AI Intelligence

Self-driving cars: The future of transportation Self-driving cars are vehicles that can travel without human input. They use sensors, cameras, artificial intelligence, and software to perceive their surroundings, plan their routes, and control their movements. Self-driving cars have the potential to improve road safety, reduce traffic congestion, lower greenhouse gas emissions, and provide mobility and convenience to people who cannot or prefer not to drive. However, self-driving cars also face many technical, legal, ethical, and social challenges. How can they cope with unpredictable human drivers and pedestrians? How can they handle complex situations such as bad weather, road works, or emergencies? Who is responsible if a self-driving car causes an accident or breaks the law? How can they ensure the privacy and security of the passengers and their data? How can they gain the trust and acceptance of the public and the regulators? The development of self-driving cars has been ongoing ...

Explainable AI: What, Why and How Artificial intelligence (AI) is a branch of computer science that aims to create machines and systems that can perform tasks that normally require human intelligence, such as perception, reasoning, learning, decision-making, and natural language processing. AI has been advancing rapidly in recent years, thanks to the availability of large amounts of data, powerful computing resources, and novel algorithms. AI applications have been transforming various domains, such as healthcare, education, finance, entertainment, and security. However, as AI becomes more pervasive and influential in our society, there is also a growing demand for understanding how AI works and what are the implications of its decisions. Many AI systems are based on complex and opaque models, such as deep neural networks, that are hard to interpret and explain by humans. These models are often referred to as "black boxes" because their internal logic and reasoning are hidde...

What is Generic AI Generative AI is a branch of artificial intelligence that focuses on creating new content or data from existing data. It can produce realistic and novel artefacts such as text, images, audio, video, code, and more. Generative AI has many applications and use cases in various domains, such as entertainment, education, healthcare, design, and business. How does generative AI work? Generative AI works by using machine learning algorithms to learn from a large amount of data and generate new data that follows the same patterns or characteristics as the original data. For example, a generative AI model can learn from thousands of images of faces and generate new faces that look realistic but do not exist in reality. There are different types of generative AI models, such as: Generative adversarial networks (GANs) : These are composed of two competing neural networks: a generator and a discriminator. The generator tries to create fake data that can fool the discriminator, ...