Monday, 31 December 2018

Reimagining e-commerce with Artificial Intelligence



There was a time when buying, selling, marketing, advertising and conducting other commercial transactions used to be physical practices. In the digital era of today, human involvement in either of these activities has been reduced to next to nil. All kinds of products and services are very easily sold and marketed online. Right from perishable goods to elaborate services, everything can be ordered, delivered, searched and tested remotely. This phenomenon was bound to shake things up in the market and pioneers like Amazon was successful in disrupting that particular market. However, many enterprises survived the onset of e-commerce and were, in fact, able to adapt very well to the changing demands of the customers. If this wasn’t a technological wonder, enter artificial intelligence, which further revolutionized e-commerce.

What initially felt like a miraculous feat, turned out to be a rather inevitable innovation in the field of automation. Artificial intelligence was very quickly incorporated into all of the systems whose functions that it could simplify. An idea, that a computer could make certain suggestions or decisions on the basis of evaluating scores and scores of data has a far-reaching impact on many processes, particularly in the business world. Practices and procedures across industries have been simplified, enhanced and made ‘smarter’ by introducing artificial intelligence in their functioning. In terms of e-commerce as well, artificial intelligence has led to many innovations that have benefitted the platforms greatly. IT support provided by Aloha Technology has made many companies equipped with the most advanced technological tools.

Chatbot Support

One of the most popular advantages of artificial intelligence has reflected in companies installing chatbots to communicate directly with their consumers. This has given companies the opportunity to connect with customers round-the-clock and give instantaneous responses. Chatbots have also made it possible to increase the rate of communication with each customer. While chatbots may yet not be successful in completely replacing a human representative, it has been equipped to deal with a number of issues that involve one or two-step procedures for resolution. This has increased interaction and improved customer relations to a massive extent.

Data-Driven Marketing

A significant wing of e-commerce websites is marketing and AI has propelled the rate at which the website can evaluate the preferences of a user. Applications have made it possible for consumers to have a purely customized experience. Moreover, artificially intelligent systems have the capability to make appropriate suggestions on the basis of the user’s previous activity online- something that it grasps from deep-learning models. AI in e-commerce has solved the issue of bringing the right product and the right person together. Digital advertising has had a massive impact on the reach, appeal and recall-value of brands. Since artificial intelligence makes insight-driven suggestions, the consumer experience of shopping online has completely transformed.

A Complete Website

Artificial intelligence is rooted in machine-learning. The system crawls through vast amounts of data in a very short time and brings relevant insights to the forefront. This helps business-leaders know their users and their audience in a much intimate way. A strong website is a key to embarking upon new relationships, be it with partners of customers. And this is especially true for e-commerce websites. By building a strong and more importantly a complete website, an e-commerce company will definitely achieve better results, more traffic and eventually more popularity. In order to enable this, it is important to leverage artificial intelligence in establishing a well-functioning website and Aloha Technology will help you to do this.

Special Assistance

A unique advantage of introducing artificial intelligence in e-commerce is providing the consumers with quality assistance. It helps consumers feel valued. They are more likely to trust a website that is especially attentive tot heir needs. In an extremely competitive market for e-commerce, it is very easy to lose out your customers on the countless sites. In this way, artificial intelligence has reimagined business to consumer interaction for e-commerce websites.

Friday, 21 December 2018

Whats your enterprise approach to AI ?

This new year 2019 is adopting technology advancement in each and every enterprise so it becomes crucial steps required for enterprises to take action for production and adapting the growth of the enterprise. Artificial Intelligence is the main thing because of which your enterprise needs to approach it. Of course, implementing AI will take multiple challenges of its own but obstacle gets addressed and find the way through which you can get the success. According to experts, these main obstacles are perception and data. Addressing these obstacles may get you lead to finding a more pragmatic approach to AI.

What are the key obstacles to making AI work for the global enterprise?

There are mainly two obstacles: perception and data. There’s a perception that if an enterprise is going to implement AI it’s going to be a tremendous undertaking that has to be applied in a really big way. There’s also a sense that you have to do a lot of preliminary things in order to prepare to implement AI.

However, a lot of the time, we’re seeing really effective implementations of AI that actually include filling in the gaps that enterprises need to be fully optimized for AI. Let us take an example When we work with the retailer to create personalized shopping advisor – a virtual agent that actually incorporated customer DNA and made personalized recommendations.

One important thing it was clear that the period of that execution was that they didn’t have actually all of the important metadata about their products to make suggestions. Therefore, we carried out visual identification to the images of their things to assist create and develop the metadata they required to get the bigger term initiative work. There’s a chance to utilize AI to a number of the small issues to assist understand the larger transformation.

The additional crucial difficulty is understanding where your data is, therefore, you need to be capable of establishing ground truth. You can’t include multiple variations of the truth. You should know exactly where your data is stored and what it signifies basically.

A Pragmatic AI Strategy

Rather than evading enterprise AI completely, keep your roadmap grounded. Be realistic about your enterprise’s functionality, however, don’t overthink it. Quite often, deficiencies could be sorted out during the adoption process. To make efforts to improve your data environment. Even Forrester predicts that good quality traditional information architecture may see continued investments in 2019 in an effort to build AI-worthy data environments.

Finding a pragmatic strategy to AI implementation might be the technique you need for successful AI adoption in 2019. To implement AI for your enterprise check out Aloha Technology who can help you to adapt AI successfully.

Thursday, 20 December 2018

Do the benefits of artificial intelligence outweigh the risks?


The discussion around Artificial Intelligence (AI) can sound a lot like Brexit. It’s coming but we don’t know when. It could destroy jobs but it could create more. There are even questions about sovereignty, democracy and taking back control.



Yet even the prospect of a post-Brexit Britain led by Boris “fuck business” Johnson doesn’t conjure the same level of collective anxiety as humanity’s precarious future in the face of super-intelligent AI. Opinions are divided as to whether this technological revolution will lead us on a new path to prosperity or a dark road to human obsolescence. One thing is clear, we are about to embark on a new age of rapid change the like of which has never been experienced before in human history.



From cancer to climate change the promise of AI is to uncover solutions to our overwhelmingly complex problems. In healthcare, its use is already speeding up disease diagnoses, improving accuracy, reducing costs and freeing up the valuable time of doctors.



In mobility, the age of autonomous vehicles is upon us. Despite two high-profile incidents from Uber and Tesla causing death to pedestrians in 2017, companies and investors are confident that self-driving cars will replace human-operated vehicles as early as 2020. By removing human error from the road AI evangelists claim the world’s one million annual road deaths will be dramatically reduced while simultaneously eliminating city scourges like congestion and air pollution.
AI is also transforming energy. Google’s DeepMind is in talks with the U.K. National Grid to cut the country’s energy bill by 10% using predictive machine learning to analyze demand patterns and maximize the use of renewables in the system.
In the coming decades autonomous Ubers, AI doctors and smart energy systems could radically improve our quality of life, free us from monotonous tasks and speed up our access to vital services.
But haven’t we heard this story of technological liberation before? From Facebook to the gig economy we were sold a story of short-term empowerment neglecting the potential for long-term exploitation.
In 2011 many were claiming that Twitter and Facebook had helped foment the Arab Spring and were eagerly applauding a new era of non-hierarchical connectivity that would empower ordinary citizens as never before. But fast forward seven years and those dreams seem to have morphed into a dystopian nightmare.
It’s been well documented that the deployment of powerful AI algorithms has had devastating and far-reaching consequences on democratic politics. Personalization and the collection of data are not employed to enhance user experience but to addict and profit from our manipulation by third parties.



Mustafa Suleyman co-founder of DeepMind has warned that just like other industries, AI suffers from a dangerous asymmetry between market-based incentives and wider societal goals. The standard measures of business achievement, from fundraising valuations to active users, do not capture the social responsibility that comes with trying to change the world for the better.



