IBM Watson – Technology Or Magic ?

Isaac Asimov, a science fiction author wrote a trilogy series called “Foundation” in 1950s. The foundation is all about a scientist named Harry Seldon who picks up a group of high IQ people in different fields at a very early age of 8 to 10 years and creates a civilization on an uninhabited planet. A super computer governs this civilization. Since all the people are of known behavioural trend, this computer not only analyses  characters and their offsprings, but also governs them silently. At any given time it can predict who is going to be their leader, how long he is going to rule and who will be the successor. It can predict the entire civilization for next 150 years. When an issue arises, the computer can predict and provides the solution for the same. It learns from the current civilization to prepare prediction for next 150 years.

Now the entire story is far fetched, but seemingly plausible, thanks to Watson. That is the power of Watson. Its artificial intelligence, though not as accurate as that depicted in the fiction, it is a starting point.

IBM Watson can analyse all the data fed into it and come up with an accurate prediction. This is not an easy task for any computer or logic. It really pains us when somebody thinks Watson just answers queries. It is not a product or a piece of code, it is an IBM (marketing) brand used for a whole bunch of stuff.

Please don’t confuse a framework with an algorithm. Tensorflow is a software library that can be used to implement a number of machine learning algorithms. It’s the algorithm itself that matters, not the framework. Tensorflow is just a library that helps with parallelism, which is only useful in a hand full of cases.

IBM developers – as far as I know – are a bit indifferent when it comes to libraries. They rely heavily on (and contribute to) open source and will use whatever works best. A lot of the components/algorithms they use are much older than TensorFlow and most machine learning libraries. If you ask me, they probably have built most of this stuff from scratch without using any particular framework.

IBM Watson is a cognitive computing based Artificial intelligence super computer which uses unstructured big data as a source. Watson is a question answering computer system capable of answering questions posed in natural language.

Watson is a question answering computer system capable of answering questions posed in natural language, developed in IBM’s DeepQA project by a research team led by principal investigator David Ferrucci. Watson was named after IBM’s first CEO, industrialist Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy!

In 2011, Watson competed on Jeopardy! against former winners Brad Rutter and Ken Jennings.

Watson received the first place prize of $1 million.

Watson had access to 200 million pages of structured and unstructured content consuming four terabytes of disk storage including the full text of Wikipedia, but was not connected to the Internet during the game. For each clue, Watson’s three most probable responses were displayed on the television screen. Watson consistently outperformed its human opponents on the game’s signaling device, but had trouble in a few categories, notably those having short clues containing only a few words.

In February 2013, IBM announced that Watson software system’s first commercial application would be for utilization management decisions in lung cancer treatment at Memorial Sloan Kettering Cancer Center, New York City, in conjunction with health insurance company WellPoint.  90% of nurses in the field who use Watson now follow its guidance wholeheartedly.

At the core, Watson is a complex NLP system. Numerous processes are involved that are rule-based, such as Lucene building a variety of indices, based on rules, as one of 20+ pre-processing steps for corpus content i.e documents that contain the domain knowledge.

There is a second phase where humans provide examples of implicit rules. A textual query is related to a portion of the corpus, Q&A, essentially telling Watson that when it sees the same query after training it should respond with the area of the corpus indicated.

The challenge is that Watson, and NLP in general, is a non-deterministic system based on probabilities. The training process above is repeated thousands of times and the algorithms  build up probabilities of the relationship of a text query to an area of the corpus.

Some experts will suggest that IBM Watson is a failure and some will tell you that it is the biggest technological marvel ever. The debate will be forever, the lesson is to take the positives from the Watson and build on it.

Harnessing its powers is the way forward.

Augmented Reality Applications

The phenomenal success of Pokemon Go showed the world the limitless possibilities of Augmented Reality in the field of entertainment and gaming. However not many are aware of the possibilities Augmented Reality opens up in the field of medicine and healthcare.

Today, we take a look at the ways in which AR can influence the realm of healthcare.

