It is the whiz-kid of the artificial intelligence (AI) world that others are trying to emulate. In the four months since its November 30 launch, ChatGPT has shown the ability to perform a wide range of tasks, from cracking the bar and medical licensing exams in the United States to writing emails and songs, building apps, and more. The fact that it is freely available for public use has opened up a plethora of opportunities previously thought beyond the realm of possibility of AI -- even though the app's makers have faced criticism for opacity around the programming they have used to train it. Developed by OpenAI, a company backed by Microsoft, ChatGPT became the fastest-growing consumer app in the world two months after its launch, with more than 100 million users by January. That early success has prompted Microsoft to integrate its Bing search engine and Edge browser with the technology running ChatGPT in the hope of improving the experience of users.

In August, Elon Musk announced that he was developing a humanoid robot called "Tesla Bot" -- a prototype of which will supposedly be ready in 2022. The presentation itself was slightly bizarre, both because the bot was represented on stage by a dancing human in a bodysuit, and because Musk has warned for years about the dangers of artificial intelligence. But he was right about one thing: AI and robotics could eventually lead to a future where technology is so advanced that our role, much of our work and even our purpose in life could fundamentally change. As someone who has studied and worked in AI for the better part of four decades, my contention is that this change will likely come faster and go further than many of us anticipate -- even if it's driven more by AI-powered software than dancing robots. The question is how we're going to prepare.

BEIJING: As a journalist, I always try to ask smart questions. But I could not beat the questions that a group of five-year-olds posed to China's top artificial intelligence (AI) guru, like the ones in the headline of this article. People pay attention to what Dr Lee Kai-Fu says – lots of people. Fifty million people in China follow him on social media, which means he has more fans than American talk show host Oprah Winfrey. One of his tag lines is "AI is reshaping the world as we know it".

BEIJING: As a journalist, I always try to ask smart questions. But I could not beat the questions that a group of five-year-olds posed to China's top artificial intelligence (AI) guru, like the ones in the headline of this article. People pay attention to what Dr Lee Kai-Fu says – lots of people. Fifty million people in China follow him on social media, which means he has more fans than American talk show host Oprah Winfrey. One of his tag lines is "AI is reshaping the world as we know it".

New technologies bring innovations, in business, and change the course of the work being done. But does a technical revolution bring shift in employment patterns too? The Industrial Revolution which began in the 18th century was a transition to new manufacturing processes characterised by new inventions. The industrial revolution effectively increased the output levels and also saw improved systems of transportation, communication and banking. But the Industrial Revolution also took some key sacrifices, the change destroyed traditional jobs, but it also created new ones.

Find out what the future of manufacturing looks like at the SMAS Future Manufacturing Conference 2017, and get practical support and advice on how you can start to leverage the opportunities of Industry 4.0. With manufacturing at a crossroads of challenges and opportunities, how will these smart technologies give your business competitive advantage, improve productivity, shorten product development cycles and produce products as efficiently and cost effectively as possible? What will it mean for your workforce as the number of routine jobs decrease, while the number of higher value jobs grows? The SMAS Future Manufacturing Conference 2017 will focus on four key themes during the packed one-day programme: Technology in Manufacturing – investing in a factory fit for the future with automation, augmented & virtual reality, sensors, additive manufacturing and cloud computing.

SITTING IN AN office in San Francisco, Igor Barani calls up some medical scans on his screen. He is the chief executive of Enlitic, one of a host of startups applying deep learning to medicine, starting with the analysis of images such as X-rays and CT scans. It is an obvious use of the technology. Deep learning is renowned for its superhuman prowess at certain forms of image recognition; there are large sets of labelled training data to crunch; and there is tremendous potential to make health care more accurate and efficient. Dr Barani (who used to be an oncologist) points to some CT scans of a patient's lungs, taken from three different angles.

We all know that technology has had and will continue to have huge benefits. And technology has always had a deep impact on human work, both destroying old jobs turned obsolete, and creating new jobs. We have seen that many times over the course of history with agriculture, steam power, electricity, electronics and IT, and now with digital, machine learning and AI. If you look at the past 20 years, technology has caused a stagnation of routine jobs, where computers and robots have already started to replace human work to a large extent. This has been compensated by a rise of non-routine jobs as indicated hereafter (US example: million jobs by type over time).

Much ink has been spilled on the subject of how the jobs market is being impacted by artificial intelligence (AI) and robotics. The well-known study by economists Frey and Osborne published in 2013, which predicts that 47% of all currently existing jobs in the United States will come under threat over the next twenty years, is regularly brought out of the cupboard as a terrifying spectre. Other far more optimistic studies, based on longer time-frames, have delivered a riposte to this – largely unfounded – scaremongering, which has in fact been repeated many times over throughout our history. However, the potential impact of AI on general education and vocational skills training – two means of preparing people for the labour market – is still being largely disregarded. The model whereby you learn during the first half of your life and spend the remaining years applying what you have learned in the world of work has held up pretty well.

SITTING IN AN office in San Francisco, Igor Barani calls up some medical scans on his screen. He is the chief executive of Enlitic, one of a host of startups applying deep learning to medicine, starting with the analysis of images such as X-rays and CT scans. It is an obvious use of the technology. Deep learning is renowned for its superhuman prowess at certain forms of image recognition; there are large sets of labelled training data to crunch; and there is tremendous potential to make health care more accurate and efficient. Dr Barani (who used to be an oncologist) points to some CT scans of a patient's lungs, taken from three different angles.