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

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

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.
Aloha Technology can develop and deploy software enabled with AI and ML.



Read Original Article here
https://www.businessinsider.in/Many-companies-are-stumbling-as-they-rush-to-adopt-artificial-intelligence-heres-whats-tripping-them-up/articleshow/66404384.cms?

How Human And Machine Intelligence Powers The Intelligent Enterprise

Transforming a company into an intelligent enterprise is not as simple as declaring it to be so, or even as simple as moving data and applications off premises and into the cloud. The intelligent enterprise is a complex organism that brings together machine and human intelligence across all business functions to deliver value to customers.

Finding the right infrastructure and ongoing support is crucial. It can enable your organization to:

• Automate everyday business processes and deliver them through consistent and personalized user experiences.
  
• Help users to manage data from any source and in any format and support the development, integration, and extension of next-generation business applications to drive innovation.
  
• Leverage intelligent technologies including machine learning (ML), artificial intelligence (AI), Internet of Things(IoT), advanced analytics, and blockchain to capitalize on data by detecting patterns, predicting outcomes, and suggesting actions.
  

While each of the above is an essential piece in powering the intelligent enterprise, today we’ll look at how a digital platform plays an indispensable role in delivering accelerated and trusted innovation for transformative business outcomes.

The innovation core

The digital platform is the innovation core of the intelligent enterprise. The key concept is to modernize your existing core business technologies and processes to create digital experiences enriched with the intelligent technologies that seamlessly connect with the platform.
With the right technology, for example, you can deploy ready-to-use business services on a custom basis, accelerating innovation while conserving resources, and build cloud-native apps using IoT, blockchain, ML, AI, and other next-generation technologies.
An intelligent enterprise must be able to manage, share, process, and analyze any information anywhere, at any time such as Aloha Technology manages all Enterprise Application. Predictive insights help invent and run intelligent processes that can lead to transformative business outcomes. And an intelligent enterprise is capable of offering faultless user experiences across all applications, enabling continuous connectivity between humans, apps, and machines. Agile technology supports the intelligent enterprise with tight integration of both data and processes, along with analytics and transactions for real-time awareness in any situation.
With the right foundation, you can integrate existing systems, processes, and crucial business knowledge to become seamlessly connected and capable of innovating with agility and speed. Read more here,

Digital Transformation Success Depends on So Much More Than Technology

There is a common misconception that digital transformation involves nothing more than installing a new technology platform: Roll out the software, and everything in your business miraculously transforms around it.

But digital transformation requires more than just a software implementation — it requires a fundamental change in the way you do business like Aloha Technology.

The beginning of a digital transformation initiative is the perfect time to take a critical look at every aspect of your operations — how you recruit talent, how you’re organized, how you make decisions, even your dress code — to determine whether you need to make changes.

As you embark on your digital transformation, consider these five aspects of the undertaking: what needs to be transformed, how your organization views technology, why you want to transform your culture, the importance of delegating authority to managers, and what KPIs need to be measured.

By following the five steps outlined here, you’ll identify the areas of your business that will benefit from digital transformation and determine how to move forward with the support of key stakeholders.

1. Understand What Needs to Be Transformed

Not everything in your business may need to be transformed. Transformation for the sake of transformation is not healthy.

First, understand why transformation is necessary and what the goal is. From there, it’s important to align your management team around your vision.

Since digital transformation affects every area of a business, it requires teams to coordinate and collaborate like never before. You must put the right people in the right places to drive change. Not only do you need inspiring visionaries in your leadership group; you also need managers who understand the technologies and strategies surrounding current operations.

2. Rethink How the Organization Views Technology

Digital transformation is more than just adding an app to your current business model. Changing to a digital phone system, choosing an analytics application or upgrading your customer relationship management system aren’t digital transformations — they’re technology deployments that enhance current services.

Digital transformation penetrates to the heart of your organization by helping you make information available, accessible and usable — from any location, at any time and with any device. It gives your organization an opportunity to reinvent products, processes and technologies — all to drive the efficiency and agility you need to create customer experiences that improve performance and generate revenue.

CompTIA research shows that while businesses have an appreciation for strategic IT, they are not necessarily prepared to execute on that vision. The IT trade association reports that 78 percent of organizations surveyed said they are using technology to drive business outcomes, but only 28 percent said they are extremely confident in their ability to apply technology to business goals.

In this case, it’s not about a specific technology platform, but about an organizational view of technology. You can’t convincingly talk to the organization about digital transformation if you’re still doing everything on paper. Start by openly embracing technology to engage the organization.

3. When It Comes to Culture, Ask ‘Why?’

Shortcomings in organizational culture are one of the main barriers to company success in the digital age. Leaders must be intentional in building a digital culture, including changing legacy technology and structures that hinder transformation.

“In my experience, culture is the hardest part of the organization to change,” says serial digital entrepreneur and McKinsey advisor James Bilefield. “Shifting technology, finding the right talent, finding the right product set and strategy — that’s all doable, not easy, but doable. Hardest is the cultural transformation in businesses that have very deep legacy and cultural roots.”

