Judging from statements published by the McKinsey Global Fashion Index, the fashion industry has tremendously increased at 5.5 percent yearly within the last decade. Also, in the year 2016, it was estimated to be worth roughly $2.4 trillion.
However, sales growth reduced by the end of 2016 and reports revealed that apparel companies have been carrying out innovations internally in a bid to reshape the fashion industry like shortening the whole fashion cycle
Moving away from the fashion front, robotics and artificial intelligence have found their way into the factory of retailers as well as warehouses to boost efficiency and productivity.
There are email marketing tools that clothing retailers can make use of as they provide personalized messaging that targets specific segments like regular shoppers or shoppers that are inactive.
AI Apps Used In The Fashion Industry
Some of the applications making waves in the fashion and retailing scene include:
To begin using it, users swiftly take a survey that asks them questions like they should rate some fashion items by tapping on either a heart or X symbol.
According to the company behind the app, this process aids in teaching algorithms the personal style preferences of users, and the data is transferred to the fashion search and recommendation tool of the app.
This app claims that it makes use of deep learning algorithms to give retailers the benefit of not just collecting but also analyzing customer data points, certain keywords, web navigation patterns, shopping cart price points, and their likes as well.
Based on the website of the company, its application can take unstructured computer vision, normal language processing as well as behavior data and convert them into fashion insights.
The application is targeted directly at apparel manufacturers, clothing manufacturers, brands, retailers, lifestyle and fashion influencers who can prospectively make use of the insights to make decisions that are informed about the fashion trend in the future.
Fashion retail now makes use of a diverse variety of artificial intelligence technology right from computer vision down to robotics. But that is not the end of the story as of 2019. Since the technology is still new, they all still demand inputs from each shopper or operators of enterprises.
There have been so many talks and debates on all the things that deep learning can make possible. It can execute tasks that humans do in:
What Is Deep Learning?
On a general note, the artificial learning field is basically when machines can execute tasks that normally demand human intelligence. It entails machine learning; where machines learn by experience and train skills without the involvement of humans.
However, deep learning is a subset of machine learning, and it is where artificial neural networks and algorithms that are inspired by the human brain learn from a huge volume of data.
Just like how humans learn from experience, a deep learning algorithm also executes repetitive tasks and tweaks it a little to enhance its outcome. The neural network of deep learning has diverse layers that allow learning to occur
Any issue that demands thoughts to figure out is an issue that deep learning can take on to solve. The algorithms of deep learning demand tons of data to learn from. This growth in data creation is among the reasons that deep learning abilities have grown.
Also, deep learning has been able to benefit from the powerful computing power that is made available today. Nonetheless, deep learning enables machines to resolve difficult problems even when a data set is being used.
Deep Learning Transformation
Deep Learning can transform machine learning in the tasks it carries out and resolves. The more deep learning algorithms learn, the better they make machine learning perform.
We are in a time when machines can easily learn how to solve difficult issues without the intervention of humans. Deep Learning can be used in different ways in a bid to transform machine learning. They are:
The more data being sent to a deep learning algorithm, the better it can act like humans in its information processing.
To Sum It Up
With all these areas where deep learning can be used, we can see how it will successfully transform machine learning as well.
Once a deep learning algorithm solves problems and is being used for daily engagements, machine learning can as well learn the tasks and be used as well.
The concept of artificial intelligence is no longer referred to as a distant reality. AI is here, and it is doing a great job in transforming how businesses function.
Specifically, it is shifting gradually into the field of human resources and changing now the HR team execute their duties like:
Similar to how texts transformed how businesses interact with one another plus their consumers, AI is stepping up to change how the human resource department functions.
Most people think that artificial intelligence is here to replace staff in some sort of futuristic Utopia, well, it has the prospects, but that is surely not what is happening or going to happen anytime soon.
Uses Of Artificial Intelligence For Human Resources
Artificial intelligence has proven to have diverse use cases in different fields, and now we will be looking at its use case in human resources. AI can be used in:
When every one of these functions is assigned to an artificial intelligence system, recruiters can easily save time in shortlist its candidates.
