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Когда у тебя дети, работа, дом — нет времени вникать в биржи и трейдинг. <a href="https://uniteto.live/ru/">UTLH</a> понравился тем, что всё понятно с самого начала. Я не ставила цель заработать миллионы, просто хотела, чтобы деньги не лежали без дела. Прошло уже полгода — каждый месяц вижу результат. Это вдохновляет. Никто не навязывает сложные действия, не требует подтверждений. Мне как маме важно, чтобы всё было просто и без нервов. И тут как раз такой случай. Теперь муж заинтересовался, тоже подключается.

I had long dreamed of financial independence, and <a href="https://uniteto.live/">UTLH</a> became one of my steps toward achieving it. By investing in the project, I not only receive stable income, but I also feel that my financial opportunities are expanding. The project gives me confidence in the future, and with each passing month, I become more convinced that I chose the right path.

After investing in <a href="https://uniteto.live/">UTLH</a> , I decided this would be my calm and predictable investment. Limited token supply, high liquidity, and stable income — these were exactly the parameters I was looking for. This isn’t a risky gamble, but a conscious choice for long-term investment.

Das <a href="https://uniteto.live/de/">UTLH</a>-Projekt stellt ein ausgewogenes Modell dar, das Risiken minimiert und die Rendite optimiert. Die begrenzte Token-Emission und die hohe Liquiditat schaffen Voraussetzungen fur eine Wertsteigerung der Tokens. Das Staking-Programm mit 24 % Jahresrendite ist im Vergleich zu anderen Angeboten wettbewerbsfahig. Die Teilnahme am Programm der Universellen Finanzhilfe eroffnet den Nutzern zusatzliche finanzielle Moglichkeiten.

Study reveals how much energy AI uses to answer your questions
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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.
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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.

Study reveals how much energy AI uses to answer your questions
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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.
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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.

Study reveals how much energy AI uses to answer your questions
tripscan top
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.
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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.

Study reveals how much energy AI uses to answer your questions
tripskan
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
трипскан
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.

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Study reveals how much energy AI uses to answer your questions
трипскан
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
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.

‘Like wildfires underwater’: Worst summer on record for Great Barrier Reef as coral die-off sweeps planet
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Great Barrier Reef, Australia
CNN
—
As the early-morning sun rises over the Great Barrier Reef, its light pierces the turquoise waters of a shallow lagoon, bringing more than a dozen turtles to life.

These waters that surround Lady Elliot Island, off the eastern coast of Australia, provide some of the most spectacular snorkeling in the world — but they are also on the front line of the climate crisis, as one of the first places to suffer a mass coral bleaching event that has now spread across the world.
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The Great Barrier Reef just experienced its worst summer on record, and the US-based National Oceanic and Atmospheric Administration (NOAA) announced last month that the world is undergoing a rare global mass coral bleaching event — the fourth since the late 1990s — impacting at least 53 countries.

The corals are casualties of surging global temperatures which have smashed historical records in the past year — caused mainly by fossil fuels driving up carbon emissions and accelerated by the El Nino weather pattern, which heats ocean temperatures in this part of the world.

CNN witnessed bleaching on the Great Barrier Reef in mid-February, on five different reefs spanning the northern and southern parts of the 2,300-kilometer (1,400-mile) ecosystem.

“What is happening now in our oceans is like wildfires underwater,” said Kate Quigley, principal research scientist at Australia’s Minderoo Foundation. “We’re going to have so much warming that we’re going to get to a tipping point, and we won’t be able to come back from that.”

Coral bleached white from high water temperatures on the Great Barrier Reef, Australia. CNN
Bleaching occurs when marine heatwaves put corals under stress, causing them to expel algae from their tissue, draining their color. Corals can recover from bleaching if the temperatures return to normal, but they will perish if the water stays warmer than usual.

“It’s a die-off,” said Professor Ove Hoegh-Guldberg, a climate scientist at the University of Queensland in Australia and chief scientist at The Great Barrier Reef Foundation. “The temperatures got so warm, they’re off the charts … they never occurred before at this sort of level.”

The destruction of marine ecosystems would deliver an effective death sentence for around a quarter of all species that depend on reefs for survival — and threaten an estimated billion people who rely on reef fish for their food and livelihoods. Reefs also provide vital protection for coastlines, reducing the impact of floods, cyclones and sea level rise.

“Humanity is being threatened at a rate by which I’m not sure we really understand,” Hoegh-Guldberg said.