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Artificial Intelligence

The term Machine Learning (ML) is much in use now, but few understand it for exactly what it is. Ultimately ML is something that uses statistics to find patterns across huge quantities of data warehousing done. Some key digital- era giants such as Facebook, Twitter, Netflix, Baidu, Google and YouTube are all at the forefront of this. Social media companies and search engines use this data to mobilize their digital marketing efforts, even using voice assistants in the process. It all owes to an invention dating back to the year 1986, by Geoffrey Hinton. The related field is called deep learning, but this one goes even more to the depths, and in much quicker time. Neural networks work similar to how the human brain is wired. This ML comes in three major forms. These are known as supervised, unsupervised and reinforcement learning.

Source:https://www.technologyreview.com/s/612437/what-is-machine-learning-we-drew-you-another-flowchart/

Uploaded Date:03 July 2019

The general understanding is that while the rise of Artificial Intelligence (AI) will cause a lot of jobs loss, it will also generate new ones. Corporate leaders must now be thinking what to do next to engage with this trend. One area in which people will need to work on will be soft skills. The frequency of management training sessions will need to be increased in order to equip employees with these skills. These will be necessary to collaborate with smart machines. Soft skills includes a whole host of skills such as social and emotional intelligence, creativity, sensory perception and complex reasoning. Responsible AI will thus mark a new frontier. Shifts in learning will now need to be accommodated for training the existing personnel.

Source:https://sloanreview.mit.edu/article/revisiting-the-jobs-artificial-intelligence-will-create/

Uploaded Date:26 June 2019

A professor from the Toronto- based Rotman School of Management has explained the economics and the subsequent impact of Artificial Intelligence (AI). Professor Ajay Agrawal, besides training the MBA students, also works with several startups from the field at the Creative Destruction Lab. He has written a new book, titled Prediction Machines: The Simple Economics of Artificial Intelligence, co- authored by fellow academicians. To harness the true powers of AI, the book says that a time- frame has to be worked out, within which the operations will be put in to place. The progress once started, will be exponential. The machines need be trusted. Before conducting any business analytics operation, based on the data available, one needs to know the requirements. The company must know what kind of insights are desired. A kind of learning loop must be created, making it easier for all team members to obtain the relevant information. Data, judgment and action and further growing in importance.

Source:https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-economics-of-artificial-intelligence

Uploaded Date:26 June 2019

The term Artificial Intelligence (AI) conjures up a certain vision reminiscent of science fiction movies. But its real impact at present is much more understated. Enterprise Cognitive Computing (ECC) is now proving to be an essential bit in the area of robotics and automation. It is utilized to use AI for enhancing business operations. It helps in getting formulaic and routine tasks done. For ECC to be successful, large quantities and clean content of data warehousing needs to be done. ECC has the ability to sieve through humongous quantities of data to bring out the useful business insights. A study conducted in 2017 confirmed, that more than three- fifths of industry representatives, want to the adoption of ECC applications within five years. But by now, few have walked the talk. ECC can also help a lot with research and development, especially in the pharmaceutical space.

Source:https://sloanreview.mit.edu/article/using-ai-to-enhance-business-operations/

Uploaded Date:24 June 2019

There is much hype now in the digital age regarding the use of artificial intelligence to business. A lot of stories have emerged on AI bots and killer robots. But before plunging headlong, any company needs to understand what exactly works, and what is mere hype. Self- driving cars are proving to be quite a rage now. But at present, more than the accrual usage, more important is the data warehousing. This will ensure that the right insights are generated for a future when such vehicles will be in greater use. A lot of the technologies which are proving to be hits, are not completely novel, but in fact extensions of earlier innovations such as that of business analytics. The Internet of Things is also proving to be a substantial hit. Investments are also soaring in. The entire investment trajectory is following the S curve. In sales and marketing in particular, AI investments are getting hot.

Source:https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/artificial-intelligence-in-business-separating-the-real-from-the-hype

Uploaded Date:15 June 2019

The payments industry has long had a challenge with obtaining fair compensation. One of the reasons for this is the spread over diverse markets as is the case presently. However, there is good news now, in the shape of reduced customer- attrition rates and volume losses. This is by use of advanced business analytics. This involves mining diverse data to extract the deeper insights. There has been a positive client- revenue impact as per data supplied by McKinsey. To make sure that usable insights are extracted, the leadership needs to ensure clean and proactive data warehousing. Otherwise, inaccuracies will creep in. Data engineering and improvements in computational engineering are further making inroads. Spark Beyond is one such new tool that is proving to be extremely useful in this. Another is XG Boost, which uses Machine Learning capabilities. All these help in early adoption of pricing rates as per customer or client requirements.