This implies that the company can easily draw applications from a very wide pool without the extra labor of determining which ten out of five hundred will be called for an interview.
Even though it is invasive, artificial intelligence bots can be used to go through the search history of staff, messages, documents, etc. All these are done just to have an idea of the staff may want to quit.
Artificial Intelligence will be capable of helping with this through the help of facilitation courses that will guide the staff through the new materials.
Also, the AI system will be able to create assessments tailored to the person in question.
While these tasks may seem vital, they can also be responsible for the consumption of valuable time. With AI, the tasks will be performed, and the HR department will focus on other tasks to save money.
To Sum It Up
AI is not here to replace our staff. Instead, it is here to take off some of the work's weight from our shoulders.
Advancements in AI will continually transform the way the HR department operates from recruiting to onboarding to managing company's policies and expectations.
The way artificial learning is utilized is what differentiates it from every other thing. When you make use of the data you can collect, you will be in an appropriate position to construct products that customers will care about.
With artificial intelligence, it is evident that our world is changing and we will be looking at why product managers need to make use of this technology.
Why Product Managers Need AI
Some of the reasons why product managers will need to make use of artificial intelligence include:
A chatbot will be a convenient tool as it helps in answering questions swiftly. However, the human alternative should never be underestimated. Users will always remember you for how easy it was to work with an actual human.
Have it in mind that the bigger the product manager gets, the most likely for his or her data to get broader and longer. The product manager will be able to make use of the additional information s/he collects.
S/He can then click through diverse rates, page time, search history, and preferences of products. All these are used to know what users spend time on, and it aids in showing them that your option is the best thing they need.
Additionally, machine learning can go a long way in helping the product manager to fine-tune his product offerings to meet the needs of the users.
According to what they select, the manager can adjust the product so that the users can see how the manager resolves issues better than other competitors.
What Product Managers Need To Know
For the product manager, he or she should be aware that there are diverse advancements in technology that are making their way into various fields. The basic thing to do is not to fight them but accept them.
Furthermore, artificial intelligence is not here to replace anyone but to improve what businesses do. It is just an avenue to make jobs more productive and effective. If the product manager wants to get the most out of AI, he or she will have to collect data continually.
To Wrap It Up
Artificial Intelligence keeps on growing at a very fast pace, and it seems like, with every passing month, a new technological product is introduced.
If you want your product to stand out, then AI is your best bet for a more productive business.
What is this Facebook Libra Cryptocurrency?
Everyone has heard of cryptocurrency, right? If you are a fan of digital currency too than your newsfeed must be flooded with the latest news too.
Yes, by the latest I mean the Facebook Libra Cryptocurrency!
Finally, Facebook has also revealed all the details of the cryptocurrency they’ve recently launched, Libra. With Libra Cryptocurrency you can buy and send stuff to people with almost zero fees. But in the case of Libra, Facebook isn’t entirely controlling it. It’ll just get a single vote in its ascendancies like the several other members of the association including Andreessen Horowitz, Visa, and Uber. All these associations are meant to promote the Libra Blockchain making it dominant and popular.
How does Facebook Libra Cryptocurrency work?
We’ve learned some basics about Libra, right? You can simply cash in the state’s currency, purchase Libra and spend it like dollars without worrying about the fees.
But it is a lot more than that. The fundamental and artificial intelligence technology, the association leading and governing it, the wallets which you’ll prefer to choose and the procedure through which the payments will work – everything has an elaborative aspect to them. Facebook has published 100+ pages of documentation regarding Libra and Calibra. Here are some interesting details we’ve extracted from the detailed documentation which might be a little hard for you to read. Let’s dive in.
The Libra Association:
Before launching the Libra Cryptocurrency, Facebook was aware that everyone wouldn’t trust the new digital currency, therefore, it started recruiting the different founding members of the association – the Libra Association.
The founding members paid $10 million equally to join and also became a validator node operator optional which means they gained one vote in the association and become eligible for a share which is proportionate to the invested amount.
Other than this, Facebook is also debuting a secondary company which is referred to as Calibra which can protect the user’s privacy by staying away from the payments made through Libra. Moreover, it is also designed to handle crypto dealings. The real ID of the users is always hidden from the transactions made publicly.
