Online spaces allow people to discuss important issues and make joint decisions, regardless of their location or time zone. However, without proper support and thoughtful design, these discussions often lack structure and politeness during the exchanges of opinions. Artificial intelligence (AI) represents an opportunity to support both participants and organizers of large-scale online participation processes. In this paper, we present an extension of adhocracy+, a large-scale open source participation platform, that provides two additional debate modules that are supported by AI to enhance the discussion quality and participant interaction.

The integration of artificial intelligence (AI) chatbots into higher education marks a shift towards a new generation of pedagogical tools, mirroring the arrival of milestones like the internet. With the launch of ChatGPT-4 Turbo in November 2023, we developed a ChatGPT-based teaching application (https://chat.openai.com/g/g-1imx1py4K-chatge-medical-imaging) and integrated it into our undergraduate medical imaging course in the Spring 2024 semester. This study investigates the use of ChatGPT throughout a semester-long trial, providing insights into students' engagement, perception, and the overall educational effectiveness of the technology. We systematically collected and analyzed data concerning students' interaction with ChatGPT, focusing on their attitudes, concerns, and usage patterns. The findings indicate that ChatGPT offers significant advantages such as improved information access and increased interactivity, but its adoption is accompanied by concerns about the accuracy of the information provided and the necessity for well-defined guidelines to optimize its use.

Ai is becoming more prevalent in the healthcare sector. India’s economy is expected to reach $1 trillion by 2035. AI spending in India increased by more than 109% in 2018, totaling $665 million. Artificial intelligence (AI) is becoming more prevalent in the workplace and is now being used in healthcare applications. The increase in healthcare data implies greater use of Artificial Intelligence (AI). Early disease diagnosis, drug design, drug trials, diabetic retinopathy, cancer treatments, cardiovascular disease, and eye care are some of the key areas where Artificial Intelligence is being...

Lung cancer continues to be the leading cause of cancer-related deaths globally, with 5-year survival rates still hovering around 20%. Tobacco use continues to be the major risk factor for lung cancer. However, in nonsmokers, exposure to some industrial toxins such as arsenic, certain organic compounds, radon, asbestos, radiation, air pollution, and environmental tobacco smoke also increases the chance of developing lung cancer. Although the incidence of these primary risk factors is decreasing, the implementation of comprehensive tobacco control and the reduction of occupational chemical exposure are not the only measures for decreasing lung cancer mortality. Artificial intelligence has been shown to be beneficial in the discovery of prognostic biomarkers for lung cancer diagnosis, treatment, and response evaluation, putting it at the forefront of the next phase of personalized medicine.

The innovations we make today are going to impact posterity in many ways. But is it necessary to keep technology and innovations away from our young kids? In fact, these young minds can become creators and thinkers by learning various technologies and computational skills. Don't you think the youth and kids should be engaged more with coding, robotics, and AI? An ISTE article Keri Gritt, technology co-ordinator at St. Stephen's and St.Agnes school in Virginia, who teaches coding to kindergartners says, "Before using programs or robots, she ties sequencing and commands to physical movement by having students follow a program listed with cards on a whiteboard, starting and stopping with begin and end commands. Students then write programs to guide a peer across the room, making turns and avoiding obstacles. They then move on to robots."

From greenhouse monitoring to seed-to-sale tracking, machine learning can be used as a technological solution in almost every stage of the cannabis retail chain. One of the largest complaints regarding the controlled environment agriculture is that it consumes too much energy. Unfortunately, cannabis cultivation, due to the nature of plants, requires a closely controlled environment in order to ensure a certain quality of harvest. This is because some of the cannabinoids found in hemp will be affected by the plant's growing conditions, i.e., it could negatively influence the concentration of cannabidiol (CBD) or other valuable chemical components. Outdoor cannabis environments, particularly in more northerly regions, are very risky and can limit your production periods to specific months of the year.

The incorporation of AI into LIMS will equip laboratories with enhanced capabilities, enabling better data retrieval and laboratory diagnostics. FREMONT, CA: The emergence of the laboratory information management system (LIMS) has transformed the pharmaceutical industry, enabling organizations to process numerous lab samples and streamline the laboratory workflow. It has bolstered the capabilities of laboratories with robust decision support and decision making. The integration of artificial intelligence (AI) with LIMS will enable organizations to resolve many of the challenges in the industry. A vast amount of data is gathered from the multiple tasks performed on a daily basis in clinical laboratories. The data has to be stored and recorded in an orderly manner to track useful information.

Manufacturers today are recognizing the significant benefits that autonomous mobile robots can offer. Conventional logistics solutions like forklifts and conveyor belts -- as well as traditional automated guided vehicles -- haven't allowed this level of flexibility or adaptability. Manufacturers and logistics companies trying to accommodate ever-changing customer demands will have difficulty if they rely solely on autonomous guided vehicles and other systems. As a result, manufacturers satisfied with one mobile robot have started to implement multiple AMRs in hopes of expanding them to internal logistics applications they hadn't realized could benefit from their use. To facilitate the process, they are using fleet management software, which offers centralized control of the robots from a single station.

There's an emerging consensus in the Great Customer-Service Debate--the one that pits human contact against automated self-service. It's that the best answer is for the two sides to join forces. Automated tools such as chatbots and interactive-voice-response (IVR) systems can be effective at handling rote requests but also work best when they're accompanied by a "click here for an agent" lifeline. And person-to-person interactions are most effective when the rep is supported by tech tools that help him deliver fast, on-point solutions to customers--not to mention the shorter wait times that can result when other customers are able to resolve their issues using self-service. Managing the handoff points between man and machine can be a challenge.

Think back to school and science class: You probably conducted an experiment where you placed an alarm clock (set to go off in 5 minutes) under a glass jar and the teacher pumped all the air out of the jar. When the alarm went off, you couldn't hear it, right? Without air, sound does not travel – nature abhors a vacuum. This is also true of artificial intelligence - it cannot survive in a vacuum and needs a rich ecosystem of data where it can thrive. This can only be achieved by integrating "trustworthy AI" systems with the rest of an organization's IT landscape.