nipunbhushan / ml-ai-world-articles

Lab for Articles

Key Notes | Recreating Images From The Brain:

Sophisticated decoding and encoding models have been developed earlier to render human brain activity into images or movies, the methods were essentially limited to the image reconstruction with low-level image bases.

Therefore, it failed to combine visual features of multiple hierarchical levels. Furthermore, while several recent attempts introduced deep neural networks (DNNs) into visual image reconstructions, they also did not fully utilize hierarchical information to reconstruct visual images.

The new research showed that visual cortical activity (visual features) can be decoded (translated) into hierarchical features of a deep neural network (DNN) for the same input image, providing a way to make use of the information from hierarchical visual features.

NOTE: Research paper has been attached for reference on this git page.

Lab | Machine Learning & AI World

Machine Learning now is one of the trending topics if you talk aboyt technology. Everyday a lot of material about this topic arrives to the media, not only news about new discovers but also a lot of tutorials and articles about people working on this.

The objectives of this lab are:

• Get to introduced into this world through the latest most important news we have had in the last years.
• Guide you to do a deeper research to understand them better.
• Practice your presenting skills

So you will be asked to read a piece of news and then share it with your partners. This way, when we finish sharing, you will have a light idea of the most important events but also you will be able to dig into one specific better.

How we will do it?

So let's start digging a litle bit. Imagine you open your today's AI&ML journal and you see a very interesting new. You read it but that is not enough. You want to understand:

• If it is so important as the title says (is it really a big step?) or you think it is more important than the title let's suggests.
• Which part of ML or AI is used and how is it related to ML or AI.
• What did they do to take the data.
• Which data did they use.
• How did they do to build the model. Which type of model is?
• Do you know any other project that applies the same techniques? Could you use something for another use case?
• Do you find any ethical implications? Collateral effects?
• Do you know any news related?

So you need to look for more information. Maybe the paper the scientists published, other articles, some information about the techniques, ...

Let's start! You will be assigned to an article and a day when you will have 5 minutes to share your research with your colleagues and then 5 minutes to discuss a little bit. Feel free to present your conclusions in the way you prefer.

News

1. AlphaGO
2. Google Autonomous Car
3. Fb Face recognition
4. Google drawing
5. Trump campaign
6. Brain AI
7. Tay Microsoft racist AI
8. Spotify recommendation model
9. Malaria spot
10. Retail AI
11. LAPD crime algorithm
12. Traffic AI
13. Captchas
14. FaceApp
15. What our eyes can tell us
16. Sports prediction
17. AI Bill of Rights
18. Coca-Cola uses AI
19. AI and Parkinson's Disease
20. AI and Covid
21. AI trends in Healthcare
22. Hurricane financial aid given by AI
23. Assesing Disasters for First Responders
24. Stopping Racist Robots
25. Robot gives testimony
26. AI like a human brain
27. Generative AI and Silicon Valley
28. New AI learning techniques