1 – Telementoring

This application of AR vastly expands the range and expertise of the physician working on a complex procedure. Suppose if a given operation requires deeply expert ands of a specialist but he/ she is not available on the hospital premises (or may be present in an altogether different geography), AR can come in handy.

With AR, a medical professional can become actively involved in an on-going procedure. This is achieved by virtually superimposing his/ her hand using Google Glasses for showing the right way to do a detailed task during the operation.

2 – Vision aid

Most of the legally blind people have a little bit of vision left in them. However this is not sufficient to do daily tasks like recognizing faces or reading or evading obstacles in their path. The startup VA-ST helps them to recreate some sense of vision using Augmented Reality. This will create a rough outline of a face (somewhat like a stenciled sketch). This will enhance the level of vision available to the user in poorly lit areas and those with lower level of visibility can figure out an object or a person in front him or her, to a better degree.

3 – Nursing aid

Nurses often find it difficult to find a vein on the patient’s vein to draw blood or inject drugs. While many can do so precisely, there are other who need 2-3 attempts before they are able to locate a vein. Accuvein is integrating Augmented Reality into its handheld scanner that makes this task quicker and more efficient. Using this scanner, nurses can easily locate the patient’s vein. The device has been tested on almost 10 million patients and the outcome has been exceptional. The device has proved to be 3.5x more likely to locate a patient’s vein on the first go itself.

4 – Better drug knowledge

Patients can get step by step dosage, mode of action, and its benefits simply by scanning across a bottle of the medicine. Users have the option to scan both the packaging as well as the printed text stuck on the bottle to uncover richer information about a particular drug’s benefit and probable side effects.

5 – Medicinal study

None of the fields within healthcare has seen the phenomenal benefits of AR as it is with the medicinal education field. Examples will be ARnatomy that uses OCR in its app to match a specific word like cranium and flash important details with visuals and information.

These are the different ways in which AR can interact with healthcare IT and create an immersive 3d world for precision based medical science education and procedures carried out by medical professionals.

Understanding Cognitive Computing

Gartner has rated cognitive computing as a platform that will bring about a digital disruption unlike any seen in the last 20 years. This makes it worthwhile for your business to check out cognitive computing capabilities and how it can deliver advantages to your business.

Cognitive computing systems bring about the best of multiple technologies such as natural language queries and processing, real time computing, and machine learning based technologies. By using these technologies, cognitive computing systems can analyze incredible volume of both structured and unstructured data.

The objective of cognitive computing is to mimic human thoughts and put it in a programmatic model for practical applications in relevant situations. This biggest name in cognitive computing – IBM Watson, relies on deep learning algorithms aided by neural networks. They work together to absorb more data, learn more, and mimic human thinking better.

Advantages Of Cognitive Computing

Today, we have compiled a list of some key benefits of cognitive computing through real life use cases:

1 – Better data analysis

Take the example of healthcare industry. Cognitive computing systems can collate information, reports, and data from disparate sources like medical journals, personal patient history, diagnostic tools, and documentation of similar lines of treatment adopted in the past from different hospitals and medical care centers.

This provides the physician with data backed and evidence based recommendation that can enhance the level of patient care provided to the patient. So here, cognitive computing will not replace the doctor, it will simply take over the tedious job of sifting through multiple data sources and processing it in a logical manner.

2 – Efficient processes 

Swiss Re is a great example of how a complex process can be made simpler by employing cognitive computing. According to officials, using cognitive computing helps them to identify and take action based on emerging patterns. It also helps them to spot opportunities and uncover issues in real time for faster and more effective response.

Its underwriting process for the Life and Health Reinsurance business unit was revolutionized when it used IBM Watson to analyze and process huge amount of unstructured data around managing exposure to risk. This enabled them to purchase better quality risk and thus add to their business margins.

