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) …
The European Union is considering new legally binding requirements for developers of artificial intelligence in an effort to ensure modern technology is developed and used in an ethical way. The EU's executive arm is set to propose the new rules apply to "high-risk sectors," such as healthcare and transport, and suggest the bloc updates safety and liability laws, according to a draft of a so-called "white paper" on artificial intelligence obtained by Bloomberg. The European Commission is due to unveil the paper in mid-February and the final version is likely to change. The paper is part of the EU's broader effort to catch up to the U.S. and China on advancements in AI, but in a way that promotes European values such as user privacy. While some critics have long argued that stringent data protection laws like the EU's could hinder innovation around AI, EU officials say harmonizing rules across the region will boost development.
Your firm produces data, so surely it can benefit from applying AI, right? Here are five questions to ask yourself about whether a business problem is "AI-solvable". Machine learning, the latest incarnation of artificial intelligence (AI), works by detecting complex patterns in past data and using them to predict future data. Since almost all business decisions ultimately rely on predictions (about profits, employee performance, costs, regulation etc.) it would seem obvious that machine learning (ML) could be useful whenever "big" data are available to support business decisions. The reality in most organisations is that data may be captured but it is stored haphazardly.
Python has massive applications in Artificial Intelligence (AI) applications, data science, Machine Learning (ML) and data analytics, US-based online education company according to Coursera. The top 10 list of courses, such as "Programming for Everybody," Python Data Structures," Python for Data Science and AI," has been dominated by python. Python has a lot of advantages. One of them is that it is extremely easy getting started with. It offers a lot of flexibility.
An artificial intelligence system that allows self-driving cars to'see' around corners in real time could help prevent accidents, according to its developers. Researchers from Stanford University in the USA have created a system that bounces a laser beam off a wall to create an'image' of objects hidden from view. The'image' captured won't make sense to a human, but using artificial intelligence technology the system can create a visual reconstruction of the hidden view. The research was funded by US government agency DARPA (Defence Advanced Research Projects Agency), and is one of a number of similar technology programmes being developed. It could also be used by soldiers to see around walls, rescue workers searching for people and even in space travel to examine the interior caves of an asteroid.
As AI has permeated our lives most innovatively, the interest and investment are expected to grow further to drive the innovation engine across all sectors of society. Such large scale investments by government or private firms will create a long-appraised impact on society and its citizens. AI researches powered by such investment will help root-out the societally relevant problems to engage people in creating a more diverse workforce to better tackle the problems. The report "A 20-Year Community Roadmap for Artificial Intelligence Research in the US" highlights six significant areas where AI research is likely to impact in the next 20 years. In the near term, chronic health conditions like diabetes, cancer, and heart and neurological diseases are likely to benefit most from new applications of AI, according to a survey of healthcare professionals.
Can sensors see behind the corners of obstacles in real time? As it turns out, yes. A study by researchers at Stanford, Rice University, Princeton, and Southern Methodist University published in the journal Optica proposes a system that's capable of producing around-the-bend images at high resolutions and speeds. It's able to distinguish the submillimeter details of hidden objects from 1 meter away, and according to coauthor Felix Heide, it could be used to make out things like the license plates of hidden moving vehicles and personnel badges worn by walking individuals. "Non-line-of-sight imaging has important applications in medical imaging, navigation, robotics, and defense," said Heide.
The recent deep learning hype aims to reach the Artificial General Intelligence (AGI): an AI that would express (supra-)human-like intelligence. Unfortunately current deep learning models are flawed in many ways: one of them is that they are unable to learn continuously as human does through years of schooling, and so on. Regardless of the far away goal of AGI, there are several practicals reasons why we want our model to learn continuously. A real applications of these two constraints is robotics: a robot in the wild should learn continuously its environment. Furthermore due to hardware limitation, it may neither store all previous data nor spend too much computational resource.
The contact centre is changing. In the past, call centre agents had to process a large volume of standard calls, really quickly. But with the deployment of new technologies like artificial intelligence (AI) and robotic process automation (RPA) these agents no longer have to carry out incredibly repetitive tasks and can rather focus their attention on tackling more complex customer concerns. For call agents, RPA makes it possible to complete simple tasks across back-end systems, which reduces the amount of time spent on admin, says Adriaan van Staden, senior sales manager at call centre tech vendor Genesys South Africa. RPA is in its broadest sense an application that is governed by business logic and structured inputs, aimed at automating business processes.
Ancestry spent two years executing its shift to the cloud. After the move the company turned attention to optimizing its presence in the cloud, manually adjusting workload settings to improve efficiency and reduce costs. "Due to the fact that it's a manual process, we iterated very slowly," said Darek Gajewski, principal infrastructure analyst at Ancestry, in an interview with CIO Dive. "It takes time for us to do performance testing and then being able to get it out into our production environment safely so that we're not affecting our customers at the end of the day." But there was still room for improvement.
Users expect to see that friendly search box in their applications. They seem to really like it, because it's so simple to use. You don't need a user manual to figure out search. In fact, if your application doesn't have search, you'll be pelted with negative reviews. No wonder you see search in so many applications. It's very difficult to implement. We all know it's more than just simple text matching. Those of us with database backgrounds know that searching for "prefix*" is a lot easier than searching for "*suffix". And users want to do all sorts of weird searches like "*run*", which should match ran, or shrunken or brunt, or--you get the idea. Quick search results and performance are important, as is accuracy and ranking.