Shamayita Acharya

On March 18, 2019, I was notified by the University of Technology Sydney that I had officially completed my PhD (yay!). As a result, I now hold a PhD in management. During my PhD, I researched how emerging information technologies such as big data analytics, blockchain and artificial intelligence, challenge organisation design and strategic management, and bring the role of data in organising to the fore. Big data analytics empower consumers and employees, resulting in open strategy and a better understanding of the changing environment. Blockchain enables peer-to-peer collaboration and trustless interactions. And, AI facilitates new and different levels of involvement among human and artificial actors. From these interactions and responses, new modes of organising are emerging, where technology facilitates collaboration between stakeholders and where human-to-human interactions are increasingly replaced with human-to-machine and even machine-to-machine interactions. My New Book:

The World Economic Forum released an encouraging report for anybody interested in a career as a data analyst. They stated that data analytics will be the fastest growing profession over the next decade. This report is consistent with statistics compiled by IBM. Big Blue said that around 700,000 new data scientist and data engineer jobs will be created by the end of next year. These types of economic forecasts tend to be reasonably accurate. However, it is difficult to cite them with exact precision. A number of conflating factors could reduce or increase the demand for data analytics jobs in the foreseeable future. Here are some of the factors that could impact future demand for this rapidly growing profession. A shortage of skilled data professionals could temper demand Supply and demand for big data professionals is a two-way street. If there is a shortage of people willing and able to fulfill the job requirements, then demand could also stagnate. Why would this occur? If n

It’s more possible than ever these days for anybody to be an entrepreneur in their own right. The rise of the ‘gig economy’ has opened the doors for people to monetize their skills on their own schedule. There are plenty of websites available for freelancers to connect with clients for business support and independent contracting for various tasks and short-term projects. This type of professional lifestyle is also incredibly attractive to younger generations entering the workforce, but it is certainly not limited to Millennials and recent college grads. More and more workers are finding ways to turn a side hustle into a major money maker. In fact, over one-third of the American workforce currently uses an “alternative work arrangement” as their primary source of income. The great news is that as the gig economy grows, businesses are finding ways to incorporate data technology to ensure that opportunities abound and alternative entrepreneurs can succeed. Let’s discuss how some of

By Lance Eliot, the AI Trends Insider A crucial element of many AI systems is the capability to undertake Multi-Sensor Data Fusion (MSDF), consisting of collecting together and trying to reconcile, harmonize, integrate, and synthesize the data about the surroundings and environment in which the AI system is operating. Simple stated, the sensors of the AI system are the eyes, ears, and sensory input, while the AI must somehow interpret and assemble the sensory data into a cohesive and usable interpretation of the real world. If the sensor fusion does a poor job of discerning what’s out there, the AI is essentially blind or misled toward making life-or-death algorithmic decisions. Furthermore, the sensor fusion needs to be performed on a timely basis. Any extra time taken to undertake the sensor fusion means there is less time for the AI action planning subsystem to comprehend the driving situation and figure out what driving actions are next needed. Humans do sensor fusion all the t

Facial recognition software is a powerful technology  that poses serious threats to civil liberties. It’s also a booming business. Today, dozens of startups and tech giants are selling face recognition services to hotels, retail stores—even schools and summer camps. The business is flourishing thanks to new algorithms that can identify people with far more precision than even five years ago. In order to improve these algorithms, companies trained them on billions of faces—often without asking anyone’s permission. Indeed, chances are good that your own face is part of a “training set” used by a facial recognition firm or part of a company’s customer database. Consumers may be surprised at some of the tactics companies have used to harvest their faces. In at least three cases, for instance, firms have obtained millions of images by harvesting them via photo apps on people’s phones. For now, there are few legal restrictions on facial recognition software, meaning there is little people

The details of the crime were uniquely specific: Wielding a hypodermic syringe as a weapon, a man in New York City attempted to steal a power drill from a Home Depot in the Bronx. After police arrested him, they quickly ascertained that he’d done the same thing before, a few weeks earlier at another Home Depot, seven miles away in Manhattan. It wasn’t a detective who linked the two crimes. It was a new technology called Patternizr, an algorithmic machine-learning software that sifts through police data to find patterns and connect similar crimes. Developed by the New York Police Department, Patternizr is the first tool of its kind in the nation (that we know about). It’s been in use by NYPD since December 2016, but its existence was first disclosed by the department this month. “The goal of all of this is to identify patterns of crime,” says Alex Chohlis-Wood, the former director of analytics for NYPD and one of the researchers who worked on Patternizr. He is currently the deputy di

In many areas of industry and research, people are excited about artificial intelligence (AI). Nowhere more so than in medicine, where AI promises to make clinical care better, faster and cheaper. Last year, UK Prime Minister Theresa May said that “new technologies are making care safer, faster and more accurate, and enabling much earlier diagnosis”. Backing developments in medical AI is seen in the UK as an important step in improving the provision of care for the National Health Service (NHS) – the UK Government recently launched a “Grand Challenge” focusing on the power of AI to accelerate medical research and lead to better diagnosis, prevention and treatment of diseases. With companies and research institutions announcing that AI systems can outperform doctors in diagnosing heart disease, detecting skin cancer and carrying out surgery, it’s easy to see why the idea of “Dr Robot” coming in to revolutionize healthcare and save cash-strapped public healthcare is so attractive. B