3 – Better level of customer interactions

Hilton partnered with IBM to enable better quality of interactions and drive a superior front desk and hospitality experience to guests. The result is Connie, a Watson enabled robot concierge. It can provide amazingly relevant, contextual, and accurate information on broad subjects around travel and hospitality, like, informing about local tourist attractions, providing information on hotel amenities, and providing fine dining recommendations. Hilton is reimagining the entire travel experience with Connie, to make it smarter, easier and more enjoyable for guests.

These advantages highlight the massive potential that cognitive computing possesses. Embracing it at an early stage will help you experiment and personalize the tremendous power of cognitive computing to deliver incredible gains to your business.

IoT – Challenges

With IoT, the concept of smart cities is rapidly gaining ground. Bolstered by bullish sentiments in the tech landscape (Cisco estimates 50 billion smart connected devices by 2020), the Indian government too has grand plans for developing 100 smart cities across the nation. Once it figures out the infrastructure and ecosystem within which a smart city will work, we will truly be on the path to having a fully functioning smart city.

The premise of better safety levels, decreased pollution, efficiency in energy utilization, and superior quality urban lifestyle, have placed the spotlight on what IoT can do to enable the concept of smart cities.

IoT systems are versatile and flexible enough to support and drive a huge range of local municipal goals and government objectives. Taking just one case in point – the use of sensors can bring about a remarkable change in the way collaboration happens across different regional, state level, or national level government departments. Then, there is the concept of smart grids that ensures optimal utilization of resources, prevents wastages and enables zero shortages of basic utilities like power and water supply.

Hence, the potential of IoT for smart cities is exciting for today and exhilarating for tomorrow.

Challenges with smart cities implementation with IoT

In order to achieve this goal, it is necessary that town planners factor in the below limitations of IoT with smart solutions:

1 – Vulnerable to hacks

Most of the connections with objects will be enabled through RFID and these are vulnerable to hacks. Enabling a hack-proof IoT ecosystem will ensure a faster realization of smart cities development.

2 – Security and privacy concerns

Right from your toaster and refrigerator to your TV and car will be connected in a smart city. This magnifies the risk of leaving privacy and security vulnerabilities open to hackers. By providing a secure access mechanism, this risk can be bought down significantly.

3 – Problems with interoperability

While open standards has been around as a concept for the last 25-30 years, nothing concrete has come out of it. Rather than using interoperable systems, we see a user taking a side (think Google and Apple in case of mobility) and then building an entire ecosystem around this. This limitation posed by interoperability too will pose a problem in the future.

The continued tech advancement has led to a spurt in the number of tools, resources, and devices that can facilitate the value derived from IoT. This in turn will propel the development of smart cities at an accelerated rate. Advantages like reduced traffic congestion, better transit ecosystem between two points, can be effectively driven by smart town planning associated with smart cities.

However, this can happen only with active long term support from technology expertise and infrastructure enablers. Here, partnerships with smart IT providers and IoT experts will provide the necessary building blocks needed for the municipal town planner’s accomplishment of the smart city dream.

PHP 7 Traits Revealed

PHP 7 comes with latest features and fast performance as compared to its previous versions. PHP 7 has been introduced with a goal to free up space which leads to improvement. It was crucial to get rid of many deprecated functionalities , old and unsupported Server APIs and extensions to increase the speed and free up space.

This clean up provides more security by removing items that have deprecated for a while in PHP 5 and not in use for a long time. PHP 7 can break the code if your app is running on older version of PHP.

PHP 7 is a platform that can deliver powerful app, all from cloud to enterprise applications and from mobile to the web Applications. Almost everything comes under the umbrella of PHP 7. This version has the most powerful impact as it decreases the memory consumption with extreme improvements in performance.

Let us have a look at some of the new features PHP 7 is equipped with.

