"Innovate or die" is now truer than ever before. AI is impacting industries across the board. It is transforming sectors that were characterized by long-standing, time-tested processes and cultures and for whom inculcating new changes was considered incredibly difficult. AI with its chatbots, recommendation systems, etc. is doing to the industry what cloud computing did 10 years ago. So much so that International Data Corporation (IDC) predicts that global spending on AI will reach $57.6 billion by 2021. Let us take a look at the various sectors which are being impacted by the surge in AI.

Radiological sciences in the last ten years have advanced in a revolutionary manner, especially when it comes about medical imaging and computerized medical image processing. These techniques help in the understanding of the disease as well as initiation and evaluation of ongoing treatment. Apart from this, the dataset of these images is used in further analysis of such diseases occurring around the world as a whole. Heather Landi, a senior editor at Fierce Healthcare, writes in an article that IBM researchers estimate that medical images, as the largest and fastest-growing data source in the healthcare industry, account for at least 90 percent of all medical data. We can use a computer to process and manipulate the multidimensional digital images of psychological structures in order to visualize hidden characteristic diagnostic features that are very difficult or perhaps impossible to see using planer imaging methods.

Search is a key part of many AI problem-solving strategies that assist in exploring the problem spaces. As explained by Peter Norvig "Normal programming is telling the computer what to do when we know what to do. AI is when we tell the computer what to do when we don't know what to do." Search in AI provides as a first step to start solving many of the problems, either it is finding a sequence of next steps to perform by an agent or deciding on the next game move. Many search strategies are used in AI for efficient and goal-oriented searches. Let's have a look at a few popular AI search strategies: Breadth-First Search (BFS) is the most basic searches and it finds the shortest path with respect to a number of steps between the start and goal. Simple BFS does not consider any edge costs or weights.

Across the globe almost each and every domain have started embracing Internet of Things (IoT). Weather its manufacturing, industrial automation, healthcare or artificial intelligence domain the impact of IOT is pretty evident. In the recent past we have seen some really exciting developments in the field of IOT especially how users have started interacting with machines. According to a research the key reason why businesses are adopting IOT solutions are primarily because to increase productivity of their workforce, reliability on their operation, and increase quality of their product or services. In the coming years IoT will create a significant impact of several industries, through this blog I am trying to briefly explain few of them.

Simple explanations of Machine Learning and Artificial Intelligence, and how they're related… but not at all the same thing. Artificial Intelligence (AI) and Machine Learning (ML) are very much on the minds of tech companies and business owners alike. Business owners are slowly coming around to the notion that they'll need something to help them make sense of an increasingly data-centric world, while tech leaders are busy investing in the future of AI. The investment in AI is already paying off for many tech companies, as software has become noticeably smarter all around us. Intelligent homes are in trend now wherein devices like smart speakers, refrigerators, lights, appliances are being integrated quickly.

Yeah journey of machine learning development and adoption is much interesting then any other once. From past story of machine learning, it has renounce with much powerful effect this time. Machine learning is just to ask machine to learn from previous data records. It is being useful in taking fast decision where human power is fail to do so. Lets take some piratical example of live world where machine learning has been already applied, self driving cars, friend's suggestion on social media, movies or videos suggestion on online video library and many more.