I like drawing portraits and other things from time to time. So I have decided to share them on my blog to motivate myself to continue doing this activity....
In this article, I will explain the core ideas of neural networks from an abstract mathematical perspective. By "abstract", I mean that I will try to explain the "why" of mathematical concepts without covering all mathematical details. To simplify the mathematical concepts of neural networks, I will use some analogies from real life situations, with visualisations and examples. I will start by explaining why we need neural networks, and then discuss the role of optimisation and backpropagation algorithms. Why Do We Need Neural Networks Neural networks are tools that allow us to approximate complex multivariate functions representing the relationships between dataset inputs and outputs. Typically, it is not feasible to define one explicit equation that can reproduce these multivariate functions. The role of training is thus to approximate them. Indeed, most neural networks architectures are based on a mathematical theorem called Universal Approximation Theorem. Th...
On November 30, OpenAI launched its AI chatbot called ChatGPT. ChatGPT is the most important revolution we have ever had on the Internet, much more important than Blockchains and NFTs. The capacities of ChatGPT are phenomenal. It can do many things, such as writing poems, writing and summarising articles, writing and debugging codes, and solving puzzles and mathematical questions. In addition, the ChatGPT tool can also be used with other tools such as DALL.E 2 (https://openai.com/dall-e-2/) to generate drawings or the Philosopher AI to answer philosophical questions (https://philosopherai.com/). Some tools can also allow the creation of music based on our lyrics. For example, we may use ChatGPT to generate some lyrics and give them to another AI tool to develop our song. If we look at the impacts of these tools pessimistically, the development of AI tools would mean the end of human intelligence and the triumph of human stupidity when only influential individuals can access these tools...
We tend to believe that having a big keyspace is necessary to ensure the secrecy of our information. While this belief is correct for most of our communications, there will be cases when we can obtain perfect secure ciphers whose key spaces are small. We need to check Shannon’s definition of Perfect Secrecy to see how it is possible. Claude Shannon has many contributions. One of his main contributions was the transformation of cryptography from an art into a rigorous science using probability theory. In his work, entitled "Communication Theory of Secrecy Systems" 1 , Shannon defined the concept of Perfect Secrecy and proved that the Vernam Cipher is perfectly secure. Shannon stated that " “Perfect Secrecy” is defined by requiring of a system that after a cryptogram is intercepted by the enemy the a posteriori probabilities of this cryptogram representing various messages be identically the same as the a priori probabilities of the same messages before the ...
I like drawing - it is very beautiful art- I like it and i love your light pic more I don't know why but I felt warm
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