The Innovative Application of Machine Learning In Product Development

No matter how much tech-savvy the world is becoming, very often people get themselves puzzled in the labyrinth of new evolving and advanced technology trends. And whenever this kind of situation occurs, people have somehow found the way to understand it and how to use it in the running situation. This is something like going on between the world and the recently emerged idea, called machine learning.

Let's begin with understanding what this machine learning actually is:

In a simple way, we can say that it is an analytical and logical method that uses algorithms to find out some particular hidden patterns of data from a large database. The whole procedure is adaptive, means the moment a new data comes at the front, the models of machine learning services modifies and refines their prediction.

The idea of this technology is new to the world, still, it has already brought about notable changes to the world of business, especially in product innovations. The impact of this trend on the growth and development of business is so great that from the large-scale business enterprises to well-established industries, everyone wants to take a fresh bite from this hot toast.

Why Is Machine Learning Taking Over Industries?

Machine Learning is the latest and trending attitude of technology in the digital landscape, turning our evaluation of data into more efficient, and reliable. The transformational flair of this technological trend is the actual reason behind its remarkable growth in popularity in the financial, healthcare, and retail sectors. It is helping the banks, insurance companies, investors, hospitals, to enhance their productivity, launching new innovative services. For example, with the emergence of the smartwatches, both the doctors and the family members can track and monitor the health telemetry of the elder people. The business owners in the financial, healthcare and retail industries have become able to enhance their client satisfaction level and manage the risk, simply by the touch of this great process.

Let's Explore That How This Technology Is Driving Product Innovation

The following are a few great examples of leveraging the concept of machine learning for better product innovation.

Siri And Cortana

Siri and Cortana are voice recognition systems that use machine learning as well as the neural networks to copy the way human interacts. Soon there will be improvements when these voice recognition systems will detect the subtle differences and semantics of each language in the world.

Facial recognition at Facebook

Facebook's 'Tag' feature is an innovative gift of machine learning. The advanced Face Recognition algorithm helps Facebook to recognize the faces in the photos easily, and tag your friends automatically on your behalf.

PayPal

PayPal is a platform to process online payments. PayPal uses a machine-learning algorithm against fraudulent activities. PayPal analyzes the data of its customers to assess and gauge the risk.

Uber

Uber also uses a machine-learning algorithm to regulate the arrival time and the locations for picking up the customers.

Google Translate

Google Translate is the most used machine translation services, all over the world. The machine learning algorithm helps the software program to single out certain patterns of language from the millions of documents.

With the emergence of this technological trend, we can say that the world is shifting towards the golden age of science and technology, and with it soon we will open the locked doors of science fiction.

Creative Ways You Can Improve Your Alexa Skills Development

Over the past decade, voice assistants have progressively entered our lives. Names like Alexa, Siri, Google Assistant, and Cortana will surely ring a bell. But it was way before these names that the concept of a voice assistant was brought to light.

As far as back in 1962, IBM launched the first-ever voice assistant, named Shoebox. If you hadn’t guessed it, its size went by its name. It could do the mathematical functions and recognize digits 0-9 and 16 spoken words. Then came Harpy with a vocabulary of a three-year-old, it could recognize 1,011 words.

All of these initials innovations had paved a way for what was to come next. Apple, Amazon, Google, and other giants got their best brains on this, and the result was for the world to see!

Fast-forwarding to today, “Hey Siri”, “Alexa!”, “Okay, Google” is commonly known.

But out of all these, Alexa stands out for the masses. Being available on 100Mn devices, it has become the talk of the industry. And it isn’t just the Talking Tom with a speaker, it actually does your chores for you, and sometimes gets you like no one else.

Technically speaking, it uses AccuWeather to provide weather reports and news with a plethora of sources such as NPR, ESPN, and local radio stations.

It understands users’ needs for the beats and streams all of the rock, pop, and midnight melodies from the owner’s Amazon Music account, and offers built-in support for Spotify and Pandora accounts. It can manage the alarms and to-do lists in the way you want and also make important calls for you.

All these tasks Alexa does is through its built-in capabilities called Alexa Skills Development. Users can teach and inculcate new skills in Alexa using the Alexa Skills Kit, which can then be accessed by making requests or asking questions. You can create smart home skills, music skills, video skills, flash briefing skills, and custom skills as well.

It is a comprehensive device operating on the latest technology and does everything that you could expect from a voice assistant at the most.