One eerie example is Google’s recently launched AI assistant under the marketing campaign “Make Google do it”. The AI will now do tasks for you such as reading, planning, remembering, and typing. After already ceding concentration, focus and emotional control to algorithms, it seems the next step is for us to relinquish more fundamental cognitive skills.



This follows an increasing trend of companies nudging us to give up our personal autonomy and trust algorithms over our own intuition. It’s moved from a question of privacy invasion to trying to erode control and trust in our minds. From dating apps like Tinder to Google’s new assistant the underlying message is always that our brains are too slow, too biased, too unintelligent. If we want to be successful in our love, work or social life we need to upgrade our outdated biological feelings to modern, digital algorithms.



Yet once we begin to trust these digital systems to make our life choices we will become dependent upon them. The recent Facebook-Cambridge Analytica scandal of data misuse to influence the U.S election and Brexit referendum gives us a glimpse into the consequences of unleashing new and powerful technology before it has been publicly, legally and ethically understood.



We are still in the dark as to how powerful these technologies are at influencing our behavior. Facebook has publicly stated that they have the power to increase voter turnout. A logical corollary is therefore that Facebook can decide to suppress voter turnout. It is scandalous just how beholden we are to a powerful private company with no safeguards to protect democracy from manipulative technology before it is rolled out on the market.



A recent poll from the RSA reveals just how oblivious the public is to the increasing use of AI in society. It found only 32% of people are aware that Artificial Intelligence is being used in a decision making context, dropping to 9% awareness of automated decision making in the criminal justice system. Without public knowledge, there is no public debate and no public debate means no demand for public representatives to ensure ethical conduct and accountability.



As more powerful AI is rolled out across the world it is imperative that AI safety and ethics is elevated to the forefront of political discourse. If AI’s development and discussion continue to take place in the shadows of Silicon Valley and Shenzhen and the public feel they are losing control over their society, then we can expect in a similar vein to Brexit and Trump a political backlash against the technological “elites”.



Long-Term Risks



Yet the long-term risks of AI will transcend politics and economics. Today’s AI is known as narrow AI as it is capable of achieving specific narrow goals such as driving a car or playing a computer game. The long-term goal of most companies is to create general AI (AGI). Narrow AI may outperform us in specific tasks but general artificial intelligence would be able to outperform us in nearly every cognitive task.



One of the fundamental risks of AGI is that it will have the capacity to continue to improve itself independently along the spectrum of intelligence and advance beyond human control. If this were to occur and super-intelligent AI developed a goal that misaligned with our own it could spell the end for humanity. An analogy popularized by cosmologist and leading AI expert Max Tegmark is that of the relationship between humans and ants. Humans don’t hate ants but if put in charge of a hydroelectric green energy project and there’s an anthill in the region to be flooded, too bad for the ants.



Humanity’s destruction of the natural world is not rooted in malice but indifference to harming inferior intelligent beings as we set out to achieve our complex goals. In a similar scenario if AI was to develop a goal which differed to humanity’s we would likely end up like the ants.



In analyzing the current conditions of our world it is clear the risks of artificial intelligence outweigh the benefits. Based on the political and corporate incentives of the twenty-first century it is more likely advances in AI will benefit a small class of people rather than the general population. It is more likely the speed of automation will outpace preparations for a life without work. And it is more likely that the race to build artificial general intelligence will overtake the race to debate why we are developing the technology at all.



Read Original article here
https://theconversation-room.com/2018/08/28/do-the-benefits-of-artificial-intelligence-outweigh-the-risks/

Its time to take a decision to adapt artififical Intelligence and machine learning to grow your business with Aloha Technology which can help you to adapt AI & ML.

Wednesday, 19 December 2018

How ready is enterprise IT for digital transformation in 2019?

The impact of technology on business over the last 20 years is well documented, but how effective are enterprises at taking advantage of technology to reconstruct their businesses? Based to a newly released info brief by IDC, 96 % of organizations have a digital transformation strategy; however, one 3 rd of them report that the distance between IT and the business is a major obstacle in their success towards digital transformation. The particular alignment of IT and the business is not optional today – it is imperative to stay relevant in a fast-moving world. How will IT choose to respond to the possibility to lead the way for digital transformation?

Very first off, we must ask yourself ‘what is a digital transformation? ’ There are several definitions, but to keep it simple, digital transformation is the “use of digital technology to provide more value to customers. ” Digital change is mostly about enhancing the customer (employees or external customers) experience and enabling business agility to support changing market dynamics. This is possible if three enterprise dimensions are optimized using modern systems and methodologies: people, hazards and processes.

The record concludes that there are four primary considerations to execute digital transformation and business innovation:
  • Governance, risk, and compliance management – In the fast-paced surroundings needed to support digital transformation, it is crucial to get the right governance, chance, and compliance processes and automation to protect company and customer data.
  • Agile delivery of applications and services – Digital change requires that organizations quickly adapt to changing business and market dynamics. To be able to address these areas, seventy-seven percent of organizations reported they want to make ITSM processes more agile to support small business.
  • Knowledge management and sharing – Transformation of the workforce to be more productive and innovative is a vital ingredient in the digital transformation journey, with knowledge management and sharing serving as a critical capability. Knowledge employees need real-time entry to the answers they need to make choices and innovate. Above 61 percent of respondents reported that they are looking for superior self-help, mobility, automation and self-service abilities that help deliver knowledge in an effective way.
  • Skills and talent management (people) – Typically the workforce is at the center of transformation. Obtaining the right people with the right skills is important for the organization to execute and innovate in today’s competitive world. A vital finding in the research is that 77 % of organizations discovered that business strategy is a key skill needed by IT leadership to support digital transformation initiatives.
In accordance with the survey results, by 2020, 60 % of CIOs will implement an IT business design and a technology-first culture that focuses on creating cameras and services that improve user and employee satisfaction. A business-oriented method to IT strategy is a must while companies navigate through the digital transformation journey. Over 75 percent of the respondents admitted that IT needs to better align their skills in business technique to keep up with the competition. An overwhelming 78% of corporations acknowledged that supporting business agility will be a key influencer inside it strategy by 2020.

IT is at the heart of digital transformation with 88 % of organizations citing IT as “very important” or “important” to successfully execute on digital advancement. In addition, ITSM can be considered a critical capability for IT to execute against the demands of digital transformation across the business. Two key areas of IT transformation discovered in the investigation that is critical for supporting the business are:

Better User Encounter: What stood out in the survey results was your importance on simplicity and easier user experience. Modern organizations are leveraging advancement from ITSM platforms to provide modern, intuitive, and satisfying user activities that boost productivity, improve collaboration that helps retain talented employees. With shifting demographics in the workplace and consumerization of services, employees and external customers demand better experiences when engaging with the business for services and support.
Key conclusions:
Improving self-service adoption to fix business issues faster was important for over half (53 %) of large organizations
Over 55 % of organizations have high volumes of service desk tickets with no self-service in place
Over 50 % of organizations cannot meet performance, availability and service quality expected by business users
68 % of organizations are establishing the ability to provide access to ITSM through role-based apps, portals, and dashboards to increase the user experience. This is the second set of standards on the wish list and it is accepted as a top priority for large enterprises
sixty-one percent of companies work to provide superior self-help, mobility, automation and self-service features that deliver knowledge in a powerful way
Advanced Automation: To support more agile business procedures and deliver better customer experiences, IT organizations are leaning read more about modern ITSM platforms to provide superior process automation, better presence into financial and service utilization data and improved governance and analytics for making technology and business service decisions. To obtain these goals, 83 % of businesses said that modernizing their ITSM tool with an even more agile solution was an overwhelming priority.

Key conclusions:
For 7 out of 10 organizations, their existing ITSM infrastructure is not agile enough to deliver IT to business faster
6 out of 12 don’t have the granular visibility to find IT service issues and fix them quickly
Over 55 percent of companies struggle in adopting best practices such as ITIL or DevOps due to ITSM restrictions
74 % of organizations are looking for ease of use and modern features and functionalities — such as drag-and-drop configuration, high scalability or low-code customization. The finding stood away as the top criteria for investment.

