The shape-shifting, artificial intelligence (AI)-powered cars seen in futuristic films aren't appearing anytime soon but AI technology certainly exists today in the auto market and will be increasingly visible in the future. Industry observers are saying that AI and machine learning have reached a tipping point and will cause enormous advances through the next few years in many markets. In the automotive sector, these technologies will be transformative. Analysis firm IHS Markit predicted that the installation rate of AI-based systems in new vehicles would rise by 109% in 2025, compared to a modest 8% adoption rate in 2015. In February 2017, Ford paid $1 billion for artificial intelligence start-up Argo AI.

Instead of talking about artificial intelligence (AI) many describe the current wave of AI innovation and acceleration with – admittedly somewhat differently positioned – terms and concepts such as cognitive computing or focus on several real-life applications of artificial intelligence that often start with words such as "smart", "intelligent", "predictive" and, indeed, "cognitive", depending on the exact application – and vendor. Despite the term issues, artificial intelligence is essential for and in, among others, information management, medicine/healthcare, data analysis, digital transformation, security (cybersecurity and others), various consumer applications, scientific advances, FinTech, predictive systems and so much more. There are many reasons why several vendors doubt using the term artificial intelligence for AI solutions/innovations and often package them in another term (trust us, we've been there). Artificial intelligence (AI) is a term that has somewhat of a negative connotation in general perception but also in the perception of technology leaders and firms. One major issue is that artificial intelligence – which is really a broad concept/reality, covering many technologies and realities – has become like a thing we talk about and also seem to need to have an opinion/feeling about, with thanks to, among others, popular culture. Hollywood loves AI (or better: superintelligence, not the same).

Recently there has been an explosion of buzz words related to Artificial Intelligence. My goal with this article is to discuss the differences between Artificial Intelligence, Machine Learning and Cognitive Technology. I invite you to join in, it is very likely I am missing elements that you might be more familiar with. Artificial Intelligence (AI) is the hype at the moment. In most cases, the hype is related to a specific subclass of AI known as narrow AI.

AI is clearly a hot topic for insurers. InsurTech startups are creating compelling new use cases and applications for data, algorithms and AI within the insurance space. It is, indeed, an exciting time for insurance. Yet many traditional insurers may read Rick's article with concern and potential fear. In a recent survey by KPMG International, 91 percent of insurance CEOs admitted being worried about the challenge of integrating automation, AI and cognitive robotics into their existing business and operating models.

US tech giant Apple is reportedly not working on Siri-powered speaker just like Amazon Echo, an artificial intelligence (AI)-based speaker that can be controlled by voice. "The future goal of the technology is to utilize Siri as an'omnipresent AI assistant across devices' rather than have a central hub," Times reported on last week. How Siri would become omnipresent is not known at this point. Earlier this week, Apple acquired Israel-based start-up RealFace that develops deep learning-based face authentication technology. Set up in 2014 by Adi Eckhouse Barzilai and Aviv Mader, RealFace has developed a facial recognition software that offers users a smart biometric login, aiming to make passwords redundant when accessing mobile devices or PCs, as reported yesterday.

Data is the new natural resource that can empower every citizen in a country like India, Microsoft's India-born CEO Satya Nadella said on Monday during a discussion on the digital world, cloud computing and artificial intelligence. There is need for "recognising that data is the new natural resource instead of looking at it as being unevenly spread" for empowering every citizen of India, Nadella said in a dialogue with Infosys co-founder Nandan Nilekani. In India, several state governments are using data resources and computing power for governance, Nadella said. The government of Andhra Pradesh is using cloud services to track high school dropouts in order to build interventions while ICRISAT is using machine learning to improve the yield of farmers, he said. "I was looking at the big consumers of the public cloud (computing) and one thing that came up was the Election Commission in Tamil Nadu,'' Nadella said with reference to the usage of CCTV cameras in Tamil Nadu at election booths in 2016. Nadella said that the broad technology areas that he is currently excited about is cloud computing, artificial intelligence and augmented reality. Much of the entrepreneurial energy in India is around cloud computing, he said. What has been seen so far in terms of artificial intelligence is statistical machine learning by using the power of data and real AI is still in the future, Nadella said. "In Punjab, I believe we took all the call centre data … We analysed the speech so that the government can get a better handle on what are the issues that can be automated and what needs human services.

Across the globe, energy systems are changing, creating unprecedented challenges for the organisations tasked with ensuring the lights stay on. In the UK, large fossil fuelled power stations are being replaced by increasing levels of widely distributed wind and solar generation. This renewable power is clean and free at the point of use but it cannot always be relied upon. To date National Grid has managed this intermittency by keeping polluting power stations online to make up the difference but Artificial Intelligence offers an alternative approach. What's needed is a smart grid which can integrate renewable energy efficiently at scale without having to keep polluting power stations online to manage intermittency.

The Microsoft chief's comments come in the wake of Bill Gates' call for levying taxes on robots that take away jobs from people, reports Ayan Pramanik Microsoft chief executive Satya Nadella has warned that embracing Artificial Intelligence without reskilling people will have an impact on jobs, even as it has displayed efficiency in delivery of government services. "I think it is an exciting future, but at the same time, you have to be very mindful of the impact of AI on jobs. That's why I want to make sure some of the skilling work we are doing in India is going to help people," said Nadella at an interaction with the architect of Aadhaar, Nandan Nilekani. Nadella's comments come in the wake of Microsoft founder Bill Gates' call for levying taxes on robots that take away jobs from people. Nadella pointed out that Microsoft had been able to use AI to improve efficiency in government services in Punjab and Andhra Pradesh.

Machine learning has simplified the heavy lifting of collecting and analyzing data. Even with the most advanced techniques, data scientists spend countless hours developing, testing and retooling analytic models one step at a time. Worse yet, most organizations cannot find enough data scientists to complete this labor-intensive work. The impact is that we have not yet fully realized the promise of continuous intelligence; until now. The field of machine learning offers promises to streamline the application of analytics and create a new era of autonomous data. It adds massive efficiencies to the process by automating the construction of these models.

Machine learning (ML) has evolved in leaps and bounds. While some still remain skeptical about its progress, most enterprises are excited about the ample opportunities that would open up with the growth of machine learning. Machine learning is a part of the gigantic field of Artificial Intelligence (AI). It has been just a few decades since AI was introduced. With machine learning, like the name implies, the machine learns.