He starts off by informing us how financial institutions are forced to rely on expensive and cumbersome KYC (Know Your Customer) initiatives to conduct verification of account opening details and to get additional customer information and documentation. And even when efficiently run this processes fail to uncover the underlying motive of the account owners.

With Financial Crime Enforcement  Network (FinCEN) having come out with new Anti –Money Laundering provisions which in its new Fifth pillar requirement mandates account specific transactional review and analysis from May 11^th, 2018, Until now the financial institutions had a client –centric approach to their customer relations and avoided review of individual accounts. But with the Fifth pillar provision coming into effect, Financial Institutions in order to improve their risk management proficiency  are now required to ascertain the accounting objective, account history along with volumes and value of transactions particular to each account.

And going further, financial institutions to mitigate risk also need to monitor, investigate suspicious client activity which involves constant maintenance and up gradation of client information.

These fifth pillar requirements may be addressed effectively by the adoption of new technologies like Artificial Intelligence (AI), machine learning and Big Data. Financial institutions can reduce money laundering risks by deploying solutions to analyze massive amounts of both structured and unstructured data to extract precise information to analyze and review a specific transaction.

Financial Institutions deploying appropriate Data science and AI technologies may address new requirements like Link analysis, Transactional analysis and it may also seek to undertake help from Outside Investigative Sources and Unsupervised Machine Learning Techniques to help meet the growing regulatory demands of state, federal and international regulators.

For more please visit: https://upside.tdwi.org/Articles/2017/08/30/ADV-ALL-AI-Helps-Financial-Institutions-Perform-Due-Diligence.aspx?Page=2

According to her, even as there are much still not convinced about the indispensable role machine learning and other artificial intelligence technologies will play in future enterprises, there are many who have used these technologies to make their enterprises smarter, faster and more creative.

Citing CB insights to bring home the point, she shows that it’s not only big tech companies buying AI firms but traditional businesses are also getting into this race by acquiring AI startups and this together with the fact that 34 AI acquisitions were done by in Q1 of 2017, highest at any point of time, indicating wider acceptance of AI.

AI is riding on the convenience of cloud computing, the pervasiveness of processing power, huge, no-cost storage options, and providing enterprises the opportunity to leverage their data by applying machine learning to deliver best in the class customer experience with optimal resources. Vivian then proceeds to bring out how different technology behemoths are using machine learning to increase customer‘s experience.

Pinterest manages to deliver the right pin at the right moment by leveraging machine learning for content discovery, in this, the content recommendations are algorithmically driven and machine learning is used to determine among billions of user interactions the right pin to deliver at the right time. Similarly, Netflix uses machine learning to understand consumer watching pattern, surfing insights thus bring data –informed decision making to content discovery. Amazon‘s Alexa team is trying to surmount the challenges of Natural Language Processing and Generation as we are moving from typing to talking computers.

For more, please visit: https://www.forbes.com/sites/vivianrosenthal/2017/05/30/how-machine-learning-will-reinvent-business/#6e1845c0715b

In this article, Hannah Williams documents the keynote address of Neil Harbisson – artist and cyborg activist at the annual SAS global forum, in this address Neil Harbisson deliberates on the cyborg project which made possible the development of artificial sensors which were then implanted in humans to transmit senses.

This project started with Neil Harbisson himself getting implanted with  antennae in the skull to overcome his inability to identify color, this antennae enabled him to hear the frequencies of light in colors.  As Neil elaborates in his address his aim was not to wear or use technology which propelled him to go for a new sensory organ, a sensory organ to sense color, a third eye for color implanted, but then this would have limited his perception of color to what was in front of him. Observing nature made him to create a antennae limited for color perception which enabled to sense colors both in the front and behind just by moving the antennae. This antennae along with its ability to perceive colors was also developed with a feature to send internet transmissions to Neil Harbisson‘s brain facilitating him to receive color from external devices from around the world.

As Neil tells in his address, he sees this as a use of internet as a sense organ or a sensory extension which he feels  will become more prevalent in 2020′s and  the internet  will not limited to be used only as a tool or   for communication but also as an extension of senses to perceive colors and other bodies.

