So far 2018 seems to be a great year for innovations and technological revolutions that are disruptively changing the shape of the industry. Be it a startup or tech giants, no stones are left unturned !! These rapidly growing trends with a high degree of volatility would reach tipping points over the next five years. Lets have a look at those top technology trends that we have identified to be dominating this 2018.
1) Artificial Intelligence
Customer personalization takes the front seat for technology break-thru. Evolving current systems and creating new systems that learn, adapt and autonomously respond efficiently will be a major area of focus for technology companies through at least 2025. The AI will be used to enhance decision making, reinvent business models and ecosystems, and remake the customer experience which will drive the payoff for digital initiatives for the next 5 years. To support this technology giants like Amazon [AWS ML], IBM [Watson], Microsoft[Azure ML] and Google [Cloud ML] have come with their own AI platforms. Major investment areas include data collection, analysis, algorithm building , model building and execution methodology. For AI to succeed several verticals have to work hand in hand esp. data scientists, business analysts & programmers.
AI techniques are evolving rapidly and organizations will need to invest significantly in skills, processes and tools to successfully exploit these techniques and build AI-enhanced systems.
Blockchain provides a distributed, secure, and unique system of records, so you can have a strongly encrypted authentication mechanism that prevents malicious users from breaking in. By storing data across its network, the blockchain eliminates the risks that come with data being held centrally. This makes it a great choice in terms of enterprise security, especially for identity access management system, which manages user logins and authentication. In 2018, we have started to see blockchain adoption in areas such as banking, financial services, and healthcare.
3) IoT Extravaganza
Though IoT has been in the context for several years, 2018 is all about hyper-connected world. Automobile industries have been working on IoT for several years and other industries are catching up rapidly. Portable mobile devices available these days are quite powerful and people can always be connected to the system thru the mobile with IoT.
Combining blockchain with IoT , AI with IoT & Immersive technologies with IoT has opened new ways of learning and understanding the system behaviors and thereby render a more efficient operation protocol.
4) Immersive technologies go mainstream
As per Gartner’s Hype cycle for AR(Augmented reality) and VR(Virtual Reality), the technologies are just heading towards the plateau of mass productivity after sustaining for the last 9 years thru several ups and down. The future is all about infinite displays and eventually all fixed display devices will be replaced by AR and VR. With companies like Facebook, Google and Apple leading the immersive technology way the transformation aint that far.
5) Data Science
A data scientist’s chief responsibility is data analysis, a process that begins with data collection and ends with business decisions made on the basis of the data scientist’s final data analytics results.The data that data scientists analyze, often called big data, draws from a number of sources. There are two types of data that fall under the umbrella of big data: structured data and unstructured data. There is always someone watching us and collecting data in the digital world. With so much data being collected from end users , sky is the limit to what could be done with that!
6) Seamless conversation [nlp, chatbots, news bots & etc]
Machines understanding and speaking human languages naturally is driving the next big paradigm shift in computer-human communications. Google’s Tacotron is a text to speech engine recently tested by Google and is found to sound just like a human ! There are several other companies working in the area of conversational chat bots that are successfully deployed and are serving the end users more efficiently. There are also bots that are deployed by media houses to write their own article based on the flash news it is fed on!
Cybersecurity has become essential to everyday life and business, yet it is increasingly hard to manage. Better the security ,even better are the exploits! Pure automation is just not enough. AI enhances the data analytics and automated scripts. We still cannot avoid human intervention. We need more funding and intensive research in using deep learning techniques to make the entire security system more robust.
8) Robotics & Assisted transportation
Intelligent things use AI and machine learning to interact in a more intelligent way with people and surroundings. Some intelligent things wouldn’t exist without AI, but others are existing things (i.e., a camera) that AI makes intelligent (i.e., a smart camera.) These things operate semi autonomously or autonomously in an unsupervised environment for a set amount of time to complete a particular task. Examples include a self-directing vacuum or autonomous farming vehicle. As the technology develops, AI and machine learning will increasingly appear in a variety of objects ranging from smart healthcare equipment to autonomous harvesting robots for farms.
9) Digital centralization: Digital twin
A digital twin is a digital representation of a real-world entity or system. In the context of IoT, digital twins are linked to real-world objects and offer information on the state of the counterparts, respond to changes, improve operations and add value. With an estimated 21 billion connected sensors and endpoints by 2020, digital twins will exist for billions of things in the near future. Potentially billions of dollars of savings in maintenance repair and operation (MRO) and optimized IoT asset performance are on the table.
In the short term, digital twins offer help with asset management, offer value in operational efficiency and insights into how products are used and how they can be improved.
10) Super cloud – Edge Computing:
All data storage and data processing are mostly done in the cloud for easy portability, ease of access and seamless interaction with other entities in the ecosystem. With advancement in cyber-security cloud storage is becoming the preference for small , mid sized and large companies too. Edge computing describes a computing topology in which information processing, and content collection and delivery, are placed closer to the sources of this information. Connectivity and latency challenges, bandwidth constraints and greater functionality embedded at the edge favors distributed models. Enterprises have started using edge design patterns in their infrastructure architectures — particularly for those which involved IoT interactions.
Thats just not it ! There are many more technologies which are in various phases of their Hype Cycle curve. These technological advancements and customer experience behaviors have forced the enterprises to upgrade their operational protocols! This marks the birth of Industry 4.0 !!