Digital transformations in manufacturing are about leveraging advanced technology to improve how a company operates. But, as the manufacturing industry focuses on digital transformation it must not forget the value of the'human element'. Concerns about the impact of technology were raised by Deloitte in an article that stated over 33% of the jobs in the UK are at risk of being replaced by automation in the next two decades. From the transportation industry to retail, automation is now taking the world by storm. Even restaurants around the world are now using iPads to streamline the process of taking orders and giving out receipts to customers.

Imagine standing in an elevator as the doors begin to close and suddenly seeing a couple at the end of the corridor running toward you. Even before they call out, you know from their pace and body language they are rushing to get the same elevator. Being a charitable person, you put your hand out to hold the doors. In that split second you interpreted other people's intent and took action to assist; these are instinctive behaviors that designers of artificially intelligent machines can only envy. But that could eventually change as researchers experiment with ways to create artificial intelligence (AI) with predictive social skills that will help it better interact with people.

This call for a better understanding of deep learning was the core of Ali Rahimi's Test-of-Time Award presentation at NIPS in December 2017. By comparing deep learning with alchemy, the goal of Ali was not to dismiss the entire field, but "to open a conversation". This goal has definitely been achieved and people are still debating whether our current practice of deep learning should be considered as alchemy, engineering or science. Seven months later, the machine learning community gathered again, this time in Stockholm for the International Conference on Machine Learning (ICML). With more than 5,000 participants and 629 papers published, it was one of the most important events regarding fundamental machine learning research.

Sensyne Health, a London-based healthcare artificial intelligence (AI) company founded by biotech entrepreneur Paul Drayson, recently launched an initial public offering (IPO) on the London AIM market. Drayson's plan is to raise $78 million. It's just one of many companies that are exploiting advances in computing, data science and AI to help identify and develop potential new drugs. Drayson was formerly the UK's Minister of Science in the Department for Business, Innovation and Skills until May 2010, and before that, Minister of State for Strategic Defence Acquisition Reform at the Ministry of Defence. Drayson co-founded vaccine maker PowderJect Pharmaceuticals in 1993 and sold it in 2003 to Chiron for 524 million pounds.

British Prime Minister Theresa May pledged in May that she would invest substantially in Artificial Intelligence (AI) to detect cancer in its early stage. This technology is expected to save 22,000 lives each year by 2033. French President Emmanuel Macron also aims to use AI to improve healthcare. He announced in March an investment of 1.5 billion euros (USD 1.7 billion) in AI development by 2022 to allow France to compete with China and the United States. 'Although Al has great potential, there are many obstacles to overcome for it to be widely accepted by the healthcare community.'

Artificial intelligence, defined as intelligence exhibited by machines, has many applications in today's society. More specifically, it is Weak AI, the form of A.I. where programs are developed to perform specific tasks, that is being utilized for a wide range of activities including medical diagnosis, electronic trading, robot control, and remote sensing. AI has been used to develop and advance numerous fields and industries, including finance, healthcare, education, transportation, and more. AI for Good is a movement in which institutions are employing AI to tackle some of the world's greatest economic and social challenges. For example, the University of Southern California launched the Center for Artificial Intelligence in Society, with the goal of using AI to address socially relevant problems such as homelessness. At Stanford, researchers are using AI to analyze satellite images to identify which areas have the highest poverty levels.[1] The Air Operations Division (AOD) uses AI for the rule based expert systems. The AOD has use for artificial intelligence for surrogate operators for combat and training simulators, mission management aids, support systems for tactical decision making, and post processing of the simulator data into symbolic summaries.[2]

You could easily be fooled into thinking that slowly but surely, robots are taking over the world. Automated processes, machine-led factories, homes that are'smart', digital friends; just a brief glance at the things that some of our more sensational media outlets use to foster a fear in human's technological advances. But, they are exactly that. It is our advances, our creations and intelligence that have propelled technology to the dizzy heights that it reaches today. In an ever-changing job market, the UK has seen many traditional roles move to automated processes.

The chief economist of the Bank of England has warned that the UK will need a skills revolution to avoid "large swathes" of people becoming "technologically unemployed" as artificial intelligence makes many jobs obsolete. Andy Haldane said the possible disruption of what is known as the Fourth Industrial Revolution could be "on a much greater scale" than anything felt during the First Industrial Revolution of the Victorian era. He said that he had seen a widespread "hollowing out" of the jobs market, rising inequality, social tension and many people struggling to make a living. It was important to learn the "lessons of history", he argued, and ensure that people were given the training to take advantage of the new jobs that would become available. He added that in the past a safety net such as new welfare benefits had also been provided.

Artificial intelligence has now become the focus of interest in most business areas. It is because in the past few years technological applications have compounded in terms of innovations and research. What failed in the late '50s (the period when AI originated) has now gained traction and is used in a vast array of areas. Tech companies and startups have now focussed on AI systems being their workhorse in tandem with their employees and have reinvented the way work is done. Additionally, AI startups are also on the rise.

I am exploring these ideas in a free coding workshop/ meetups in London. There is already a waiting list. We may hold more workshops next year depending on how these go. I have been involved in teaching Data Science for a few years now (Oxford University - Data Science for Internet of Things and also online). Over the years, I have tried to improve my teaching .. and adopt ideas from other domains into my teaching One such technique is Deliberate practice a technique which probably originated in the former Soviet Union to train world class athletes.