And as with everything else nowadays, the aspect of security is one big questions for which answers need to be found since according to Gartner study, 25% of security attacks in enterprises will be from IoTs and as another HP study discovered an average IoT device has around 25 security flaws most of which the enterprises and users are unaware of. And with internet connected sensory devices built to be implanted in human bodies the security fears raises to different level altogether.

Hannah William in this article cites another example of attempt to merge technology with human brain, this one coming from Elon Musk of Tesla fame, launching a company – Neuralink, where the focus is on the development of neural lace with embedding of string of small electrodes in human brain. The company is working on the concept of merging human brain with computer technology.

Accompanying these examples of artificial  sensory  devices , is the concern about security , since internet as a stand- alone is not secure and how can one be sure when it is paired with human brain.

For more on this please visit  : http://www.cbronline.com/news/internet-of-things/cognitive-computing/rise-cyborg-ready-augmented-humans/

AI advancement – Big Data is advancing the speed and capacity of Artificial Intelligence and taking it to the next level, for example  Google DeepMind AI beating humans in the game of Go, and becomes unbeatable as the game progresses due to AI and the Big Data applied to its functioning.

Tax Shelters Unveiled – Investigative journalists collaborating across continents and using cloud based data analytics and Big Data were able to pursue effectively and unveil tax shelters now famously known as “Panama papers”.  This is one of the first known instance of the real-world good, Big Data can contribute to bring about.

Human Trafficking – Big Data is lending its helping hand to “Polaris Project” in its fight against human trafficking, even though Polaris project has made tremendous progress over the years  in their fight, Big Data became their strongest tool in the year 2016 to decipher the complex numbers and patterns to give useful insights and help victims of this  horrific crime.

Cancer Research – Intel’s Bryce Olson , himself a cancer survivor lead, Trusted Analytics platform is “ a collection of Big Data tools and data analytics, to help in breaking down of DNA – the complex code of human genetics to give insights into where cancer begins and how it can be controlled”.

HIV Outbreaks – When Centre of Disease Control were struggling to contain the HIV outbreak in 2016, which was taking extensive death toll and seriously damaging the health of survivors, they turned to Big Data for insights to fight the outbreak.

In 2016 we were witness to the fact that Big data in addition to its applications in optimizing business efficiency and effectiveness can also be deployed to harness real- world good, and we are sure to see more such deployments in the coming years.

For more on this, please read: http://insidebigdata.com/2017/02/26/2016-big-year-big-data/

Quoting figures from various market research agencies, Gil Press starts off by showing how artificial intelligence markets is growing and will continue to grow in the coming years, for instance he cites Narrative Science survey to tell that 38 % of all enterprises are using AI in some form or other and this reach 62% by the year 2018, or IDC estimates the AI market to grow from 8 Billion in 2016 to 47 Billion by 2022.

Artificial Intelligence, the word coined in 1955 to describe one of the disciplines of computer science todays encompasses various technologies of which some have stood the test of time and some new.

Based On Forrester‘s TechRadar Report On Artificial Intelligence, Gil Press lists out his top ten artificial intelligence technologies

1. Natural Language Generation                                              6.Decision Management
2. Speech Recognition                                                                  7.Deep Learning Platforms
3. Virtual Agents                                                                             8.Biometrics
4. Machine Learning platforms                                                9.Robotic process Automation
5. AI Optimized Hardware                                                          10.Text Analysis & NLP

As with every technology AI too faces few obstacles for adaption along with some big benefits and according to a survey Forrester   conducted last year, some of the obstacles voiced were – No clear use case – 42%, To clear for what it can used for – 39%, No required skills – 33%, First to invest in data management systems -29%, no budget -23%, AI systems are not proven – 14%,

Forrester concludes that once enterprises overcome these obstacles they will be ready to use AI and gain from using AI in customer facing application and developing an interconnected web of enterprise intelligence.

For more, please visit:  http://www.forbes.com/sites/gilpress/2017/01/23/top-10-hot-artificial-intelligence-ai-technologies/2/#252d8c64179e