Aloha Technology provides a unique solution for your enterprise so go with it.


Read original article on
https://www.itproportal.com/features/how-ready-is-enterprise-it-for-digital-transformation-in-2019/

Tuesday, 11 December 2018

Find the Right Technology Solutions for Your Company

Starting a business can be a complicated experience, but it is often rewarding. If you are starting a business, you should consider using technology solutions to make the business run more efficiently.

Use Technology for Time Management

Time management is a necessary part of starting a business. You need to have a timeline, goals for your time and know what you’re doing at all times. If you know these things, you’ll always know exactly when you need to be performing a task or something similar. It’s important to start doing this right away.

IT Operations Matter

Handling IT aspects can be hard especially for someone who has never worked in IT before. Using Managed IT operation services might make it easier for you to handle different aspects of IT. It may also make it easier for you to form connections with the people you’re working with since it can be easier to get started with your business if you handle the technological aspects of it.



Team up for Technology

If there is a piece of technology you really want but just aren’t quite ready to invest in right away, you might want to team up with another company that’s getting off the ground. Split the cost of the tool and then split your use of it. There are different ways you can do this, but the easiest is finding software that can easily switch between different systems or companies.

Work Smarter, Not Harder

Technology is all about working smarter instead of working harder. Dedicate different tasks to the way you want to work and make sure you’re doing everything you can to make the tasks easier. It’s important to try different things and make sure you’re prepared for anything that could come in the way of your business being successful.

Research before Investing

Always do your research. The chances are you researched about your business before you invested your time and money in it. Do the same thing with technology you plan to use in your business. If you know what you want, start researching it right away so you can make the necessary changes. It’s important to focus on how technology can improve your business instead of how it could cost your business a lot of money.
Starting a business doesn’t have to be difficult. Even though it takes a lot of work, there are things you can do to ensure the process goes smoothly.
Aloha Technology is a global IT services firm delivering digital transformation by putting digital and data to work to create a competitive advantage. Aloha's domain expertise spans across several business verticals like Retail, Healthcare, Telecommunication, Business Intelligence, BFSI, Enterprise Collaboration, Supply Chain, Internet Advertising and CRM.

For more updates follow us on twitter @alohatechnology

Monday, 10 December 2018

Some Facts About Artificial Intelligence

Artificial Intelligence is a concept that concerned people from all around the world and from all times. Ancient Greeks and Egyptians represented in their myths and philosophy machines and artificial entities which have qualities resembling to those of humans, especially in what thinking, reasoning and intelligence are concerned.

Artificial intelligence is a branch of computer science concerned with the study and the design of the intelligent machines. The term of "artificial intelligence", coined at the conference that took place at Dartmouth in 1956 comes from John McCarthy who defined it as the science of creating intelligent machine.

Along with the development of the electronic computers, back in 1940s, this domain and concept known as artificial intelligence and concerned with the creation of intelligent machines resembling to humans, more precisely, having qualities such as those of a human being, started produce intelligent machines.

The disciplines implied by the artificial intelligence are extremely various. Fields of knowledge such as Mathematics, Psychology, Philosophy, Logic, Engineering, Social Sciences, Cognitive Sciences and Computer Science are extremely important and closely interrelated are extremely important when it comes to artificial intelligence. All these fields and sciences contribute to the creation of intelligent machines that have resemblance to human beings.

The application areas of artificial intelligence are extremely various such as Robotics, Soft Computing, Learning Systems, Planning, Knowledge Representation and Reasoning, Logic Programming, Natural Language Processing, Image Recognition, Image Understanding, Computer Vision, Scheduling, Expert Systems and more others.

The field of artificial intelligence has recorded a rapid and spectacular evolution since 1956, researchers achieving great successes in creating intelligent machines capable of partially doing what human beings are able to do.

Obviously, researchers have encountered and still encounter several problems in simulating the human intelligence. An intelligent machine must have a number of characteristics and must correspond to some particular standards. For instance, the human being is able of solving a problem faster by using mainly intuitive judgments rather than conscious judgments.

Another aspect that researchers have considerably analyzed was the knowledge representation which refers to the knowledge about the world that intelligent machines must have in order to solve problems such as objects or categories of objects, properties of objects, relations between objects, relations such as those between causes and effects, circumstances, situations etc.

Moreover, another challenge for researchers in the field of artificial intelligence refers to the fact that intelligent machines must be able to plan the problems that need to be solved, to set a number of goals that must be achieved, to be able to make choices and predict actions, they must be able learn, to understand the human languages and to display emotions and be able to understand and predict the behavior of the others.

Artificial intelligence is an extremely challenging and vast field of knowledge which poses many questions and generates many controversies but also solves many problems that technology and industry are confronting with today and may offer many answers in the future.

Aloha Technology Helps Global Companies Race to the Top With Artificial Intelligence and Machine Learning. Artificial Intelligence and Machine Learning are technologies that can enhance data collation and analysis to release employees from rudimentary and time-consuming efforts. Aloha Technology can develop and deploy software enabled with AI and ML.

Thursday, 6 December 2018

Top challenges to IoT in modern enterprise


The Internet of Things is supposed to induce the 3rd biggest technology innovation in history after the Business Revolution of the 1800s accompanying with the Internet Revolution of the 1990s. The capability to utilize computer data from any specific and every type of device in the system, and also employ the data to attain a larger outcome, is beginning to change the method we reside our lives or run our businesses.

Even though a variety of sensors are now being utilized from a few decades, the mixture of data gathering and analytic software, which IoT solutions represent, is fairly modern. It provides limitless opportunities for extracting real-time information, and develop superior systems or manages the business better. And Aloha Technology is at the forefront of IoT innovation and business process adaptation.

Common challenges faced by ISVs

From a data architecture point of view: With more and more organizations implementing BYOD or ‘bring your own devices’, the data architecture for an IoT system must factor various devices, instruments and a host of softwares, along with their native operating systems. This gives the system the flexibility to gather or capture data from any source, anywhere in the enterprise.
From an infrastructure point of view: The above point implies that data-gathering devices must be liberally embedded all over the offices and physical infrastructure of the organization. Aloha Technology offers IoT integrations in the form of RFID tags, Bluetooth beacons, and a host of sensors to measure temperature, humidity, pressure, movement, etc.

Server-side programming languages:

Fleet Management: From cargo-ships to an assortment of vehicles used on the road, every vehicle can relay its position to a cloud-based system using sensors

Preventive maintenance: Vehicles and hardware equipment such as instruments or devices can be monitored for the possibility of breakdown or the need for repair

Retail business: While RFID tags can monitor customers’ movements; facial recognition software can analyze their expressions. This is then used to drive discounts or offers

Farm Productivity: By monitoring climatic data, farmers can be advised on when, and how much to irrigate their fields

Implementing an IoT System: Requirements and Challenges

Infrastructural preparedness: Public and private infrastructure remains the biggest hurdle for most business organizations around the world. An IoT system generates a lot of data which must be relayed to the cloud or to other systems through the internet. This calls for robust, high-speed internet connections and a mature communications infrastructure. Metros in India and most countries are adopting 5G which offers high data speeds required to maximize RoI from an IoT system.

System and Data Security: An IoT-based system generates and interacts with a lot of data, some of which are sensitive, such as facial recognition information, bank and financial transactions, movement or availability of humans in a particular environment, etc. Such data can reach the hands of hackers and criminals who may use it for harmful intent. We at Aloha Technology believe that it is then imperative that security is thoroughly planned and executed before commissioning an IoT-based system.

Component Visibility: The above point automatically implies that administrators of an IoT-based system have clarity on which are the devices plugged into or not plugged into the system at any point of time, to weed out unauthorized devices or users.

Lack of standards and best practices: Despite its widespread use, IoT is still in its infancy, so standards and best practices are yet to evolve. By partnering with Aloha Technology, organizations can overcome challenges with calculated experimentation while making innovations easier to integrate and use.

