Propelled by the rapid development of innovative technologies and agribusiness-tech partnerships, modern farming is on the verge of the kind of digital transformation process seen across many other industries. In fact, research predicts that by 2026, the AI in agriculture market will grow at over 25% per year to reach a value of $4 billion. According to the same study, this impressive acceleration in the adoption of AI is due to the "increasing implementation of data generation through sensors and aerial images for crops, increasing crop productivity through deep learning technology, and government support for the adoption of modern agricultural techniques." But where is this tech-led innovation being focused? Smart farming, for example, is an autonomous end-to-end system that can gather and process key datasets to give actionable insights.

All businesses need a system to accurately track their expenses. Without it, they would not be able to keep reliable records and would likely soon find themselves in financial trouble. To track expenses, most businesses rely on some form of expense management software. However, not all expense management software options are created equal. One such example is expense management software that's powered by AI.

Among various applications of AI technology in the pharmaceutical industry, some are viewed as most important and worth more depth of exploration. The first step in drug development is to understand the biological origin and mechanism of the disease, and then to determine suitable targets through high-throughput technologies such as shRNA screening and deep sequencing, and finally to find relevant patterns through a large number of diverse data sources. This is huge work and often presents an important challenge for traditional methods. Unlike traditional methods, AI can systematically analyze existing literature and data in just a few seconds. This real-time "omics" database analysis can more accurately understand pathological cells and molecular mechanisms, and it can be used for complex diseases such as neurodegenerative diseases.

Artificial intelligence is now becoming an integral part of our lives and has defined its role in various fields. Now Artificial Intelligence is no longer just confined to movies related to science fiction. We find it is a part of our routine lives and in our classrooms. Since there are many AI tools in the market such as Google Assistant, Amazon Alexa, and Apple's Siri, we are just starting to see the presence of AI in the field of education as well. Here are some key benefits of Artificial Intelligence in education which helps in the overall learning experience. The personalization in education is one of the benefits that Artificial Intelligence is expected to contain in its armory.

Enterprises are adopting machine learning at a rapid rate and the reasons why are clear.

Automation is often seen as one of the main reasons to adopt machine learning. By automating tasks, enterprises can reduce human errors and free their workforce up to focus on more valuable tasks. In industrial settings, this often means programming physical machines to perform a task. Increasingly, these robots are being given a layer of machine learning to help them perform the task more intelligently. Image recognition and computer vision are enabling bots to navigate the physical world, helping them perform things like sort shipments and move pallets.

Previously I have written about the reality and potential of ongoing efforts to integrate blockchain with the internet of things (IoT). Now I am going to look at how encrypted, distributed ledgers could unlock new frontiers for another cutting-edge technology: artificial intelligence (AI). AI, as the term is most often used today is, simply put, the theory and practice of building machines capable of performing tasks that seem to require intelligence. Currently, cutting-edge technologies striving to make this a reality include machine learning, artificial neural networks and deep learning. Meanwhile, blockchain is essentially a new filing system for digital information, which stores data in an encrypted, distributed ledger format.

Decisions made by AIs can sometimes be hard for humans to understand. This is because they are capable of assessing a large number of variables independently of each other and "learning" which ones are important to the overall task it is trying to achieve. As an example, AI algorithms are expected to increasingly be used in making decisions about whether financial transactions are fraudulent, and should be blocked or investigated. For some time though, it will still be necessary to have these decisions audited for accuracy by humans. And given the huge amount of data that can be taken into consideration, this can be a complex task.

Previously I have written about the reality and potential of ongoing efforts to integrate blockchain with the internet of things (IoT). Now I am going to look at how encrypted, distributed ledgers could unlock new frontiers for another cutting-edge technology: artificial intelligence (AI). AI, as the term is most often used today is, simply put, the theory and practice of building machines capable of performing tasks that seem to require intelligence. Currently, cutting-edge technologies striving to make this a reality include machine learning, artificial neural networks and deep learning. Meanwhile, blockchain is essentially a new filing system for digital information, which stores data in an encrypted, distributed ledger format.

Previously I have written about the reality and potential of ongoing efforts to integrate blockchain with internet of things (IoT). Now I am going to look at how encrypted, distributed ledgers could unlock new frontiers for another cutting-edge technology: artificial intelligence (AI). AI, as the term is most often used today is, simply put, the theory and practice of building machines capable of performing tasks that seem to require intelligence. Currently, cutting-edge technologies striving to make this a reality include machine learning, artificial neural networks and deep learning. Meanwhile, blockchain is essentially a new filing system for digital information, which stores data in an encrypted, distributed ledger format.