Cybersecurity refers to security devices, tools and laws aimed at protecting computer systems
against attacks from cyberspace.

In this week’s Muse newsletter, we explore the extent to which artificial intelligence pretexts a third revolution in modern warfare. A global test case for the wartime use of AI has been seeded deep in the drama and pain of the current Ukrainian conflict.

The Metaverse is already upon us: 2.5 billion people who are interacting and trading money online in the market areas of digital worlds. Multiple visions of its future have been built upon the convergence of virtual reality and of ambient computing.

A non-fungible token (NFT) is essentially a tradeable code attached to metadata about a real- work event, object, or transaction. A secure network of computers records the sale of an NFT on a digital ledger (a blockchain), giving the buyer proof of both authenticity and ownership.

The vision of Web3 is built upon open-source technology, utilizing blockchain technology to build trustless and permissionless information architectures.

“AI for Good” is a mindset that focuses on the process of data-driven decision-making in business and society.

In what conditions can AI improve human potential? In the field of Human Resources, management is looking to artificial intelligence to redefine the function, to improve its contribution to the organization, and/or optimize its core processes.

The application of artificial intelligence in business raises the question of managerial responsibility: to what extent are managers held responsible for the ‘automated’ decisions taken by the tools entrusted to them? Automated decision-making leverages algorithms based on derived profiles, as well as assumptions about how we think.

Industry 4.0 refers to “smart” and connected industrial systems designed to sense, predict, and interact with the physical world that support production in real time.

Artificial intelligence has the potential to revolutionize healthcare by improving patient prognostics, increasing the efficiency of therapy, and reducing costs of treatment.

Digital well-being refers to the overall well-being of individuals in our increasingly digitally intermediated society. The notion of digital well-being encompasses our physical, mental, and emotional well-being as it relates to the use of digital technology.

Artificial Intelligence (AI) is rapidly transforming higher education in a multitude of ways. When harnessed to bolster student outcomes, AI gives higher education institutions the ability to anticipate enrollment trends, optimize recruitment efforts, and elevate academic performance.

Artificial intelligence (AI) presents numerous opportunities for the banking and finance industry, ranging from improved customer experiences to enhanced risk management and fraud detection.

We look here at the unique legal and ethical challenges that both the legal profession and their regulators need to address.

As applications of artificial intelligence in both business and society become more ambitious, digital ethics has become a growing concern for both individuals and governments.

Leveraging Artificial Intelligence can significantly enhance supply chain management through improving forecasting accuracy.

Machine learning models today analyze historical data and real-time information to predict demand, allowing companies to optimize the flow of goods and services, avoiding stockouts, and/or minimizing the costs of unneeded inventory.

In the 19th century, battlefields were located in open fields hidden from public scrutiny. In the 20th century, and especially in the 1930s, the battlefield moved into cities, where victory or defeatwasshaped byurbanbuildingsandarchitecture.Inthe21stcentury,thebattlefieldhas moved on to cyberspace where it is no longer constrained by physical realities. Aggressor and defender are no longer engaged face to face, but on screens thousands of miles apart.

Augmented soldier, whether wearing exoskeletons or an AR helmets, can gather and transmit real- time information, helping them to better identify their targets.

The editors of Muse™ would like to complement COP28 with a look at how the development of prediction models based on artificial intelligence (AI), more specifically machine learning (ML) and deep learning (DL), can help to improve weather predictions and to combat the consequences of climate change disruption.

AI may not be the miracle tool capable of combating climate change. It can, however, improve weather forecasting results by revolutionizing current calculation methods.

The use of artificial intelligence (AI) is increasing each year across an increasing number of domains (business activities, artistic creation tools, weather prediction, etc.) in our society.

The monetary costs of deployment vary with the economic models used by each organization.

However, there exists a hidden cost of which few people are aware. This is the environmental cost (carbon dioxide [CO2] emissions) of training an AI model.

In the realm of banking and finance, organizations of all sizes have harnessed the power of artificial intelligence to enhance operational efficiency, gain insights into customer behavior, and pioneer innovative financial products.

In this exploration of Developing an AI Talent Supply Chain, MUSE™ is pleased to welcome
Ismaelle Haddouzi

CEO & Founder e-Peak People HR, SaaS solutions for managing human potential, skills, competencies and performance. And thanks to Davy Cielen for his contribution to the introduction.

Leveraging artificial intelligence in smart grid management creates opportunities for optimized energy processes, predictive maintenance, and efficient demand-side management.

AI-driven predictive analytics can anticipate and mitigate potential grid failures, optimize energy generation and distribution, and enable proactive maintenance strategies, leading to cost savings, reduced carbon emissions, and improved resource utilization. Additionally, AI-powered optimization algorithms can optimize energy dispatch, grid congestion management, and demand response programs, further enhancing grid efficiency and resilience.

Before we start looking at the various uses of artificial intelligence (AI) in the agronomy sector. It’s important to remember what agronomy is, and isn’t.

Agronomy, like AI, is not just about one discipline, it’s about many. Agronomy includes all the sciences related to the world of agriculture. It includes the natural sciences (chemistry, biology, zoology…), economic and social sciences (finance, management…), STEM (Science, Technology, Engineering, and Mathematics).