The interesting fact is that the other founding members along with Facebook can earn the profit on the money which is cashed by the users. This is primarily done to keep a stable value.
Facebook’s impudent offer to develop a universal digital currency that endorses fiscal enclosure for the unbanked essentially has more confidentiality and decentralization in-built than many anticipated. Rather than attempting to manage Libra’s future or crush tons of money out of it directly, Facebook has chosen to play the long-game by dragging costs into the online domain.
Cryptocurrencies have made it easier to transfer cash straight to someone and also helps quite a lot in business. Nonetheless not confidential, cryptocurrencies are often referred to as pseudonymous. Certain cryptocurrencies, particularly bitcoin, consists of a cap on its number which can be issued, this means that the owners of already existing coins wouldn’t have to stress about the capricious development of new coins like Libra.
Retailers are always looking for new and innovative ways to progress the buyer’s experience to boost sales. Exploring the evolvements in retail technology helps in advancing the customer’s knowledge, which ultimately increases sales. This has helped in shaping the retail industry quite a lot.
Back in the 1800s, several department stores were launched, which marked the emergence of the modern retail industry. From the small-town shops of expert -only stores, the department store provided an array of options for the customers giving a much extensive choice.
With time, the department stores became popular as it marshaled in the progression of retail technologies. Moreover, cash registers also appeared for the first time during that time, though they weren’t that popular it did stop the extra effort employees had to put.
Furthermore, purchasing items ‘on-credit’ is also part of the retail industry; however, the credit cards didn’t appear until the 1940s. By this time, the majority of the banks started launching plastic credit cards. This helped in the evolution of retail stores quite a lot.
Here is an elaborative overview of the distinctive eras of retail. You’ll find out how it has evolved so rapidly over the past few decades.
From the 1900s to 1940s:
In the early 20th century, customers usually visited the local corner stores since there were no department stores at that time. The local stores were mainly family-owned small stores that were particularly located in a single physical position. Later, the revolution in technology occurred when the self-service model was introduced where the customers could touch and examine the items themselves without requiring any help from the associates at the store. This significant change eventually involved the customers more occupied in the process.
In the early 1900s, the UK has the most ground-breaking department stores which had elevators and public washrooms there too. This attracted the customers even more and enabled the buyers to spend more time shopping.
From the 1940s to 1970s:
During this time the majority of the people owned cars and began moving to the outskirts of towns. This is one reason why enclosed shopping places began to appear. The first entirely-enclosed, climate-regulated mall was introduced in the United States back in 1956. The advancement in technology was seen in such malls since they had air-conditioners, escalators, and automatic doors which attracted the customers to a great extent.
From the 1970s to 1990s:
The primary category killers that are still seen today started to squash out several less critical businesses during the 1980s. This is one apparent reason why retailers began filing for bankruptcy. This happened because they were quite slow to amend the buyers’ progressing needs.
From the 1990s to today:
This was the time when the retail industry revolutionized entirely due to the establishment of e-commerce. This also removed the international borders that ultimately broached the bar of the purchasers' experience. The latest technology allowed ‘regular’ individuals to sell their products online on websites like Etsy, Amazon, and eBay. In fact, by 1999, even a small retail shop should already be on Amazon. By 2019, if the store doesn't have an independent e-commerce website searchable on the internet, its end was going to be near. Then came Alibaba, where Chinese manufacturers can distribute their goods all over the world.
With the use of social media, the retail industry ads are more aggressive and targeted than ever. The use of artificial intelligence is also used in retail apps such as AliExpress for users to scan merchandise they like, which alert manufacturers and help them find the items that match the users' taste.
With the evolution of technology, players in the retail industry need to evolve with it. Similar to every industry, the ones unable to adapt will not be able to survive and thrive.
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Artificial Intelligence has been a ruling concept since technology has become a part of human life. Artificial intelligence is related to computer sciences in which the computers are trained in a way that they can imitate human activities and even feelings. With the time development is being done in artificial intelligence so that so in future it takes over anything that a human being can perform and do it in a much easier and quicker way. However, one question that pops up in everyone’s mind is whether artificial intelligence can detect fake news or not?