In this guide, we’ll look at custom Alexa skill development, but before that,

“Alexa, what all should I know before building an Alexa-skill?”

 The common (obvious) prerequisite to building any type of skill is an account on the Developer Console, which would be used to create the configuration for your skill.

The configuration would require the information about the skill, such as the name of the skill, the type of interaction model, the content feed or endpoint, and other information. This configuration is used to determine the user requests that should be sent to the Alexa service for your skill.

Tools to build a Custom Skill:

You will need an internet-accessible endpoint to host the cloud-based service, Amazon Web Services(AWS) account, and Amazon developer account to use AWS Lambda, an appropriate developer environment, and an Alexa-enabled device for testing.

Tools to build a Smart-Home Skill:

You would need an account with AWS, an appropriate developer environment for your preferred programming language. You can use Node.js, Python, Java, C#, or Go to author a Lambda function. For testing, you must have an Alexa-enabled device.

Tools to build a Video Skill:

Building a Video Skill would require a cloud-enabled video service provider with a public API or access to the cloud-based service, an account with AWS, an Alexa-enabled device, and an appropriate developer environment for coding.

Tools to build a Flash-Briefing skill:

You will need a content feed that would be accessible via the Internet, using RSS or JSON, which would refresh with the new content.

Tools to build a Music skill:

For a music skill, you need to have an Amazon developer account, an Alexa-enabled device registered to it, an AWS account, a music service to stream music and a cloud API to control it.

“Alexa, how do I make you work?”

 Alexa could be requested for telling the horoscope in two ways, one is,

Alexa, ask Horoscopes Today for the horoscope for Pisces.” where the sample utterances are matched with the invocation, the other is:

“Alexa, what is my horoscope?”, where an Alexa custom skill is indirectly invoked.

It is all a simple play of intents and utterances, your sample utterances should match the invocations you use to ask questions or request Alexa.

The invocation name is combined with a command, action or question which further sends an “IntentRequest” with the intent corresponding to the user’s requests. The command, action, or question in your invocation phrase is defined in the sample utterances and mapped to the intents.

Times may come when the users would want Alexa to just get whatever they are saying, to ease the exasperation that may result, provide a plethora of sample utterances written in various forms.

Also, who would not want to get their personalized playlist listed beside every mood that a day could encounter. Alexa can stream music and media as you ask it to. Once the Alexa device is registered to the user’s Amazon account, they can request any track from their fully-accessible Amazon Music Library.

“Alexa, what are your Technical Aspects?”

What are the technicalities to keep in mind?

Now, there should be no ambiguity in the answer to this question. The job here is to create a cloud-based service to handle the request for the skills and host it in the cloud.

To build a custom skill, the AWS Lambda function is used. An alternative to this is writing a web service (in any language), in which case the web service would respond to the request sent by Alexa.

An Interaction Model is defined when creating a custom skill. It is used by Alexa to fetch the words from the voice and translate them into a request, which is then sent to a particular skill.

The other skill types have their APIs which provide a built-in interaction model.

“Alexa, how do I build a Skill?”

The skill-building process is organized on the Developer Console in a systematic way from creating a skill on the Build page to testing and analyzing it.

• Building a Skill:

On the Build Page of the Developer Console, perform the setup and configuration of the skill. Specify the corresponding interaction model and the endpoints for the service. All these options are easily available on the Developer Console.

However, it depends on the model of the skill that what specific options should be used here. For a custom model, intents and sample utterances are created. For pre-built smart home models, an endpoint is specified and account linking configuration is performed.

• Testing a Skill:

A skill could be tested in multiple ways. Utterance Profiler is used to test the custom interaction model.

On the Test page of the Developer Console, there is a simulator that gives access to the Alexa Skill development Kit features, and it is used for testing the skills. Another option is to test using an Alexa-enabled device.

The skill can also be tested from the command-line using ASK CLI commands.

Or else, Skill management API provides the skill-testing features for the same.

• Previewing a Skill:

The Distribution page on the Developer Console is used to determine the availability of the skill and have a glance at how it would appear when viewed in the Skill Store.

The metadata used here is language-specific. The details are required to be filled in each language supported by the skill. This data would then be displayed on the skill detail page accessible in the skill store.

• Verifying a Skill:

On the Certification page, verify that your skill is all ready and submit it for the certification process. The publication status of the skill will be displayed on the Status column of the Developer Console.

Once the skill is published, the publication status changes to live. Here, the skill can also be hidden or removed.

