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) …
In media news today, a women's group says'good riddance' to Chris Cuomo after CNN firing, Brooke Baldwin calls on the liberal network to replace Cuomo with a woman, and an MSNBC anchor appears to downplay Bob Dole's accomplishments because of his support for Trump. Washington Post columnist Dana Milbank doubled down Monday on his recent op-ed that claimed "sentiment analysis" data proved the media is tougher on President Biden than they were on former President Trump. Milbank's piece, titled, "The media treats Biden as badly as - or worse than - Trump. Here's proof," cited research from Forge.ai, a data analytics unit of the information company FiscalNote. The study used algorithms focused on adjectives and their placement in articles - more than 200,000 of them - to rate the coverage Biden received in the first 11 months of 2021 and the coverage Trump got in the first 11 months of 2020.
In the 21st century, the concept of a twin need not be confined to fraternal or identical--a twin can be digital too. Digital twins have caught the eyes of some of the biggest companies in the world--Amazon and Nvidia, for instance, both made announcements about new digital-twin initiatives within the last month--as well as those of specialists like infrastructure engineering software company Bentley Systems. The concept started gaining traction at the beginning of the century, and picked up steam in the early 2010s when the rise of IoT made digital twins more feasible. As of 2020, it was estimated to be a $3.1 billion market, per Markets and Markets, and projected to grow into a $48.2 billion industry by 2026. So...what is a digital twin?
Advancing trustworthy AI and machine learning to mitigate agency risk is a priority for the US Department of Energy (DOE), and identifying best practices for implementing AI at scale is a priority for the US General Services Administration (GSA). That's what attendees learned in two sessions at the AI World Government live and virtual event held in Alexandria, Va. last week. Pamela Isom, Director of the AI and Technology Office at the DOE, who spoke on Advancing Trustworthy AI and ML Techniques for Mitigating Agency Risks, has been involved in proliferating the use of AI across the agency for several years. With an emphasis on applied AI and data science, she oversees risk mitigation policies and standards and has been involved with applying AI to save lives, fight fraud, and strengthen the cybersecurity infrastructure. She emphasized the need for the AI project effort to be part of a strategic portfolio.
Data accuracy is the most crucial part of the decision making in any business. An error that occurred in the process may cause you enough damages to crash you down. This is the core reason for the birth of data entry services or data processing services where businesses ask help to digitize and manage their data. Accurate data is a major component in the success of any firm, and no one is going to reject this fact. Artificial intelligence and automation are used currently to ensure that man-made mistakes are negligible and hence the accuracy is high in the database.
CURT NICKISCH: Welcome to the HBR IdeaCast from Harvard Business Review. A growing number of companies are turning to artificial intelligence to solve some of their most vexing problems. The promise of AI is that it can go through vast amounts of data and help people make better decisions. And one area where companies often search for profitable use cases for the technology is in marketing. It's harder than it looks. Data scientists at one consumer goods company recently used AI to improve the accuracy of the sales forecasting system. While they did get the system working better overall, it actually got worse at forecasting high margin products. And so the new, improved system actually lost money. Today's guest says that many leaders lean too heavily on AI and marketing without first thinking through how to interact with it.
Probability is one of the most common terminologies, not only in mathematics but also in the real world. We use the word probability frequently. About seven years ago, I was in my secondary level of education and got introduced to the term probability as a topic of mathematics. At that time, I had solved so many mathematical problems regarding probability. Unfortunately, it did not seem interesting to me.
The amount of input being generated for the Internet is making an adversarial network of all the minds available to it. Generative adversarial networking individual intelligences is the legacy of freely communicating new concepts built by mental media connections that billions of independent cognitive creators have to each other because of the Internet. The concept of GAN training a neural network is a trivial attempt to comprehend how creativity can be applied to Artificial Intelligence. But this has only led to a recognition that a digitized data absorption of information gleaned from the Internet, as a resource, has natural response functions of the human brain speeding past GPT-3's ability to anticipate directions it's possible for Artificial Intelligence to take. An interconnection of minds is actually recognized by Artificial Intelligence as more meaningful to it than the value of its applications.
Jean-Michel Besnier is a French philosopher who teaches at Sorbonne University in Paris. His research focuses on the philosophical and ethical impact of science and technology on individual and collective representations and imagination. We met with him to talk about the consequences of the explosion of robotics and artificial intelligence (AI) in the healthcare sector, especially since the beginning of the Covid-19 pandemic. MedicalExpo e-magazine: Can you give us your definition of artificial intelligence? Jean-Michel Besnier: I have the same definition that everyone has. I am more attentive to the conceptual extension of the notion of artificial intelligence, which at the beginning referred to something rather simple, that is to say the implementation of devices capable of solving problems in an automatic or algorithmic way.