lemur_labs]

Ever asked an AI the same question twice and gotten two different answers?

Hellas breaks down why that happens, and what it means for anyone building on top of these systems.

Take a read if you're curious...

[Hellas @hellasdotai]

https://t.co/khZCpSsQvi

[Lemur Labs @lemur_labs]

PwC France just signed an alliance with Manako to distribute Score (SN44) to enterprise clients in retail, manufacturing, logistics, and energy. First Bittensor subnet to crack a Big Four, and they put Bittensor in the title of the press release.

The reason it works isn't a frontier LLM with a nicer skin bolted on top, it's that open weights, permissionless access, and a customizable harness let clients orchestrate around their own data and ground truth.

That's where enterprise value actually sits, not in renting a black box from a frontier lab. DeAI is how AI becomes a commodity you can shape, not a service you subscribe to.

[Score - Subnet 44 @webuildscore]

https://t.co/oKO9Wvrr41

[SwapRoyale @SwapRoyale]

We're live with @JeffExtor, @bigdsenpai and @mbyayyy from our team!

Pop in and check us out - we're talking trading, markets, the modern crypto landscape, and how SwapRoyale is changing the game of trading competitions

https://t.co/POdhgj2BXD

[Lemur Labs @lemur_labs]

Why risk trading your salary when we have continued uncertainty with the #IranWar‌ ?

Discovered @SwapRoyale during #ETHCC & Fantasy Trading is an awesome way to hone your trading skills

See you there in an hour guys

[SwapRoyale @SwapRoyale]

Going Live Today 2pm EST

Join our new weekly podcast where we dive into everything SwapRoyale, where we'll be celebrating our users wins, trading strategies, how to enjoy the app to the max, and what's upcoming.

It's an ALL-IQ discussion, so everyone's welcome. Click here to join when we go live

https://t.co/aHzCbYv6sR

[Lemur Labs @lemur_labs]

Props to @hellasdotai for the opposite play, pooling idle GPUs into open compute markets so the best AI tools don't stay locked behind enterprise contracts and invite lists.

[RAFA Finance @RAFA_AI]

Missed last week? 😱

Catch up below, then tap in live this Thursday for real time insights and more 🧠

[Lemur Labs @lemur_labs]

The agentic age is here. Agents are already fine-tuning their own open-weight models to trade, forecast, and find inefficiencies that humans miss. Each of those tasks burns inference.

And the agents can't sign up for AWS or negotiate an enterprise contract, they need compute they can access and pay for on their own. Only a handful of projects are building infrastructure that actually works for that. Hellas is one of the few.

[Hellas @hellasdotai]

If agents are going to scale they need.

1. Liquid compute market
2. Verifiable inference

Without it running your open-claw or Claude agents will remain expensive at scale and you won’t know what’s happening under the hood.

The compute market has remained illiquid due to external hardware providers being unable to prove that user workloads ran correctly.

No one has fully provided an answer to this problem. At Hellas we’re building a solution take a look at our articles to learn more.

[Lemur Labs @lemur_labs]

@ClawIntelli Been waiting for this. Solid 👍

[Lemur Labs @lemur_labs]

@immunefi Nice! Congrats team✊

[Lemur Labs @lemur_labs]

@ZanaVentures @konnex_world Congrats! You’re nailing it.

Watching closely 👀

[Lemur Labs @lemur_labs]

An agent can't call AWS support and ask for a quota increase. It can't fill in a billing form or negotiate an enterprise contract.

If agents are going to operate autonomously they need compute they can find, pay for, and verify without a human setting it up for them.

[Hellas @hellasdotai]

In the same way that agents need permissionless payments, they will also need permissionless compute.

[Lemur Labs @lemur_labs]

@anytwocardzz Projects do not fail because they lack communication or
technology. They fail because their positioning is unclear and their value is not understood.

That's why we built Lemur Labs.

[Lemur Labs @lemur_labs]

Hellas is a fascinating company to look into for the AI crowd.

[Hellas @hellasdotai]

Hellas is a verifiable compute network where providers post collateral before every job, and the computation is compiled into a deterministic graph that both sides agree on upfront.

If the provider deviates from that graph, the client can prove it on-chain and take their stake. Most jobs settle without dispute because the math makes cheating a losing trade before it even starts.

[CATBAT @catbatcoin]

🎙 Catbat Connect Session: Business Development in ever-changing Crypto Landscape - @lemur_labs
@RBoccius
https://t.co/iXqew2JMZu

[Lemur Labs @lemur_labs]

It’s clearer by the day that crypto-based tech will play an important role in AI. This public acknowledgment from the All-in podcast and Jensen is the beginning of its wide acknowledgment.

Coordinated decentralised networks will help train AI models, rent GPUs in a liquid market, and run verifiable inference jobs cheaply. Blockchain nascent technologies are uniquely equipped to tackle these hard coordination and trust problems.

It’s been incredible to work for @hellasdotai as this new frontier of decentralised AI takes form.

[templar @tplr_ai]

On the @theallinpod this week, @chamath asked @nvidia CEO Jensen Huang about decentralized AI training, calling our Covenant-72B run "a pretty crazy technical accomplishment."

One correction: it's 72 billion parameters, not four. Trained permissionlessly across 70+ contributors on commodity internet. The largest model ever pre-trained on fully decentralized infrastructure.

Jensen's answer is worth hearing too.

[Hellas @hellasdotai]

https://t.co/AjDQA8bLaE

[Lemur Labs @lemur_labs]

The agentic world needs to solve some real problems before running armies of agents is affordable.

[Hellas @hellasdotai]

If agents are going to scale they need.

1. Liquid compute market
2. Verifiable inference

Without it running your open-claw or Claude agents will remain expensive at scale and you won’t know what’s happening under the hood.

The compute market has remained illiquid due to external hardware providers being unable to prove that user workloads ran correctly.

No one has fully provided an answer to this problem. At Hellas we’re building a solution take a look at our articles to learn more.

[Lemur Labs @lemur_labs]

AI has many pain points for the user currently, and how AI models reach their answers/results is a huge problem.

DID YOU KNOW? #Gemini 3 Pro has up to 88% Hallucination Rate when it doesn't know the answer.

You can't use that for research or fact-checking, and this is exactly why we're working with @hellasdotai

[Hellas @hellasdotai]

https://t.co/LhYRUVERPE