CryptoSherry

Industria AI a devenit excesiv de dependentă de furnizorii de servicii cloud pentru calculul AI și stocarea datelor AI în ultimii ani, ceea ce duce la o gamă largă de probleme care amenință creșterea și dezvoltarea viitoare.
În acest articol, analizăm modul în care aceste probleme pot fi rezolvate prin integrarea Inteligenței Artificiale cu soluțiile DePIN - permițând crearea de aplicații AI mai inteligente și mai eficiente.

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Antrenamentul modelului AI și inferența AI sunt sarcini de calcul complexe care necesită diferite resurse hardware pentru a fi executate eficient.

Hugging Face a introdus recent SmolLM, o serie de modele inovatoare de limbaj mic (SLM) care depășesc semnificativ SLM-urile preexistente, inclusiv cele dezvoltate de giganții tehnologiei.
În acest articol, oferim o scurtă perspectivă asupra SmolLM și analizăm modul în care AIOZ DePIN Nodes le poate alimenta pentru performanțe îmbunătățite în lumea reală.

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Modelele de limbaj mari (LLM) sunt destul de renumite pentru cantitatea de putere de procesare și energie electrică de care au nevoie pentru a gestiona eficient sarcinile complexe de calcul.

AI has become a pivotal force in modern society, reshaping everything from daily personal activities to professional job functions. Traditionally, the reins of AI have been held by large corporations like Microsoft, Google, and Facebook, which control the underlying infrastructure and data.
Yet, in the rapidly evolving realm of AI, a revolutionary transformation is underway: DePIN+AI.
This innovative model confronts the monopolistic control exerted by established AI giants, introducing a blockchain-powered DePIN alternative. By merging these technologies, DePIN+AI addresses key issues such as data privacy, verifiability, and user empowerment. In this article, we will introduce a typical example of DePIN+AI, Web3 AI (W3AI), from the AIOZ Network.

Challenges Faced by Small Entities in AI
While many factors have aided the ongoing monopolization of the AI industry, a few stand out for putting small entities like AI developers, businesses, and individuals at a significant disadvantage against tech giants.
Let’s analyze these factors below:
1.) AI Compute Requirements: AI computational tasks, such as model training and inference, require substantial processing power, often exceeding the financial reach of smaller entities due to the soaring costs of CPUs & GPUs.
2.) AI Data Storage Requirements: AI development and applications demand extensive and costly disk space (HDD & SDD) for storing training data and generated data, a demand that has intensified with the rise of Generative AI.
3.) Strict Data Privacy Laws: Increasing regulations aimed at protecting user data across various jurisdictions have complicated the ability for small entities to access valuable private data for AI model training.
4.) Low Accessibility to AI Assets: The processes involved in developing advanced AI models and curating large datasets for training are usually beyond the budget and capacity of many smaller entities.
Given these factors, smaller entities often stand little chance against tech giants in the race for AI development, effectively leaving them without competition in their quest to monopolize AI.
However, W3AI represents a transformative shift from centralized to decentralized AI systems, heralding a new era of user empowerment.
Empowering Users with DePIN+AI
1.) Decentralized AI Compute Infrastructure:
W3AI will leverage the combined processing power of DePINs to provide small entities with robust infrastructure capable of executing AI training and inference tasks in a trustless manner.
Its decentralized nature will allow it to scale effortlessly on demand, maintaining affordable pricing for smaller entities over the long term.
2.) Decentralized AI Data Storage Infrastructure:
W3AI will enable small entities to utilize the disk space of AIOZ DePIN nodes for storing AI training and generated data via the W3S service.
W3S allows its users to pay only for what they use, without hidden charges, facilitating effective budgeting for data storage costs. Its decentralized nature also ensures data availability and security for its users.
3.) Federated Learning Integration:
The AIOZ Node V3 app, the software powering the W3AI service, enables edge devices to engage in Federated Learning.
This innovative AI training method preserves the privacy of data owners, allowing small entities to train AI models using local private data on AIOZ DePIN nodes without risking violation of strict data privacy laws.
4.) W3AI Marketplace:
W3AI will feature a decentralized marketplace that facilitates the exchange of high-quality AI assets between AI developers, businesses, and individuals.
This marketplace provides small entities with access to AI assets they would otherwise struggle to develop and fosters collaboration across the AI industry.
These four solutions will equip smaller entities with essential tools to effectively challenge tech giants and prevent monopolistic control of the AI industry.
The Future of DePIN+AI
As DePIN+AI continues to evolve, it promises not only to revolutionize the deployment of AI but also to address the ethical and technical challenges facing the AI industry today.
By aligning AI developments with the principles of decentralization, transparency, and user control, DePIN+AI could pave the way for a fairer, more equitable AI future.