As a part of any digital transformation initiative, an important question to ask is “why?” Here are some specific questions that will help you find an answer:

Why do we have our desks organized this way? Do we need to investigate different arrangements, like desk-sharing, flex space or co-working spaces?

Why do we have this specific dress code?

Do we need to all be in the office? Would we be more effective, or would we be able to recruit the right type of talent, if we had more flexible working arrangements?

How do senior managers interact with the rest of the organization? Does it need to change?

Why do we have standing meetings? Are they still necessary?

Asking “Why?” helps us understand the impact of remaining in stasis, what we can achieve if we head in a new direction, and how moving away from legacy aspects of culture can support a transformation initiative.

Read Original Article on https://www.cmswire.com/digital-workplace/digital-transformation-success-depends-on-so-much-more-than-technology/

Data is at the Epicenter of Digital Transformation

Digital Transformation is leading to many changes in the way organisations function these days. It has generated new markets, new positions, eased existing jobs as well as added value in various existing business processes like production, supply-chain, communication and logistics.
Digital technologies like Artificial Intelligence, Machine Learning, the Internet of Things and Virtual Reality have impacted every component of business and transformed the different procedures that traditional businesses used to practice. At the epicentre of all of these technological overhauls is massive amounts of data.

As organisations are starting to adopt the digital revolution in their day-to-day activities, it is becoming necessary for enterprise owners to consider efficient methods of synthesising all of the data that Digital Transformation has entailed.

The Pricing Hurdle

An important hurdle in dealing with data analytics effectively is the fact that the cost of data, specifically the cost of storage of data is skyrocketing. Despite the availability of tools like cloud processing and other storage alternatives, the average cost of data storage is tilting toward being unsustainable.

Apart from that, due to the complexities of Big Data, data processing is also turning out to be a costly affair. The sophisticated digital systems that we work with today require real-time data and massive volumes of it. To achieve this, enterprises will have to hike up their investments in data storage and processing.

The Skills (Personnel) Hurdle

The need for dedicated executives for data analysis is extremely essential in the current climate. Digital Transformation is touching upon business processes in a vital way, and data being a crucial component in the process, it requires a dedicated department to ensure its smooth processing and analysis.

The whole point of Digital Transformation is to strengthen business operations productively and save time and money. If data management would take up a lot of time of top officials, the purpose of digitisation gets diluted. Companies must recognise the implication of Digital Transformation and invest in personnel with appropriate expertise.

Future of Data Analytics – Dismantling Hurdles

Big Data has emerged as an essential component of Digital Transformation in business. Companies are highly concerned about their well-being in the long term. For this, organisations are investing heavily on predictive data processors. Data analysis is a key task in multiple business operations including marketing, finance, security and insurance.

Essentially, data gathered in a computer system is of next to no use. The right kind of expertise must be channelled into making productive use of the gathered data. At the current rate, Big Data is most likely to evolve at a higher pace and hence, in the near future, companies must look at long-term plans to ensure that consistent data analytics efforts are being conducted.

Industries can invest in technology that augments the stories that Big Data and analytics provide in real-time, driving decision making on the basis of real data. Vouching for services like the ones offered by Aloha Technology can help startups and small enterprises get a head start on data-driven Digital Transformation. Aloha Technology is a suitable option for large businesses as well because consistency and experience play an important role in long-term data management.

The ultimate goal of any organisation is to convert vital data into actionable insights so that the bottom line is positively and appropriately affected by it. Investing in the perfect personnel, investing the right amount of money and assigning enough capital and space to data management will help a company go a long way at a time when the entire market is engulfed by Digital Transformation.

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Digital Transformation Leads to Legacy System Modernisation

Many organisations cling very tightly to the age-old traditions or legacies. It may be a certain ritual, a formality adhered to by each employee or it may be a piece of hardware that was a part of the company’s origin. In a way, legacy shapes the culture of the organisation, it paves the way for the progress of the company while still holding on to its roots.

Many modern tech giants began a very long time ago. Obviously, the kind of technology that existed at that time would be vastly different from the one we utilise now, yet many organisations prefer holding on to certain legacy systems that were an inherent part of the company’s foundation. Many sectors still use fairly outdated tools and systems to perform their day-to-day tasks.

There may be varied reasons behind this fallacy. Some organisations may be having a hard time letting go of their beloved legacy systems, and some may be so rigidly habit-bound that they wouldn’t be keen on venturing into new possibilities, restricting themselves by the fear of unknown and undiscovered technology and may wonder how it may impact their business in the positive. With the wave of Digital Transformation, all these hurdles will soon be swept away.

Brickbats of Legacy System

Organisations may argue that sticking to a legacy system may turn out to be beneficial for the specifics of the business as those systems would serve exactly the purpose that is required out of it. However, there are many brickbats of retaining outdated legacy systems. Some of the glaring examples being its incapability to interact with modern systems. Security is a crucial sphere where foolproof mechanisms may not be guaranteed with legacy systems.

Moreover, using legacy systems in their outdated structures may culminate into losing out on opportunities for expansion as the agility and pace of the functioning of an organisation is heavily impacted by the under-performance of legacy systems.

