Rock

World

Edge

IoTeX

<a href="https://network3.io/" rel="noopener noreferrer nofollow" target="_blank">Network3</a>, an AI Layer2 that helps global artificial intelligence developers train or validate models conveniently, quickly, and efficiently, has announced its new local Large Language Model (LLM) feature.&nbsp;
The announcement was made earlier this week at the R3al World Summit organized by the DePIN modular infrastructure provider IoTeX in Singapore at the TOKEN2049 conference.&nbsp;
On the first day of the event, Network3 announced the brand new LLM feature, which, according to the project founder Rock, will “significantly boost the efficiency and performance of Edge AI technology.”
Edge AI is the deployment of AI models and algorithms directly on local devices such as smartphones. This technology moves data processing and storage closer to devices that actually create and use the data to reduce cost and latency while improving application performance. By processing large volumes of data with greater speed and reliability, Edge AI delivers responses almost instantly and provides real-time feedback.
The global Edge AI market size was valued at <a href="https://www.fortunebusinessinsights.com/edge-ai-market-107023" rel="noopener noreferrer nofollow" target="_blank">$20.45bln in 2023</a> and is projected to surpass $269bln in the next eight years.
“While EdgeAI is already a part of our daily lives, its potential is often overlooked,” noted Rock and illustrated how our mobile phones can process data so efficiently at night, demonstrating the power of edge devices using idle resources.
<h2 class="wp-block-heading" id="strong-transforming-smart-devices-into-ai-training-assets-strong">Transforming Smart Devices into AI Training Assets</h2>
Network3, which has <a href="https://www.theblock.co/post/306471/web3-ai-firm-network3-raises-5-million-in-funding" rel="noopener noreferrer nofollow" target="_blank">raised $5.5 million</a> so far and is already preparing for the next funding round, aims to make Web3 &amp; AI technologies widely accessible and promote their widespread adoption.&nbsp;
For this, it integrates DePIN with AI to enable IoT devices available all around us to train small AI models. This way, individuals can participate in AI training by sharing IP, bandwidth, datasets, and the computing power of their devices while earning rewards — effectively turning smart devices into value-generating assets.&nbsp;
Now, with its local LLM feature, the project aims to further optimize the processing capabilities of smart devices during idle times. The new LLM will also reduce their dependence on cloud computing and cut down bandwidth usage while enhancing data security and privacy.&nbsp;
The AI L2 Network3 has been focused on building for the last few years and has over 320,000 active nodes spread all over the world.&nbsp; They also recently released a physical mining device called N3 Edge V1, which can mine IoTeX and Network3’s native tokens simultaneously. The dual mining device is easy to set up, has DePIN verification, and offers monetization options in terms of rewards and the ability to boost N3E credit points.&nbsp;
Now, with its latest local LLM update, Network3 is offering its users the opportunity to enjoy AI chat services on their mobile devices without the need for expensive cloud infrastructure.&nbsp;
Network3 will launch a test version in the coming weeks, which users will be able to download through the official website. By interacting with the model, users get to earn tokens and personalize their AI experience.&nbsp;

Network3 Unveils Local LLM Feature at TOKEN2049 DePIN Summit to Optimize Smart Device AI Capabilities

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