👉 Learn how to build AI systems for medical imaging domain by leveraging tools and techniques that I share with you! | 💡 The newsletter is read by people from: Nvidia, Baker Hughes, Harvard, NYU, Columbia University, University of Toronto and more!
ChatGPT Passed a Coding Interview!
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Hello Reader, Welcome to another edition of PYCAD newsletter where we cover interesting topics in Machine Learning and Computer Vision applied to Medical Imaging. The goal of this newsletter is to help you stay up-to-date and learn important concepts in this amazing field! I've got some cool insights for you below ↓ |
Have you heard of ChatGPT? It's the latest model from OpenAI. It's capable of doing incredible things!
I've seen many people using it for different applications and the results are nothing short of outstanding!
I tested the model myself. I asked ChatGPT the following questions: "Can you create a program of a neural network that performs image classification using Pytorch and Python?"
As a response, I got this:
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The way it answered my question is just so..human! It even gave me a code snippet of how to build such a neural network. Here's the code that was generated by ChatGPT:
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Isn't this incredible!
There are a few things to fix such as the input size of the network but the rest is mostly correct!
The code is not complete though but I believe that this is mostly due to the limit that's set regarding the number of characters that a response should have which I think has been set by the OpenAI team to limit the processing time, since access to ChatGPT is free for now.
I've also seen a great video by Clément on Youtube where he asked ChatGPT some coding questions that you would usually see in a coding interview for hiring a software developer at Google or Facebook. ChatGPT was able to solve 3 coding questions ranging from: easy, medium to hard. The code that was generated by ChatGPT was basically perfect!
This is insane when you think about it!
Have you tried ChatGPT yet? If not then I highly encourage you to do so here!
That's it for this week's edition, I hope you enjoyed it!
Machine Learning for Medical Imaging
👉 Learn how to build AI systems for medical imaging domain by leveraging tools and techniques that I share with you! | 💡 The newsletter is read by people from: Nvidia, Baker Hughes, Harvard, NYU, Columbia University, University of Toronto and more!
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