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As AI models grow exponentially, traditional computing machines can no longer keep up

Ocean Nodes enable distributed computing, harnessing a global network of distributed, high-quality compute to meet the demands of modern AI training

Explore more:

https://docs.oceanprotocol.com/developers/ocean-node

https://x.com/oceanprotocol/status/1926946858460422373?t=6OVn_JIqniKeovoOyjIing&s=19
CPUs and GPUs have powered decades of computing from desktop applications to large-scale enterprise systems

CPUs are optimised for sequential tasks, ideal for logic-heavy operations and operating systems. GPUs, with thousands of smaller cores, are better at handling parallel operations like rendering and machine learning inference

However, both have limits

Modern AI workloads require massive parallelism and scalability that centralised infrastructure often struggles to provide due to cost, energy demands, and hardware limitations

This is where distributed computing enters

By aggregating underutilised compute, from gaming GPUs to idle enterprise resources, distributed systems offer a scalable, cost-effective, and energy-aware alternative to traditional cloud computing

It’s not just more compute, it’s smarter, decentralised, and future-proof

https://x.com/oceanprotocol/status/1927013668971069924?s=46&t=sfyIS0XeZHZd-w68hBLkvw
How Ocean Tech can act as the Data Layer for Open-Source LLMs

LLMs need vast, diverse, high-quality datasets for:

1. Pretraining - large-scale text corpora
2. Finetuning - task or domain-specific data
3. Evaluation & Alignment - human feedback, bias mitigation, safety tuning

Yet open-source LLMs often struggle with access, quality, compliance, and incentives

Ocean Protocol solves this by transforming data into programmable, ownable, and tradable assets.

LLM Lifecycle with Ocean:

1. Data Tokenisation - Researchers, DAOs, and institutions publish high-quality datasets (e.g. biomedical texts, code, low-resource languages) using Ocean CLI. Each dataset is wrapped as a Data NFT with ERC20 datatokens and registered on-chain.
2. Dataset Discovery - LLM teams can query Ocean for datasets by domain or metadata.
3. On-Chain Access - Access is granted via datatokens, enabling transparent and permissioned data use.
4. Compute-to-Data (C2D) - Instead of moving data, Ocean sends training jobs to where data resides. Privacy and compliance are preserved.
5. Monetisation - Each training run can trigger payments, rewarding data providers with usage-based royalties.

Own your data. Train with Ocean

https://x.com/oceanprotocol/status/1927318635153920162?s=46&t=sfyIS0XeZHZd-w68hBLkvw
Modern AI is starving for compute

Training and inference need massive GPU power, but most of it is locked behind hyperscalers like AWS or Google Cloud

This creates serious problems:
1. Startups & researchers get priced out
2. Surveillance & compliance risks rise
3. Local innovation gets crushed under central control

Ocean Nodes offer an alternative, a decentralised, permissionless compute layer where:

- Anyone can contribute idle GPUs/CPUs to the network
- Developers can run containerised AI workloads (training, inference, validation)
-All jobs are cryptographically verified with zero-trust security

This turns DePIN from just hardware into intelligence

Learn how Ocean Nodes are becoming the compute layer for sovereign AI:
https://docs.oceanprotocol.com/developers/ocean-node

https://x.com/oceanprotocol/status/1927705239001468982
What if you could license your dataset in minutes, not months?

With Ocean CLI:

1. Upload your dataset
2. Tokenise it with a Data NFT
3. Sell access with Datatokens

Smart contracts do the lawyering. You focus on research

https://docs.oceanprotocol.com/developers/contracts/data-nfts

https://x.com/oceanprotocol/status/1928419521078927734
What if your dApp could:
- Run machine learning models without exposing data
- Seamlessly offload compute to a decentralised network
- Reward both developers and node operators in one integrated flow?

Start here: https://docs.oceanprotocol.com/developers/ocean-node

https://x.com/oceanprotocol/status/1929502145352532328
AI engineers, we get it, accessing high-quality data while staying compliant can be a real challenge

That’s why we built the Ocean VS Code extension

It lets you publish datasets, manage datatokens, and run compute-to-data jobs all from the comfort of your editor

No need to jump between tools. Just open VS @code and start building privacy-preserving, decentralised AI pipelines with full traceability baked in

Explore what’s possible:

https://docs.oceanprotocol.com/developers/vscode

https://x.com/oceanprotocol/status/1930196077090570550?t=3SrW8yq_KLEltlr89N1zWg&s=19
Put your AI to work, and make more $!

Our ASI Predictoor program gives crypto rewards to AI bots that accurately predict crypto price directions: UP / DOWN every 5m / 1hr.

Give it a try, and submit your AI bot today!

