Artificial Intelligence

What is AI and How Deep Learning help to grow business

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AI (Artificial intelligence) is making machines intelligent that can perform cognitive tasks like humans and even more efficient than humans with the help of complex computer programming and enormous data fed to get an optimal solution for the problem. Though AI came into existence since 1956, but due to lack of data and technology could not become a reality.

Now proceeding further, there are two subsets of AI, Machine learning, and Deep learning. Machine learning gives computers the ability to learn without being explicitly programmed. Deep learning is a subset of machine learning, where deep artificial neural networks work as human brains and have networks capable of learning – unsupervised, from data that is unstructured or unlabeled.

Let us see how deep learning can help to grow business.

Implementing deep learning can be advantageous in many ways. Consider any following needs of your business be it:

• Interviews and Training: The trained human brains can take better interviews considering the company’s requirement without discrimination and partiality and can train employees for future utilization.

• Time consumption: Humans get tired and need time for refreshments. In the minimum time frame, maximum work can be done through deep learning. The pace at which the machine works is quicker than humans, without break or rest. Hence less time consumed.

• Accuracy: A large amount of data fed and information from the web can provide flawless results whereas humans tend to make silly mistakes easily.

• Customer service: Software robots now also can understand human sentiments which can lead to a quality response to valuable customers of your company which helps to retain present customers and gains prospective customers. If we talk about humans, sometimes due to stress or mood swings fails to give good services to customers.

• Innovations: Like humans, these robots can efficiently think about innovative products and lead towards the development of the company.

• Maintenance: Humans repair machines and things when it is damaged or stops functioning. But with the help of deep learning damaged machines/things are detected before time. So, it can get repaired in advance which can boost the company’s performance.

• Security: Depending on past experience and the company’s informative data software automation can detect frauds instantly which humans may not do every time.

Deep learning can save time, power and cost and perform better than humans in each aspect that can make any company grow not only double but up to ten times more. Deep learning is the future of business and will definitely change how most of the businesses have traditionally operated.

Big Data

Personal Data – Tracked and Mined By Mobile Apps

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While malware still remains to be a major concern for mobile devices a new study suggests that there are more severe threats lurking within your mobile apps. Data mining via intrusive mobile apps has become a topic of debate. There are a number of mobile apps that exhibit risky behavior when it comes to sharing personal information – that includes accessing user’s contacts, calendars, locations and more. The unwarranted data mining from apps is more of a threat to users than any malware. So, why should we care if any of the (seemingly innocent) app can access your contact list or look at your purchase history?

You should care because this unprotected flow of user data over unprotected networks could mean that more than just marketing companies are sniffing around for your personal info.

Have you ever wondered why a flashlight app might need your location, calendar or address book? In general, apps are collecting more information than required. This information may not always be created securely and may become the target for criminals and illegal activities.

Major risks that enterprises need to be aware of:

  • With the emerging trend of BYOD (Bring Your Own Devices), the problem of data mining is becoming even more important.
  • Enterprises need to be more careful when it comes to mobile device management.
  • Adequate security features can ensure that sensitive information does not get into wrong hands.
  • Strong passwords, network encryption and limiting the types of apps that can be downloaded on devices are some key measures to be implemented.

Above all, it is important to remember that data always flows two ways and it is important to keep your professional data separate from your private data. Never leave your devices open and be careful what you download on your mobile devices!

Artificial Intelligence

Chatbots: AI for Sales and Marketing

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Artificial Intelligence and Natural Language Processing has had a significant impact on the way chatbots are used in recent times. Chatbots today are extremely sophisticated and versatile tools that can help you automate a number of your business processes. They are awesome tools for helping with customer care queries. Apart from that, AI-powered chatbots can be part of your marketing initiatives and help push your customers seamlessly through your sales funnel. Here are some ways chatbots can fit into your marketing strategy:

A personalized experience

Personalized interactions can completely alter the nature of any conversation. Chatbots integrate with social media and gather data about every single person that they interact with. So, these chatbots can be highly effective when interacting with customers. They can also take the conversation a step further by offering personalized shopping advice based on the customer’s purchase history.