Speed Improvement

PHP 7 is benchmarks for consistently showing speeds twice as fast as PHP 5.6 . It provides unmatched computation speeds and flexibility to adapt to an ever changing environment. Thanks to the new Zend Engine 3.0, apps see up to 2x faster performance and 50% better memory consumption than PHP 5.6, allowing you to serve more concurrent users without adding any hardware. Designed and refactored for today’s workloads, PHP 7 swiftness paves a new path for all developers. 

Type Declarations

Type declarations simply means specifying which type of variable is being set instead of allowing PHP to set this automatically. PHP is considered to be a weak typed language. In essence, this means that PHP website development does not require you to declare data types. Variables still have data types associated with them but you can do radical things like adding a string to an integer without resulting in an error. Type declarations can help you define what should occur so that you get the expected results. This can also make your code easier to read.

Since PHP 5, you can use type hinting to specify the expected data type of an argument in a function declaration, but only in the declaration. When you call the function, PHP website development will check whether or not the arguments are of the specified type. If not, the run-time will raise an error and execution will be halted.

Also, with PHP 7 we now have added Scalar types. Specifically: int, float, string, and bool.

Error Handling

Handling fatal errors in the past has been next to impossible in PHP website development. A fatal error would not invoke the error handler and would simply stop your script. On a production server, this usually means showing a blank white screen, which confuses the user and causes your credibility to drop. It can also cause issues with resources that were never closed properly and are still in use or even PHP 7, an exception will be thrown when a fatal and recoverable error occurs, rather than just stopping the script. Fatal errors still exist for certain conditions, such as running out of memory, and still behave as before by immediately stopping the script. An uncaught exception will also continue to be a fatal error in PHP website development in 7.

New Operators

-Spaceship Operator: The spaceship operator, or Combined Comparison Operator, is a nice addition to the language, complementing the greater-than and less-than operators. The most common usage for this operator is in sorting.

-Null Coalesce Operator: The Null Coalesce Operator, is effectively the fabled if-set-or. It will return the left operand if it is not NULL, otherwise it will return the right. The important thing is that it will not raise a notice if the left operand is a non-existent variable.

Easy User-land CSPRNG

What is Easy User-land CSPRNG? User-land refers to an application space that is external to the kernel and is protected by privilege separation, API for an easy to use and reliable Cryptographically Secure Pseudo Random Number Generator in PHP website development. Essentially secure way of generating random data. There are random number generators in PHP, rand() for instance, but none of the options in version 5 are very secure. In PHP 7, they put together a system interface to the operating system’s random number generator. Because we can now use the operating system’s random number generator. Secure random numbers are especially useful when generating random passwords or password salt.

There are quite a few other features added in PHP 7, like unicode support for emoji and international characters. Another big area that could cause trouble, are features that have been removed. This should really only be an issue if you’re working with an older code base, because the features that have been removed are primarily ones that have been deprecated for a long time. If you’ve been putting off making these necessary changes, the huge advantage in speed with PHP 7 should help convince you, or management, to take the time needed to update your code.

That Thing About Internet

We are in the midst of one of the greatest shifts in manufacturing since the Industrial Revolution. At the heart of this disruption is the IoT. Smart connected products provide manufacturers incredible insight into how customers use products and services. This new level of understanding, combined with manufacturers’ deep product knowledge, is rapidly evolving business models and creating a competitive advantage. Manufacturers can use the data collected from IoT to lower costs, reduce downtime, improve future designs, and even push new features to equipment directly via the Internet. Forward-thinking manufacturers are using IoT to transform their business models by moving from one-time product transactions to ongoing product-as-a-service offerings. 

But what is IoT?

And how did it emerge as a game changer?

The Internet of Things allows objects to be sensed or controlled remotely across existing network infrastructure, creating opportunities for more direct integration of the physical world into computer-based systems, and resulting in improved efficiency, accuracy and economic benefit in addition to reduced human intervention.

When IoT is augmented with sensors and actuators, the technology becomes an instance of the more general class of cyber-physical systems, which also encompasses technologies such as smart grids, virtual power plants, smart homes, intelligent transportation and smart cities. Each thing is uniquely identifiable through its embedded computing system but is able to inter-operate within the existing Internet infrastructure. Experts estimate that the IoT will consist of about 30 billion objects by 2020.

