Fist line of code which was taught to every programmer before learning a programming language that is hello world. But choosing the correct hardware essential in the learning process, if you are looking for a job or starting own business, so choose accordingly. Today we will deep dive into the essentials of cpu,gpu and tpu.
This blog is all about spreading the awareness and reducing the fear, ai is stealing the job and eleminating the jobs, I will tell you the throught,those companies which create ai that isn't allowing to use ai in their projects, so do not fear, ai has increased the jobs.
You are looking for which one to choose cpu(the central processing unit) or gpu(Graphics Processing Unit) , CPU is the door and gpu is the home for games, ai bots and complex tasks are handled efficiently. But gpu is costly and it costs you much.
If you need to train a model for image processing and video processing systems ,so you need the gpu,the best system for these type of application. Tensor Processing Units (TPUs), as you know that tensorflow is good for ai , so there is no rocket science ,the tpu will be the good for creating the ai and machine learning workloads.
Stand up from your office chair and look towards the sky and you will found the electricity cables which are spread accross the city and these wires ,if you place those wires onto the circuit of computers for parallel processing in computer architecture, while you are performing the task, gpu architect uses the more than 1000 cores for processing the data. We can understand that we have connected the dots, more than 1000 computers are working together to process your data, and this increases the cost.
Here are the current prices: the NVIDIA RTX 5060 starts around 299 euros, while the RTX 5080 begins at about 1,129 euros. The RTX 5090 is priced around 3,171 euros.
Why to use gpu in place of cpu? The throttle explains you ,how much air places arround the engine, the same concept can also apply for cpu vs gpu, when you need the simple tasks to complete, the cpu is efficient and when you are dealing with graphics efficient and complex tasks, so gpu is mandatory on such cases.
NPUs ,these are neural processing Units, designed for copying the human brains, just like a parrot, say hello to the parrot,it will repeat exactly, this makes the ai related tasks quite easy and ai /agentic ai companies started using them, but they will never tell the truth to you, what is powering agentic ai. It's npu that connects the cpu and gpu , the main advantage of using npu , it has a capacity of less power consumtion.
tpu (tensorflow processing unit),think like a specialist and he is a spacialist doctor for ai related and mathematical tasks. It helps to run the ai models.
If you are a agentic ai compony, or thinking to train your own model,choosing the gpu is increasing the cost and the best thing is choose npu over the cpu,gpu and tpu. It's just a suggestion, sometimes using the unstable devices and technologies also provides the help.
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