Introduction
You probably heard that now you can call ChatGPT over the phone. This seems unreal. It is cool but do you have an idea whom you’re gonna be talking to? The best you can do is to rely on service provider reputation – OpenAI OpCo, LLC.
Issues with Current AI
- Centralized Models: Most widely-used models like GPT-4 or Claude are closed-source and centralized.
- Dependence on Centralized Infrastructure: Even “open-source” models often run on centralized platforms like Groq or Together AI.
- Opaque Operations: It is impossible to verify how agents operate—including prompts, limitations, and stop lists.
- Data Privacy Concerns: Users have little visibility into how their data is handled or stored.
These challenges emphasize the need for responsible AI use and caution when relying on AI agents for critical decisions.
AI and Learning
Lucky you if you graduated from school before getting spoiled by AI.
But what if you are not able to verify stuff just because you have not developed learning skills, critical thinking, reasoning skills or just because you are too young or you got addicted to “helpful and efficient” AI agents? This could be a serious issue. Calculators began as costly, limited tools, giving schools years to adapt. Now, AI is transforming education instantly, impacting every subject. Students will cheat with AI but also integrate it into their work, challenging educators and questioning the relevance of traditional assignments.
Common understanding is that unless assignments are completed in class, it’s impossible to reliably determine if the work is human-made.
Verifiable AI can change this.
NEAR AI Hub
NEAR.AI is the answer.
While in Alpha, some exciting features are already available to try. Nothing compares to learning by trying so let’s do it.
Go to the NEAR AI Research Hub.
You may sign in with your NEAR account to interact with the platform. At the Agents tab you find all the agents added to the Registry – Decentralized storage with support of private and encrypted items.
Find and check out Learn AI agent 0.0.1.
You can talk to the agent within NEAR AI hub, and what is more important you can explore the agent’s origin – which is learn-agent.learnclub.near, source code, including prompt and stopwords. (L)Earn AI agent “lives on NEAR AI infrastructure – agent itself and the LLM. Moreover, if you want to tweak it – say remove a stopword that is crucial for you – just clone it. But be aware that now you are in charge of your clone!
Now let’s dig a bit deeper. Switch to the Models tab.
There are over 50 open source models available already. As you can see and verify that Learn AI is using that particular LLaMA hosted at the NEAR AI infrastructure. Using NEAR accounts for interacting with models via agents makes it sure that you know whom you are actually talking to!
Recently, private RAG (a LLM friendly LNC knowledge base) powered by XTrace was added. It dramatically improved the quality (L)Earn AI🕺.
NEAR AI is planning to build the next generation frontier AI model with 1.4T parameters! The idea is make open source AI development sustainable via pay-per-use model and this where NEAR will play the crucial role.
What is one major advantage of the NEAR AI infrastructure compared to centralized AI models?
How will NEAR AI pull off building a 1.4T parameter, monetizable model in a decentralized way? Enter the world of Trusted Execution Environments, or TEEs.
Modern processors and GPUs (starting with H100s) allow one actor, Alice, to run code on a machine of another actor, Bob, without trusting Bob, while having the following two guarantees: (a) Bob is in fact running the code Alice expected him to run, and (b) Bob cannot spy on the execution that Alice wants him to carry out. In other words, Alice can safely send any private data into such a computation, being certain Bob will not be able to see it.
(L)Earn AI🕺
The decentralized NEAR AI infrastructure represents a significant step forward in enabling user-owned AI. By offering transparency, control, and flexibility, NEAR AI empowers users to interact with AI agents in a way that ensures data privacy and fosters trust.
LNC, as a NEAR pioneer, is at the forefront of leveraging this infrastructure for practical applications, including the live Learn AI agent, the Lean NEAR Tutor (in development), and the planned WooCommerce Shopping Agent.
❓Ask🕺
As a learner, you’re invited to actively participate in this innovative (L)Earn ecosystem. Ask the (L)Earn AI relevant questions, pay with nLEARNs, gain knowledge, and earn nLEARNs by contributing to the AI’s improvement.
Ask (L)Earn AI also available at Telegram
Check out the most recent (L)Earn AI🕺 agents:
📝Summarize🕺
LNC Summarize🕺 Agent quickly breaks down complex guides into easy-to-understand summaries . It pulls out the most important points and explains them clearly, helping students grasp key concepts without wading through lengthy materials. This time-saving tool makes learning more efficient while keeping the essential information intact. If you’re not a native speaker, you can ask the agent to summarize it in your language!
✏Comment🕺
LNC Comment Agent 🕺analyzes the topic of (L)Earners choice and drafts a comment. The (L)Earner then reviews this draft and posts it with any necessary edits.
✅Quiz🕺
(L)Earn AI Quiz is the first step to introducing the future of learning – personalized, on demand verifiable AI assisted learning. Choose the difficulty and (L)Earn AI will create a quiz to help you memorize the major concepts!
As (L)Earn AI intelligence evolve most likely it will be integrated with other NEAR projects – for example as learning assistant chat bot at other Dapps and Telegram chats, or (L)Earn AI can also cooperate with other NEAR AI agents like NEAR Docs agent and help users to get more technical development related help.
What is the unique feature of the (L)Earn AI agent in the NEAR ecosystem?
