Post Image

Anteral Academy is back and today we talk about one of the latest trends: Artificial Intelligence With the recent launch of ChatGPT, eveyone is talking about #AI but, do you know what it is? From the self-driving cars to the smart assistants like Siri and Alexa, Artificial Intelligence is a growing part of everyday life. Do you want to learn more about it?

What is Artificial Intelligence? Definition and origin.

We can define Artificial intelligence as the simulation of human intelligence processes by machines.

Now let’s talk about its origin. After helping the Allied forces win World War II by breaking the Nazi encryption machine Enigma, mathematician Alan Turing changed history a second time with a simple question: “Can machines think?” Turing’s 1950 paper “Computing Machinery and Intelligence” and its subsequent Turing Test established the fundamental goal and vision of AI: the endeavor to replicate or simulate human intelligence in machines.

How does AI work?

In general, AI systems work by ingesting large data, analyzing the data for correlations and patterns, and using these patterns to make predictions about future states. For example, it can learn to identify and describe different objects in images by reviewing millions of examples.

The learning process focuses on acquiring data and creating rules for how to turn the data into understandable information. These rules are called algorithms.

Artificial Intelligence example

Strong AI VS Weak AI

Types of artificial intelligence:

  • Weak AI, also called Narrow Artificial Intelligence (ANI), is trained and focused to perform specific tasks and it encompasses most current AI applications. Some examples are Apple’s Siri, Amazon’s Alexa or Netflix’s and Spotify’s recommendations.
  • Strong AI includes Artificial General Intelligence (AGI) and Artificial Super Intelligence (ASI), also known as superintelligence. It is a theoretical form of AI where a machine would have an intelligence equaled or superior to humans. It would have a self-aware consciousness that has the ability to solve problems, learn, and plan for the future.This AIs are still theoretical with no practical examples in use today

Deep Learning VS Machine Learning

Deep learning and machine learning (ML) are sub-fields of artificial intelligence that can learn from data and make decisions based on patterns observed. Deep learning is actually a sub-field of machine learning.

  • Machine learning can automatically adapt with minimal human interference.
  • Deep learning is an evolution of machine learning that uses artificial neural networks to mimic the learning process of the human brain. Deep learning can leverage labeled datasets, also known as supervised learning, to inform its algorithm, but it doesn’t necessarily require a labeled dataset. It can ingest unstructured data in its raw form (e.g. text, images), and it can automatically determine the hierarchy of features which distinguish different categories of data from one another. Unlike machine learning, it doesn’t require human intervention to process data, allowing us to scale machine learning in more interesting ways.
Machine Learning vs Deep Learning

Use cases for radar technology – uRAD

In Anteral, we love innovation, and we try to make the most of the latest technology for our applications. IA is a powerful tool that we use in our radar applications.

Some use cases for different applications are:

  • Traffic monitoring -> Vehicle classification, license plate recognition, traffic prediction, occupancy prediction
  • Vital sign recognition -> Signal classification, Vehicle in-cabin sensing
  • Gesture classification -> Signal classification
  • People counting -> Position prediction, tendency analysis
Merry Christmas and Happy New Year!