Source:https://www.mckinsey.com/industries/financial-services/our-insights/how-machine-learning-can-improve-pricing-performance

Uploaded Date:15 June 2019

Artificial Intelligence (AI) may now well be considered the automobile that symbolizes the digital economy. Its fuel is big data. SMEs will need to create value so that they may leverage the power of AI, else as is the trend, the Big Tech firms will continue to monopolize this too. The AI Forum was held recently in Singapore to discuss the future of the industry and the challenges that will be associated. First of all, AI will need to be demystified. Before embarking on its full- scale adoption, a complete audit needs to be done on it, to understand its expected financial impact. The INSEAD in order to cope with these changes, has added micro- classes on the topic, in its Executive MBA curriculum. Which all applications are to be adopted, also need to be determined. The boundaries of work and transformation sought, too need to be well- defined at the outset.

Source:https://knowledge.insead.edu/blog/insead-blog/three-objectives-for-moving-forward-with-ai-11561

Uploaded Date:08 June 2019

There are major ways in which the world economy has by now been affected by Artificial Intelligence (AI). The potential to contribute to the pool of global economic activity has risen multifold. A study conducted by the McKinsey Global Institute confirms that by the year 2030, about seventy percent of the companies would have adopted AI in some form or the other. The adoption rates for AI though could differ widely among companies, workers and even countries. Among companies, digital- natives or early adopters would be the ones primed to take key advantage. Workers will be affected by the talent recruitment patterns, where those with higher digital skills will get preference. Among countries, it is those which are either developed, or on the cusp of high growth, who will gain from most of the AI initiatives. Skilling and reskilling people is now of utmost concern for most players in the market.

Source:https://www.mckinsey.com/featured-insights/artificial-intelligence/notes-from-the-ai-frontier-modeling-the-impact-of-ai-on-the-world-economy

Uploaded Date:07 June 2019

Enterprise decision- making is now being influenced a lot by the newer paradigms that are gaining strength. Business decisions are now being made by making use of the vast treasure troves of data now available. Artificial Intelligence (AI) is set to combine with the latent human intelligence to curate greater autonomy at work. Organizations are now investing a lot on business analytics, so now increasingly resembling math houses. Data science is being made use of for extracting business insights. Even AI is being tweaked from the predictive to the prescriptive model. Companies need to build an engineering mindset in their teams to take advantage of this era of change. Constant learning, relearning and unlearning has to take place. Design thinking and behavioral science will need to act as the pivots behind this transformation.

Source:https://www.forbes.com/sites/cognitiveworld/2018/10/15/reimagining-enterprise-decision-making-with-artificial-intelligence/#3e86ccf52fd6

Uploaded Date:07 June 2019

It is now well- appreciated that Machine Learning (ML) and Artificial Intelligence (AI) will both play a major role in all kinds of up coming businesses, including in manufacturing. The foundation for the success of this is data warehousing, which needs to be executed with utmost care. If one can collate this with Maslow’s Hierarchy, then data is the base level on which all else is dependent on. This includes external data, sensors and user- generated content. The right infrastructure and data’s storage form the second tier. Business analytics, metrics, features and aggregates find themselves higher up the chain. Further ahead is A/B Testing and ML algorithms. Right on top of this pyramid lie AI and deep learning. This pyramid has been created by Monica Rogati.

Source:https://www.forbes.com/sites/willemsundbladeurope/2018/10/18/data-is-the-foundation-for-artificial-intelligence-and-machine-learning/#6215dac251b4

Uploaded Date:07 June 2019

Newly minted technologies are not only disrupting the age- old work styles, they are questioning the very existence of industries. Indeed, this is further giving way to more questions on the society itself. Pitched battles are now figuratively being fought between teams of robots and humans on either side. While the former do bring a certain sense of order and efficiency, the latter may have the edge when it comes to creativity and understanding emotions. Talent recruitment processes too are getting altered, as several industries are staring at a possible jobless future. Silicon Valley and Wall Street are both getting bombarded with such ideas. The human agenda thus needs to be reclaimed. Algorithms cannot provide us with direction, but are merely a means of completing the tasks.

Source:https://www.strategy-business.com/article/Team-Human-vs-Team-AI?gko=4d55d

Uploaded Date:20 May 2019

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