Google TPU And Quantum Computer: Milestones In AI
I am sure everyone will agree with me if I say that Google is omnipresent and our life is incomplete without it. Since the beginning of this year, a lot of announcements regarding the Android O launch and much more came forth. But the recent developer’s conference by Google gave us Google TPU(Tensor Processing Unit). It is a computer chip and it will be changing the whole scenario of machine learning.
Furthermore, to deepen its roots in the world, Google is planning to venture profoundly into Artificial Intelligence. They are working hard to master the manufacturing of AI hardware devices and machines.
Come, let us find out What is Google TPU and How it will be changing the world?
Google TPU For Machine Learning(ML)
Google TPU or the new processor is also known as the Cloud TPU. The name TPU came from TensorFlow, Company’s machine learning framework. Machines working on Artificial Intelligence will be leaving a positive impact on our lives. TPU or Tensor Processing Unit will help the user in voice recognition and a better understanding of the language. Hence TPU will enable us to interact with the technology in a natural way. Businesses can tap frauds and can rely on machine learning for their work and can enhance their security networks. Machine learning is increasingly helping the medical science to improve medical imaging. Furthermore, this is helping in accurate diagnosis and hence saving lives.
Google TPU Increases The Learning Speed
Cloud TPU has inbuilt programmes that let a machine learn and perform a task with accelerated speed. Hence, the user can increase the workload of the machine as well. Every single Cloud TPU has the power to deliver 180 teraflops of performance. Furthermore, it gives 64 gigabytes of ultra-high bandwidth memory. This performance can occur simultaneously with the learning mode. Hence Cloud TPU can help you to take your business to scale new heights.
Access To ML Accelerators
The user can get an on demand easy access to the powerful Machine Learning Accelerators. Moreover, the user doesn’t need any kind of capital investment in it. Even if you require Cloud TPU for a longer duration of time, you can get the apt machine learning acceleration for the necessary task. Furthermore, you don’t have to create your own data centre for this.
Accepts TensorFlow Workload
Even if you are running a Machine Learning workload on TensorFlow. You can easily take the workload to the Cloud TPU. Owing to the open source nature of the TensorFlow and its high-level API’s easily allow the models to move across CPU’s, GPU’s, and TPU’s. Moreover, you do not have to change the coding for this.
Benefits Of Google TPU
While running machine learning workloads on Google TPU, it gives you some benefits like storage, data analytics and networking. Google offers a unified cloud storage facility. The user can store live data tapped by most demanding applications to cloud archive solutions. Furthermore, it gives a consistent speed, latency and API.
Google TPU gives an end to end data solution. This allows the user to capture, process, store and analyse the data. Data analysis can be done through Google BigQuery which an analytics data warehouse. Google CloudData Flow analysis data in batches and in stream flow. Furthermore, Google Cloud DataProc easily processes bid datasets using the powerful and open tools.
Google TPU will certainly be a stepping stone in the functioning of the Super Computer or the Quantum Computer by Google. The company is planning to launch the first ever supercomputer by the end of this year. Quantum computers are known to perform the tasks easily that are out of reach of the normal computers. The processing unit of the supercomputers is made up of the superconducting qubits. Google is planning to create an integrated circuit of a 7-by-7 array.
Furthermore, the tech giant is aiming to have a chip superiority over normal computers. Recently Google ran a dry run of the process on a 9-by-1 array of qubits. Moreover, a test of fabrication technology on a 2-by-3 array was done. The scaling of the qubits needs to work with efficiency. Google is planning to manufacture a 50-qubit chip.
Whether or not Google achieves the supremacy in producing the quantum supercomputer, is the thing to be witnessed in future. Nonetheless, the Google TPU is phenomenal in machine learning and will be accomplishing the Google in AI.
Video Source: YouTube
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