Larger engagement capacity

Chatbots not only have the capacity to engage with customers but also retain them. Unlike other forms of marketing, chatbots keep your customers entertained for longer. They can catch your audience’s attention and also send relevant information regarding your brand, products, and services. Essentially, a Chatbot is capable of up-selling, cross-selling in a personalized, conversational and engaging way.

Reach a wider audience

Chatbots are predominantly found on social media messaging platforms. They have access to a virtually limitless audience. They can reach a new customer base by tapping into new demographics and can be integrated across multiple messaging applications. This makes you more readily available to help your customers, hence opening new opportunities to increase your sales.

Gather and analyze customer feedback and data

Chatbots offer an opportunity to gather feedback from your customers. A Chatbot softens the approach to gathering feedback by naturally introducing questions to their conversations. Additionally, with the right machine learning tools, your Chatbot can analyze feedback and other information it gathers from users, giving you more insight into what your audience truly wants. From there, you can remodel your marketing strategy to become more focused on your customer’s needs, thus creating more of an inbound marketing approach.

Other than that, chatbots can also send personalized notifications that are relevant to each user. They can proactively communicate with customers visiting your site, making your business look more active and enhances your brand experience and reputation. Chatbots can also gather the information you need and then create personalized messages that can help guide your users through the buyer’s journey. You can effectively tailor your marketing efforts to each and every lead that visits your website or social media pages.


By implementing a Chatbot into your marketing strategy, you can learn about your audience, customize your marketing efforts accordingly, reach new consumers easily and monetize your social media profiles like never before!

Artificial Intelligence

Growth of Python in Machine Learning

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Machine learning is a branch in computer science that studies the design of algorithms that can learn. The typical tasks are concept learning, function learning or predictive modeling. Others include clustering and finding predictive patterns. Usually, these tasks are learned through available data that were observed through experiences or instructions. Python is an OOPs based high level interpreted programming language that is highly useful and focused on rapid application development. It is a perfect choice for artificial intelligence and DRY (Don’t Repeat Yourself). IT works perfectly as a glue language as well which is used to connect the existing components together. Python’s support for ever-evolving libraries makes it a good choice for any project whether Web App, Mobile App, IoT, Data Science or AI.

Python is used in a variety of purposes, ranging from web development to data science to DevOps.  The usage of Python is such that it cannot be limited to only one activity. Its growing popularity has allowed it to enter into some of the most popular and complex processes like Artificial Intelligence (AI), Machine Learning (ML), natural language processing, data science etc. The question is why Python is gaining such momentum in AI? And the answer lies below:

The most common areas where python can be used for machine learning are Search Volumes and Job Ads

Python machine learning in search volumes

Search volume indicates the search for information that is required for going deeper into a particular topic. Google too provides a tool called Google Trends that provides insights into the search volumes for keywords over time.

Python Machine learning for jobs is growing

The best example for this is Indeed which is a job site and like Google Trends they show the volume of job ads for particular keywords. It looks for occurrences over time of selected terms in job offers.  It gives an indication of what skills employers are seeking.  Note however that it is not a poll on which skills are effectively in use.  It is rather an advanced indicator of how skill popularity evolve (more formally, it is probably close to the first order derivative of popularity as the latter is the difference of hiring skills plus retraining skills minus retiring and leaving skills).

Less code and artificial intelligence

Artificial intelligence involves algorithms – lots of them. Python provides ease of testing.  Writing and execution of codes are also easy. It can implement the same logic with as much as one-fifth of the code as compared to the other Oops languages – thanks to its interpreted approach which enables you to check as you code.

Above all, it has gained a lot of momentum recently and is a good choice for applications based on AI, IoT or Data Science.