The concept of a network of smart devices was discussed as early as 1982, with a modified Coke machine at Carnegie Mellon University becoming the first Internet-connected appliance, able to report its inventory and whether newly loaded drinks were cold. Mark Weiser’s seminal 1991 paper on ubiquitous computing, “The Computer of the 21st Century”, as well as academic venues such as UbiComp and PerCom produced the contemporary vision of IoT. In 1994 Reza Raji described the concept in IEEE Spectrum as ” small packets of data to a large set of nodes, so as to integrate and automate everything from home appliances to entire factories”.

Between 1993 and 1996 several companies proposed solutions like Microsoft’s at Work or Novell’s NEST. However, only in 1999 did the field start gathering momentum. Bill Joy envisioned Device to Device (D2D) communication as part of his “Six Webs” framework, presented at the World Economic Forum at Davos in 1999.

The term “The Internet of Things” was coined by Kevin Ashton in a presentation to Proctor & Gamble in 1999.  Ashton is a co-founder of MIT’s Auto-ID Lab.  He pioneered RFID use in supply-chain management.  He started Zensi, a company that makes energy sensing and monitoring technology.  He later sold the company to Belkin.  He has been involved in other startups, such as ThingMagic.  He is also the author of the book How to Fly a Horse: The Secret History of Creation, Invention, and Discovery.

In a 2009 article he wrote for RFID Journal, Ashton explained the term:

“The fact that I was probably the first person to say “Internet of Things” doesn’t give me any right to control how others use the phrase. But what I meant, and still mean, is this: Today computers—and, therefore, the Internet—are almost wholly dependent on human beings for information. Nearly all of the roughly 50 petabytes (a petabyte is 1,024 terabytes) of data available on the Internet were first captured and created by human beings—by typing, pressing a record button, taking a digital picture or scanning a bar code. Conventional diagrams of the Internet include servers and routers and so on, but they leave out the most numerous and important routers of all: people. The problem is, people have limited time, attention and accuracy—all of which means they are not very good at capturing data about things in the real world.

And that’s a big deal. We’re physical, and so is our environment. Our economy, society and survival aren’t based on ideas or information—they’re based on things. You can’t eat bits, burn them to stay warm or put them in your gas tank. Ideas and information are important, but things matter much more. Yet today’s information technology is so dependent on data originated by people that our computers know more about ideas than things.

If we had computers that knew everything there was to know about things—using data they gathered without any help from us—we would be able to track and count everything, and greatly reduce waste, loss and cost. We would know when things needed replacing, repairing or recalling, and whether they were fresh or past their best.

We need to empower computers with their own means of gathering information, so they can see, hear and smell the world for themselves, in all its random glory. RFID and sensor technology enable computers to observe, identify and understand the world—without the limitations of human-entered data.”

From a remote machine of coke which could report its inventory to a city which operate on itself,  IOT has indeed come a long way.

How to create a MarketPlace for your business

Probably you have a novel business idea that is keeping awake until late night, or you are just excited at the sudden success and trend of collaborative economies such as Air Bnb, Uber and want to try your hand at building a similar business model, then we can safely assume that you are interested in setting up your own marketplace.

Starting up today has become more easier than before and as the trend sees it, Startups are soon the way of the future. Sam Altman, the president of Y Combinator emphasizes that for any Startup to excel, there are 4 areas that need a concrete vision:

1. Idea
2. Product
3. Team
4. Execution

(Read more about this in Sam Altman’s lecture here..)

Image source: Art of Education

Whatever you are building, be it a multi-national business or a non-profit organisation, it all begins with the idea.

So, before you build your marketplace, we want to ensure that you have these five things sorted out to help you sail easily through your business.

