Opinion

Scientists recently digitized a single cubic millimeter of a mouse’s visual cortex, a project that generated 1.6 petabytes of data to map 84,000 neurons and half a billion synapses. To put that into perspective, the number of synapses in that tiny piece of brain tissue is comparable to the number of parameters in large-scale AI like DeepSeek or GPT models. It’s significantly more than the 29 billion parameters in a model like GigaChat. This comparison is a useful analogy for scale and complexity: just as synapses determine a brain’s processing capacity, parameters define the “power” of an AI. ...

Yesterday was a day focused on relationships. I was at a CLUB 500 event discussing friendship and its direct impact on team stability, project success, and the overall atmosphere within a company. Here are three thoughts I took with me: 1. Development Happens Only Through Interaction Sitting in a lotus pose is for stabilization. Real growth begins where there is live, human connection. Not over Zoom, not in a chat, but in a shared physical space. True progress is fueled by the kind of high-bandwidth, direct interaction that digital tools can only simulate. ...

Last Thursday, I attended TgConf, a key conference focused on traffic, monetization, and the future of the Telegram ecosystem. As I continue to develop my own channel, I’m constantly looking for new opportunities for integration and growth. The sessions covered advertising, the development of applications, and the strategic direction of the platform. ...

A recent study by the Tow Center for Digital Journalism at Columbia University delivered a stark reality check on the current state of AI-driven search. The findings are a critical reminder that while generative AI is advancing at an incredible pace, its reliability in retrieving and citing factual information is still deeply flawed. The researchers tested eight leading AI search systems, including prominent models like ChatGPT and Google’s Gemini. The results demonstrate a significant gap between capability and accuracy. ...

A Pragmatic Look at the Quantum Computing Supply Chain I came across an insightful market map from The Quantum Insider that breaks down the current quantum computing landscape. In a field often dominated by news of qubit counts and theoretical breakthroughs, this provides a practical, engineering-focused view of the ecosystem that is actually being built. It’s a clear signal that the industry is maturing beyond pure R&D and into a complex supply chain with distinct, specialized layers. Here’s a summary of the key players and technologies shaping the field, based on that research. ...

NVIDIA has released the source code for cuOpt, its platform designed to solve complex optimization problems in logistics, resource management, and scheduling. This is an important shift. Previously, such powerful technologies were locked behind expensive licenses, accessible only to large corporations with significant budgets. Now, cuOpt is free to use and adapt, democratizing access to high-performance optimization. With this tool, companies can now achieve significant operational efficiencies: Dynamic Route Planning: Recalculate truck routes in seconds to adapt to changing road conditions, traffic, or supply chain disruptions. This directly reduces fuel costs, shortens delivery times, and improves customer service. Warehouse Optimization: Streamline warehouse operations by reallocating goods between logistics centers to minimize surpluses and accelerate order fulfillment. Real-Time Scheduling: Adjust airline schedules in real-time during delays or weather events to prevent cascading cancellations and airport congestion. Energy Grid Balancing: Help grid operators respond faster to fluctuations in demand and better integrate renewable energy sources. This move enables even small companies to implement advanced optimization methods without the massive expense of in-house development. It offers a genuine competitive advantage to businesses that know how to leverage technology effectively. ...

Just six months ago, many AI products felt like experiments. Today, the consumer AI market has clearly formed: key players are solidifying their positions, audiences are growing, and competition is intensifying. The Numbers Confirm the Growth The data shows a clear trend of maturation and user adoption: ChatGPT now has 400 million weekly users, a two-fold increase from six months ago. The fact that 175 million of them use the mobile app shows AI is becoming a fixture in daily routines. 17 new AI products have broken into the top 50 web services in the last six months alone. AI video has reached a new level of maturity, with platforms like Hailuo, Kling, and Sora establishing their own dedicated audiences. From Hype to Real Revenue We are witnessing the tangible conversion of hype into real money. The market is not just growing in users, but in profitability. ...

I recently completed the Gallup CliftonStrengths assessment, which involves 200 questions with a strict 20-second limit for each. The value of this test is that it doesn’t force you into a rigid ‘personality type.’ Instead, it identifies the five most dominant talents out of 34 that define your unique style of working and making decisions. Here are my top 5 results: ...

I came across a recent Forbes article analyzing the future of the generative AI market in the BRICS+ nations, and the numbers are staggering. A report by Yakov and Partners estimates the economic impact could reach $350–$600 billion by 2030. However, the distribution of this value is heavily skewed. The report projects that 86% of this total ($301–$516 billion) will be captured by China. The remaining 14% ($49–$84 billion) is left to be divided among India, Brazil, Russia, the UAE, Saudi Arabia, and South Africa. For Russia, India, and Brazil combined, the share is not expected to exceed 12%, or $42–$72 billion for all three. ...