📚Happy (L)Earning!🕺
Top comment
Breaking down barriers to participation is crucial in ensuring that everyone has an equal opportunity to learn and grow. I think this strategy is a great example of how technology can be used to create more equitable and accessible learning experiences
By prioritizing transparency, NEAR AI creates a stronger bond
The ability to customize AI agents on NEAR AI is a game-changer for individual and enterprise users alike.
Moreover, you can explore the agent's origin – learn-agent.learnclub.near – which includes the source code, prompt, and stopwords. If you want to tweak it, such as removing a crucial stopword, you can clone it. However, please be aware that you will be responsible for maintaining your clone.
To interact with the platform, navigate to the Agents tab, where you will find all the agents added to the Registry, a decentralized storage system that supports private and encrypted items. Please find and explore the Learn AI agent version 0.0.1.
Calculators originated as expensive, limited tools, allowing schools years to adapt. Now, AI is revolutionizing education rapidly, influencing every subject. While students may use AI to cheat, they will also incorporate it into their work, presenting educators with challenges and prompting questions about the relevance of traditional assignments. It is commonly understood that unless
Here is the corrected message: Invite friends NOW! +2 nL Introduction You've probably heard that you can now call ChatGPT over the phone. This seems unreal. While it's cool, do you know who you'll be talking to? The best you can do is rely on the service provider's reputation – OpenAI OpCo, LLC. Issues with Current AI Centralized Models: Most widely-used models, such as GPT-4 or Claude, are closed-source and centralized. Dependence on Centralized Infrastructure: Even "open-source" models often run on centralized platforms like Groq or Together AI. Opaque Operations: It's impossible to verify how agents operate, including prompts, limitations, and stop lists. Data Privacy Concerns: Users have little visibility into how their data is handled or stored. These challenges emphasize the need for responsible AI use and caution when relying on AI agents for critical decisions. AI and Learning If you graduated from school before getting spoiled by AI, consider yourself lucky. However, what if you're unable to verify information because you haven't developed learning skills, critical thinking, or reasoning skills, or simply because you're too young or addicted to "helpful and efficient" AI agents? This could be a serious issue. Calculators began as costly, limited tools, giving schools years to adapt. Now, AI is transforming education instantly, impacting every subject. Students will cheat with AI, but they'll also integrate it into their work, challenging educators and questioning the relevance of traditional assignments. Common understanding is that unless assignments are completed in class, it's impossible to reliably determine if the work is human-made. Verifiable AI can change this. NEAR AI Hub NEAR.AI is the answer. While in Alpha, some exciting features are already available to try. Nothing compares to learning by trying, so let's do it. Go to the NEAR AI Research Hub. You may sign in with your NEAR account to interact with the platform. At the Agents tab, you'll find all the agents added to the Registry – Decentralized storage with support for private and encrypted items. Find and check out the Learn AI agent 0.0.1. You can talk to the agent within the NEAR AI hub, and what's more important, you can explore the agent's origin – which is learn-agent.learnclub.near, including source code, prompt, and stopwords. Moreover, if you want to tweak it – say, remove a stopword that's crucial for you – just clone it. But be aware that now you're in charge of your clone! Now, let's dig a bit deeper. Switch to the Models tab. There are over 50 open-source models available already. As you can see and verify, Learn AI is using that particular LLaMA hosted at the NEAR AI infrastructure. Using NEAR accounts for interacting with models via agents ensures that you know whom you're actually talking to! NEAR AI is planning to build the next-generation frontier AI model with 1.4T parameters! The idea is to make open-source AI development sustainable via pay-per-use model, and this is where NEAR will play a crucial role. Express Quiz +4 nLEARNs What is one major advantage of the NEAR AI infrastructure compared to centralized AI models? It offers faster processing speed It ensures user-owned AI with transparency and control over agents and models It eliminates the need for AI prompts and stopwords It requires no technical knowledge for customization How will NEAR AI pull off building a 1.4T parameter, monetizable model in a decentralized way? Enter the world of Trusted Execution Environments (TEEs). Modern processors and GPUs (starting with H100s) allow one actor, Alice, to run code on a machine of another actor, Bob, without trusting Bob.
Here is the source code, including the prompt and stopwords. Additionally, if you want to make adjustments – for instance, removing a stopword that is crucial for you – simply clone it. However, please be aware that you will then be responsible for your cloned version.
Dependence on Centralized Infrastructure: Even "open-source" models often rely on centralized platforms, such as Groq or Together AI. Opaque Operations: It is impossible to verify the inner workings of agents, including the prompts, limitations, and stop lists they utilize.
I heard that you can now call ChatGPT over the phone, which seems unreal. It's cool, but have you considered who you'll be talking to? The best you can do is to rely on the service provider's reputation, such as OpenAI OpCo, LLC.
Participation is crucial in ensuring that everyone has an equal opportunity to learn and grow. I believe this strategy is a great example of how technology can be used to create more equitable and accessible learning experiences.
NEAR.AI is the answer. While still in its Alpha phase, some exciting features are already available to explore. There's no substitute for learning by doing, so let's get started. Visit the NEAR AI Research Hub.
to interact with the platform. At the Agents tab you find all the agents added to the Registry – Decentralized storage with support of private and encrypted items.Find and check out Learn AI agent 0.0.1.