Looking ahead

The earliest adopters of IoT have been Healthcare, Energy, Utilities, Manufacturing, Financial Services, Hospitality and Agriculture. Other industries will follow suit with the IoT market getting crowded. There are more than 400 IoT platforms and by 2020, funding for IoT-related ventures is expected to reach USD 290 billion. This will create a vibrant ecosystem for business organizations, end-users, solution providers and third-party vendors who will add value in various ways, thereby enriching the IoT ecosystem. Talk to Aloha Technology and see how you can integrate IoT into your business strategy.

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Read Original Article on : http://www.alohatechnology.com/blog/internet-of-things-challenges-for-the-modern-enterprise.html

Wednesday, 5 December 2018

Economics and Ecosystem with IoT platform


Every technological shift only scales when there are proven economic advantages, and the IoT and Industrial IoT are no exception. In fact, according to Eric Simone, founder and CEO of ClearBlade, an Enterprise IoT Edge Computing platform company, “given the number of moving parts in any meaningful enterprise IoT deployment, there’s no getting away from the requirement to prove to end customers how connecting things will save money or increase revenue.”

Simone, who worked twice at IBM and established ClearBlade in 2007, over ten years ago when IoT was starting to take off, knows what it takes to cross the chasm of cool ideas into massively scaled deployments.

“In addition to solid software,” Simone said, “two elements are mission critical to successful projects – economics and ecosystems. Without understanding how to create profitable business models, and without working well with partners, in both the hardware, software and networking domains, even the most visionary projects will not work.”

Start-ups, large enterprises, investors, developers, governments and systems integrators have embraced the IoT with great energy given its natural potential to improve communities, manage urban growth, secure towns and cities, and make factories and farms more productive and efficient.
Simone says “innovation has outpaced implementation, and that has caused some understandable wariness. We’re getting through the early period, however, when miscalculations and unintended consequences have caused disappointments and losses.”

Traditional Business Models Need Not Apply

Traditional hardware business models, including hardware and software combined models, do not apply to IoT and IIoT.

The logic is straightforward: IoT devices require an upfront commitment, followed by recurring costs for connectivity. Applications are dynamic and, done well, result in long-term value for customers.
“Getting to the ROI is different in this world,” Simone said. “Especially when you layer in machine learning and AI, advantages improve over time, as information collected can make a huge different in improving services and yield over years and even decades. From monitoring to predictive maintenance, compliance monitoring, equipment monitoring, asset tracking, and more, with well-designed systems the data generated can be analyzed in so many productive ways.”

ClearBlade has won large deals across different applications and industry verticals, from the largest private smart community development in NYC since the building of Rockefeller Center, to projects with tier 1 rail providers, and medical device companies.

“Getting the technology right was one thing in winning these incredible projects, getting the economics right was another,” Simone said. “In some cases, the cost savings created a nearly immediate ROI, in other cases the impetus was more about safety and regulation, but even in those cases making sure the economics worked made all the difference in the decision.”

From Economics to Ecosystems

Simone also credits interoperability and integration as key to success, even if partnering can get complicated. “There is no one company who can do everything well, which is why we have spent a lot of time building our own ecosystem and joining others.” This includes Linux Foundation’s EdgeX Foundry, where ClearBlade is a charter member, NPM (Node Package Manager) the world's largest software registry for developers, and the Industrial Internet of Things Consortium (IIC).

“The edge is naturally important and really hard to do,” Simone said, “but the edge isn’t everything. We engineered and continue to evolve our platform and products to operate at scale in any cloud, on-premises and edge deployment, with the same technology; that said, we knew we needed to ensure protocol compatibility, and hardware agnosticism.”

The agnostic approach by its nature requires a lot of development cycles, to ensure the technology works across many different types of equipment and networks, as well as interfacing with other platforms and code.

“It took us years to get to this point, and nobody else we are aware of has all the capabilities we deploy today in all environments. This was hard and expensive to do, but we committed to doing this the right way, and we’re attracting a lot of new ecosystem partners as a result, and winning deals together.”

ClearBlade works with any cloud (AWS, Microsoft Azure, Google, IBM), has been built into vertical solutions (with large enterprises and projects including BNSF, Hudson Yards, Becton Dickenson, Mining (via Nanotron), and even connected cows (via Nanotron).

With Ingram Micro, ClearBlade is the technology underpinning their new IoT Platform-as-a-Service (PaaS), and with Nanotron and Corvalent they provided OEM embedded licensed IoT software.

Edited by Ken Briodagh

Read Original news here https://www.iotevolutionworld.com/iot/articles/440527-what-iot-platforms-have-been-missing-economics-ecosystems.htm

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Tuesday, 27 November 2018

6 digital transformation trends for 2019


Business transformation will pick up speed in 2019 as enterprises make critical decisions about their digital strategy. Our six digital trends will guide those decisions.

1. Enterprises go after digital business moonshots

In 2019, more enterprises will make bet-the-company commitments to digital business. It’s a new kind of corporate race as companies adopt these moonshot goals. Expect to see a range of innovation: new business models, new technologies and even entire new businesses built from digital.
Enterprises will have to beat back resistance from those following hybrid traditional-digital strategies and internally competing business unit strategies — and unify the entire business around a common digital program. Concentrate your talent, funding, operating model and executive attention on this program. Having a unified digital strategy between the business and IT is the only way to unload the technical debt that is holding companies back from exploring moonshot digital initiatives.

2. Enterprises adopt next-generation IoT platforms

As enterprises map their physical world to an intelligence-rich one, smart “things” will become a driving force. Enterprises will start to implement next-generation platforms in 2019 that can analyze large quantities of industry-specific data streaming in from the internet of things (IoT) and use artificial intelligence (AI) and machine learning (ML) to find novel correlations between data previously thought to be independent.
For example, precision medicine integrates data from new sources (such as WiFi-connected heart monitors, fitness watches, location data or the human genome) with traditional sources (such as blood chemistry or dietary information). Working with these multiple data inputs and their correlations will result in more precise diagnoses and treatment plans.

3.  Action at the edge disrupts the cloud

In 2019 more apps and data will move to the edge, requiring enterprises to manage apps and data differently via what we call “the Matrix,” the pervasive, intelligent information services that go beyond cloud.
Data “gravity” becomes a primary design principle for multi-latency systems. Because data’s context is frequently local, the ability to maximize data’s value depends on local reaction time. Data gravity means data accumulates locally; the analytics needed to react move toward the data. This brings us back to the Matrix, which puts that intelligent interaction — and us — ever closer to the data.
Hence the shifts toward event-driven applications and serverless architectures that allow very small applications to run in lightweight environments as close as the device in your pocket, on your wrist, retrofitted to your desk or outside your house on a pylon. And yes, 5G wireless will change the data accumulation patterns in disruptive ways.

4.  Enterprises enter an age of Information Enlightenment

As enterprises shift to intelligent operations, they are challenged by increasing data arrival volume (digital trend 3) and data analytic complexity (digital trend 2).  The shift to intelligent operations means reacting faster becomes a competitive imperative.  Data value does decay quickly over time;  the value may be highest right when the data is created but much lower only seconds or minutes later.
So, in 2019, translating broad and deep information into actions will become a core competency. In this age of Information Enlightenment, companies will understand their information ecosystems better and know what to do to make better, faster, data-driven decisions. ML tools will be key for training systems and speeding response times. Enterprises will realize it’s sometimes better to take action based on a strong probability of being right (e.g., 70 percent) than hold out for being perfect (100 percent). That means paying attention to how ML rules are built.