In current times, fake news prevails in the world like a rocket. And it is pretty hard to detect between fake news and a legitimate one. To stop people from believing in the fake news it is important to dig into it and let the right knowledge prevail in the society. It is quite difficult to verify the authenticity of the news because of which the journalists either struggle or take advantage of it. However, with the help of artificial intelligence, this matter is being taken care of. Artificial intelligence can rate the news according to its authenticity of being fake or not. That is why using automated machines is being considered as the best way to tackle fake news. As technology is becoming smarter, it is suggested that people need to be educated as well on how not to believe in every news at its face value.
There are four different ways in which artificial intelligence helps in identifying fake news:
Web Pages Scoring:This is a method that was introduced by Google. In this method, the accuracy is scored on each web page according to the facts they have on it. It has been a great success that is why more advancement is being done on it as it evaluates the context of every page without relying on any other party.
Weighing Facts:The artificial intelligence here plays a part in scanning through a whole story from its heading, main body to its geographical location. This scan helps in determining whether all the sites are on the same wavelength regarding the facts and later on these facts are weighed against all the reported media links.
Reputation Prediction:The websites are being predicted in artificial intelligence through machine learning tool, as it backs up every data regarding the particular sites it becomes easier to predict reputation of a website through their domain and ranking of the web.
Discover Lurid Words:To grasp the attention of people relating to new things, the headline is the best key to achieve it. The analytics of keywords finding is used in artificial intelligence to tackle the headlines regarding fake news.
As the question was asked whether Artificial Intelligence can identify fake news or not, after the research, it has been answered that yes it certainly can identify fake news and is better at it than any human being can. Because of this discovery more and more research is being done on this specific matter and how artificial intelligence can assist in it.
Artificial Intelligence (AI) comes under the branch of computer science that focuses on building machines that are capable of performing jobs and activities that normally require human intellect. It is rapidly growing in today’s world and is being used in various areas of human life and work such as business, labor, construction, digital marketing, facial detection and even for driving a car. Some examples of AI being used are Google’s search Algorithms and IBM’s Watson.
Here are 6 AI Podcasts that one must listen to:
The Data Skeptic: In the show, the episodes have various formats ranging from mini-shows that explain a particular technique to interview shows. The couple Kyle and Linh Da explains complicated topics in a very easy way in mini talk shows. The podcast discusses and critically analyzes important machine learning and data science problems.
Artificial Intelligence in Industry: Dan, the CEO of Tech Emergence which is a research and consulting firm on artificial intelligence-based in San Francisco, provides help in AI procurements and technologies that help in learning machines. His podcasts are mainly introductory and highly recommended to executives and non-practitioners who aim to have a vast but basic knowledge and understanding of the ways artificial intelligence can be applied.
O Reilly Data Show: This show highlights Ben Lorica and here the Chief data scientist talks to various experts in different fields on very technical topics such as big data and other scientific topics but overall the discussions are very enlightening and interesting to hear.
Concerning AI: This show's idea of artificial intelligence is relatively different from the other podcasts in a way that Brandon Sanders and Ted Sarvata look at the concept of AI from a Philosophical perspective. They look at how artificial intelligence can be used in society today as well as in the future. Although artificial intelligence can get a bit frightening at times overall the concept is very thought-provoking.
Data Stories: This show focuses more on data visualization and sometimes the topics do overlap but each week, Enrico Bertini and Moritz Stefaner talk about different topics with their guests. The recent episodes on viewing data from space and data ethics are particularly very fascinating.
Talking Machines: This show focuses on different conversations with various people who are experts in the field. Various discussions on industry-related topics are held and all sorts of queries are resolved. This podcast is rather old focused on AI being started by Katherine Gorman, who is a storyteller, and Ryan Adams who learns the machine.
With the rapid improvement in technology, AI has become an important concept that the world should know more about. It has started to play an integral part in our daily lives and hence these podcasts provide good Insight to the topic as well as sufficient learning for those who want to learn.
