top 10 trending technologies in 2018

Artificial intelligence will reshape business strategies

Nowadays, AI brings enormous changes to the business, reshaping the entire industries with the power of advanced technologies and software. Some companies have acknowledged that it is time to implement an AI strategy for their businesses; however, the main part is still on the way. The large companies are more likely to have an AI strategy is with at least 100,000 employees, but for them, this process is especially intimidating. 2018 will be the year when the best firms will incorporate AI applications into strategic and organizational development. There is a potential for algorithms marketplaces, where the best ones created by engineers or companies can be shared, bought, and deployed for organization’s personal use.
Moreover, the constant development of machine learning and AI technologies promises that every business will be data-driven and every industry will be smart. With years of background work on prototypes and ideas, the changes now will be breathtaking. From healthcare to construction, banking and finance to manufacturing, almost every industry will be reshaped. Things that were hard to believe in are now becoming a reality. Virtual assistance for patients, computational drug discovery, genetics research, can give you a glimpse of the amazing use cases in medicine. There are many more applications for automation, robotization, data management and more in different industries that will bring significant changes.

Blockchain will reveal new opportunities in different industries

Everyone is now talking about blockchain, a revolutionary decentralized technology that stores and exchanges data for crypto-currencies. Blockchain actually opens other new possibilities way broader than that. The blockchain is a distributed database, a digital register of transactions and contracts. It stores an ever-growing list of ordered records, called blocks, each containing a timestamp and a link to the previous block. Affecting a variety of applications, blockchain has impressive prospects in the field of digital transactions which will open new business opportunities in 2018.
Due to the growing role of social responsibility and security on the Internet, blockchain technologies are becoming more and more relevant. In a system using blockchain, it is almost impossible to forge digital transactions, so the credibility of such systems will grow. This approach can lay the fundamentals of disruptive digital business for enterprises and startups. Companies, which were previously established in the offline space, will be able to translate the processes into a digital environment completely.
In addition, as the hype around blockchain in the financial services’ industry will slow down, we will see many more potential use cases in government, healthcare, manufacturing and other industries. Companies need to take blockchain risks and opportunities into account and analyze how this technology can influence customers behavior. Also, blockchain strongly influences intellectual property management and opens new insights in protection from copyright infringement. Some websites like Blockai, Pixsy, Mediachain and Proof of Existence have promised to apply blockchain technology for such purpose.

New approaches to privacy and security are coming

With the development of technologies and the growth of data and its importance, hacking techniques become more and more progressive. The increasing amount of devices connected to the internet not only creates more data but also makes it more vulnerable and not very well protected. Discussed above IoT gadgets are extremely insecure, and as they become more popular and widely-spread, our privacy continues to be threatened. In addition to IoT, almost all large enterprises are under threat of being hacked, as it happened with Uber or Verizon in 2017.
However, the solution is coming, and this year we will see increased activity in the direction of protecting our safety. Machine learning will be the most significant security trend establishing probabilistic, predictive approach to ensuring security. It implements techniques like the behavioral analysis that gives the ability to detect and stop an attack capable of bypassing static protective systems. There is also already mentioned blockchain technology, which brought to attention a new technology called Zero Knowledge Proof which will develop much more in 2018 enabling transactions that secure users’ privacy using mathematics. Another new approach to safety is CARTA (Continuous adaptive risk and trust assessment). It consists of a continuous evaluation of the risks and the degree of trust, adapting to the situation. This applies to all business participants: from the company’s developers to its partners. So, although our security continues to be threatened, there are promising solutions that can bring more privacy into our lives.

The Internet of Things will become intelligent

Intelligent things are everyday devices that are capable of smarter interaction with people and the environment. These things operate semi-autonomously or autonomously in uncontrolled real-world conditions without the need for human intervention.
Intelligent things have been in a spotlight for several years, and with a continuous expansion and enhancement in 2018 they will influence another worldwide recognized trend — Internet of things.
As this tendency proliferates, a network of collaborative intelligent things will be created, where multiple devices will work together developing IoT to its fullest potential. Connected to the global web and combined with each other with wired and wireless communication channels, things will turn into one big integrated system driving a shift in human-machine interaction. As a result of the fusion of artificial intelligence and the Internet of things, we may see some amazing technologies that are able to create smart homes and even smart cities.

