Bangalore: India has been ranked on the third spot after the USA and China in terms of artificial intelligence (AI) implementation, according to BCG study- "The Ghost in the Machine: Artificial Intelligence in the Factory of the Future." The Boston Consulting Group (BCG) study surveyed manufacturing and technology managers from about 1100 industrial companies worldwide about their applications of and willingness to invest in AI. Almost 90 percent of executives said that they aim to integrate AI in their processes in the next three years. Nonetheless, so far only 28 percent have created a clear strategy for AI in manufacturing. Nine out of ten executives' worldwide plan to apply artificial intelligence (AI) in manufacturing in the next three years.

Smart machines are giving storytellers and risk managers alike a helping hand. Burgeoning data analyzed by ever more intelligent machines are opening pathways to surprising applications and providing solutions to problems that have been out of reach. In the film industry, machines "watch" movies and videos, charting their emotional intensity and giving content creators clues about to how to make stories more appealing. And in banking, AI's ability to detect anomalies among millions of transactions helps bank risk officers eliminate false positives that are a drain on productivity. For a growing number of industries, AI is tilting the playing field--you'll need to understand how before your competitors do. Machine-learning models can help screenwriters and directors fine-tune scripts and imagery.

Automatic classification of trees using remotely sensed data has been a dream of many scientists and land use managers. Recently, Unmanned aerial vehicles (UAV) has been expected to be an easy-to-use, cost-effective tool for remote sensing of forests, and deep learning has attracted attention for its ability concerning machine vision. In this study, using a commercially available UAV and a publicly available package for deep learning, we constructed a machine vision system for the automatic classification of trees. In our method, we segmented a UAV photography image of forest into individual tree crowns and carried out object-based deep learning. As a result, the system was able to classify 7 tree types at 89.0% accuracy. This performance is notable because we only used basic RGB images from a standard UAV. In contrast, most of previous studies used expensive hardware such as multispectral imagers to improve the performance. This result means that our method has the potential to classify individual trees in a cost-effective manner. This can be a usable tool for many forest researchers and managements.

The Butterfly Effect is the theory where one small change in the starting condition of an event can have a monumental effect on the outcome of such an event. The term was coined by Edward Lorenz and is derived from the metaphorical example of the details of a tornado being influenced by minor effects of the flapping of wings of a distant butterfly several weeks earlier. Lorenz discovered the effect in 1961 when he was running a numerical computer model to redo a weather prediction. The result was a dramatically different weather scenario. Interestingly, he did this on a computer.

The creation of ethics modules that can be inserted into a variety of classes may help ensure that ethics as a subject is not marginalized and enable professors with little experience in philosophy or with fewer resources to incorporate ethics into their more technical classes. This post will outline some of the topics that professors have decided to cover in this field, as well as suggestions for types of assignments that may be useful. We hope that readers will consider ways to add these into their classes, and we welcome comments with further suggestions of topics or assignments. With regards to ethics, some of the key topics that professors have taught about include: deontology, consequentialism, utilitarianism, virtue ethics, moral responsibility, cultural relativism, social contract, feminist ethics, justice consequentialism, the distinction between ethics and law, and the relationship between principles, standards, and rules. Using these frameworks, professors can discuss a variety of topics, including: privacy, algorithmic bias, misinformation, intellectual property, surveillance, inequality, data collection, AI governance, free speech, transparency, security, anonymity, systemic risk, labor, net neutrality, accessibility, value-sensitive design, codes of ethics, predictive policing, virtual reality, ethics in industry, machine learning, clinical versus actuarial reasoning, issue spotting, and basic social science concepts.

While slightly more than one-quarter (27%) of working Canadians fear their job is at risk due to the potential introduction of A.I./machine learning/automation in their workplaces, nearly one-in-three (31%) believe the introduction of these new approaches would help them do their job better – more so than any other mainstream technology available today. Three-in-five (59%) said they believe A.I. and automation will have a positive impact on the workforce overall in the future. "Much of the narrative around A.I. and automation in the workforce to date has included speculation about job loss," said Holger Kormann, President, ADP Canada. "However, the reality is that many Canadian employees see these tools as the next wave of resources to help them improve personal productivity and performance and not as a threat to job security or future employment prospects." Nearly all respondents (97%) say that technology has impacted the way they work each day, with smartphones (83%), laptop (80%) and desktop (79%) computers and social media (61%) having the greatest impact.

Despite the off-putting headlines and the ongoing shuttering of physical store locations, fashion apparel retailers might have reason to be hopeful. New technologies continue to serve as a beacon of hope -- and survival -- for merchants and suppliers.As chief scientist of JDA Software Group Inc.'s research and development team and supply chain innovation hub, Suresh Acharya described current conditions as "amazing times where new innovations" are coming out of research and are "capturing people's imaginations." Machine learning, artificial intelligence and predictive analytics is transforming retail. Here, Acharya shares his thoughts on the technologies that are shaping and disrupting the industry.WWD: There is a lot of discussion in the market about how artificial intelligence and machine learning is transforming business processes.

The BBC is "really worried" by a new tactic by fake news propagandists and fraudsters who are exploiting the rise of chat apps to spread false content carrying the broadcaster's trusted branding. The organisation has found itself repeatedly targeted by what appears to be a mixture of state-backed political activists, opportunistic fraudsters and malicious pranksters, who are grafting the BBC's famous logo onto false reports that are shared on the largely unregulated chat platforms. The trend represents a new dimension in the fake news threat and a major challenge to democratic processes and to news organisations in protecting their brand reputations. The BBC last week felt obliged to issue a formal warning after a clip purporting to show the BBC reporting on the outbreak of nuclear war between Russian and NATO forces in the Baltic went viral on WhatsApp and other chat platforms as a piece of breaking news. In other instances, the BBC's branding has been used to give a false sense of authentication to concocted election results, and in creating malicious news'reports' designed to damage corporate targets.

Machine learning is already a big part of modern life. Machine learning algorithms work in Google's search results, Spotify's music recommendations, and Uber's ride-sharing matches. The use of the technology will accelerate as companies find new applications in finance, health, energy, manufacturing and other sectors. Machine learning brings great opportunities for new businesses, but poses significant disruption to established companies and traditional employment. There's much uncertainty but it's clear that machine learning will be a transformational force over the careers of current MBA students.

Kiwi businesses need to get on board with artificial intelligence - despite mass adoption of the technology being years away. AI is expected to increase productivity and skilled workforce, according to a leading national report commissioned by the AI Forum New Zealand, to be released on May 2. New Zealand AI Forum executive director Ben Reid says artificial intelligence could soon become part of our daily working lives in a similar way as the internet or electricity has. Both of those changes were transformational to the way that the economy and businesses operate," Reid said. "If AI adoption follows a similar pattern to those other major technologies, then it will be a similar number of years in terms of business uptake, so between 20 and 40 years for mass adoption of AI throughout all businesses and all society." AI and machine learning will be front and centre at the next PwC Herald Talks event in Auckland and Wellington.