Five things to keep in mind while building a MarketPlace

1. Solve a real-life problem

Most entrepreneurs are always very excited about their Startup idea. But do you have a vision that can translate this idea into a real-life product?

When creating a marketplace, you need to be 100% convinced of solving a real problem – for both the user and the service provider. That is how collaborative economies work – it is all about bring buyers and sellers on a unified platform and transacting business (something similar to e-commerce)

For example: Air BnB has disrupted the hospitality and travel industry because it solved one simple but important problem – finding cheap and nice places to stay. Hotels are not always an economic option especially for those who travel on budget trips. At the same time, Air BnB has shown that even the real estate market can be open to the hospitality industry with the right strategy. 

The only way to test your idea is by developing a minimum viable product and launch it. In this way you can be sure of the market and demand for your product / service.

2. Think as a Collaborator

If you are looking to tap into the collaborative economy, then you need to start looking at unused or idle assets that you can unlock. Whether it is creating a marketplace to make aviation parts easily available or creating an online metal trading portal, you need to think of your marketplace as a key that unlocks resources that would have otherwise not been easily available to consumers.

The benefit of creating a marketplace is that you can start one for almost anything – renting bikes, teaching classes, food or even gardening. As per the collaborative economy Honeycomb study by Jeremiah Owyang, the hottest startups are in transportation, goods and services and money.

Innovation is not always about creating something new, it is about doing the same thing in different ways. It is time that you put your thinking hat on and look at the resources around you in a different way. Think of opportunities of how you can acquire the maximum potential and that is when you will have a great marketplace idea.

Image source: Juggernaut

3. Look for fragmented markets

One of the key ingredients to the success of a marketplace is when you reduce the gap between customers and service providers. Think of the small players and the inaccessible products that are of great value but lack an organised business structure.

For example: A big challenge in the freelance market has been to find qualified and dependable freelancers who can work your projects. With marketplaces like UpWork, it has just become so easy to filter out the right freelance workers for your business – be it video, content writing, design etc. Thus, both buyers and service providers can easily communicate and transact business at ease.

Thus, think if your marketplace as a one-stop shop to satisfy all your customer requirements – right from finding the product / service, evaluating it, reading reviews and buying it. As a service provider, your platform will be his door to a larger target audience. Hence it is a win-win for both parties, solving both problems – thus re-iterating point number one – solving a real problem.

4. Enable a layer of trust

Trust forms the basis for any business and the same rule applies to online marketplaces as well. One of the biggest reasons for users to shy away from transacting online has been the quality of products and trust in sellers.

Transacting second-hand goods (such as OLX) has become more acceptable these days only because the portal allows buyers to directly interact with sellers, check product reviews, thus enabling a layer of trust between the two parties.

Your marketplace is not a directory to just list products and services. It is about creating an environment where buyers and sellers collaborate and communicate before transacting business.

For example: Skill Share is one such trusted platform for education where users who want to learn new and diverse skills can reach out to industry experts and sign up for their classes. Skill Share has a policy which checks and establishes the credentials of the teacher.

Marketing gurus such as Seth Gordan have their courses listed on Skill Share and this creates a brand trust at a subconscious level, thus enabling easy on-boarding of users.

Thus, it is very essential that your marketplace is able to create this initial level of trust with users.

5. Narrow your market focus

While it is nice to spread your wings wide and fly, when it comes to creating a marketplace, it is best when you cater to a particular segment of products / services and users.

Don’t think of yourself as Amazon or eBay with a hundred million products. Just focus on solving just that ONE single problem that your marketplace has been designed for.

The only reason Air BnB and Uber have been successful in disrupting the market is because the former focused on providing temporary accommodation while the latter focused on creating an on-demand transport service for users. Both of them has a clear and narrow focus on the problem they wanted to address and solve for users.

Also, when you narrow down your focus you will be able to identify your true competition. There could be a particular niche that has not been tapped into and you could create a marketplace for that particular product.