By Berge Ayvazian, Senior Analyst and Consultant at Wireless 20/20 I attended the Mobile World Congress in Barcelona last month to learn more about how the wireless industry is leveraging AI and intelligent cloud technologies on the road to deploying 5G networks.  Among the many software and hardware companies leading the AI revolution, I was most impressed by IBM which has aligned with its major operator clients and partners to showcase the cloud and AI technologies that will underpin the 5G era. IBM is uniquely positioned to help companies bridge their on-premises systems to different cloud platforms and vendors so that they can manage data, workloads, and processes across the breadth of their IT systems—from the enterprise, to the cloud, to the device, to the edge of the network.  The recently-acquired Red Hat is now at the heart of IBM’s hybrid cloud strategy and the company’s push to make Watson available anywhere. IBM has also established partnerships with leading telecom com

IoT (Internet of Things) is increasingly creating new opportunities for businesses as well as markets. And the technologies that created IoT is not changing the Internet, but everything that is connected to the Internet. In fact, IoT connected devices are generating so much data that the question on technology leaders’ mind is - How to make all this data secure & reliable? Although a huge amount of research is still required, it is believed that IoT’s flaws, in terms of security, can be fixed by merging Blockchain with IoT. Blockchain is, without any doubt, the safest way to encrypt & secure data. Blending blockchain with IoT can provide the highest-level of security protocols, especially for data as well as a transaction process. How Can Blockchain Level-Up IoT Security? First of all, Blockchain is highly secure and impossible to manipulate by anyone connected to the blockchain network. Ever since Bitcoin, blockchain development has come a long way and can now store

There’s a dark side to outsourcing business services. Beyond the advantages of cost efficiency and flexibility, outsourcing comes with inherent security risks. Investing heavily in securing your in-house network isn’t enough. One misstep when working with a third-party service provider can give attackers direct access to your most sensitive data regardless of your perimeter defenses. According to a 2018 Ponemon Institute study, 59% of companies have experienced a third-party data breach. And in light of this fact, 51% of CISOs now see the failure to control third-party data usage as a major security concern. When collaborating with third-party service providers, you need a way to maintain control of your sensitive data. With proper endpoint security, you can control access and mitigate the risks of a third-party breach. Learning from major third-party data breaches In 2013, in one of the largest data breaches of all time, retail giant Target’s systems were compromised as a re

Regardless of how fascinating future of AI might be, there would always be some amount of scepticism coupled with the subject. Movies have conditioned us to believe the age of Robots might take over humans but people often ignore the upside of AI and Machine learning. If utilised well, mankind could do wonders with smart machines. They could impact our daily lives immensely and most certainly, life would get easier. For businesses, it could change the way people interact with their products and services. It could be as redefining as changing the logo of a company. Some people believe that a minor change of logo could do a lot more to a company’s reputation than one could imagine. You might want to do that as well with the help of a brand like Trailor brands that has been helping brands for ages. Coming to the point, beyond a shadow of a doubt, the subject of AI and Machine Learning has always been a hot topic of discussion in recent years. It has and will impact our lives in unimagin

Data is everywhere; it can give both an accurate insight and the fog of visibility at the same time. Over recent years, streaming data technologies has become the latest norm whether it’s through the internet of things (IoT), Mobile and Big Data Pipelines. Several businesses are found struggling to put better data management practices. Unrelenting pressure from non-traditional players is seen driving organizations transform themselves digitally. Generating massive amounts of data from new sources is no longer a luxury; it has become a necessity Right from customer information to financial transaction, product and service purchase histories, customer journeys, marketing campaigns, service inquiries, market feeds, social media streams, Internet of Things (IoT) streams, software logs, and text messages (including emails and SMS), plus those newer sources, companies require capturing it all. Although the data management landscape seems to have evolved in 2018, in 2019 it will be even

Technology doesn't serve any purpose or function if it cannot increase the quality of life for the average person. After all, this should be the ultimate goal used for guiding society's movement into the future. With our current wealth of technological resources and understanding, it should be a fairly easy transition to improving the lives of everyone in society. Fortunately, there are many cities already leveraging IOT to improve living standards. Here are just a few ways in which IOT is revolutionizing urban living. Reducing Congestion on the Highways No major city is free from the plague of traffic congestion. With millions of people hitting the roads at the same intervals, it is nearly impossible to have any organization. However, many cities are leveraging IOT to help reduce congestion on the roads and highways. Some of the primary initiatives include directed parking, safer roads, smarter traffic systems, frictionless toll and more. According to Juniper Research, the

By Melissa Pandika As increases in computational power allow researchers to churn out massive amounts of data, scaling up analysis of it has grown ever-more challenging. At the Molecular Medicine Tri-Conference in San Francisco, a multidisciplinary cadre of thought leaders tackled this issue in the Machine Learning and Artificial Intelligence track. They shared their latest applications of these technologies to large-scale data to streamline drug discovery, clinical trials, and diagnostics. The Machine Learning and AI track launched on Monday with a focus on translating data into therapies. Asim Siddiqui , chief technology officer at NuMedii, discussed how his company develops technologies that allow for the integration biological data and creation of models that can predict drug-disease pairings. By accurately predicting these pairings, NuMedii aims to improve the probability of successful clinical trials. Siddiqui pointed to the high failure rates of clinical trials and noted that