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If you would like to harness the power of artificial intelligence to aid you in the creation of your next song or music video. You might be interested in a new video created by AI enthusiast Matt Wolfe. Artificial intelligence (AI) has emerged as a game-changer a wide variety of different sectors including AI art generation, writing and more. As well as offering innovative tools that can assist in creating songs and music videos.

This AI music writing overview guide provides an in-depth look into how some of these AI tools can be utilized to create a new songs and accompanying music videos, a process that is not only fascinating but also accessible to anyone with an interest in music and technology.

They were then assigned a series of practical consulting tasks for a fictional shoe company and had their performance graded by human and AI raters.

The greatest gains were seen by below-average performers using AI, whose average performance improved by 43%.

Their above-average counterparts only saw an average performance increase of 17% from using AI.

Artificial intelligence (AI) is the term used to describe the use of computers and technology to simulate intelligent behavior and critical thinking comparable to a human being. John McCarthy first described the term AI in 1956 as the science and engineering of making intelligent machines.

This descriptive article gives a broad overview of AI in medicine, dealing with the terms and concepts as well as the current and future applications of AI. It aims to develop knowledge and familiarity of AI among primary care physicians.

PubMed and Google searches were performed using the key words ‘artificial intelligence’. Further references were obtained by cross-referencing the key articles.

Antibiotic resistance is a major danger to public health that threatens to claim the lives of millions of people per year within the next few decades. Years of necessary administration and excessive application of antibiotics have selected for strains that are resistant to many of our currently available treatments. Due to the high costs and difficulty of developing new antibiotics, the emergence of resistant bacteria is outpacing the introduction of new drugs to fight them. To overcome this problem, many researchers are focusing on developing antibacterial therapeutic strategies that are “resistance-resistant”—regimens that slow or stall resistance development in the targeted pathogens. In this mini review, we outline major examples of novel resistance-resistant therapeutic strategies. We discuss the use of compounds that reduce mutagenesis and thereby decrease the likelihood of resistance emergence. Then, we examine the effectiveness of antibiotic cycling and evolutionary steering, in which a bacterial population is forced by one antibiotic toward susceptibility to another antibiotic. We also consider combination therapies that aim to sabotage defensive mechanisms and eliminate potentially resistant pathogens by combining two antibiotics or combining an antibiotic with other therapeutics, such as antibodies or phages. Finally, we highlight promising future directions in this field, including the potential of applying machine learning and personalized medicine to fight antibiotic resistance emergence and out-maneuver adaptive pathogens.

The use of antibiotics is central to the practice of modern medicine but is threatened by widespread antibiotic resistance (Centers for Disease Control and Prevention (U.S.), 2019). Antibiotics are a selective evolutionary pressure—they inhibit bacterial growth and viability, and antibiotic-treated bacteria are forced to either adapt and survive or succumb to treatment. The stress of antibiotic treatment can enhance bacterial mutagenesis leading to de novo resistance mutations (Figure 1A), promote the acquisition of horizontally transferred genetic elements that confer resistance, or trigger phenotypic responses that increase tolerance to drugs (Davies and Davies, 2010; Levin-Reisman et al., 2017; Bakkeren et al., 2019; Darby et al., 2022;). Additionally, antibiotic treatment can select for the proliferation of pre-existing mutants already in the population (Figure 1B).

In recent years, there has been a growing trend in higher education to incorporate modern technologies and practices in order to improve the overall educational experience. Learning management systems, gamification, video assisted learning, virtual and augmented reality, are some examples of how technology has improved student engagement and education planning. Let’s talk about AI in education. The classroom response system allowed students to answer multiple-choice questions and engage in real-time discussions instantly.

Despite the many benefits that technology has brought to education, there are also concerns about its impact on higher education institutions. With the rise of online education and the growing availability of educational resources on the internet, many traditional universities and colleges are worried about the future of their institutions. As a result, many higher education institutions need help to keep pace with the rapid technological changes and are looking for ways to adapt and stay relevant in the digital age.

By now, you’ve probably heard about ChatGPT, the AI chatbot developed by OpenAI, that has been taking social media by storm. But what exactly is ChatGPT, and why is everyone talking about it? We asked it directly, and here is a comprehensible answer for non-tech people:

When people program new deep learning AI models — those that can focus on the right features of data by themselves — the vast majority rely on optimization algorithms, or optimizers, to ensure the models have a high enough rate of accuracy. But one of the most commonly used optimizers — derivative-based optimizers— run into trouble handling real-world applications.

In a new paper, researchers from DeepMind propose a new way: Optimization by PROmpting (OPRO), a method that uses AI large language models (LLM) as optimizers. The unique aspect of this approach is that the optimization task is defined in natural language rather than through formal mathematical definitions.

The researchers write, “Instead of formally defining the optimization problem and deriving the update step with a programmed solver, we describe the optimization problem in natural language, then instruct the LLM to iteratively generate new solutions based on the problem description and the previously found solutions.”

ChatGPT went down on Wednesday morning — and the timing of its outage couldn’t have been more unfortunate. While OpenAI’s world-beating chatbot suffered its second major outage in as many weeks, big tech executives were convening in Washington to plead their case to lawmakers over the future of AI.

Among several notable figures in attendance was Sam Altman, CEO of the AI startup — who probably hoped to put on a better face amidst increased scrutiny over ChatGPT’s falling user traffic for the past several months.


This was yet another notable outage that ChatGPT has suffered in the past several weeks as user traffic falls.

The CEO of Polish drinks company Dictador is an AI-powered humanoid robot who works 7 days a week. The AI boss, named Mika, told Reuters that she doesn’t have weekends and is “always on 24/7.” Mika helps to spot potential clients and selects artists to design the rum producer’s bottles.

The humanoid robot CEO of a Polish drinks company is one busy boss.


Polish drinks company Dictador appointed an AI-powered humanoid robot called Mika as its experimental CEO in August 2022.

Imagine living in a cool, green city flush with parks and threaded with footpaths, bike lanes, and buses, which ferry people to shops, schools, and service centers in a matter of minutes.

That breezy dream is the epitome of urban planning, encapsulated in the idea of the 15-minute city, where all basic needs and services are within a quarter of an hour’s reach, improving public health and lowering vehicle emissions.

Artificial intelligence could help urban planners realize that vision faster, with a new study from researchers at Tsinghua University in China demonstrating how machine learning can generate more efficient spatial layouts than humans can, and in a fraction of the time.