Trying to be the next Air BnB or Uber with your market place is not the best strategy to move forward. Instead, trying to create a seasonal renting space or creating a taxi service specially for women / kids could be the kind of marketplace innovation that you must think of.

To sum it all up….

All we can say is, you can create a marketplace for practically any product under the sun, but these five points will help you stay focused on what matters.

Also, at GoodWorkLabs we have a fool-proof solution that can help you build a marketplace solution that can help you promote your business to millions of users across the world.

Read about our marketplace solution here.

Microsoft Azure

The tech giant, Microsoft has launched major new machine learning tools. The company has made exciting announcements for developers who want to build new AI models.

Microsoft has launched three new tools at company’s Ignite conference. The new set of tools are designed to help developers working new AI models as well as those who want simply want to use pre-existing models. The company has launched Azure Machine Learning Experimentation service, Azure Machine Learning Workbench, and the Azure Machine Learning Model Management service.

Azure Machine Learning Experimentation Service

The service is designed to help developers train and deploy ML experiments. Microsoft has added the support for popular open source frameworks like PyTorch, Caffe2, CNTK, TensorFlow, and Cahiner. The service is designed to scale from local machines to hundreds of GPUs in the cloud. It also supports Apache Spark on Azure HDInsight clusters.

Azure Machine Learning Model Management Service

This is a desktop client for Windows and Mac. The tool can act as a control panel for your development lifecycle. Microsoft is projecting the tool as the great way to get started with machine learning. The new model management service uses Docker containers. The developers and data scientists can manage and deploy their models to any Docker container. Microsoft has included its own Kubernetes-based Azure Container Service.

Microsoft will continue to expand its toolbox for developers that want to build machine learning applications. The company is promoting its tools among startups that are working on innovative technologies. Microsoft’s latest offerings in Machine Learning can fuel the innovation across the globe.

Learning The Right Way

Technology, as a practitioner, is counter-intuitive.  This is perhaps the hardest concept for people learning to become technologists to understand.  It seems simple, but it affects so many things that will occur as you learn and grow your skill-set and build things.  The purpose in most cases of course is to build useful abstractions that make using technology feel intuitive to the end user, but as the practitioner you have to deal with the burden of this inherent lack of intuitiveness so that your users don’t have to.  

Bad technologies do exist, and in many cases, they’re bad because they attempt to make things easy which are not in any way easy or generally considered solved, and therefore encourage bad practices or hide critical problems.  PHP is a perfect example of this, MongoDB is another example of this.  There are hundreds of examples though that meet this criteria.  

Many of these bad technologies are very popular with beginners simply because they are easy to learn and work with.  The problem is, you will end up learning bad habits and putting trust in things which are not trustworthy.  This may not matter much when you’re just playing around on your own time to see how something works or try something new.  But the things you learn always end up coming back to you.  Your time is perhaps your most valuable asset, and how you invest it will determine many of the future choices you will end up making when you’re professionally using those skills to build something.

Because, ultimately, technologies are tools, just because a technology is bad in the general case doesn’t necessarily mean it should never be used.  But, it takes a significant amount of experience and expertise to adequately understand all the possible pitfalls of using a bad technology and whether or not those trade-offs are acceptable.  When you’re in the stage in your career where you’re still learning, this is not the time to throw away your very valuable time by investing in learning bad technologies.  You are much better off investing in learning technologies which are generally good, and ensuring you understand where all their skeletons are buried and what pointy edges exist, so that you can accurately and intelligently decide what trade-offs you’re willing to make in your designs.

The Definitive Answer

This is kind of the philosophical answer as to why we recommend not learning PHP as their first language.  While PHP is very easy to learn at a superficial level, it has a lot of faults and glitches that are not immediately apparent and are a direct result of it having a fundamentally bad language design.  These glitches can be near invisible, because they may not even prevent your application from working, but they could lead to opening up serious remotely exploitable security vulnerabilities or create a ticking time bomb waiting for the right conditions to cause the application to crash.  This type of unpredictable behavior is extremely frustrating even when you understand what is causing it, but as someone who is learning it wastes your time and distracts you from learning a clear understanding of the abstract concepts involved.

