One of the big confusions we all has was what is the difference between Artificial Intelligence AI,Machine Learning ML and Deep Learning DL. As these terms are maturing today some of the definitions of these terms are not still concrete and there is a lot of media hype where people use these terms interchangeably.

In order to clarify and throw some light at what is the difference between these terms. These definitions ad differences discussed in this article may not be hundred percent accurate since most of these areas are vastly developing.

Let’s begin with Artificial Intelligence  AI. AI is basically is in a nutshell which enables computers to think. There has been various stages of AI since almost early 1950’s. Artificial Intelligence AI is now the broad area which enables computers to think. Machine learning is a sub area inside AI.

ML are a bunch of statistical tools to learn from data. Which means ML is a subset of AI or a part of AI. Coming to Deep Learning DL, DL is a much more recent area which has taken shape since 2006. Dl is all about using something called Multi Layered Neuro Networks. A huge impact of AI has been occurring in DL. For all of these terms there are mathematical tools. There are tools in probability, tools in statistics, tools in Linear Algebra and Matrix Algebra etc. These are all fundamental mathematical areas and there is of Course computer programming. Without computer programming and algorithm you can’t train computers to think.

For a long time we were trying to replicate our thoughts by giving a lot of rules to computers. And we thought as a result, we could build an AI and what it turned out to be is a terrible way. Instead, researchers started to create algorithms that learn from themselves. And it was the beginning of ML. Hence ML is the subdivision of AI which enables machines to learn from data without explicitly programmed instructions and rules.

For example, suppose that you have to build an algorithm that can play tic tac toe. We have two cases in the AI case, you would have to take it from its hands and give it many logical rules to learn how to play. As a result you cannot build a machine that is good at tic tac toe without being good at it yourself. In the machine learning case you may not know how to play tic tac toe by yourself. Yet you can come up with a great software. Unlike the AI case you give it many examples of previous games and let it learn the rules by itself. Hence today ML is providing the tools the industry and society can use.

Deep Learning DL is the subset of Machine Learning ML. Consider it as the cutting edge of the cutting edge. Like in ML the data is fed through neural networks which are algorithms that take inspiration from the human brain and those neural networks will extract a numerical value called output for every data. It may be audio, video or images. And then it will classify it as data. For example I can tell whether a given picture is a cat or not.

In ML case we would have to define features such as if the animal has ears. And if yes, then if they are pointed. We would have to define all the facial features and let the system learn which features are the most important to classify a specific animal. But deep learning takes a step ahead and automatically finds out the features that are important for classification. Well, that’s what we could gather up for you on AI, ML & DL.

 

Image credit: Nvidia,Google.

Here is a list of recent product releases and updates for December, from companies that offer services to online merchants. There are updates on email marketing, same-day delivery, one-click purchasing, e-gifting, sensory branding, and shopping from your car’s dashboard.

 

 

Ecommerce Product Releases

Magento Commerce launches one-click instant checkout. Magento Commerce, the ecommerce platform, has announced the launch of Instant Purchase, becoming the first commerce platform to deliver the functionality since the Amazon 1-Click patent expired in September 2017. The new capability helps merchants drive repeat purchases for returning customers with a streamlined checkout process. The Instant Purchase feature was developed in conjunction with enterprise solution partner Creatuity and is now available.

 

Amazon expands Prime delivery services. Amazon has expanded Prime Free Same-Day Delivery and Prime Free One-Day Shipping to members in more than 8,000 cities and towns. To find eligible items, Prime members can look for logos next to product listings or filter using the checkbox located in the filter menu. Select free same-day or one-day shipping at checkout and eligible orders over $35 will be delivered for free. Eligible same-day orders placed in the morning arrive from 6 – 9 p.m.; orders placed in the evening or through the one-day option arrive the next day.

GM launches Marketplace for in-car shopping and reservations. General Motors has announced that it will be equipping new cars with an in-dash ecommerce system for drivers to order food, find fuel, and reserve hotel rooms. Drivers will be able to transact by tapping icons on the dashboard (rather than a smartphone) while driving. Developed with IBM, the Marketplace technology will be available in 4 million vehicles by the end of 2018.

Target adds e-gifting option to website. Target has unveiled a new feature on its website called “GiftNow,” letting shoppers pick out items that are sent via email to gift recipients. A recipient can then accept the gift by providing a shipping address, change the size of the item, or even exchange it for another product.

Payment Rails launches Global Payout API to 220 countries. Payment Rails, an API-first payout platform, has announced the launch of a global payout platform for sending payments to roughly 220 countries in approximately 135 currencies. Through a single simplified integration, businesses and platforms can now access global banking, payment, and real-time networks around the world in a fully compliant and regulated environment. The Payment Rails platform has no setup fees, monthly minimums, or long-term contracts.