Deep learning will be faster and data collection better

Nowadays, deep learning faces the challenges of data collection and the complexity of the computations. Due to the last problem, a big part of the innovation in hardware is aimed at speeding up the deep learning experiments, like new GPUs with a greater number of cores and different from today’s architecture that are now under development. According to Marc Edgar, a senior information scientist at GE Research, in the next 3–5 years, deep training will shorten the development time of software solutions from several months to several days. This will lead to better functional characteristics, increased productivity and reduced product costs.
Speaking of data collection, now almost all large firms have realized its importance and influence on the effectiveness of the work. In the coming year, companies will start using even more data, and the success will depend on the ability to combine disparate data. In 2018, companies will collect customer data via CRM, ticket systems, BMP and DMP, omnichannel platforms. Also, there is a rise in popularity in collecting data on specialized sensors like LIDAR. The integration of existing systems and the integration of all types of client data into a single information pool will definitely be a trend. Moreover, startups will continue to create new methods for gathering and using data, and therefore the costs for it will be reducing.

AI will refine auto constructing and tuning of models

Since Google’s launch of AutoML last year, the use of AI tools to accelerate the process of constructing and tuning models is rapidly gaining popularity. A new approach to AI development was revealed, automating the design of machine learning models. It showed the ability to construct models without the human input with one AI becoming the architect of another.
This year, experts expect the growth of the popularity of commercial AutoML packages and the integration of AutoML into large machine learning platforms.
After AutoML, a computer vision algorithm called NASNet was built that is able to recognize objects in video streams in real time. The “reinforcement learning” on NASNet was implemented with AutoML showing not only the ability to train the model without humans but even better results in comparison with algorithms with human input.
These developments significantly broaden the horizons for machine learning and will completely reshape the approach to models construction in the next years.

The CDO role will grow extensively

With the establishing of CDOs (Chief Data Officers) and other senior data professionals in top management, large organizations are changing their approach to data management. CDOs are now the driving force behind innovation and differentiation. They are in charge of revolutionizing existing business models, improving the communication of the company with the target audience, and revealing new opportunities to improve business performance. Their position in the company is relatively new, but it is quickly becoming mainstream. According to Gartner, by 2019 CDO position will be present in 90% of large organizations, but only half of them will manage to succeed. In addition to personal qualities, understanding the responsibilities, and awareness of the obstacles they might encounter, there is one more important thing that the company should do to unlock CDOs potential. Firms should consider branching the IT department into “I” and “T” separately, and CDOs should take the lead in the new group that is responsible for information management.

The debates on ethics will flare up

As AI industry makes significant progress performing various tasks and actions from everyday life, the question about ethics, responsibilities, and human engagement arises. First of all, who will be to blame if an artificial intelligence unit performs an illegal act? Do AI bots need some regulations? And, finally, will they be able to take all of the human jobs?
The first two questions assume that one-day bots will be legally recognized as a person and could take the responsibility and be punished for its actions. Although this perspective is still years ahead from now, the debates on ethics are happening right now, and the heat from the is only growing. Considering different possibilities, scientists are trying to find a compromise on bots rights and responsibilities.
In contrast to these debating questions, the possibility that robots will take all the workplaces is close to zero. Of course, the AI industry is developing extremely quick, but it’s still is very much in its infancy. 2018 promises to take the hype around this question down. And as soon as we dive deeper, understand how to interact with AI, and get used to it — the myth about robots taking over will be dispelled.

No more specific commands: growing of NLP

The usage of chatbots in customer service became one of the leading trends of the outgoing year. In 2018 applications will need the ability to recognize the little nuances of our speech. The users want to get a response from their software by asking questions and giving commands in natural language, and not thinking about the “right” way to ask. The development of NLP and its integration into computer programs will be one of the most exciting challenges of the 2018 year, and we have high expectations about it.
What is a simple task for a human — to understand the tone of speech, it’s emotional coloring, and double meaning — is also a difficult task for a computer that is accustomed to understanding the language of specific commands. These complex algorithms require many steps of predictions and computations, all of them must occur in the cloud and a split-second. With the help of NLP, people will be able to ask more shaded questions and receive apposite answers and, as a result, make better insights on their problems.

Self-teaching AI will be more confident without the human data

From the first invention of artificial intelligence, the future in this field comes faster than we expect. Experts predicted that AI would be able to beat a human in Go game in 2027. But it happened 10 years earlier — in 2017. It took only 40 days for the algorithm AlphaGo Zero to become the best Go player for the whole history of mankind. It was teaching itself without the input of any human data and developed strategies impossible for human players.
Next year the race for the creation of a developed, self-taught artificial intelligence will only continue. We look forward to AI breakthrough in solving many human routines: decision-making, developing businesses and scientific models, recognition objects, emotions, and speeches, and remaking the customer experience. Also, we expect that AI will be able to cope with these tasks better, faster, and cheaper than people. And exactly the possibility of algorithms for self-learning brings us closer to the implementation of AI into many areas of human life.