Coverage path planning (CPP) is the task of computing an optimal path within a region to completely scan or survey an area of interest using one or multiple mobile robots. Robots equipped with sensors and cameras can collect vast amounts of data on crop health, soil conditions, and weather patterns. Advanced analytics can then be applied to this data to make informed decisions, improving overall farm management. In this paper, we will demonstrate one approach to find the optimal coverage path of an agricultural field using a single robot, and one using multiple robots. For the single robot, we used a wavefront coverage algorithm that generates a sequence of locations that the robot needs to follow. For the multi-robot approach, the proposed approach consists of two steps: dividing the agricultural field into convex polygonal areas to optimally distribute them among the robots, and generating an optimal coverage path to ensure minimum coverage time for each of the polygonal areas.

Efficiency and productivity gains are two of the most-often cited benefits of implementing AI within the enterprise. The technology handles tasks at a pace and scale that humans can't match. At the same time, by removing such tasks from human workers' responsibilities, AI allows those workers to move to higher-value tasks that technology can't do. This allows organizations to minimize the costs associated with performing mundane, repeatable tasks that can be performed by technology while maximizing the talent of their human capital. "CIOs need to see where AI can help functions do more with less time and less resources, so they can [enhance] the experience for employees and users alike," said Beena Ammanath, executive director of Deloitte AI Institute.

If you have ever worked with text data, you have likely encountered the challenge of dealing with high-dimensional and sparse data. One popular solution to this problem is latent semantic analysis (LSA), also known as latent semantic indexing (LSI). LSA is a technique for extracting latent (hidden) semantics from a collection of documents or text data. It does this by mapping the documents into a lower-dimensional space, where the relationships between the documents and the underlying concepts they represent can be more easily understood. One of the key benefits of LSA is that it can handle large amounts of data efficiently and is robust to noise and sparse data.

If you have ever worked with machine learning algorithms, you have likely encountered the naive Bayes algorithm. This simple yet powerful classifier is widely used in a variety of fields, including natural language processing, spam filtering, and medical diagnosis, and has a number of attractive features that make it well-suited to these tasks. At its core, the naive Bayes algorithm is a probabilistic classifier that uses Bayes' theorem to predict the class label of a given sample. It does this by estimating the posterior probability of the class given the features, using the assumption that the features are independent of one another. One of the key benefits of the naive Bayes algorithm is its simplicity.

Just over a century since The Manifesto of Futurist Architecture declared the city must be rethought and rebuilt like an "immense and tumultuous shipyard" – "everywhere dynamic", and the house like a "gigantic machine", it may be that author Antonio Sant'Elia had things the wrong way around. Because although his machine-fetishising sketches inspired our common vision of a science-fiction future – as in Fritz Lang's 1927 film Metropolis, with its technological Tower of Babel an imposing centrepiece – it might be the gigantic machines that are making our houses. Architecture and AI visionaries – forming especially around MIT in the 1950s, through to the later work of MIT Media Lab co-founder Nicholas Negroponte – and design pioneers have long thought about automating the creation of our environments. Now the technology is catching up to their ideas, and a radical shift into AI-assisted design is taking hold, with implications that could radically transform the form, feel and function of the places we inhabit. Completely automated design is not quite there yet. This crop of generative, AI-assisted tools is rather new.

Obtaining Insights – While many service leaders jump to the cost savings potential of AI, one of AI's key benefits is in its ability to obtain insights and predictions. Insight generation allows organizations to move beyond cutting costs to generating value. Organizations can use these insights to guide agent and application decisions, ensuring customers receive the best service experience possible. Three examples of how AI is used to obtain insights in customer service are personalization, customer lifetime value and AI-based customer routing. Ensuring Optimal User Experiences – Another key benefit of AI is in how it creates optimal customer and agent experiences.

So, what are the benefits of Robot Process Automation? More efficient use of resources in the business (inbound/outbound) resulting in reduced cost and increased revenue streams by reducing overtime hours and higher productivity on projects, leading to more efficient use of time, personnel, capital, and other forms of capital.

Every day across Australia, truckies are driving thousands of kilometres to get fresh produce from farms to markets. But what if the truck could do this job, without a driver? The NASDAQ-listed company TuSimple is celebrating a milestone, after transporting watermelons from Arizona to Oklahoma City using an autonomous truck. There were two humans in the truck during the trial -- and they did take control of the vehicle at the front and back end of the journey -- but for more than 1,500 kilometres, the truck was driving itself. "Our business case is to take the human driver out," TuSimple's Jim Mullen said.

I like to say that I was born in Information Technology (IT) from my career perspective. I had my adolescence when Cloud Computing (Cloud) was the hot word and emerging technology. Now, I am entering my adult life with Artificial Intelligence (AI). Hopefully, I will live my third age and my retirement with art and philosophy, but we still have a lot of time for that. And across these years, I saw how AI and Cloud Computing had transformed humanity, both in consumer relations and social and professional habits.

"CIOs need to see where AI can help functions do more with less time and less resources, so they can [enhance] the experience for employees and users alike," said Beena Ammanath, AI managing director with Deloitte Consulting LLP. "As you deploy data and analytics into the enterprise, it opens up new opportunities for businesses to participate in different areas," he explained. For example, autonomous vehicle companies, with the reams of data they're collecting, could identify new revenue streams related to insurance, while an insurance company could use AI on its vast data stores to get into fleet management. Delivering a positive customer experience has become the price of doing business, said Seth Earley, author of The AI-Powered Enterprise and CEO of Earley Information Science. "We're trying to embody everything we know about the customer, the customer's needs, our solutions and the competition and then present to the customer what they need when they need it," Earley said.