5.  Enterprises redesign customer experiences amid stronger data privacy rules

In 2019, protecting customers’ personal data will force companies to rethink their digital strategy as the full effects of the General Data Protection Regulation(GDPR) set in. Failure to comply with GDPR will thwart an enterprise’s ability to conduct business globally. Innovative companies will see this digital trend as an opportunity to deliver better customer experiences and to build customer trust and loyalty.
Enterprises must have a clear strategy for managing customer data and processes. They will have to consider changes across their data landscape, especially in marketing databases, demand generation systems and customer relationship management systems.
Enterprises will also need to reimagine their information ecosystems with partners and suppliers, creating privacy-centric information ecosystems built on analytics and security, as they aim to deliver secure interactions and superior customer experiences.

6.  Enterprises begin closing their data centers

The enterprise data center is frequently “in the wrong place at the wrong time”. In 2019 we expect to see a noticeable shift of enterprise data center workloads to multi-tenant data centers in the public cloud. Information processing is becoming a utility, and customers (and their data) are widely distributed. Public cloud providers are providing massive bandwidth and strategically-placed data centers, and enterprises are shifting to them for efficiency and to maximize their data’s value.
In effect, enterprise data centers will become virtual compartments in multi-tenant public clouds and thus will be shut down except for their mainframe workloads. Mainframe workloads will migrate to specialized data centers until they, too, eventually go away. We will see a lot of “lift and shift” in 2019, but the trend will play out over the next 3 to 5 years, as cloud migration gives way to “built for cloud” replacements.
Taking these six digital trends into account will help to ensure that the enterprise’s digital transformation journey like Aloha Technology continues to be successful.




Read Original article on https://blogs.dxc.technology/2018/11/15/6-digital-transformation-trends-for-2019/




Monday, 26 November 2018

How AI is reinventing the mobile apps?


The word “Mobile App” is so familiar nowadays that there are thousands of applications for a newborn baby to 100 years old. There are almost 3.8 million Apps in the play store. Every day at least 10 applications are coded and uploaded into different play stores available in the market. Mobile app development became a passion for many as it is yielding impeccable benefits for everyone.


With Artificial intelligence in the market, Mobile Apps are taking its full advantage to make our day to day life simpler and automated. Even though there are millions of applications in the play store, only a few are successful. So it is very important to choose the best mobile application development company to stand out among your competitors.



What is artificial intelligence?

In a simple phrase, we can describe Artificial intelligence as “Intelligence beyond Humans”. We have been listening to the phrase “Robots will replace humans very shortly”. But have you ever thought how it would be possible?

Artificial Intelligence is a computer science engineering subject. In this field, we study how to make robots think intelligently. So that they perform all the tasks that a human can do. AI is everywhere and vast in use from health care to technology. The concept behind automatic cars or trains is Artificial intelligence.

How Artificial intelligence can work with mobile apps?

If you are up to date with the Amazon products or technology, then you must have known about the Amazon product Alexa. It works on your voice commands when connected to your households. If not electronics, have you heard about the driverless car apps?

These both work on artificial technology. Both artificial intelligence and mobile app reduce our work thereby our efforts. So mobile app development with artificial intelligence will lay roads to our future.

Benefits of mobile apps with AI

As said AI reduces human effort by maximizing the computerized technology. There are a lot of benefits by using AI with mobile Apps, some of them are
  • Chatbots (instant reply)
  • Big data analytics
  • Online reviews
  • More revenue
  • Voice assistants (Siri)

Conclusion:

Artificial intelligence is our future. If you want to be a successful person in the era of technology, then choosing the best mobile application development and artificial intelligence services is the first step to your success. Visit the news about Aloha Technology which Helps Global Companies Race to the Top With Artificial Intelligence and Machine Learning.

Tuesday, 20 November 2018

Big Data & its Revolutionary Impact on Analytics




Organizations across the world have only recently come to realize how much of an essential asset database is. It is highly valuable for digital transformation as well as business development. It aids the smooth functioning of machines and systems that carry out important tasks like production, logistics, transformation as well as personnel management.

It is also highly vital for being familiar with the preferences and tastes of the consumer in a dynamic market. Big Data has been a unique phenomenon that forced organizations to develop analytical and processing tools that could be capable of processing a massive volume of data, which is unstructured, complex and being generated at a phenomenal pace.

Big Data has had a revolutionary impact on business analytics. It has enabled organizations to make credible, data-driven decisions. It has also paved the way for technological innovation by being a significant precursor to technologies like the Internet of Things (IoT) and Machine Learning (ML). Let us look at some of the factors behind the immense impact of the Big Data revolution.

The Foundation for Digital Transformation

For technologies like Machine Learning, which involves recognizing patterns and trends within a stipulated set of data, the emergence of Big Data has essentially been a foundational element, bringing about a massive scope for further innovation.

Machine Learning technology relies heavily on historical datasets. Larger the volume of the data, more accurate is the system’s suggestions. Thus, IT professionals have been able to use Big Data to their advantage for exploring the potential of many such technological tools like Artificial Intelligence (again, a historic-data reliant technology) as well as the Internet of Things.
Innovation in the field of cloud computing and storage has been propelled to a great extent. Big Data is also proving to be responsible for introducing a culture of developing insight-driven systems and machines. Big Data has led to the development of analytical and processing tools that are able to crunch scores of data in a very short amount of time.

Companies like Aloha Technology offers many such unique IT services that can pave the way for digital transformation in an enterprise. And it can be said that Big Data has been the cornerstone for most of the contemporary disruptive technologies.

Smarter Business Processes

Business development, strategizing and business expansion involves a lot of crucial decision-making. Leaders across the globe have recognized the value that Big Data provides in this process. Big Data renders a complete 360-degree view of the consumers of a particular product or service.
In an ever-changing market, business leaders know how vital this information is. For analytics, Big Data provides a considerable quantity of database. In terms of the quality, this data is not only diverse but also emerges from a varied source. This helps practices like pattern-finding for strategizing for the future.

Decisions relating to investments, insurance and capital generation can be made easily by relying on Big Data accumulated by the organization. Aloha Technology offers varied services related to Big Data Analytics and Processing as well, which can help your organization make your business processes smarter!

The Impact of Big Data

Looking at the two broad areas mentioned above, it is certain that the impact of the Big Data Revolution is far-reaching. It has touched upon every aspect of business as well as technological evolution. We can now say that we have been ushered into a new era of data-analytics with the advent of The Big Data Revolution.

Website: http://www.alohatechnology.com
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Thursday, 8 November 2018

AI in the Context of Digital Transformation



In the enterprise, no buzzword is as buzzy as the term “digital transformation”. If you spend any amount of time reading whitepapers, analyst research, or attending webinars you’ll see the term digital transformation used in conjunction with a wide range of enterprise-focused technologies ranging from data centers to application development, to enterprise architecture and AI and blockchain. But what does digital transformation even mean? And how does AI fit into the picture of how enterprises are thinking about AI and related cognitive technologies?

What is Digital Transformation?


Many industry pundits and authorities like to talk about the subject of digital transformation, but the concept boils down to the key idea that technology, and in particular digital technology (computers, networks, data, embedded systems, and the like), lead companies to transform the way they work to take advantage of the more efficient and advanced ways of working. You can think of digital transformation as the after effect of applying digital technology, perspectives, and methods to traditional problems.
In essence, digital transformation is key for organizations who want to remain relevant as technology continues its relentless advance. Organizations who remain bound to old and outdated paper-based processes, human labor-intensive activities, who operate with low information visibility and usage, and with low-skilled labor forces face a future where they could be rendered obsolete by organizations that dominate with the power of a business transformed by the use of digital technology like adapted by Aloha Technology. So, corporations, organizations, and countries don’t have much choice: they must find ways to digitally transform their organizations at increasing levels or face disastrous consequences.

Digital Transformation and the AI-Enhanced Organization


Since Industry 3.0 is at least 60 years old, and Industry 4.0 is now approaching three decades, many ask why companies haven’t already fully transformed their businesses to be digitally centric. Indeed, many of the above research institutions, consultancies, and think tanks are tackling that exact issue. The study conducted by McKinsey & Company said that “On average, industries are less than 40 percent digitized, despite the relatively deep penetration of these technologies in media, retail, and high tech”. Many studies point blame at the complexity of digitizing their businesses and difficulty working with their existing technology systems. It’s an odd paradox: these companies and organizations want to increasingly transform more of what they are doing, but their existing technology is getting in the way. The more technology an organization has, the harder it seems to transform them further. This sounds like a real problem.