Why System Modernisation is Necessary for Business

Legacy systems modernisation is an essential need of the hour. Primarily, this is because every industry is experiencing a wave of transformation accelerated by digitisation. The legacy system may not be able to comply with this phenomenon and as a result, restrict your business growth.

Modernisation represents a step toward making your business future-ready. In terms of the harsh competition, it is necessary for your organisation to have a competitive advantage and system modernisation would definitely contribute toward that.

Method of Legacy Systems Modernisation

There are multiple approaches that a company can take toward legacy systems modernisation. You can either opt for a complete overhaul of the existing systems or go for the quick evolution of the current system. The latter guarantees that the original purpose that the legacy system served is retained and enhanced due to the digital tweaks it would be subjected to.

Companies can opt for services provided by Aloha Technology for Legacy Systems Modernisation in a way that it could render productive results fast.

In conclusion, business owners must take the current scenario of innovation and quick transformation into consideration while deciding the fate of their legacy systems. For a business to have a bright and promising future, leaders must recognise the need to adapt to newer technology and this would involve letting go of the older, outdated one.

Thus, in the race to reach the summit, you must embrace the changes that the industry experiences every step of the way.

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Landmark changes brought about by Artificial Intelligence and Machine Learning

This past week, some of you may have carried out a few regular, day-to-day activities via mobile phones like ordering food online, booking a cab, and reserving seats for a movie or book a table at a restaurant. Surprisingly, less than a decade ago, almost all of these tasks would have required us to interact with many different people - but today, all these and many more actions can be carried out without any human contact. Such is the impact of enterprise apps and Artificial Intelligence (AI) and Machine Learning (ML).
Gradually, almost all the brands that we interact with on a daily basis are making us communicate with machines and bots for basic functions, grievance redressal, and guidance such as Aloha Technology. Customer service is an essential pillar of all businesses. Artificial Intelligence (AI) and Machine Learning (ML) are making this pillar much more accurate, quick, cost-efficient and far more intelligent than ever before.
Here’s how AI & Machine Learning are transforming Enterprise Customer Services:

Cost-Effectiveness 

It is a fact that infrastructure and IT support for chatbots and AI-enabled services are proving to be extremely cost-effective. Bots essentially replace a human Customer Service representative and this quite evidently proves to be much more lucrative as reactions are immediate and 24*7.
Moreover, in our fiercely competitive market conditions, the standards of Customer Relationship Management (CRM) has elevated formidably. This has raised costs considerably. AI proves to be a viable economic alternative. Third-party services like the ones provided by Aloha Technology will prove to be remunerative by introducing automated, AI-enabled CRM software to your custom enterprise apps.

Prompt Customer Service

Artificial Intelligence and Machine Learning have essentially augmented the experience of answering customer queries and complaints because a machine can attend to the customers round-the-clock - a feat that is expensive for human employees to carry out. The average time taken by machines as compared to humans is also much shorter. This considerably enhances the quality of customer experience.
For startups or small businesses, a CRM mechanism enabled with AI and ML can be extremely beneficial. It can successfully regulate customer relationship much more efficiently and for a longer duration than human employees and retain valuable clients through the process.

Quality Service

In this digital age, business owners are vying for the best quality services at the least cost. In business terms, we call this ‘optimization’. Artificial Intelligence and Machine Learning can deliver one of the best data-pools required for functions like automated Customer Service. With innovations being carried out in this field every day, bots are becoming smarter and they are capable of replacing humans in digital communication for rudimentary functions, no matter how complex the requests or queries.
Due to the vast bank of knowledge that a machine possesses, especially in comparison with a human being, it is incomparably more advanced than what humans can provide. This doesn’t mean that humans are replicable. It’s just that rudimentary work can be done with cheaper and more accurate alternatives. Today, it has become a dire necessity for enterprises to step up their game by inculcating technology profitably in processes like CRM.

Challenges…and Solutions

Technology-wise like Artificial Intelligence and Machine Learning are at a nascent stage. But for its power to revolutionize a process? The stage is prime to drive business-value for any type or size of business. Companies like Aloha Technology strive to support business operations and processes that are key to helping streamline business workflows and save costs.
In terms of streamlining of costs, Artificial Intelligence and Machine Learning serve as a boon to business owners. The technology is capable of delivering quality services and has a higher potential for efficiency, considering the alternative. In the future, the quality of customer service can only tread the path of increased speed and efficiency of Artificial Intelligence and Machine Learning.

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The Rise of AI & Machine Learning in the Transportation & Logistics Industry

Rapid digitization is forcing enterprises to refine their operations. Companies are looking to become more agile and efficient. Tasks that would once require weeks to be carried out are being conducted in minutes. Thanks to superior enterprise technology, business strategies are focused on fast results in lower costs.
The development of Artificial Intelligence and Machine Learning have set the wheels of evolutionary automation processes in motion. Outsourcing services providers like Aloha Technology are making new strides in the development of such technologies in assisting business operations.
Business processes relating to communication, logistics, data collection, data analysis as well as interfacing with customers have been handed over to machines. AI & ML is revolutionizing the Transportation & Logistics Industry.