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) …
Most energy companies today struggle with the complex technological and economic challenges involved in detecting, monitoring and preventing cyberattacks on critical infrastructure. The operational technologies (OT) and information technologies (IT) responsible for running energy systems today were never engineered to be secured in a digital environment; doing so poses a technical challenge tough to solve and difficult for small and mid-sized operators to afford. Yet in today's digital energy ecosystem, the failure of weak links can take down critical infrastructure for all participants. Protecting the entire system requires all industrial operators – both large and small – to detect and defend against cyberattacks. New developments in artificial intelligence (AI) based solutions can help all energy companies put defenders ahead of attackers, while adapting to the changing energy landscape.
When you hear the term "AI," many people would think that this is a super robot that is going to destroy the world. Although this is a part of AI, that isn't what AI is. Artificial Intelligence is intelligence demonstrated by machines, which is the opposite of our intelligence, Natural Intelligence. How were we able to create an intelligence inside of code? The answer is pretty simple.
In my first article on Time Series, I hope to introduce the basic ideas and definitions required to understand basic Time Series analysis. We will start with the essential and key mathematical definitions, which are required to implement more advanced models. The information will be introduced in a similar manner as it was in a McGill graduate course on the subject, and following the style of the textbook by Brockwell and Davis. A'Time Series' is a collection of observations indexed by time. The observations each occur at some time t, where t belongs to the set of allowed times, T. Note: T can be discrete in which case we have a discrete time series, or it could be continuous in the case of continuous time series.
Artificial intelligence technologies are being used across industries to automate and improve the efficacy of different activities. The advanced machine learning systems are equipped to replicate the discreet thinking and analysis patterns demonstrated by humans. This allows companies to leverage AI in performing some of the complex cognitive tasks with minimal human intervention. While AI can be applied to varied use-cases, social media is one segment where it has become a major catalyst for companies to grow. For example, AI chatbots for business are helping companies to stay connected with their audience.
There is an old saying that data rises to meet available storage. That is one reason I laughed at the phrase "big data" when it came out. We've always been working with as much data as possible. What has changed now is that the data volumes in artificial intelligence (AI), HPC, and other modern arenas is finally hitting a wall that's not storage space or processing power, it's the bandwidth for the two work together with low latency for the variety of data requests that exist. Newer solutions are coming out in order to address that problem.
COVID-19 virus hit us hard. Warnings from Nicolas Taleb that our interconnectedness could cause wide pandemic were true. Schools are closed and most of us are working from home, spending time in isolation and trying not to spread the virus. At the moment when I am writing this, all the borders in my home country are closed, all bars and malls are closed and you can not go out after 5 PM. Apart from that, this pandemic has a huge impact on the economy.
In a survey of hundreds of healthcare decision-makers, Intel found that the percentage of respondents whose company is currently – or will be – using artificial intelligence nearly doubled after the onset of COVID-19. Among the predicted use cases for AI: early intervention analytics, clinical decision support and specialist collaboration. "Artificial intelligence in health and life sciences has greatly accelerated," said Stacey Shulman, vice president of the Internet of Things Group at Intel, in a blog post accompanying the findings. "From helping clinicians develop personalized protocols to streamlining clinical workloads or unlocking insights in genomics, infusing AI into these industries may be much closer than many initially thought," she said. Intel conducted an online survey of 200 senior decision-makers at healthcare organizations in April 2018, and then 230 in July 2020.
We are excited to be talking with Future of Work thought leaders about remote work and on-demand talent in our Uprisor podcast series. Clinton Bonner, VP at Topcoder, recently spoke with Davar Ardalan, the founder and storyteller in chief at IVOW AI (IVOW stands for Intelligent Voices of Wisdom). In this episode, Clinton and Davar discuss the evolution of artificial intelligence and Ardalan's work of shaping AI with cultural intelligence. Enjoy the conversation and check out highlights below. As a tech entrepreneur and storyteller, Davar is dedicated to improving the future of automation by shaping it with the important element of cultural intelligence.
Geoffroy Didier (FR, EPP) is a vice-chair of Parliament's Special Committee on Artificial Intelligence in a Digital Age While AI technologies are beneficial and deserve to be encouraged at the European level, they must nevertheless be regulated to remain trustworthy. AI must be a tool for humans, mastered by, and at the service of, humans. As rapporteur for the EPP Group, I campaigned for, and obtained from all the political groups, a commitment that the European Parliament officially advocates for a fair balance between technological progress and human respect. We have convinced all political groups of the need to regulate only high-risk technologies so as not to hinder economic innovation, particularly among SMEs. While some technologies, such as facial recognition, are significant and clearly deserve to be controlled, others - such as leisure applications on a cell phone - should in no way be subject to the same normative constraints.