Showing posts with label AI. Show all posts
Showing posts with label AI. Show all posts

Thursday, 7 February 2019

AI and ML trend to watch in 2019

In 2019, companies will want to use data more efficiently, maintaining the 2018 trend. Optimising and managing multicloud environments was a priority for many companies last year, and so was the need to integrate security at a basic level. None of these trends will disappear in 2019, and we will see an interesting mix between “evolution” – expanding and developing already-existing trends – and “revolution” – demands that are always changing and forcing companies to adopt digitalization and new technologies more quickly, according to a report released on Thursday by Cisco.

AI-ML will become routine

AI (Artificial Intelligence) and ML (Machine Learning) have progressed quickly over the past few years. AI-ML innovation has solved old problems, leading to a conviction that these technologies can be a solution for many challenges. Consumer apps with high visibility such as driverless cars or digital robots that “look like humans” have caught the public’s attention, but this enthusiasm is only partly justified as companies are still learning what needs to be done to adopt AI-ML.
Cisco uses AI and ML to solve real problems with a pragmatic approach. For example, they analyse huge volumes of data in the network, identify and block security threats or ensure continuous workflows. Cisco DNA Analytics can extract anonymous data from client networks, identify patterns and develop statistics. This leads to cost savings in network operation and security is improved. Encrypted Traffic Analytics from Cisco uses ML to find malware programs in encrypted traffic without a need to decrypt it, a first in the industry. We will see fast and interesting development in AI-ML in 2019.

Read Original Article on http://business-review.eu/tech/six-technology-trends-to-watch-in-2019-196139


Take a look about Aloha Technology Which helps companies to top in AI and ML

Monday, 28 January 2019

AI innovation key to UAE’s digital transformation’: VMware

On a trip to the UAE this month, VMware’s Jean-Pierre Brulard, senior vice president and general manager EMEA, talked about how 2019 will be the year for the UAE to adopt Artificial Intelligence (AI) innovation in order to fuel nationwide digital transformation.
“Artificial Intelligence and machine learning will see major breakthroughs in 2019, and the UAE’s government and industry verticals are ideally-positioned to encourage and adopt these to drive digital transformation,” said Brulard.
Brulard predicts that, in 2019, businesses in the region – especially across education, energy, financial services, and governmental – will leverage the power of AI to confront security challenges.
“From Expo 2020 Dubai to Dubai’s Smart City initiatives, AI is becoming the foundation for organizations to react to peoples’ needs in real-time, predict how government services will transform citizen experiences, and ensure that costs, security and innovation are optimized,” said Brulard. “The UAE’s leadership is one of the most visionary in the world, encouraging connectivity and recognizing the potential for technology to serve as a force for economic growth and societal good.”
Brulard believes the UAE has a tradition of leading digital innovation for the region – especially the UAE’s Strategy for Artificial Intelligence, and the potential of this to drive digital transformation and drive the future economy.
Regarding technology infrastructure, he predicts that 2019 will be the era of the ‘self-driving data center’ – in which AI and machine learning will be deeply infused into private and public clouds, reducing complexity and driving the next generation of digital infrastructure. All achievable by laying a strong digital foundation.


Related News about Digital transformation

Wednesday, 23 January 2019

Artificial Intelligence is Transforming the Workplace in 2019

Artificial intelligence ( AI ) is an advantage to modern workforces.
AI can deal with ordinary and repeated tasks across the organization, freeing up people in HR, IT, marketing, and more to exercise ingenuity, resolve complicated issues, and elsewhere focus on obtaining impactful work performed. Aloha Technology is helping organization to enhance there work productivity by utilizing Artificial Intelligence
Put simply, AI allows contemporary knowledge workers to give attention to the most engaging parts of their jobs while making their companies more effective.
At the Gartner Application Technologies and Solutions Summit held in November 2018, John Kostoulas, senior director analyst, proven that different t groups and group leaders that directly boost an absolute heritage would surpass their targeted goals. Referring to a Leadership Validation Survey CEB-Gartner conducted in 2016, Kostoulas revealed that higher gender diversity teams paired with effective addition practices enhance teams’ performance.
Take a look at these types of AI-powered software tools to find out more about just how AI is transforming the workplace for the better.



How AI is transforming the hiring process




Filling open positions is usually time-consuming, costly, and annoying.
It’s among the areas where AI is already getting a substantial impact. HR departments, recruiters, and hiring managers are utilizing various sorts of AI-powered tools to develop the hiring process for everyone involved :



Textio makes use of AI to assist employers and hiring managers to write much more powerful job descriptions. It utilizes data it’s gathered from the company’s past job postings—as well as identical postings from other companies—to recommend changes to word, formatting, and content which will produce much more applications and interest from job-seekers.



How AI is removing repetitive admin tasks




You can get lots of tasks that experience workers spend some time on that offer little—if any—value.For example, say you have to schedule an appointment to obtain consensus on an option before moving forward, however you need 5 people to join the meeting. It’s simple to invest a lot of time sending message back-and-forth or perhaps finding an open port on everyone’s calendar.



That’s not the most rewarding use of your time for you or your company.
Recording, transcribing, and publishing conference notes are yet another inglorious—yet often helpful—use of time.



How AI is transforming internal communications and support




AI would not need to describe us or exchange us; we have now the possibility to explain AI in the context of corporate communications, which include both external and internal communications.
Personnel on the people that offer employee support possess their hands full along with other responsibilities, too. HR teams focus on creating the type of company people really like working for. IT retains the company’s network and keeps data secure. Office managers often work big events like holiday parties.



AI is furthermore transforming workplace communications by enabling employees who speak various languages to quickly understand one another in near-real-time conversations. Skype Translator’s AI instantly converts for both parties in a conference call :



How AI is transforming marketing, sales, and customer service




AI-powered chatbots assist with exterior support as well. Identical to with internal support tools like Spoke, these types of chatbots learn from real internet marketers, salespeople, and customer service repitions and ultimately capable of answer questions as precisely as a knowledgeable person.



Related Links:
https://www.reuters.com/brandfeatures/venture-capital/article?id=56598












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.

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.

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.

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/

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/




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