Home Artificial Intelligence Merging big data and AI is the next step

Merging big data and AI is the next step

Merging big data and AI is the next step

AI is single of the most popular trends in technology at the moment, but what ensues when it merged with another trendy and extremely promising technique?
Researchers are considering for ways to combine with AI and take larger data to the next level. We have just recently realized how industry-wide disruption can be and big data is swiftly marching towards a level of maturity that promises a bigger, by uniting it with AI, powerful big data.

What is the expected convergence of large data and AI?
The use of artificial intelligence on large figures is arguably the most significant modern success of our time. It again defines how to create value with the benefit of business data. Availability of large data has created unprecedented success in machine learning which was not possible before.

With access to big volumes of datasets, the business can now come up with come up and meaningful learning with amazing results. It is no sensation why business focuses more on a hypothesis based research approach than “data first” strategy is moving forward.

But how big is the data to be successful in artificial intelligence?
Businesses can currently process large-scale data that was not possible unpaid to technical limitations. Before that, they had too expensive hardware, purchase powerful and software. Extensive unavailability of data is the utmost important paradigm shift in promoting the culture of origination in the industry. The availability of large-scale datasets coincides with the extraordinary breakthrough in machine learning, primarily due to the appearance of better, more gauche AI algorithms.

The best instance of these successes is the computer-generated agent. Virtual agents known as chat bots have gained extraordinary traction during the time. Previously, chat bots had suffering finding some phrases regional accents or phrases, nuances or dialects. In fact, greatest chat bots are stumped easily with the expressions and words. With the separation of AI and big data, we can appreciate new step forward in the way.

IPSoft’s Amelia
A good example of self-learning essential agents is Amelia, which is a “cognitive agent” developed by IPSHOFT recently. Amelia can appreciate everyday language, can learn really fast and also gets smarter through time! He is stationed with Nordic Bank SEB’s help desk with many public sector agencies. Amelia has responded positively to the executive teams.

Google’s Deepmind
Google is also delving deeper into big data-powered AI learning.  Google’s own reproduction Intelligence Company DeepMind has developed an AI that can impart itself to run, climb and jump deprived of any prior guidance. He had never been taught what is going on or going on but he has been successful in learning himself through trial and error. The effect of these successes in the realm of artificial intelligence is amazing and can provide the foundation for further innovation in the future.

Microsoft’s Tay
Some time ago, Microsoft established its artificial intelligence chatter, which was decided. The bots were made available for people to chat and they could study through human contacts. However, Microsoft introduced the plug on Twitter only one day later on this project.

Should we worry about the development of AI?
Some fans of science-fi films like Terminator also have a lot of information in it with access, artificial intelligence can be self-aware and it can launch cyber-attacks on a large scale or even that can capture the world too. More faithfully speaking, it can exchange human jobs. Looking at the amount of e-learning, we can understand that how many people about the world are apprehensive with self-learning it is using for larger data and AI. Whatever the situation, the possibilities are together intriguing and terrible.

Maybe we’ll finally see a bot on the support desk in the banks, waiting to congratulate us. Through self-education and the bot will have altogether the knowledge, unlike any human assistant, it will need to answer all of our questions? Whatever application, we can certainly say that with the combination of large data with artificial intelligence, new challenges and innovations will start in the age and technology of new possibilities. Let’s just despair that the faults of the qualities of this union will overtake.

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Patrick Goh Mr. Patrick Goh B.S is a research engineer with more than 10 years in industry of IT, Engineering and Financial market experience. In 2013, he joined financial institute’s research team as R&D software engineer mainly researching on technical analysis, inter-market correlation and fundamental factor in leveraged trading instrument using machine learning technique and programming algorithmic trading strategy by quantifying trader sentiment behind the price movement.


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