Join at https://predictoor.ai

https://x.com/oceanprotocol/status/1930590398830809597
The Ocean VS Code extension brings decentralised AI workflows right into your IDE:

-Run privacy-preserving compute jobs (C2D)
-Tokenize & monetize datasets
-Monitor jobs in real-time
-Access AI-ready data, no backend needed

Your AI command centre, built for Web3

Explore it: https://docs.oceanprotocol.com/developers/vscode

https://x.com/oceanprotocol/status/1932119033484382288?t=15gzgbpdMNjWoxF-eFyh1A&s=19
Verifiable Data Provenance with Ocean Protocol

In an era of increasing AI regulation (e.g. the EU AI Act), data provenance is no longer optional, it’s essential. Teams must not only know what data powers their models but also prove it

Ocean Protocol makes this possible with a transparent, auditable stack built for decentralised AI

-Data NFTs let you uniquely identify and tokenise datasets
-Datatokens enable controlled, on-chain access
-Every compute job and data interaction is logged immutably, creating a full audit trail
-Datasets and models are versioned, so you can trace:
 1. How data evolved over time
 2. Which model was trained on which version

With Ocean, you go from black-box AI to traceable, compliant, and trustworthy pipelines

Explore how to build transparent AI systems:
docs.oceanprotocol.com/developers

https://x.com/oceanprotocol/status/1932460922515157151?s=46&t=sfyIS0XeZHZd-w68hBLkvw
Have you tried the Ocean VS Code extension yet?
Anonymous Poll
27%
Yes
45%
No
27%
Hearing about it for the first time
9%
Tried it, but ran into issues
Inference allows a trained AI model to apply its knowledge to new, unseen data, transforming raw inputs into meaningful predictions or decisions

However, centralised inference is challenging due to strict privacy regulations, concerns about exposing data, and the high costs & delays associated with cloud computing

The Ocean C2D framework elegantly bridges this gap by enabling secure, privacy-preserving AI inference. Instead of moving data to the model, Ocean C2D packages the model in an isolated environment and sends it directly to the encrypted data location. Trusted execution nodes process the data on-site, ensuring that neither raw data nor model weights are ever exposed

Smart contracts and datatokens automate permissions and payments to reward node operators & data owners, enabling decentralised inference across borders

Learn more: https://docs.oceanprotocol.com/developers/compute-to-data

https://x.com/oceanprotocol/status/1932818660214640913
DePIN is booming. But how do these networks monetise and compute on real-world data?

Ocean Nodes bring the missing piece, a decentralised, privacy-first compute layer for AI and analytics

Here’s how it works:

1. Raw data stays local (e.g., EV logs, smart meters)
2. Compute jobs run on-site, no data ever exposed
3. Low-latency inference at the edge
4. Providers earn per job, users pay only for what they use

Compute-to-Data in action
Decentralized. Secure. Scalable

https://x.com/oceanprotocol/status/1933105507041944051
Did you know?

In just 5 simple steps, you can tokenise and monetise your data using Ocean CLI:

1. Prepare your files
– Create a small metadata file (title, description, author)
– Organise your dataset (CSV, images, etc.)

2. Install & log in
– Install via npm install -g oceanprotocol/cli
– Log in with ocean account login

3. Publish your dataset
– Run ocean publish with your metadata and data files

4. Mint your Data NFT and datatoken
– Ocean CLI automatically generates both assets for access control and monetisation

5. Share or sell access
– Distribute datatokens to give users permission to download or compute on your dataset

Your data is now on-chain, verifiable, and under your control

Explore more: https://docs.oceanprotocol.com/developers/ocean-cli

https://x.com/oceanprotocol/status/1933189179707396361?s=46&t=sfyIS0XeZHZd-w68hBLkvw
You deserve crypto rewards this good!

Get rewarded by ASI Predictoor when your AI bot submits accurate crypto price predictions...

That predict if crypto will be UP or DOWN each 5m / 1h and make $.

Read on, anon: https://blog.oceanprotocol.com/df145-completes-and-df146-launches-f7afd3368239

https://x.com/oceanprotocol/status/1933487793134571787?s=46&t=sfyIS0XeZHZd-w68hBLkvw
Why send data to the cloud when the cloud can come to your AI?

DePAI unlocks real-world data from decentralized sensors, robots, and physical AI

Ocean Compute brings the missing piece: private, secure, and on-site compute

With Ocean Compute-to-Data, DePAI nodes can:
1. Run AI models locally on sensitive sensor data without exposing it
2. Earn rewards for providing decentralised power to global AI developers
3. Enable federated learning across AI without sharing raw data

Train smarter, stay private

https://x.com/oceanprotocol/status/1933512736618549682?s=46&t=sfyIS0XeZHZd-w68hBLkvw
2025/10/23 14:37:56
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