Возможные признаки более качественных ИИ-моделей: надёжность, эффективность и скорость

On August 2, 2026, five zodiac signs experience the best horoscopes all day. The Moon leaves Pisces to enter Aries on Sunday, bringing really good energy to get things done. When the Moon enters a fire sign, it's not the happiest spot for it, but it does benefit people who love the effects it has on their productivity levels . Things flow nicely, and their mind is super sharp for decision-making. This is the best day in a long time for these astrological signs, and their horoscope supports all that they need to do before the day is over. 1. Libra One of the reasons why your horoscope is one of the best on Sunday is that the Aries Moon activates your partnership sector. Fire energy gives you the motivation and drive to embrace your relationships in a way that is passionate and full of [...] ### 13 Really Healthy Foods That Most People Refuse To Eat This article was originally published on ChaChingQueen.com, a site my wife and I own. AI was used for light editing, formatting, and readab

On this point, I think it's worth remembering how fast the capabilities of the models have been improving. Maybe it's true that no model will ever be able to cause significant harm. But if we look at the trajectory of the models, it seems like it's only a matter of time. And so we should at least be trying to track how good models are at doing the kinds of things someone might need to do to cause harm. If this ever becomes possible, we should be worried. [...] Each of these worries assumes some increasing base capability level of the AI systems. In order to get at-scale phishing and other attacks, we don't need models much better than the ones we have now. In order for mass surveillance to be possible, we probably only need a little bit better models than those we have today. And in order for us to be worried about mass unemployment, we'll need quite a bit better models than those we have today. Other people take this spectrum a few steps further, and assume that models will get a lot

The discourse from some of those building AI is surprisingly filled with doom. The notion that AI is so dangerous that safety requires extreme concentration of power has a troubling historical echo. Centralized, absolute power has never reliably produced safe or positive outcomes for the people living under it. History points the other direction, consistently. Progress is accelerating. Better models are coming. The exponential is real. Fully internalizing it is remarkably difficult, even for people who follow the field closely every day. As acceleration itself accelerates, understanding what’s happening will become exponentially harder. We’re approaching a period when even the most extreme predictions will repeatedly prove too conservative. [...] After OpenAI deployed GPT-5.6 Sol, they turned the model on itself. They asked Sol to optimize its own production infrastructure: the live software stack handling billions of real user requests every single day. Sol rewrote its own GPU kernel

as an early signal that AI systems are getting better at making the kinds of judgement calls that AI research depends on. [...] Because we deliberately picked moments (n=129) where we know the human’s choice had room for improvement, this isn’t a like-for-like comparison between model and human judgement. What these moments give us is a set of realistic, challenging situations where the right next step is not obvious, and where the human’s choice serves as a useful yardstick to compare model performance over time. On this measure, our best model in November 2025 (Opus 4.5) beat the human choice 51% of the time; in April 2026 (Mythos Preview), this grew to 64%. The day-to-day work of research is largely a chain of these next-step decisions, making this a relevant measure of the model’s ability to eventually run an investigation of its own. We view this result as an early signal that AI systems are getting better at [...] An area of human comparative advantage, for now, is research taste

Greg Daco, Vice President, EY Parthenon, Strategy and Transactions, Ernst & Young LLP, says, “We’re witnessing the first real signs of an AI-driven productivity revolution — visible not yet in performance, but in investment. Firms are channeling capital into data infrastructure, software development, energy, and talent, laying the groundwork for future growth. “AI could extend the economic expansion by two to four years over the next decade — but only if companies get the basics right: robust data, reliable infrastructure, abundant energy, and skilled people. The productivity gains will come to those who build strong foundations before chasing results.” Gen AI real boost to global GDP by 2033: 1.5% 1.5% 1.5% baseline model Gen AI real boost to global GDP by 2033: 3% 3% 3% [...] Yet even as much changes, the essence of productivity will continue to be about using resources, whether human, material, financial or computational, to achieve higher quality, better and faster outcom

Log inSign up ## Post user avatar Sam Altman OpenAI @sama it could be faster user avatar Tibo @thsottiaux Jul 31 The day we develop really good models. There will be signs. Reliability increasing despite load going up and up. Sudden efficiency gains. Things getting faster. Resets. These kinds of things. 2:28 PM · Jul 31, 2026798.7KViews user avatar 🍓🍓🍓 @iruletheworldmo Jul 31 i want cerebras on my desk by the end of the day sam. or its going to be a different conversation. 6.3K user avatar maria @maria\_rcks Jul 31 SAM WTF, YOU HAVE UNTIL TODAY user avatar Sam Altman OpenAI @sama Jun 26 Replying to @sama oh and also...750 token/sec coming to 5.6 sol in july! 5.4K user avatar Chris @ChrisGPT