AI EXPOSED BY SWISS STUDY AS ILLOGICAL AND IRRATIONAL
SOMETHING WE MIGHT EXPECT FROM THE EMPIRE OF THE BEAST OF REVELATION
ARE FLAWED AI MODELS THE REASON WHY THE PENTAGON, CENTCOM , BESSENT KUSHNER AND THE TRUMP ADMIN ARE LVING ON ANOTHER PLANET IN REAL TIME?
A Swiss study has delivered yet another devastating critique of AI models.
The study found AI weather models cannot predict extreme weather events or their scale and intensity, a vital task for weather models.
https://www.swissinfo.ch/eng/research-frontiers/weather-forecasts-ai-fails-precisely-on-extreme-events/91342493
The authors make essentially the criticism I have been making
The problem is fundamental. The design, the conception is completely wrong.
AI based on LLM models treat data points as knowledge,
They treat an aggregation of data points and statistical averages of data points calculated using random algortithms as sure knowledge while ignoring the fact that it is logic, which determines knowledge.
Logic is a set of rules to extract knowledge from maths, science, physics and masses of data points.
Logic is completely different from data points.
You cannot extract logic from mere data points.
Logic is a framework of reasoning imposed on data points.
Incidentally, logic is why Plato concluded humans must have a divine mind. For us to have logical abilities and the capacity to reason must come from somewhere outside the natural, material world. Logic, maths etc does not come from observation, nature etc. It comes from the human mind. Animals also do not have the capacity to reason.
Because traditional physical models of weather forecasting do use logic, do use physics, science maths, they are better at predicting extreme weather events than AI.
This is the conclusion of the Swiss study.
In short, all those trillions of dollars and vast amouns of Nvidia chips and computer power have been wasted. The AI models are worse than the non AI models.
Yet, these models are being used for all kinds of tasks, and may even be used by the Pentagon for its Iran war planning. It is a diaster but Hegseth and the Pentagon, Brad Cooper at Centcom cannot seem to see wheere the disaster is, they are so confused. Is it flawed AI models which are confusing them all?
Does Cenctom s Brad Cooper belong to the uneducated, semi literate generation of crony contemporary US military commanders who cannot add 2 and 2 together but who are beloved by Presidents and their donors,, the defence corporations because they are ready to expend every last missile and billions for nothing guaranteeing more orders and profits for the corporations and the likes of the Kushners?
The fact these LLM AI models are the brainchild of the Epstein Billionaires in Silicon valley, means their falure give us insights into their inventors confused, muddled, chaotic and uneducated thinking and why are always failing
The moron is always going to be the ultimate loosers.
Lacking all curiosity, all interest in questions of what is knowledge, of what is the truth, of what is intelligence, how do we get to know things, how can we replicate intelligence , the Epstein Billionaires did not even think to hold a seminar or commision some academic papers on what would constitute AI.
Instead, it appears the likes of Bill Gates tinkered with a statistical languge computing machine, got some language output on the basis of some programme to generate random statistical averages, mistakenly thought this was not just knowledge but consciousness and scaled their flawed product up using trillions of dollars without every examining their assumptions.
Trump has pinned the US economy on AI.
The stock market is held up by investments in AI.
The AI failure is an intellectual and economic failure, which could be the final nail in the US coffin as it struggles with debt and energy shocks.
AI is supposed rescue the USA, increase productivity, pave the way for an advanced civilization
But the fact it turns out to be another disasters should not surprise us given it was the Epstein Billionaires behind it as they are behind every disaster, including now closing Hormuz on the basis of all kinds of wild, fantastical ideas.
A moron is one thing. But a moron who assumes he is a genius and so never wants to learn, is another thing altogether.
Such a moron is an animal by the defintion of Plato. It is the animal who does not use reason. There are human animals. Philosophy and logic, reason actually belong to Western civlization and basic education also through the classics.
But you do not need to study to be logical.
Logic is a natural and inherent (divine) capacity of the human mind.
Plato showed this in his maths experiment in Meno 2,500 years ago. We human beings have logical powers inherently.
To be illogical is unnatural for a human being.
It is natural for animal but not for a human being who can do maths,think logically if they want to make the effort.
To be illogical and irrational is to be a beast, a monster, not human.
Their animal like AI creation is an insight into the dark and confused minds of the likes of the Epstein billionaires Gates, Trump, Kushner and the explanation of their delusional decisions, which they actually think are good ones because they never examine them. They assume an automatic brilliance, which is not there in reality,assume criticism is personal and never substantial. For how could they,the great gods of the 21st century, be wrong? Solipsism!
The confused AI also gives us an insight into the darkness that reigns inside the mnds also of Satanically evil paedophiles, murders,liars and tricksters and racist eugenicists.
Yuval Noah Harari is another example of someone so confused, so muddled, so unable to think clearly, to define basic terms, i constuct a clear argument, identify fallacies, it is actually funny. Yet, he passes nowadays as an academic and is even celebrated by the Epstein billionaires for his illogical thinkslop.
It is not worth commenting on the chaotic AI slop now coming out Trumps admin, the Pentagon, DC, Wall St and the US media.
From media
Precisely when the weather becomes extreme and threatens the security of people and infrastructure, machine learning-based models show their Achilles’ heel. This is revealed by a new study led by the University of Geneva and published in the American journal Science Advances.
The researchers compared three of the most advanced AI systems for weather forecasting – GraphCast, Pangu-Weather and Fuxi – with the HRES physical reference model of the European Centre for Medium-Range Weather Forecasts (ECMWF). The verdict is clear: in the face of record events, the AI is systematically wrong.
According to the study, extreme cold spells are generally predicted to be less intense than they turn out to be in reality. On the contrary, heat peaks are underestimated by predicting less extreme values than in reality. The predicted temperatures are lower than the actual ones. There are also significant deviations for strong wind events.
But that is not all: the AI models not only predict the intensity of extreme events too weakly, they also predict them too rarely compared to what actually happens. “These results highlight a central challenge for the use of AI in the prediction of weather events with a large societal impact,” write the authors of the research.
In their view, the problem lies at the very heart of how AI works. Models learn from historical data: they recognise sequences and correlations that have already occurred in the past. But record events, by definition, fall outside this range of experience. What has never happened (or has happened very rarely) escapes the statistical logic of machine learning.
Physical models, by contrast, work in a radically different way. They simulate the evolution of the atmosphere based on immutable natural laws – thermodynamics, fluid mechanics – that apply regardless of whether a certain phenomenon has already been observed. “Physics does not change,” the researchers summarise. This is why traditional models are able to calculate even extreme situations never seen before.
The discovery comes at a crucial time. With climate change, extreme weather events are on the rise and with them comes the need for reliable forecasts to protect lives, infrastructure, agriculture and energy supply. “It is crucial for early warning systems that a model reliably predicts the occurrence of extreme events,” the scholars point out. If a heat wave is underestimated or a storm is recognised too late, the consequences can be severe for public health, security of supply and civil protection operations.
According to its authors, the study does not see this as a complete failure of AI in meteorology. On the contrary, the research team recognises that machine learning models offer “vast new possibilities”. The question is how to exploit its strengths without being penalised by their limitations.
https://www.swissinfo.ch/eng/research-frontiers/weather-forecasts-ai-fails-precisely-on-extreme-events/91342493
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