From the presidential election debate last night, it doesn't seem like the world is ready for AI. Only one candidate addressed the consequences of technology and AI, while the other candidates were still talking about the past. Can we even accept the present and future of AI?
As scientific horizons widen, so do technological outlooks. But are we ready to be beaten by our creation which is Artificial Intelligence? Will we ever be able to accept something faster, stronger and smarter than us? Is the world ready to be beaten by the non-living?
What is Artificial Intelligence?
A machine learns on its own. For instance, if you are shown a caution sign once, you can identify practically any caution sign anywhere in the world. Similarly, artificial intelligence works the same way. Once you enter the basic data into their system, they keep improving their software by a feedback system until a point reaches where they start making unprecedented strategically decisions.
How Artificial Intelligence will make the world a different place?
For better or for worse, we can’t say for sure how the full impact of artificial intelligence would be on human life. In 2016, Artificial Intelligence named AlphaGo won against the human Go game grandmaster. AlphaZero is the new chess master after beating the world champion by using its human-generated parts and improving its mathematical errors in just a couple of hours, it was indisputable. It took 1500 years for humans to achieve this high cognition level that artificial intelligence achieved so rapidly. This indeed marks an important milestone in the tech world but did the human Go grandmaster celebrate Alpha Go’s victory? Quiet unlikely.
The world is still not sure about welcoming Artificial Intelligence to take over their victories, jobs, and homes. Most people see artificial as a threat to human existence. The reason being that simply robots work on manmade software, they teach themselves from the mistakes it makes corrects them by algorithmic theorems which may be and may not be ethically and morally correct.
If we start learning from our man-made artificial intelligence, we might be able to get smarter at calculations, estimations, might come up with even better environmental solutions but this won’t be concept based thinking. Artificial intelligence is unable to ponder, find the deeper meaning of life, it cannot reason outside the box. Feelings and emotions are something the human race craves. The artificial intelligence is devoid of reaching any level of consciousness shortly.
Another threat the world feels is the weapon harnessing artificial intelligence which will most probably cause the end of the human race. The problem is that robots don’t always interpret emotions right neither can it solve abstract problems. While artificial intelligence may save us from road traffic incidents by automatic safe driving cars, robotic surgeons save lives with better operation precisions, are we still ready for such perfection?
Not everyone in the world is good at heart and the world is really afraid of “evil scientists” of whom the world thinks might use for their malicious purposes. Also, once artificial intelligence starts making decisions for us that are greater than what we can figure out, they might start treating us an inferior race. But who knows when we will get there?
With our gradual move into the digital era, it is no surprise that almost all networking vendor has various visions for network automation.
The autonomous network is the type of network that functions without the intervention of humans, or, if at all there is any human intervention, it is very minimal.
Furthermore, the network is capable of monitoring, configuring, and maintaining itself all on its own.
All these are not new to the digital world as the term automation itself and the concept of technologies self-providing, self-diagnosing, and ultimately, self-healing has been in existence for a very long time.
Nonetheless, the advancements of artificial intelligence, as well as cloud technologies, has swiftly brought all of these ideas into reality.
Technology like these is mostly used by service providers and even enterprises to enhance efficiency and decrease errors made by humans as well as operating expenses.
They are used more in networks that are heavily burdened with outdated and really old equipment, spreadsheets, and old protocols.
Artificial Intelligence Merging With Autonomous Network
Currently, the majority of us make use of apps that have been enabled by artificial intelligence. Some of which ranges from Apple’s prominent Siri down to Amazon’s Alexa.
We make use of them by asking them to help us with one task or the other. There is also the streaming service such as Netflix that aids us in picking movies as well as television shows that make use of AI.
In this world of the submarine and terrestrial networks, artificial intelligence and all of the elements that build up the cloud are steadily mixing up to allow a new level of networking.
All of these elements range from the following:
More On Autonomous Network
On a general note, the autonomous network can be of optimum use when it is used to speed up specific processes that are repetitive like:
To Sum It Up
Automation needs to be seen holistically and not just as a conglomeration of diverse processes.
With artificial intelligence embedded in it, the automation network will have wider coverage than it already has.