Just a few years ago, artificial intelligence seemed like an incredible achievement of humanity — a technology meant to make life easier. But now, as it has become a common element of our reality, a question arises more and more often: are we paying too high a price for this comfort? AI not only helps us — it changes our psyche, our perception of the world, and even the way we think. And these changes happen quietly, gradually, yet inevitably.
Artificial intelligence is undergoing another stage of evolution — and this time, the changes may be even more significant than during the emergence of GPT models or the mass adoption of chatbots. The Chinese company Kimi has introduced the Kimi K2 model, which, according to the developers, not only approaches the performance of the most powerful systems on the market but also offers a much lower cost of use. In some tests, K2 outperforms GPT-5 and Claude Sonnet 4.5, while demonstrating efficiency in complex multilingual tasks, agent-based programming, and processing large volumes of information. The most interesting part is that this model may be several times cheaper than its counterparts — and therefore has the potential to influence the entire market’s economy.
Recently, Microsoft introduced a new concept of AI agents that can act not just as assistants, but as independent participants in the workflow. Within these tools, it is now possible to create artificial “digital units” that understand the context of a task, initiate actions, communicate with other systems, and even coordinate the work of individual employees. This is not just another software update. It signals that artificial intelligence is transitioning to a new stage of development, where it stops being a passive tool and becomes an active agent in the business environment. For the automation market, this may mean a fundamental shift in the principles of work organization.
In a world where every second counts, the domain registration process is undergoing a technological revolution. What once required manual checking, registry communication, and confirmation, now happens automatically — within seconds. Automation systems and artificial intelligence algorithms are reshaping not only the speed but also the very logic of how we work with domains.
Ukraine is launching AI Factory — the first national infrastructure project aimed at supporting and developing artificial intelligence within the public sector. The idea is to create a reliable, secure, and centralized platform where key AI services of the state will operate — such as the assistant in Diia, the AI tutor in Mriia, and later, systems for healthcare, science, and defense.
This infrastructure will include GPU clusters, data centers with liquid cooling, data storage, tools for dataset preparation, and integration with government registries — all designed to ensure that AI models run fast, reliably, and with full data security compliance.
On October 6, 2025, AMD announced a strategic partnership with OpenAI — and the market literally exploded. Within a single day, AMD’s stock soared by more than 25%, marking one of the most impressive surges in the company’s history. Investors called it a “moment of truth” for the AI industry, as for the first time in years, Nvidia gained a real competitor.
This partnership is not just another contract in the tech world. It could become a turning point for the entire AI infrastructure — from large data centers to VPS platforms that host business applications, analytics, and automation. AMD and OpenAI have set a course toward building a more powerful, open, and accessible ecosystem for artificial intelligence — a foundation for the new digital era.
The development of artificial intelligence (AI) raises many questions: what will happen to careers in IT, will algorithms replace people, where should one look for work? AI helps automate routine tasks, but it cannot fully replace professions that require critical thinking, creativity, and responsibility. These are precisely the specialists who remain in demand in the labor market, even during periods of active automation.
ChatGPT is a powerful tool that generates text-based answers from a vast dataset, but it is not a database of facts. It produces plausibly sounding responses (answers that seem convincing and logical, even if they may be inaccurate or fabricated) by relying on language patterns. This means that even when answers sound confident, they may still be false or incomplete. Reviews show that the model can make mistakes in simple questions and continue making them even after corrections. This means its conclusions should be treated as suggestions rather than absolute truth. That is why it is important for users to follow safety rules and verify the information.
