AI & Machine Learning

Machine learning jobs has been considered as one of the most sought after jobs by most industries. The job role such as ML engineer offers lucrative salary packages with a promising career. The machine learning field is one of the fastest-growing domains in the current technology industry.According to Indeed, a machine learning engineer has topped

Takeaway: AI is a hot technology, but many people have misconceptions on what exactly it entails. Here we take a look at some of the myths surrounding AI and examine the facts. Why is everybody talking about AI, yet we still do not see friendly robots like Data from “Star Trek” walking among humans? Did we remember to add

Each nation has its ancient monument or a pagan holiday — the relic of the days when our ancestors tried to persuade their gods to give them more rain, no rain, better harvest, fewer wars and many other things considered essential for survival. However, neither Stonehenge nor jumping over fire could predict the gods’ reaction.

Voice search emerged as one of the most popular technologies. Voice search is particularly popular for the teenagers and the millennial that prefer searching the web and popular platforms like YouTube with voice commands. For various app niches that require on the go searches, voice search is doubly useful.  Voice search and voice interactions in the mobile app space are there to grow and flourish. Voice search in the years to come will become more common to mobile user experience and for the vast majority of apps across the niches.

This article explains how to approach evaluating and ranking different AI Projects. Every organization has limited resources which they need to allocate to maximize impact. Depending on your position along the AI Maturity Journey, the trade-offs between impact and risks of AI Projects become more important. This post aims to give you a practitioner’s guide for evaluating different AI Projects. These methods have been tried and tested and are applied in the industry today. 

This article discusses and shows implementation of various exploratory data analysis methods for text data. Some common, some lesser-known but all of them could be a great addition to your data exploration toolkit. Hopefully, you will find some of them useful in your current and future projects. To make data exploration even easier, the article contains an “Exploratory Data Analysis for Natural Language Processing Template” that you can use for your work.

Workplace dynamics are shifting and employees require advanced technology to feel empowered, motivated and valued in their careers.  When it comes to ERP and the systems that employees interact with on a day to day basis, AI is a powerful tool to not only making processes easier, but equips people within the organization with the resources to best leverage their valuable time and talents. In today’s complex and dynamic business arena, the people experience reigns supreme, and internal AI investments are crucial to winning top talent.

There are many fields where specialised artificial intelligence is replicating human-like reasoning and cognition. Deep learning algorithms used by social media platforms like Facebook, for instance, are becoming increasingly more adept at recognising objects and people. That said, there is still a limit to what such technologies can accomplish. Are we on the cusp of achieving artificial general intelligence? It certainly might feel this way, but in reality we have a long way to go before we achieve true artificial general intelligence

The landscape of marketing has shifted from the physical to the digital and marketing, like many other disciplines, has had to adapt to this shift; reaching customers via different platforms with different means. The message has also changed and in today’s world, personalisation is king. Artificial intelligence in marketing is more common than you would think and today, the CMO and CTO are working more closely to make it a success

Machine learning will reinvent the enterprise as it redefines enterprise software itself. The enterprise will adapt faster to the external business environment with the automation of data processing and faster execution of business decisions based on insights gained from algorithms that shorten the time to learn from data. The enterprise has started to integrate AI and ML into its operations, but not nearly to the extent that many internet businesses have. Help from these companies could be the key to enterprise AI adoption.

AI is a big focus of new-age “faiths,” with aficionados envisioning a world where a globally universal machine would oversee life on earth and enforce morality in a completely objective, fair-“minded” fashion. But it’s not necessarily revolutionary. But the futurist money is on new spiritual inventions as we move forward, because the modern, technologically sophisticated world offers so many new and fertile fields for even seemingly outlandish beliefs. Anything is now possible in the realm of faith.