Join the TES Seminar on Saturday, September 14, 2019
at 11 AM – 11:50 AM
During this presentation we are going to discuss Principles of AI & Human collaboration, Use Cases which are being already used by top companies in dating & adult industries and the impact of ML on different departments in the companies.
Conferences for artificial intelligence, machine learning, and chatbots, have in recent years equated artificial intelligence with machine learning, as well as machine learning with neural networks.
The hype surrounding “Machine Learning” in the last few years has persuaded the majority of the IT industry that AI is when we find giant Big Data and give it to Artificial Intelligence, which then gives its own insights and finds the perfect solutions for different problems. But it’s not really the truth. Machine learning is a buzzword in the technology world right now, and for good reason: It represents a major step forward in how computers can learn.
ML can be used in many different ways. Usually smart businesses start with analytics departments and such visualization programs as Weka or What-If Tool(WIT) and then when businesses start to understand results and their product managers start to use this data in the beneficial for the business numbers way, it goes to the developers (or analytics with programming skills) who are capable to build proper models which can help businesses to grow.
Artificial intelligence is becoming good at many “human” jobs—diagnosing UX difficulties for heavy payers, translating languages, providing customer service—and it’s improving fast. This is raising reasonable fears that AI will ultimately replace human workers throughout the economy. But that’s not the inevitable, or even most likely, outcome. Never before have digital tools been so responsive to us, nor we to our tools. While AI will radically alter how work gets done and who does it, the technology’s larger impact will be in complementing and augmenting human capabilities, not replacing them.
Certainly, many companies have used AI to automate processes, but those that deploy it mainly to displace employees will see only short-term productivity gains. In Harvard Business research involving 1,500 companies, they found that firms achieve the most significant performance improvements when humans and machines work together. Through such collaborative intelligence, humans and AI actively enhance each other’s complementary strengths: the leadership, teamwork, creativity, and social skills of the former, and the speed, scalability, and quantitative capabilities of the latter. What comes naturally to people (making a joke, for example) can be tricky for machines, and what’s straightforward for machines (analyzing gigabytes of data) remains virtually impossible for humans. Business requires both kinds of capabilities.
Companies benefit from optimizing collaboration between humans and artificial intelligence. To take full advantage of this collaboration, companies must understand how humans can most effectively augment machines, how machines can enhance what humans do best, and how to redesign business processes to support the partnership. Through our research and work in the field, we have developed guidelines to help companies achieve this and put the power of collaborative intelligence to work.
Anyway, the hype surrounding machine learning has made it to our industry, and maybe soon, it will make it to your businesses as well.
The machine learning in dating & social networks derives much effort from psychologists to build computational model for solving tasks like recognition, prediction, planning and analysis even in uncertain situations.
Speaker: Anastasiia Bilous