If there are any certification failures or issues, then they are fixed for successful validation and certification.

• Analyzing a Skill:

The Analytics page on the Developer Console is used to view the usage metrics for a skill. This dashboard depicts detailed information about how the customers are using the skill.

The present demand of the Voice Assistants has made it clear that they are changing the lifestyle of the people for good. It has been analyzed that the people who do not own a smart voice assistant desire to purchase one.

It is anticipated that the voice assistants would be made so smart that on your slightest whisper of “Alexa, I’m hungry”, it will automatically order your most favored cuisine.

AI has the capabilities that will help the smart speakers to think and learn by themselves without being programmed for every other intent. Artificial Intelligence is going to be the market leader and Voice Assistants, being a product of it, and always learning and improving, aren’t going anywhere. The Voice Assistants are here to grow and stay.

Now, if you’re looking for Alexa skill development for your company, make sure you hire a professional team and avoid any last-minute hassles. It’ll not only help you improve your customer services, but also help you save your time while placing you ahead of your competitors.

If you are looking for Alexa Skill & Mobile app development services, visit our Website: http://itpathsolutions.com/

The Direction That IOT Is Going to Take

The term IoT or Internet of Things is no longer tech-speak in the latter half of 2019. It has acquired a social dimension to itself with more and more people, not all of them necessarily technically very savvy, beginning to realize that IoT is going to play an increasingly important part in their daily lives.

They are even beginning to rue its presence a little as evidenced by the many funny anecdotes we hear about the various digital assistants performing in very unintended ways. From Alexa creepily laughing for no apparent reason at all to it sending people's recorded private conversation to some other user, there have been questions raised about their very desirability.

That being stated, there seems to be a gradual realization that IoT and the various devices it empowers are soon going to be as ubiquitous as smartphones. Let us take a look at the various uses to which IoT is going to be put soon:

Industrial Applications

IoT is largely talked about in the context of how it impacts us personally what with all that talk about autonomous smart homes taking decisions for us. But it is in its industrial application that IoT might show its true worth. A digitally connected factory, for instance, can use IoT to transmit real-time operations information to an operations manager at another location. This will lead to a far more efficient monitoring and resolution of operations-related issues than is currently possible.

Inventory can similarly be globally tracked right across the entire supply chain. Another area of use would be smart packaging. Products embedded with sensors can transmit data about their condition while in transit. This will one to improve and enhance the quality of the product and its packaging.

There is a buzz developing around IoT or the Internet of Robotic Things that will empower one to measure a robot's performance over an industrial cycle. Enabling advanced robotic capabilities by the linking of robotic things (sic) is achieved by leveraging the power of communication technologies like cloud computing and cloud storage. This allows the robots to have access to powerful computation resources, which does away with the necessity of costly updates and maintenance. This imparts tremendous flexibility to networked robotics to ideally apportion shared computational resources and enhance their output exponentially.

Smart Cities Galore

Going forward, it won't just be people and industries that will increasingly rely on IoT development devices to enhance efficiency and make things easy for themselves- whole cities will turn to it to make things run better. Cities will be able to collect, collate and leverage data with the help of cabs, public kiosks, surveillance video cameras, and any other form of gadgetry with a public interface.

This will help towns and cities optimally deploy and utilize resources and be able to reach vital services to people in the best possible manner. This will effectively solve many of the typical problems faced by urban centers around the world-traffic snarls, power shortages, poor access to educations and healthcare centers and so on.

5G Networks to Power IoT

With more and more nations making the rollout of 5G telecom networks, the IoT will truly come into its own. This is because the greater speed provided by these networks will make it possible to connect devices across the board like never before.

Faster internet speed will make it possible for the data collected by the myriad devices to be interpreted faster and better. This will provide a fillip to the creation of new and innovative IoT products that will increasingly find their way into our daily lives.

Auto Industry Reboot

IoT deployment aided by lightning-fast 5G networks will revolutionize the auto industry as we know it today. Driverless vehicles aided by greater interconnectedness and will come into their own in the coming years. People will come to believe in the concept like never before and driver-less automobiles will become increasingly ubiquitous.

The Way IoT is Headed

One can gauge future trends concerning the universal adoption of IoT by the following facts:

1. The number of IoT enabled devices in the world will touch a whopping 20 billion by 2020.

2. Total investment by business in IoT by 2021 is estimated at a gargantuan $6 trillion by 2021.

3. By some estimates, one can look forward to an addition of $15 trillion