What would you do if we told you that this text you’re reading was created by AI-based software? You’d probably start paying more attention and looking for clues pointing to its “artificiality.” And you might find a few. At least for now. But tomorrow? Remember, the long road to humanity’s robotic missions to Mars today began with its invention of the wheel millennia ago. Thousands of years of trial and error, transfer of experience, curiosity, and necessity have constantly developed human intelligence. Now artificial intelligence is undergoing the same process, and we have no doubt that its progress will be much faster than ours has been.
Challenging the Limits of Intelligence
Since the invention of computers, everyone from engineers and scientists to philosophers and science-fiction writers has dreamed of machines one day being able to think like humans. There have been heated debates about the issue ever since Alan Turing asked the question “Can machines think?” in 1950. In the years since, different models of how the human brain processes information have been proposed, which then paved the way for revolutionary advances that laid the mathematical foundations of machine intelligence. So great have these advances been that computers today can compete with and even outperform human intelligence in many areas. And we think this is just the beginning, because for us, intelligence isn’t a skill limited to humans, but rather a form of material organization, a universal and evolutionary movement, one whose limits are defined only by how willing we are to challenge them.
Big Data for Learning Systems
Whenever we make a decision, our minds draw upon years of accumulated experience via complex nonlinear patterns in the brain to judge the potential usefulness of the different possible outcomes to which our decision might lead. These patterns are modified and perfected throughout our lives every time we make a decision. Machines can be trained using a similar method, inputting sufficient data to produce the desired output. Like the countless data that humans encounter and process in various fields, the intelligent systems we design need big data to learn. That is one of the reasons why we conduct R&D projects in e-commerce and medicine that collect big data, so that we can use it to train our AI systems and artificial neural networks to become advanced expert systems.
Artificial Intelligence is the Key to the Revolution
At Tekhnelogos, we focus primarily on areas where the use of AI offers a big cost and efficiency advantage. One of these areas is e-commerce logistics, where we combine the robotic products we have developed in this field with the AI-centric software BeeSmart. We aim to make our second-generation logistics robots fully autonomous with AI support. Moreover, we are developing smart product-recommendation engines so that e-commerce customers can access the right products faster. Our most important AI product is a pioneering medical decision system that offers disease diagnosis and treatment recommendations based on patient data. This system can be trained with disease data obtained from health centers in a particular area, country, or region to ensure that its diagnostic and treatment recommendations are geared toward particular geographical demographics
For a Higher Quality of Life
Despite the dystopian predictions of some, AI stands to greatly improve human quality of life. An economic system in which intelligent machines are strategically put to work will provide a greater equality of opportunities and a wider range of services than one in which they are not. We view AI as a human-oriented technology and work to develop products that harness its potential to maximum effect. We are particularly focused on the great opportunities AI offers for cheap, widespread, and quality healthcare services across the world.
AI and Society
We believe that AI is going to be vital to the future of scientific and economic development at the national and international level. For this reason, we carry out various community projects to develop AI awareness and to promote a shared understanding of AI’s potential. We also organize national and international AI game tournaments and local AI student camps to encourage young engineers to develop their AI skills.
Assistant Professor Tuna Cakar
Thanks to machine learning and deep-learning algorithms, the number of self-learning systems is growing. Over the next 20 years, the active use of such systems is only going to grow further in sectors from education and finance to marketing and medicine. In the fields of health and medicine, AI will provide physicians and specialists innovative diagnosis and treatment solutions and aid them in making informed decisions. In the field of finance, AI models will be able to analyze loan applications and help determine the suitability of applicants. And in education, AI applications coupled with adaptive learning models will help educators prepare content tailored to students’ levels, thereby maximizing student learning.
Our AI Products
A smart software program that gives orders to hundreds of robots navigating e-commerce warehouses, setting their routes and allowing for quick collection of orders.