Python is an extremely sane, structured language, which is designed specifically to enforce good practices and help guide new programmers into understanding the proper way to build things.  Some of this is enforced in the interpreter, some of this is enforced in the community and the standards of companies and projects that use Python.  Either way, Python is an excellent first language to learn.  

The absolute best way to become a competent programmer, somebody who your peers look up to and rely on to be the person who can really solve problems, is to put a lot of effort in early on learning things the hard way.  Rather than picking heavily abstracted frameworks and technical tools that do a lot of heavy lifting for you, it’s important to understand why those pieces of heavy lifting are being done and what is going on in the background.  Python is a great introduction to this, because it’s abstracted enough to keep it from making you get dejected while learning, it provides immediate feedback because it’s interpreted, and it also provides an easy sliding scale to get you into deeper systems understanding.  

As technology continues to change and improve we have no doubt that there will be a need for you to continuously learn new things.  Don’t start from a easy to learn foundation, learn the fundamentals in a proper way so you have the right knowledge to act as building blocks for a long time to come.  

The choice is ultimately yours.

Progressing The Right Way

Irrespective of the platform, responsive and progressive mobile apps have always enjoyed immense popularity amongst users. The number of iOS app downloads for the year 2015 is around 25 billion. The amount exactly doubles to 50 billion in case of Android apps.

These statistics speak a lot about the immense significance of mobile web apps. It’s because of this popularity that numerous business owners and entrepreneurs make it a point to invest in enterprise app development.

Enter progressive mobile apps

With the ubiquitous presence of mobile applications, the biggest global search network, Google, has come up with a great proposal, keeping in mind the growing mobile users worldwide. Google has recommended a stronger ranking signal for progressive mobile apps that aligns with the mobile-first ethos of a growing number of organizations.

By leveraging browser capabilities and modern web, progressive apps aim to offer immersive experiences on web applications. In simple words, the term ‘progressive web apps’ represent technologies capable of bringing native application-like performance to web applications.

Essential browser features

Knowing the features of progressive mobile applications will help you understand their functioning. Browser makers will require adding some unique features for progressive apps. Some of these features include:

• Service workers: Independent scripts, running in backgrounds at browser side.
• Web-app manifest files: With the help of these files, developers can specify app attributes.
• Enhanced cache (offline): It maintains the state of apps in between visits.

These are some necessary changes that web browsers need to make for successful progressive web app development and functioning.

On that note, let’s check out some of the amazing features or highlights of progressive applications.

Tracking the difference

Progressive web apps mark the arrival of a new age in mobile app development. By ensuring an amazing and immersive experience for users, these apps redefine the way businesses can target customers, personalize their mobile browsing experience, and elevate overall user experience to an altogether new level. The following features are totally characteristic to progressive mobile apps and come across as its biggest USP:

1. Progressive: Offers perfect functioning across browsers
2. Responsive: Seamless operations across numerous platforms
3. App-like experience: Users will have the opportunity to experience app-style navigation and use app integrations.
4. Connectivity-independent: With these applications, users can also operate in poor connectivity.
5. Secure: Operates only through HTTPS
6. Installable: You can also install it on your home screen
7. Discoverable: Search engines can identify them easily as applications.
8. Linkable: Share your progressive web apps via a URL. No need to rely on app-store installations

Although the browser support for progressive web apps is not quite impressive currently, Chromium-based browsers such as Opera and Chrome are on the way to provide the necessary support. With Mozilla Firefox and Microsoft Edge developing their interface, it won’t be long before progressive web applications find a strong foothold in the tech arena.

Let’s not forget that Google Inbox and Flipkart have already joined the progressive web bandwagon. With such developments, the future of mobile web and progressive apps seems to be quite bright and impressive.