In our newsletter and research on the AI-Enabled Future, we talk about the idea of the AI Enhanced Organization. In this vision of the future, we see three primary ways in which organizations will enhance their operations with AI. Summarizing the major conclusions from that research:


Read Original Article on https://ctovision.com/ai-in-the-context-of-digital-transformation/

Tuesday, 6 November 2018

Nursing for Sickest Patients Artificial Intelligence can provide Solution

In a hospital’s intensive care unit (ICU), the sickest patients receive round-the-clock care as they lie in beds with their bodies connected to a bevy of surrounding machines. This advanced medical equipment is designed to keep an ailing person alive. Intravenous fluids drip into the bloodstream, while mechanical ventilators push air into the lungs. Sensors attached to the body track heart rate, blood pressure, and other vital signs, while bedside monitors graph the data in undulating lines. When the machines record measurements that are outside of normal parameters, beeps and alarms ring out to alert the medical staff to potential problems.
While this scene is laden with high tech, the technology isn’t being used to best advantage. Each machine is monitoring a discrete part of the body, but the machines aren’t working in concert. The rich streams of data aren’t being captured or analyzed. And it’s impossible for the ICU team—critical-care physicians, nurses, respiratory therapists, pharmacists, and other specialists—to keep watch at every patient’s bedside.
The ICU of the future will make far better use of its machines and the continuous streams of data they generate. Monitors won’t work in isolation, but instead will pool their information to present a comprehensive picture of the patient’s health to doctors. And that information will also flow to artificial intelligence (AI) systems, which will autonomously adjust equipment settings to keep the patient in optimal condition.
At our company, Autonomous Healthcare, based in Hoboken, N.J., we’re designing and building some of the first AI systems for the ICU. These technologies are intended to provide vigilant and nuanced care, as if an expert were at the patient’s bedside every second, carefully calibrating treatment. Such systems could relieve the burden on the overtaxed staff in critical-care units. What’s more, if the technology helps patients get out of the ICU sooner, it could bring down the skyrocketing costs of health care. We’re focusing initially on hospitals in the United States, but our technology could be useful all around the world as populations age and the prevalence of chronic diseases grows.
The benefits could be huge. In the United States, ICUs are among the most expensive components of the health care system. About 55,000 patients are cared for in an ICU every day, with the typical daily cost ranging from US $3,000 to $10,000. The cumulative cost is more than $80 billion per year.
As baby boomers reach old age , ICUs are becoming increasingly important. Today, more than half of ICU patients in the United States are over the age of 65—a demographic group that’s expected to grow from 46 million in 2014 to 74 million by 2030. Similar trends in Europe and Asia make this a worldwide problem. To meet the growing demand for acute clinical care, ICUs will need to increase their capacity as well as their capabilities. Training more critical-care specialists is part of the solution—but so is automation. Far from replacing humans, AI systems could become part of the medical team, allowing doctors and nurses to deploy their skills when and where they’re needed most.
At Aloha Technology we are ready to provide the AI solution for your healtcare units. Just keep in touch with us.
Read original article on https://spectrum.ieee.org/biomedical/devices/ai-could-provide-momentbymoment-nursing-for-a-hospitals-sickest-patients

Sunday, 4 November 2018

Does Synthetic Data Hold The Secret To Artificial Intelligence?


Could synthetic data be the solution to rapidly train artificial intelligence (AI) algorithms? There are advantages and disadvantages to synthetic data; however, many technology experts believe that synthetic data is the key to democratizing machine learning and to accelerate testing and adoption of artificial intelligence algorithms into our daily lives.
What is synthetic data?
When a computer artificially manufactures data rather than measures and collects it from real-world situations it’s called synthetic data. The data is anonymized and created based on the user-specified parameters so that it’s as close as possible to the properties of data from real-world scenarios.
One way to create synthetic data is to use real-world data but strip the identifying aspects such as names, emails, social security numbers and addresses from the data set so that it is anonymized. A generative model, one that can learn from real data, can also create a data set that closely resembles the properties of authentic data. As technology gets better, the gap between synthetic data and real data diminishes.
Synthetic data is useful in many situations. Similar to how a research scientist might use synthetic material to complete experiments at low risk, data scientists can leverage synthetic data to minimize time, cost and risk. In some cases, there isn’t a large enough data set available to train a machine learning algorithm effectively for every possible scenario so creating a data set can ensure comprehensive training. In other cases, real-world data cannot be used for testing, training or quality-assurance purposes due to privacy concerns, because the data is sensitive or it is for a highly regulated industry.
Advantages of synthetic data
Huge data sets are what powers deep learning machines and artificial intelligence algorithms that are expected to help solve very challenging issues. Companies such as Google, Facebook and Amazon have had a competitive advantage due to the amount of data they create daily as part of their business. Synthetic data allows organizations of every size and resource levels the possibility to also capitalize on learning that is powered by deep data sets which ultimately can democratize machine learning.
Creating synthetic data is more efficient and cost-effective than collecting real-world data in many cases. It can also be created on demand based on specifications rather than needing to wait to collect data once it occurs in reality. Synthetic data can also complement real-world data so that testing can occur for every imaginable variable even there isn’t a good example in the real data set. This allows organizations to accelerate the testing of system performance and training of new systems.
The limitations for using real data for learning and testing are reduced when using fabricated data sets. Recent research suggests that it is possible to get the same results using synthetic data as you would with authentic data sets.
Disadvantages of synthetic data
It can be challenging to create high-quality synthetic data especially if the system is complex. It’s important that the generative model creating the synthetic data is excellent or the data it generates will be affected. If synthetic data isn’t nearly identical to a real-world data set, it can compromise the quality of decision-making that is being done based on the data.
Even if synthetic data is really good, it is still a replica of specific properties of a real data set. A model looks for trends to replicate, so some of the random behaviors might be missed.
Applications of synthetic data
Whenever privacy concerns are an issue such as in the financial and healthcare industries or an enormous data set is required to train machine learning algorithms, synthetic data sets can propel progress. Here are just a few applications of synthetic data:
  • Synthetic data with record-level data can be used from healthcare organisation to inform care protocols while protecting patient confidentiality. Simulated X-rays are combined with actual X-rays to train AI algorithms to identify conditions.
  • Fraudulent activity detection systems can be tested and trained without exposing personal financial records.
  • DevOps teams use synthetic data to test software and ensure quality.
  • Machine learning algorithms are often trained with synthetic data.
  • Waymo tested its autonomous vehicles by driving 8 million miles on real roads plus another 5 billion on simulated roadways. Other automakers are using video games such as Grand Theft Auto to aid its self-driving technology.
While synthetic data isn’t fool proof, it is an important tool to augment machine learning algorithms when real data is too expensive to collect, inaccessible due to privacy concerns or incomplete.
Aloha Technology Helps Global Companies Race to the Top With Artificial Intelligence and Machine Learning


Read Original Article on https://www.forbes.com/sites/bernardmarr/2018/11/05/does-synthetic-data-hold-the-secret-to-artificial-intelligence/#50742be342f8

