Creating videos of moving synthetic animations that look just like real people.
All Machine Learning Models Explained in 5 Minutes
Confused about understanding machine learning models? Well, this video will help you grab the basics of each one of them. From what they are, to why they are used, and what purpose do they serve.
Pitfalls of Artificial Intelligence
In an era where artificial intelligence seems to be rapidly developing by the day, should society begin to question to reliability of the fairly novel technology? We hear from co-host Ben Swann and cybersecurity expert Morgan Wright on the potential shortfalls of the computer intelligence and the perils that could accompany complete reliance.
Deep Neural Network in Machine Learning
Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on models and inference instead. It is seen as a subset of artificial intelligence.
A good AI needs time to develop and training, aka machine learning process, and it usually takes a large amount of time and effort to analyze and tweak. A good machine learning protocol and infrastructure is ideal in order to shorten the time of development.
If you are interested in developing any form of automatic or semi-automatic smart appliance that is capable of making decisions based on previously trained behaviors from big data that is known as Artificial Intelligence, you need to train your AI. Thus, you need machine learning.
From Artificial Intelligence to Superintelligence: Nick Bostrom on AI & The Future of Humanity
Artificial Superintelligence or ASI, sometimes referred to as digital superintelligence is the advent of a hypothetical agent that possesses intelligence far surpassing that of the smartest and most gifted human minds. AI is a rapidly growing field of technology with the potential to make huge improvements in human wellbeing. However, the development of machines with intelligence vastly superior to humans will pose special, perhaps even unique risks.
Most surveyed AI researchers expect machines to eventually be able to rival humans in intelligence, though there is little consensus on when or how this will happen.
One only needs to accept three basic assumptions to recognize the inevitability of superintelligent AI:
– Intelligence is a product of information processing in physical systems.
– We will continue to improve our intelligent machines.
– We do not stand on the peak of intelligence or anywhere near it.
Philosopher Nick Bostrom expressed concern about what values a superintelligence should be designed to have.
Any type of AI superintelligence could proceed rapidly to its programmed goals, with little or no distribution of power to others. It may not take its designers into account at all. The logic of its goals may not be reconcilable with human ideals. The AI’s power might lie in making humans its servants rather than vice versa. If it were to succeed in this, it would “rule without competition under a dictatorship of one”. Elon Musk has also warned that the global race toward AI could result in a third world war. To avoid the ‘worst mistake in history’, it is necessary to understand the nature of an AI race, as well as escape the development that could lead to unfriendly Artificial Superintelligence.
To ensure the friendly nature of artificial superintelligence, world leaders should work to ensure that this ASI is beneficial to the entire human race.
Machine Learning Explained
A Harvard expert talks about one of the most rapidly progressing branches of artificial intelligence and where it holds the most promise to accelerate medicine.
Introduction to Machine Learning: Part One
Here is a beginner’s introduction to artificial intelligence, machine learning, and deep learning. Learn quick stats on the growth of AI, how to use and distinguish supervised learning from unsupervised learning, what is labeled data, when to use a clustering algorithm, and more.
AI Show – Deep Learning vs. Machine Learning
This episode helps you compare deep learning vs. machine learning. You’ll learn how the two concepts compare and how they fit into the broader category of artificial intelligence. During this demo we will also describes how deep learning can be applied to real-world scenarios such as fraud detection, voice and facial recognition, sentiment analytics, and time series forecasting.
MACHINE LEARNING TUTORIAL (2020)
In this video we will look at the introduction to Machine Learning.
Artificial Intelligence vs Machine Learning vs Deep Learning Explained
This video discusses the basics of Artificial Intelligence, Machine Learning and Deep Learning.