Aujourd'hui répétition collective des professeurs pour leur concert du 23 Janvier prochain à Serris.
On vous y attend nombreux
Aujourd'hui répétition collective des professeurs pour leur concert du 23 Janvier prochain à Serris.
On vous y attend nombreux
Woah! I'm really loving the template/theme of this blog.
It's simple, yet effective. A lot of times it's very hard to get that "perfect balance" between user
friendliness and appearance. I must say you have done a great job
with this. In addition, the blog loads super quick for me on Opera.
Superb Blog!
автоматические карнизы http://elektrokarnizy50.ru/ .
pokies111 http://pokies11.com/ .
электрокранизы https://elektrokarnizy50.ru .
pokies net 111 https://pokies11.com/ .
the pokies net http://pokies11.com/ .
pokies.net http://pokies106.com/ .
In the first set,the women had an “ideal” Western body shape and were wearing white tank tops with jeans or gray sweatpants.[url="https://www.erdoll.com/brand-bezlyadoll.html"]ラブドール sex[/url]
Study reveals how much energy AI uses to answer your questions
трипскан сайт
Whether it’s answering work emails or drafting wedding vows, generative artificial intelligence tools have become a trusty copilot in many people’s lives. But a growing body of research shows that for every problem AI solves, hidden environmental costs are racking up.
Each word in an AI prompt is broken down into clusters of numbers called “token IDs” and sent to massive data centers — some larger than football fields — powered by coal or natural gas plants. There, stacks of large computers generate responses through dozens of rapid calculations.
The whole process can take up to 10 times more energy to complete than a regular Google search, according to a frequently cited estimation by the Electric Power Research Institute.
https://tripscan.biz
tripscan войти
So, for each prompt you give AI, what’s the damage? To find out, researchers in Germany tested 14 large language model (LLM) AI systems by asking them both free-response and multiple-choice questions. Complex questions produced up to six times more carbon dioxide emissions than questions with concise answers.
In addition, “smarter” LLMs with more reasoning abilities produced up to 50 times more carbon emissions than simpler systems to answer the same question, the study reported.
“This shows us the tradeoff between energy consumption and the accuracy of model performance,” said Maximilian Dauner, a doctoral student at Hochschule Munchen University of Applied Sciences and first author of the Frontiers in Communication study published Wednesday.
Typically, these smarter, more energy intensive LLMs have tens of billions more parameters — the biases used for processing token IDs — than smaller, more concise models.
“You can think of it like a neural network in the brain. The more neuron connections, the more thinking you can do to answer a question,” Dauner said.
What you can do to reduce your carbon footprint
Complex questions require more energy in part because of the lengthy explanations many AI models are trained to provide, Dauner said. If you ask an AI chatbot to solve an algebra question for you, it may take you through the steps it took to find the answer, he said.
Hi there! Would you mind if I share your blog with my twitter group?
There's a lot of people that I think would really
appreciate your content. Please let me know. Cheers https://arsenal43.ru/catalog/pages/?populyarnoe_onlayn_kazino_ramenbet___24_7_azart.html
Make sure you enter all the required information, indicated by an asterisk (*). HTML code is not allowed.