AI has learned another function that I don't need, please stop pretending you understand me.

Tech giants are rushing to promote generative AI, but as user excitement turns into fatigue, the market may face a functional cleanup. (Background: Vitalik Buterin wrote a long article: GKR password protocol can quickly prove Ethereum, zk-ML is accelerating AI LLM) (Additional context: Bitcoin miners' “valuation logic shifts”: the revenue from powering AI far exceeds mining Bitcoin) From the Metaverse to Web3, and then to generative AI, Silicon Valley has repeatedly created hype. But have you felt recently that as AI functions flood into daily life, a sense of “AI fatigue” is emerging behind the heat? Many consumers are gradually feeling burdened by these new functions, even questioning their true value. As AI functions multiply, users are shouting “I can't handle it”. In the past year, from mobile phones, emails, presentations to search engines, almost every update has touted generative AI. Samsung's real-time translation on its phones and Google Bard's writing suggestions in Gmail seem convenient on the surface, but a large number of users report that the applicability of the scenarios is low, and the operations increase the learning curve. An article specifically discussing the “forced feeding” of AI functions to users describes that the flow of functions is like being forcibly fed. Over time, not only does it fail to enhance the experience, but it also complicates the interface and lengthens the process. The capital market FOMO drives giants into an AI arms race. Why are companies eager to fill up on AI? Behind this is a deep business motivation: investors' enthusiasm for AI concepts drives up market capitalization, and management fears being labeled conservative if they fall behind. As soon as one company announces new progress, other competitors immediately follow suit, creating a spiral of “if you have it, I must have it too”. More critically, AI is seen as a new engine for subscription revenue. Reports have emerged that Samsung is evaluating a paid model for some AI services, indicating that functions are not just technical showcases, but also related to revenue prospects. When cash flow and stock prices are tied together, the quantity of functions can easily overshadow real demand. True innovation should return to addressing pain points rather than just showcasing technology. An excellent AI function is fundamentally about invisibly enhancing efficiency, rather than requiring users to input prompts every day for it to work. Currently, many “universal” tools are misaligned with users' actual scenarios, leading to a situation where “those who know how to use them find them troublesome, and those who don't understand them”. Industry observers point out that the next step in value should focus on vertical fields, such as financial analysis, manufacturing scheduling, or medical diagnosis in highly specialized scenarios. Rather than stacking AI on the interface, it is better to delve into a few key processes, allowing the algorithm to run quietly, with users experiencing only faster, more accurate, and simpler functions. The heat will eventually cool down, and only truly useful AI will remain. Looking back at the rise and fall of historical technology, when the novelty fades, the market will eliminate superficial additional features. Generative AI is no exception. As consumers begin to calculate the value of payment, if companies rely solely on marketing rhetoric and feature stacking, they will soon be marginalized. In contrast, applications that can solve deep-rooted problems and reduce operational costs may become standard equipment after the next round of reshuffling. Facing the upcoming rational period, brands need to reduce the “catch-up mentality” and redirect R&D budgets back to experience design and long-term service, rather than chasing short-term topics. The potential of generative AI is unquestionable, but the true path lies in being human-centered. As the arms race among giants intensifies user fatigue, it also reminds the industry to return to its original intention: technology should invisibly empower life, rather than shifting complexity onto users. The next wave of winners will be those companies that understand restraint, use the right scenarios, and make AI a background capability. Related reports Billionaire Kevin O’Leary says “the next step under the AI wave is web3”: LLM cannot create Starbucks but blockchain can. Citadel founder Ken Griffin says “generative AI is useless”: unable to discover Alpha, Wall Street still needs to beat the market with manual effort. The Wall Street Journal warns: America is “gambling addiction bubble” from sports to AI, Trump is the instigator. <AI has learned another feature I don’t need, please stop pretending to understand me> This article was first published in BlockTempo, the most influential blockchain news media.