Thursday, 1 November 2018

Why AI-driven analytics will have the measure of the digital enterprise


As the name succinctly says, big data has always been about scope, scale and volume; a more the merrier ethos when it came to the intelligence suddenly at business's disposal
The sheer volume of insight generated by big data was considered a prerequisite for accurate decision-making. It brought gigabytes and terabytes to mainstream parlance, while signalling a whole new era of data handling and management with greater complexity and opportunity in terms of application.
However, as this data overload became the new norm, our expectations evolved to demand a more strategic approach to how we can derive greater value from the intelligence flooding our systems. Many have learnt the hard way that more isn’t always better when it comes to data-driven decision making, as quantity rarely surpasses quality when it comes to more discerning and meaningful interventions.
Aloha Technology's Digital Transformation solutions bring innovative technologies to assist enterprises of any size or industry.
Perhaps not surprisingly, this realisation brings us to a growing trend in the digital enterprise. Defined by a shift in mindset from simply collecting intelligence to the more forensic measures used to drill down into it and extract the specifics, the use of advanced analytics is enabling us to do more with less data. This move increasingly underpins higher operating margins and ultimately creates a competitive advantage.
Fuelled by machine learning technology, this traction is in fact, forcing a re-evaluation of the traditional ‘more is more’ Big Data strategy that has long been a pervasive mantra in the digital environment.
In this context, artificial intelligence combined with visual analytics becomes the game changer. This powerful proposition is perfectly equipped to sift through the reams of information and define the relationships and anomalies between the data sets to uncover actionable intelligence that augments human intelligence for greater business value.
While AI puts in the ground work, at a speed and scale impossible for a human to compete with, visual analytics provides a more accessible and intuitive approach to data analysis. This can have deeper repercussions for an organisation more broadly, specifically in terms of promoting a more entrenched data culture.
As a result, a greater section of the workforce can be involved in data-driven decision making, as opposed to a privileged few, a move that far from simply being a ‘nice to do’ will become a fundamental requirement to offset the scarcity of specialist data skills.
Figures from McKinsey and Company highlight the extent of the problem, with the US, for example, facing a shortage of 190,000 people with analytical data skills and 1.5 million managers and analysts equipped to understand and make decisions based on the analysis of Big Data.
So how does AI-powered analytical innovation and data democracy translate into tangible gains when applied to the real-world industry environment? Notable proponents such as the health, finance and manufacturing sectors have been quick to embrace the approach. Heatlhcare professionals are harnessing the technology to detect abnormalities in X-rays, for example. And banks are using the advanced algorithmic capabilities to drive deep content analysis of a customer’s financial status, objectives, risk aversion and can respond to the nuances of their personality and behaviour to best tailor the approach to the user’s needs.
Now we see others playing catch up, such as the oil and gas sector. Here, pressure over ever tighter margins induced by the global drop in oil price has demanded even greater accurate insight to optimise production, as well as to inform continuous monitoring and intervention needed for the smooth and seamless running of critical operations. As a result, a more measurable and quantifiable approach to the enterprise becomes the game changer, as science and business converge ever more closely to keep the business efficient and competitive.
Machine learning is harnessed to provide recommendations and to make predictions over the control and management of assets processing billions of data points in real-time from equipment ratings to thermal gradients. This creates a full picture and level of precision that removes all guess work from the equation.
As a result, gut feel is replaced with an augmented human brain, thanks to algorithmic prowess.
Read Original Article on https://www.information-age.com/ai-analytics-digital-enterprise-123471664/




Is your automated technology a threat to customer relationships?


Companies claim that automating communication with the customer is making their journey much more efficient and streamlined. But is that really the case or are companies just putting a barrier between them and their customers?
We’ve all been there: trying to call our bank, GP, or utility provider, and having to press an infinite number of keys to get through to an automated voice that will make us wait on the line while letting us know that we’re number 20 in the queue. Companies claim that automating communication with the customer is making their journey much more efficient and streamlined. But is that really the case or are companies just putting a barrier between them and their customers?

The broken process: using technology to replace human interactions

It seems almost impossible nowadays for customers to get through to anyone on the phone when calling a company. Bearing in mind customers are likely to only pick up the phone when they want to sort something out quickly or they have a problem, this poor experience is probably going to have a damaging effect on brand perception and loyalty. A Times investigation for instance recently found that Britain’s Big Six energy suppliers were taking more than 20 minutes to answer customer phone calls in some instances, prompting many to switch suppliers. In today’s competitive market, businesses cannot risk losing their customers because of poor service. They need to develop good relationships with them rather than relying on technology to do it for them. They need to stop hiding behind automated processes and chatbots and distancing themselves from their customers.
Forcing customers to communicate with robots through several layers of filtering and recorded voices can make them more frustrated and their lives more difficult than a quick conversation with a customer service agent. For customers, there is nothing worse than feeling like the organisation they are trying to reach is not prioritising their needs. Avoiding unpleasant conversations by hiding behind technology only makes it harder for customers to trust the brand and build a positive relationship with it.

The solution: using technology to enhance human interaction

Fortunately, we live now in an age of unprecedented technological advancement; which means that for every pain point organisations have, there is usually some technology available to solve it. Advancements in telephony technology mean that businesses have the resources to make the phone experience much more enjoyable and insightful for both their customers and their staff. Businesses no longer need to see the phone as the conduit for difficult conversations, but as one for insights that benefit the business.
The first thing organisations need to keep in mind, when it comes to their customers, is that they want to have the company’s whole and undivided attention. This means a personalised experience, which entails knowing your customers well enough to provide that experience. When customers know they are being cared for, they start thinking positively about brands, and might be inclined to expand their conversations beyond complaints or issues. When conversations become more pleasant, this is an opportunity for brands to build positive relationships with their customers and gain more insights. There are now smart solutions that allow companies to record information about every conversation that they have with a customer over the phone; keeping track of their details, what was discussed and even the tone of the customer’s voice to track whether it was a positive or negative call. When a customer calls back, the system uses that information to provide a personalised journey right from the beginning. Often it is strong emotions – stress or confusion – that lead us to pick up the phone. Making that experience as easy and helpful as possible will make a huge difference to that customers’ perception of your brand.
Technology can also help businesses provide greater job satisfaction to customer service agents by ensuring their skills are properly used and they get the training they need. Skills-based routing can for instance allow customers to be automatically directed to an agent equipped with the skills needed for that particular customer’s profile; this is made possible thanks to artificial intelligence collecting and analysing data from previous interactions between the customer and the brand like Aloha Technology.
When speaking to a customer, a salesperson or call centre worker will be able to help them quicker and more effectively if they have information about previous conversations, language preference and company name at their fingertips. Not only will this improve customer service, but it will also make staff more efficient and productive. By that same measure, technology can also be used to spot ways to improve staff performance. For example, Artificial Intelligence is starting to be used to determine good calls from bad calls. As well as helping personalise the experience for the customer, as discussed above, this is also crucial information for staff development. In a contact centre environment, where calls and sales performance are recorded and logged, managers can listen to the calls to identify particular trends and spot potential areas of improvement. That way the employer can provide training specific to the individual’s needs. In the same environment, managing how calls are allocated between the team ensures that workers are not overloaded, and employees can create a more relaxed and productive working environment. Ultimately, businesses want their call centre staff spending less time redirecting or inadequately answering customer queries and more time on building relationships with customers – which an automated phone system cannot do by itself.

Read article on https://www.itproportal.com/features/is-your-automated-technology-a-threat-to-customer-relationships/

Wednesday, 31 October 2018

How Machine Learning Enhances The Work of Whole Industries

The time has come to speak about artificial intelligence and machine learning, robots, in the present tense. They are no longer just around the corner. They’re here today!
Merrill Lynch, the investment arm of The Bank of America predicts the global market for AI and robots will approach $153 billion by 2020. Moreover, some industries will experience up to a 30% productivity increase by incorporating these technologies.
Fully functional artificial intelligence (AI) is closer than we might think. Working prototypes already exist. Computer engineers haven’t yet created a true AI — but their work in this area has already had a great impact on several industries.

AI vs. ML

Before looking at machine learning in various industries, we need to take a look at the difference between ML and AI.
ML and AI are nearly synonymous. Yet, there is still a distinction. Artificial intelligence is a computer program. It is able to perform what humans normally can, such as speech recognition, translation from one language to another, or decision making. These computer programs can take steps to accomplish certain objectives.
Machine learning is a form of AI where computer systems actually learn, develop, enhance themselves and “evolve” when introduced to new and/or additional data. There is no need to program the computer in a traditional sense. Machine learning models are based on human learning techniques.
Intelligent machines are actually able to differentiate between streams of new information using available knowledge while making logical connections, combining ideas, and following thought patterns just like humans do. As Jen-Hsun Huang, CEO of Nvidia put it: “You essentially have software writing software.”

