The Afeka Academic School of Engineering in Tel Aviv is a university founded in 1996. Specialized in engineering and science, its students then enter the Israeli and global fields of high technology, research and development, defense, electronics, software, medicine, machinery and management, among others.
Together with TheMarker, Afeka conducted a survey revealing the most important skills for Israel's high-tech sector. Presented during the annual Skills&Tech conference, the “Skills Index Survey,” conducted for the second time, collected data from 150 managers supervising at least 25 employees in high-tech and other sectors in June this year.
The results indicate that understanding AI is now the most crucial skill for hiring in the sector.
The study also highlighted the growing value of mental resilience among employees, a skill that did not feature among the 13 prominent soft skills in last year's survey. Specialists indicate that this may be related to the context of crisis that Israel has faced since the Hamas attack on October 7 of last year.
Ami Moyal, the President of Afeka College, stated that “the need for basic skills such as critical and creative thinking remains a priority and has even increased in terms of importance since last year. This is because those are the skills necessary to make the most of the AI tools".
For his part, the CEO of Google Israel, Barak Regev, who participated in the conference, expressed that “high technology has been the engine of this economy during the last decade. It is responsible for 53% of our exports, but only 10% of our workforce is part of this industry. Think of the possibilities if we increase that percentage to 15 percent.”
Programming an AI in itself is not very complicated for most programmers, surprisingly it is a simple knowledge to learn and put into practice, at least for a normal level or the level that most AI programmers handle. , because the so-called programming libraries and APIs provide almost everything done, the most complicated part of the programming codes is already prepared and ready to use in common codes or in remote services of multinationals and other large AI companies. On the Internet you can find a lot of information, example codes, and online courses, even free. A very different case is to innovate or improve an AI at the lowest level or the most complicated level of its programming, or the tests to find optimal performance or results are not simple, or to apply the best option among the different algorithm possibilities. of known AIs and optimize the data for the initial training of the AI. But at a less technical level, the most important thing to develop AIs, at any programming level, may be to have, in addition to experience, eclectic knowledge or a team of experts who know very well the limitations of AIs or how to apply real science tasks in an AI that achieves practical results.