Visa announces sensory branding. Visa has announced a sensory branding suite that will support the Visa brand in an expanded universe of connected, payment-enabled devices. These new sound, animation, and haptic (vibration) cues will help signify completed transactions in digital and physical retail environments when consumers pay with Visa. The sound of Visa will debut in Visa’s global advertising campaign ahead of the Olympic Winter Games PyeongChang 2018.

Prime Now and Amazon Handmade team up to offer fast delivery for local artisans. Prime Now, Amazon’s one and two-hour delivery service, and Amazon Handmade, a site for handcrafted items, have announced that unique, handcrafted products from local artisans are now available on Prime Now. This is the first time Amazon Handmade Artisans is using Amazon’s fastest delivery method to extend the selling season through Christmas Eve on Prime Now. Amazon Handmade products are available through the holiday season via Prime Now for members in Austin, Brooklyn, Manhattan, Minneapolis, Phoenix, Portland, Raleigh, San Diego, San Francisco Bay area, and Seattle.

First contemporary art purchased with Bitcoin in U.S. American artist Mark Flood’s painting was the first art piece to be purchased with Bitcoin in the U.S. It sold last week in New York for 12.3 BTC (equivalent to $100,000) by The White Company, a purveyor of fine art and luxury goods that specializes in working with clients in the cryptocurrency space. “Select a Victim,” a 2013 painting by Flood, was offered privately to an anonymous Canadian citizen. The White Company was started for consumers who hold wealth in cryptocurrencies to purchase luxury goods without giving up their desire for anonymity.

Shopventory officially launches on Shopify app store. Shopventory, a provider of inventory management, sales reporting, and optimization solutions for small-to-medium size businesses, has announced its formal launch on the Shopify app store of its Shopventory inventory and channel management platform. Shopify users can now easily push their Shopify catalog to a multitude of point-of-sale providers, such as Square, Clover, and PayPal Here while mobile point-of-sale users can expand their online offering by sharing their POS catalog with the Shopify platform.

Heap introduces a new platform to derive customer insights. Heap, an analytics provider, has announced a process to automate all phases of customer insights. Heap’s autonomous customer insights platform has three key layers: data capture, control, and insights. The data capture plane automatically captures all behavioral data from sources across departments and domain-specific tools into one standard schema. The control plane assures data integrity and the ability to change event definitions on the fly; and the insights plane produces networked insights across marketing, sales, and customer success silos.

Dynamic Yield launches a complete suite for email personalization. Dynamic Yield has announced the launch of a full suite of email personalization capabilities, enabling marketers to deliver personalized, engaging emails to their customers. Dynamic Yield for Email is built into Dynamic Yield’s core personalization suite so marketers can leverage user data and preferences across all customer channels to deliver true personalization in email. Personalize and synchronize the entire customer journey from start to finish including web, mobile web, mobile apps, campaign landing pages, advertising and now, email.

 

Source: Practical Ecommerce, SIG UELAND.

AI battle between China and America

Since the evolution of this new technology China and America has been heavily investing to take the lead. There has been a neck-to-neck competition going on between the two economies. In this article we will assess the position of both of these countries on the AI rivalry list on certain parameters like investments, the number of companies etc.

 

Investment, talent pool and the number of firms: -

Starting with the number of forms, America has definitely taken the lead. There are approximately 1.8 times more AI based companies in the states as compared to China. The investments are 1.5 times higher and America leads the talent pool count by nearly 2 times.

The talent pool in America is over seventy-eight thousand people as compared to China which is less than half of the states’ talent pool has only thirty-nine thousand people in this sector. The major reason for this gap is that a major number of artificial intelligence colleges and institutions are affiliated to the American institutes (16 out of the top 20 in the world).

The states have over 42% of the AI companies followed by China which hosts approximately 23%. Both of these combined leave being many other developed and developing nations like Singapore, Britain etc.

Image: http://www.scmp.com/tech/article/2077845/future-here-China-sounds-clarion-call-ai-funding-policies-surpass-us

Companies: -

The early rise or the first mover advantage of American companies in this sector like Google, Facebook, Microsoft, IBM etc. may be the reason of this significant lead. But China is far behind, Chinese companies like the BAT, self-driving Apollo, Xiaomi, Tencent etc. have also come up with huge investments in this sector.

Not only the old Chinese companies (giants) investing in this upcoming tech, but every now and then a new company based on it can be seen springing out in the country.

Image: https://technode.com/2017/10/22/China-vs-us-ai/

As depicted in the image above, in almost all the sectors of the industries, Unites States is leading the market except a few. Although China is not far behind, it would need to buckle up and in order to cover up the remaining gaps.

The medical industry in China has witnessed a significant boost after the evolution of artificial intelligence. New companies are simplifying their processes with the help of this revolutionising technology like medical imaging, record analysis etc.

