Explore our diverse range of use cases and discover how GuardTPU can elevate your projects. With our seamless server services, tailoring your needs is effortless – simply complete the form and gain instant access to your cloud tenor processing unit.
Tap into AI's potential with Guard's Cloud TPU rentals, opening doors to innovation. Accelerate your projects with specialized hardware designed for fast and precise machine learning tasks. Benefit from lightning-fast computations, flexible scalability, and empower your team to push boundaries. Dive into deep learning, scale confidently, and drive impactful business outcomes.
Empower your AI journey with Guard's CloudTPU's seamless integration and dive into accelerated development. No coding required to set up. Unlock creativity, drive innovation, and shape the future of AI effortlessly with CloudTPU by your side.
Step into the Future of AI, where decentralized technologies and collaborative communities propel AI evolution, empowering a diverse range of innovators to chart new territories, foster inventive solutions, and sculpt the landscape of artificial intelligence with limitless potential for advancement and exploration.
A TPU, or Tensor Processing Unit, is a specialized hardware accelerator for machine learning workloads. It is optimized for performing tensor operations, which are fundamental to deep neural networks.
TPUs are primarily used for training and executing deep machine learning models also known as artificial intelligence.
TPUs are favored for their specialized tensor processing capabilities and efficient handling of the high computational demands inherent in deep learning algorithms.
TPUs outperform CPUs and GPUs in deep learning due to their specialized design for tensor operations. This specialization results in faster training times and lower energy consumption, making TPUs the preferred choice for deep learning tasks.
✅ Image Recognition
✅ Natural Language Processing
✅ Recommendation Systems
✅ Speech Recognition
✅ Drug Discovery
✅ Autonomous Vehicles
✅ Healthcare
✅ Financial Services
✅ Robotics
✅ Climate Modeling
Hosting provides server space and services for websites and applications, while TPUs are specialized hardware for accelerating machine learning tasks, offering faster performance and lower energy consumption.
Guard´s CloudTPU revolutionizes the landscape for developers and researchers by introducing a groundbreaking solution: a decentralized marketplace for renting high-performance Cloud TPUs.
This innovative approach eliminates dependency on centralized cloud providers and offers the following advantages:
➡️ Efficiency in Terms of Costs: Rent TPUs on-demand, eliminating the need for upfront hardware costs.
➡️ Ability to scale: Seamlessly adjust your TPU usage to align with project requirements, ensuring optimal resource utilization.
➡️ Transparency & Control: Gain more control and transparency over your TPU rental transactions by utilizing the security and dependability of the Ethereum blockchain.
We are dedicated to democratizing access to state-of-the-art AI computing. We envision a world where everyone, regardless of their background or resources, can harness the power of AI.
Through the creation of a decentralized marketplace fueled by $GUARDAI tokens, our goals are clear:
➡️ Remove Barriers: Ensure that high-performance TPUs are within reach for all.
➡️ Encourage Innovation: Empower developers and researchers to explore new frontiers in AI.
➡️ Foster Collaboration: Cultivate a vibrant community ecosystem for collaborative AI development.
Choose the optimal Cloud TPU setup tailored to your project needs from our diverse range.
Easily pay for your Guard TPU rental using Ethereum (ETH). Coming soon: $GuardAI will be accepted.
Get started on your AI development adventure with Guard´s TPUs instantly by receiving all the access details you require over email.
Ideal for basic inference tasks and small-scale text processing, such as lightweight machine learning model predictions and simple text analysis.
✅ Virtual CPUs: 1 virtual CPU is allocated for processing tasks
✅ Architecture: The architecture of the system supports both the i386 and x86_64 instruction set architectures, ensuring compatibility with 32-bit (i386) and 64-bit (x86_64) software.
✅ Memory: Equipped with 2GB of RAM for efficient operation and task execution.
Suited for training small models and basic image processing tasks. Examples include training lightweight machine learning models and performing basic image manipulation or preprocessing.
✅ Virtual CPUs: 1 virtual CPU is allocated for processing tasks
✅ Architecture: The architecture of the system supports both the i386 and x86_64 instruction set architectures, ensuring compatibility with 32-bit (i386) and 64-bit (x86_64) software.
✅ Memory: Equipped with 2GB of RAM for efficient operation and task execution.
Suitable for training moderate-sized models and larger-scale data preprocessing. Tasks may include training medium-sized machine learning models and preprocessing larger datasets for machine learning tasks.
✅ Virtual CPUs: 2 virtual CPUs are allocated for processing tasks
✅ Architecture: The architecture of the system supports both the i386 and x86_64 instruction set architectures, ensuring compatibility with 32-bit (i386) and 64-bit (x86_64) software.
✅ Memory: Equipped with 8GB of RAM for efficient operation and task execution.
Well-suited for training larger models and conducting deep learning research with extensive datasets. Examples include training complex deep learning models and exploring advanced architectures and techniques in deep learning research.
✅ Virtual CPUs: 4 virtual CPUs are allocated for processing tasks
✅ Architecture: The architecture of the system supports both the i386 and x86_64 instruction set architectures, ensuring compatibility with 32-bit (i386) and 64-bit (x86_64) software.
✅ Memory: Equipped with 16GB of RAM for efficient operation and task execution.