A helping “iron hand” for the steel industry

For instance, steel manufacturing companies can greatly benefit from AI tools such as ML-based optimization, control systems, and sensors. AI has the great potential and capacity to implement different technologies. In the end, steel production can be done more efficiently and more profitably.
Let’s take a look at two areas where ML can be of use in steel manufacturing.
Optimization of production: When it comes to steel manufacturing industries, there are always a few unplanned events. For instance, the molten steel can break and pour out of the mold during the casting process. This can slow down the production of steel and even endanger the lives of workers. This can be both dangerous and expensive. ML play an important role in predicting such occurrences and thus helping to minimize them.
Predictive maintenance: Steel manufacturing companies schedule weekly maintenance check-ups. ML can assist in this procedure by predicting a particular machine required maintenance. So instead of the fixed weekly maintenance schedules, an as need-based maintenance plan can be implemented. This is vital for manufacturing companies who have a large quantity of on-site industrial machines.

Applications of ML in pharma and medicine

The healthcare sphere is sitting on the brink of a treasure trove. The more data one has in the realm of healthcare, the more successful it is. ML helps achieve a more precise decision-making process. It also enhances the efficiency of clinical research, trials and newer tools for physicians and insurers.
ML healthcare applications during the last three years have attracted the highest level of funding. ML and AI assist physicians by informing them of more precise diagnoses of their patients due to a more comprehensive pool of database information. Some unique scanners are equipped with special hardware and systems which help to find health problems quicker and more accurately.

Business and marketing adopting ML

General business is also being impacted by the AI invasion. Of the 168 largest companies in the world, as many as 76% are using machine learning technologies to enhance their sales growth strategies, according to an MIT survey.
MarketMuse is an AI-powered research assistant that accelerates content creation and optimization so you can win more often in organic search. This is basically banking on AI as it also is moving toward helping determine more of your content marketing strategy.

AI in the media and entertainment industry

After certain breakthroughs in ML, many smart products have made the leap from sci-fi movies to the home. Superhero Ironman’s virtual assistant JARVIS (Just A Rather Very Intelligent System) is echoed in smart assistants such as Alexa and Google Assistant. It may not detain criminals but it can do a range of practical chores via IoT household devices. NVIDIA uses VR technology to create a Holodeck similar to one in the sci-fi series Star Trek.
ML and AI technologies are being used for creating movies, enhancing visual design, post-production, and many other processes.
AI applications in the M&E industry exist mainly in four categories: marketing and advertising, service comprehension, search and classification, and experience innovation.

Conclusion

AI and ML are popping up everywhere. They are seen in education, transportation or in financial services, which could be an article on its own for the next blog. Machine learning systems continue to pave a new road for humanity. Machine learning influences entire industries and will continue to do so.

Aloha Technology helps Global Companies Race to the Top With Artificial Intelligence and Machine Learning

Read Article on https://medium.com/@onix_systems/how-machine-learning-enhances-the-work-of-whole-industries-5623d9ec685

Tuesday, 30 October 2018

Robotic Process Automation: A Gateway Drug to AI and Digital Transformation



Robotic process automation (RPA)—typically used to automate structured, back office digital process tasks—turns out to be the opening gambit in many organizations’ digital transformation strategies. It also appears to be a precursor to artificial intelligence (AI). In a recent research project on priorities in process and performance management, APQC, a business research institute, found that RPA was a nucleus of 69 percent of digital strategies. In another survey on investments in process automation, anticipated RPA projects were right behind analytics and data management, and almost twice as likely as near-term investments in AI or intelligent automation. Only 12 percent of those APQC surveyed had no plans to invest in any of these technologies in 2018.

APQC also found that the number of RPA projects per organization doubled from 2017 to 2018. The average number of projects per organization was 8.6 in 2017 rising to 14.9 in 2018. (See Figure 2).

In a separate project, one of the authors (Davenport) conducted a study with a team from Deloitte—described that found 71 of 152 early cognitive technology projects were RPA.

According to APQC’s Holly Lyke-Ho-Gland, who led the project, “Organizations spent the last two years getting smart and testing RPA through proof of concepts or pilot programs. Now they’re scaling up.”

What is fueling this early and rapid adoption of RPA? There are three major factors: ease of implementation, the proof from successful pilots, and the partnerships successful pilots require.

Aloha technology helps gloal enterprises to top in Industry wih Digital transformaion

Read the aricle on https://www.forbes.com/sites/tomdavenport/2018/10/29/robotic-process-automation-a-gateway-drug-to-ai-and-digital-transformation/#27ae78513a70



Sunday, 28 October 2018

Most of the companies are in hurry to adapt artificial intelligence- here whats tripping them up


  • Companies that are rushing to embrace artificial intelligence technologies are running into big problems with their data.
  • Some companies don't have enough data, others have it in disparate places, and still others don't have it in a usable format.
  • Because of such challenges, some early adopters have abandoned AI projects.

    If there's one big thing that might thwart companies' headlong rush to adopt artificial intelligence for their businesses, it's data.
AI generally requires lots of data. But it needs to be the right kind of data, in very particular kinds of formats. And it often needs it to be "clean," including only the kind of information it needs and none of what it doesn't.
Troy Wolverton All of that adds up to a big problem for many businesses.
"The biggest challenge most organizations face when they start thinking about AI is their data," said Paul Daugherty, the chief technology and innovation officer of consulting firm Accenture, in an interview earlier this month. He continued: "Often we're seeing that that's the big area that companies need to invest in."
Corporations large and small and across multiple industries are enthusiastic about AI and related technologies such as machine learning. Many are already adopting it to do things such as improving their customer service, flagging suspect transactions, andmonitoring employees' performance. Accenture considers AI the "alpha trend" — the most important trend in technology not only today, but for the next 10 to 20 years.
But for companies to really reap the benefits — to be able to detect trends, identify anomalies, and make predictions about future behavior — they're going to have to come to terms with their data.
And unfortunately, many companies aren't in good shape when it comes to data. In a recent survey by consulting firm Deloitte, a plurality of executives at companies that are early adopters of AI ranked "data issues" as the biggest challenge they faced in rolling out the technology. Some 16% said it was the toughest problem they confronted with AI, and 39% said it ranked in the top three.

Companies are facing multiple problems when it comes to data

Some companies don't have the data they need. Others have databases or data stores that aren't in good shape to be tapped by AI. Still others are dealing with issues related to trying to keep their data secure or maintain users' privacy as they prepare for it to be used by AI systems.
"Getting the data required for an AI project, preparing it for analysis, protecting privacy, and ensuring security can be time-consuming and costly for companies," Deloitte analysts Jeff Loucks, Tom Davenport, and David Schatsky said in the report. "Adding to the challenge is that data — at least some of it — is often needed before it is even possible to conduct a proof of concept."
Deloitte
One particular problem companies are facing on the data front is that it's often housed in different departments and disparate databases, noted the Deloitte analysts. Customer service data may be in one place, for example, while financial records may be elsewhere. The trouble for companies is that their AI systems will often need to tap into multiple data stores.
"AI creates a need for data integration that a company may have managed to avoid until now," Loucks, Davenport, and Schatsky said in their report. "This can be especially challenging in a company that has grown by acquisition and maintains multiple, unintegrated systems of diverse vintages."
Indeed some companies have run into such big problems in trying to get the data they needed for an AI effort that they've ended up abandoning or postponing the project, the Deloitte analysts said.
That's why it's crucial that companies assess the state of their data before embarking on AI projects, said Daugherty. It helps them set realistic expectations, he said.
"The big expectations factor for companies is really understanding the data — what shape the data's in to drive the right AI results," he said.
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