Following the growth in the medical sector is the automobile industry, education, finance etc. 

Research: -

Since China has surpassed the United States in the research for artificial intelligence, it is clearly seen that it is doing the best it can in order to minimize the gap in both technology as well as the education sector in comparison to the states.

Conclusion: -

With a detailed analysis of the data above, it can be said that at present the artificial intelligence industry is currently being led by the United States with China on the second position. But with the upcoming new developments and companies in both of these nations, it is possible that the rankings can change in the near future.

  

Artificial intelligence has been a mixed bag of debate and opinions where some people consider it to be revolutionizing technology whereas others look at the dark side and fear it taking over the humans or causing devastations etc. But one thing they both agree on is the actual risks of artificial technology, is it really beneficial in the long term?

Let’s start with a little description first. The AI we see and notice today is commonly referred as narrow AI or weak AI meaning that it is designed to perform narrow tasks like internet searches, auto-driving cars etc. But the developers have bigger plans and want to develop it into a strong AI in the future performing all human tasks better than them.

Potential Risks: -

  • Destruction: - Destruction is considered as a major risk in the risks of AI. In the wrong hands, AI can cause massive mass destructions which could not be controlled by the humans leading to collateral as well as life damage. The invention of autonomous weapons that are specially programmed to kill, “I keep sounding the alarm bell but until people see robots going down the street killing people, they don’t know how to react because it seems so ethereal” as stated by Elon Musk (the CEO of Tesla and Space X).
  • Unemployment: - Even with the use of narrow AI problems like unemployment exists. The AI can be used for complete automation in industries which may lead to massive unemployment taking a toll on the economy and many others…

Reason for recent rise of interest in the risk of AI: -

The major reason of the rise of the public in the risks of the artificial intelligence industry is because of recent statements of many big people like Elon Musk, Stephen Hawking’s, Bill Gates and many others in the media about the risks involved in this fascinating sector as they have come to realize that with the current super-speed of its developments, one day strong AI will surely come into existence.

Elon Musk went a step ahead and even stated that “AI is a fundamental existential risk for human civilization and creators must slow down”. It has been the tendency of humans to create what they themselves do not properly or completely understand and the recent developments in AI may be the same.

He told the creators to slow down before creating a technology that they themselves do not understand.

Although, despite many risks, there exist certain benefits too. AI in healthcare, education, fashion etc. have really helped the public and saved a ton of time of the companies as well. Recommendations, strategic advertisements etc. have helped a lot of forms convert searches to sales. Hence, it turns out to be really difficult to for the people to decide about the other side of AI a=while they currently enjoy the bright side, maybe this is the major reason for the existence of mixed opinions about this technology.

 

Artificial intelligence has rapidly evolved from a dream to reality really quick. It is even used by you when you perform tasks as simple as shopping on Amazon, searching on Google, shopping on different websites etc.

Companies have come to realize that the use of AI can really improve their presence on the internet and help improve their revenue and government and the public sector is no different.

Although the use of artificial intelligence in government and public sector is still a debatable issue in some countries, other countries like the United States of America, United Kingdom have already adopted such technology in their functioning and have achieved great results.

The best example of the use of artificial intelligence in the public sector is the postal services. The government is now able to save tons of gallons of fuel by simply adopting this new technology, defence agencies, healthcare, fraud minimization etc. are some other uses and sectors.

The following are the sectors where the use of AI can help the government make a difference: -

  1. Policymaking: -

Policymaking is an important sector where the application of artificial intelligence can really have a positive impact on the public. Knowing the public opinions about a certain decision or plan before its executions can help the government mould the policy framework in favour of the people.

  1. Saving time and money: -

The introduction of AI can save a ton of time and money of the public sector. Leaving the routine, mechanical work such as going through a ton of paperwork and other non-core tasks etc. can be left to AI and the core activities can be performed with full dedication and focus like client service etc.

  1. Increasing efficiency and customer service: -

Lag in the customer service and long process and processing times is the sector where the government can really implement artificial intelligence. Online processes, assessment, quick processing through AI is the need of the hour.

This will not only improve the customer service but will also result in increased efficiency.

  1. Safer cities: -

Every country has tons and tons of security cameras to ensure proper monitoring and maintenance of law on the streets of the country, but the lack of so many people to manually manage and monitor each camera is physically impossible. The use of artificial intelligence can prove to be really helpful in this situation. Traffic signals synchronization and recognition of any person disobeying the law are some of the features that would be performed with the help of this technology.

Further, the government can put together humans as well as artificial intelligence together complementing each other skills. This will improve the overall effectiveness and give faster and better results. Plus, the humans will still feel that they are in the driver’s seat and have control.

 As the AI revolution gains a ton of momentum with every passing moment, the government and the public sector needs to understand the uses of this technology and use it for the benefit of the public.

 

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