They believed that global population growth, industrialisation, pollution, food production and resource depletion would inevitably lead to economic collapse during the 21st century. They believed that global population growth, industrialisation, pollution, food production and resource depletion would inevitably lead to economic collapse during the 21st century. They were concerned not just about environmental issues, but also about economic ones: namely, that increasing population growth would lead to overconsumption and ultimately cause a collapse in resources (the so-called "Malthusian trap"). They believed that global population growth, industrialisation, pollution, food production and resource depletion would inevitably lead to economic collapse during the 21st century. They believed that global population growth, industrialisation, pollution, food production and resource depletion would inevitably lead to economic collapse during the 21st century.

Metaverse technologies are changing the game for manufacturers. From the way we make products to the way we manage them, there are some fundamental shifts underway thanks to AI, IoT and AR. The confluence of these technologies is enabling manufacturers to envision products and factories digitally before manifesting them physically. There are many interesting use cases in play already. The metaverse enables you to test as you build.

I am spending my last weeks on thinking about climate actions, sustainability and economical aspects of these. I listened to a lot of podcasts about these topics, and I have tens of notes from these podcasts. I decided to express my ideas about this topic. But no, it is not my turn to spread the ideas. Only thing I wrote for this article is headline and a couple of keywords.

Healthcare is on the brink of revolution, owing to the rapid industrialisation of medicine. We are not talking about'global challenges', but far from meeting them. Healthcare is very splintered across the geography that it would be impractical to implement "technological advances" without giving due cognisance to socio-cultural issues. I find it surprising, because investors' "money (either in the form of grants or venture capital) can be better used by working on modest goals, thereby scaling them. Academia is highly risked averse in several ways; grant committees find it easier for a group think and there's no funding of a breakout idea.

"Every company is a technology company." This quote from Gartner represents businesses increasingly adopting sophisticated technologies to achieve their goals. Artificial Intelligence is one of the most important business opportunities in 2019. Knowing what it takes to apply these new technologies to work at scale and give a greater competitive edge, is the real differentiator. As with any other technology, a business considering AI should undergo a Proof of Value (POV) to get started.

The last few years have been auspicious for artificial intelligence. Once the preserve of Silicon Valley's tech giants, AI has emerged as a tool that businesses small and large have become keen to harness for disparate use-cases in domains ranging from cybersecurity to customer service and analytics. Data scientists, tasked with creating machine learning-driven tools, are now ubiquitous in most industries. As AI's presence and influence grows across the business world, one key potential pitfall should not be overlooked: data. AI systems are generally powered by machine learning, a technique that creates smart systems through the recursive training of algorithms on vast troves of data – in the case at hand, we are talking about data that companies create and gather throughout their daily businesses.

Automation and the advancement of technology is reshaping the modern economy, how we consume and how we produce. Can the digitisation of daily interactions, whether transactional or relational, engender improved human relations? Digital technological development can be considered a liberating and connecting force in some contexts, while its threat to human livelihoods and liberties raises ethical issues as its integration with social and economic exchange grows. Developed societies are supported predominantly by a service economy, which is increasingly shaped by the nature and capabilities of the digital technologies that facilitate it. The nature and use of these technologies is disrupting traditional social behaviours and expectations.

Bias – both human and data-based – is the biggest ethical challenge facing the development and adoption of artificial intelligence, according to a panel of world-leading AI luminaries. Speaking at last week's Dreamforce conference, Salesforce chief scientist and adjunct professor of Stanford's computer science department, Dr Richard Socher, said the rapid development of AI will inevitably impact more and more people's lives, raising significant ethical concerns. "These algorithms can change elections for the worse, or spread misinformation," he told attendees. "In some benign natural language processing classification algorithms, for example, you may want to maximise the number of clicks, and find something with a terminator image has more clicks so you put more of those pictures in articles." But it is the bias coming through existing datasets being used to train AI algorithms that arguably presents the biggest ethical problem facing industries.

Global IT services major Accenture said it has started seeing industrialisation of digital technology services such as cloud, analytics, cyber security. The company, which claims to have 60 per cent of the new deal bookings in digital cloud and cyber security, has started seeing a shift from the proof of concept (PoC) stage for digital technology-based services. Accenture said its new order book in the first quarter of 2018 (ended on November 30) stood at $10 billion. "Indeed, we see a shift of the budget to the digital technology at large...We are moving from what i would qualify in last couple of years proliferation of the PoC and now we are moving to the industrialisation of the deployment of the digital capabilities and of course it is creating strong demands," Pierre Nanterme, Chairman and chief executive officer, Accenture, told analysts in a call. IT services players across the global such as Accenture, IBM, Tata Consultancy Services, Infosys, Cognizant, Wipro witness an increasing demand for service delivery using technologies such as cloud computing, artificial intelligence, machine learning.