If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
New Zealand Police has recruited an unusual new officer to the force: an AI cop called Ella. Ella is a life-like virtual assistant that uses real-time animation to emulate face-to-face interaction in an empathetic way. Its first day of work will be next Monday, when Ella will be stationed in the lobby of the force's national headquarters in Wellington. Its chief duties there will be welcoming visitors to the building, telling staff that they've arrived, and directing them to collect their passes. It can also talk to visitors about certain issues, such as the force's non-emergency number and police vetting procedures. After three months on the job, Ella's future on the force will be evaluated.
If you looked up the term "artificial intelligence" on Google and found your way to this article, you've used (and hopefully benefitted from) AI. If you've ever taken an Uber or had your phone auto-correct a misspelled word, you've used AI. Although it may not always be immediately obvious, artificial intelligence impacts nearly all aspects of our lives in a nearly uncountable number of ways. In this article, we'll take a look at eight examples of how artificial intelligence saves us time, money, and energy in our everyday life. Before we can identify how artificial intelligence impacts our lives, it's helpful to know exactly what it is (and what it is not).
AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner It is not software or data, but the Trans-AI will eat the world. While the Real-World #AI implies the Transdisciplinary Science, Engineering and Technology. We have innovated a Trans-AI model integrating narrow and weak AI models with statistic ML/DL algorithms. The Trans-AI General Purpose Technology is to enable a new, smart and sustainable Trans-AI World marked by a cybernetic synergy between humans and genuinely intelligent computers and AI systems. We create a huge universe of data, a data hyperreality, which denizens are: Statistics, facts, recordings, Observations, Web data, Bigdata, Data sets, Data points, Time series, Structured or unstructured data, Images, Graphs, charts, plots, charts, Statistic graphics, Tables, database Data items, Game positions, Computer programs, Mathematical functions, Text, data documents, Coded data, software, information, and knowledge.
There are different modules to realize different functions in deep learning. Expertise in deep learning involves designing architectures to complete particular tasks. It reduces a complex function into a graph of functional modules (possibly dynamic), the functions of which are finalized by learning. Recurrent Neural Network (RNN)is one type of architecture that we can use to deal with sequences of data. We learned that a signal can be either 1D, 2D or 3D depending on the domain. The domain is defined by what you are mapping from and what you are mapping to.
In a similar study of Eurostat It turns out that 7 percent of Norwegian companies used AI in 2020. The most common is workflow automation. And despite the fact that we hear a lot about robots, drones and self-driving cars and often associate AI with them, KI technologies are used by the least, just 1%. This group excels in the use of AI compared to the others – and is also the largest user of all KI technologies. On the other hand, there are accommodation and catering activities, automobile trading and repair, transportation and warehousing, with the shares amounting to 2, 3 and 3 percent respectively. The proportion of companies using artificial intelligence is increasing in line with the scale.
As artificial intelligence has evolved, it has found its way into more aspects of our lives – from social media to digital marketing. How AI is transforming the future of digital marketing? In this blog post, we will examine 9 ways in which AI is changing how companies market themselves online. In today's competitive business environment where every businessman is trying to make their brand stand out from others. Marketing strategies play an important role here because it helps you reach people easily.
EM (Expectation-Maximisation) Algorithm is the go to algorithm whenever we have to do parameter estimation with hidden variables, such as in hidden Markov Chains. For some reason, it is often poorly explained and students end up confused as to what exactly are we maximising in the E-step and M-steps. Here is my attempt at a (hopefully) clear and step by step explanation on exactly how EM Algorithm works.
If we break down the word itself, it is a combination of 2 words, machine learning, and operations. Where machine learning stands for model development or any kind of code development and operations means production and deployment of code. A more technical definition of MLOps is a set of principles and practices to standardize and streamline the machine learning lifecycle management. Well, it is not a new technology or tool but rather a culture with a set of principles, guidelines defined in a machine learning world to seamlessly integrate/automate the development phase with the operational development phase. It is an iterative incremental process where data scientists, data engineers, and operations worlds collaborate to build, automate, test, and monitor the machine learning pipelines like a Dev-ops project.