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Mastering Algorithm Efficiency

Analytics Vidhya

Introduction In the world of technology, understanding algorithm efficiency is like having a superpower. Algorithm efficiency isn’t just for computer scientists; it’s for anyone who writes code. In this guide, we’ll explore the vital role of algorithm efficiency and its measurement using notations.

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Computer Scientists Inch Closer to Major Algorithmic Goal

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A new paper finds a faster method for determining when two mathematical groups are the same. If someone asks you to determine whether two objects are …

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From blackboards to algorithms: the rise of AI in Canadian classrooms

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Canada is advanced in the field of artificial intelligence research home to computer scientist Geoffrey Hinton, the Godfather of AI who recently shared the Nobel Prize for his work on artificial neural networks and is a global talent hub for AI expertise. As one of the global leaders in AI

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Computer scientist explains why even in the age of AI, computing isn’t limitless

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A computer’s power is still limited by the number of operations it can execute per second and the efficiency of the algorithms it runs.

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A brief history of cryptography: Sending secret messages throughout time

IBM Journey to AI blog

Coinciding with the invention of modern computing in the 19th century, the dawn of the digital age also heralded the birth of modern cryptography. If the ciphertext is intercepted and the encryption algorithm is strong, the ciphertext will be useless to any unauthorized eavesdroppers because they won’t be able to break the code.

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Cryptography use cases: From secure communication to data security 

IBM Journey to AI blog

While modern cryptographic algorithms are far more advanced, the fundamental steps remain very similar. Cryptographic algorithms Cryptographic algorithms are the mathematical formulas used to encrypt and decrypt data. At a basic level, most cryptographic algorithms create keys by multiplying large prime numbers.

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Explainable AI Using Expressive Boolean Formulas

Unite.AI

Indeed, some “black box” machine learning algorithms are so intricate and multifaceted that they can defy simple explanation, even by the computer scientists who created them. In this problem we have two competing objectives: maximizing the performance of the algorithm, while minimizing its complexity.