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YouTube’s New AI Search Feature Is a Content Discovery Game-Changer

YouTube’s New AI Search Carousel Is Changing How We Discover Videos — Here’s What You Need to Know You know that moment when you type something like “best cafés in Paris” into YouTube, and you’re buried under a flood of random vlogs, listicles, and unrelated reviews? Yeah, we’ve all been there. But that chaotic hunt for the right video might soon be a thing of the past. YouTube just rolled out an AI-powered search carousel — and it’s not just another shiny feature. It’s a smart, intuitive, and (honestly) much-needed step forward that could completely change how we search for and interact with video content. Let me break it down — not like a press release, but like someone who geeks out about this stuff and actually uses YouTube every day. --- What Is YouTube’s AI Search Carousel? In simple terms: YouTube now shows an AI-generated video carousel when you search for things like: Travel recommendations Local activities and attractions Shopping inspirati...

Energy consumption of AI language models like ChatGPT





🔌 The Hidden Cost of Intelligence: How Much Energy Does AI Really Use?





⚠️ Let’s Be Honest: We’re Not Asking the Right Questions About AI
We’re living in a world where AI is becoming as common as coffee. It writes our emails, recommends our next Netflix binge, helps diagnose medical issues, and even tries to explain Shakespeare. But with all this “smart” happening, there’s a question we aren’t asking loudly enough:
> How much energy does all this intelligence actually cost us—and the planet?



While companies are in a gold rush to build the most powerful models, the public is left in the dark when it comes to the environmental toll of using AI.

The irony? We’re using AI to fight climate change and wasting enormous energy doing it. Sounds counterproductive, right?



💡 Quick Fact: How Much Energy Does ChatGPT Use?

Sam Altman, CEO of OpenAI, recently claimed that the average ChatGPT query uses 0.34 watt-hours—roughly the energy of an oven for one second or a high-efficiency lightbulb for a few minutes.

But here’s the catch: What exactly is an "average" query? Does it include image generation? Long conversations? Server cooling? Model training? Nobody really knows.

Many experts, like Sasha Luccioni from Hugging Face, are skeptical. And for good reason. The data just isn’t transparent.

> “He could have pulled that out of his ass,” Luccioni said bluntly.
And you know what? She’s not wrong.




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🔍 Why We Need Transparency: The Emissions Black Hole

Let’s take a look at the core issue: No one is obligated to share how much carbon their AI systems emit.

That means as consumers, developers, and policymakers, we’re operating blind. According to a 2025 study by Luccioni and others, 84% of LLM traffic in May came from models that disclosed zero environmental data.

Imagine if car companies stopped publishing fuel efficiency numbers. You’d be furious. So why is it okay for AI companies?


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🔄 The Google Comparison Myth

You’ve probably heard that a ChatGPT request uses 10x more energy than a Google search.

That claim originated from a 2023 remark by Google's own chairman, John Hennessy. It was an off-the-cuff comment, not a peer-reviewed statistic. Yet it’s been quoted in headlines, policy reports, and pitch decks across the world.

> In other words, one company’s educated guess about another company’s black-box tech is being treated as fact.



That’s how desperate we are for any information.


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🧠 Smarter ≠ Greener: The Energy Divide in AI Models

A fascinating study published in Frontiers in Communication put 14 open-source LLMs to the test using 1,000 questions—from history to philosophy.

What they found was both alarming and expected:

Reasoning-intensive models used 50% more energy than concise ones.

More tokens = more “thinking” = more power drawn.

Bigger models often gave better answers—but with a bigger carbon footprint.


In short: Accuracy costs energy.


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🏗️ It’s Not Just the Model—It’s the Whole Machine

Here’s what many reports miss: You’re not just running a query on a model. You’re waking up a beast of infrastructure.

Let’s break it down:

Hardware matters: Older GPUs like Nvidia’s A100 are more efficient than newer but power-hungry ones like the H100.

Data centers consume extra: Cooling, networking, lighting—it all adds up.

Location matters too: A data center in India using coal-fired power emits more CO2 than one in Norway powered by hydropower.


MIT’s Noman Bashir puts it well:

> “Measuring AI energy use without the whole picture is like revving a car wheel in the air and calling it a fuel test.”




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✅ The Case for Smarter AI Usage

We don’t need to quit using AI—but we need to use it smarter.

Here’s how:

1. Route simple queries to lightweight models.
Not every question needs GPT-4 or Claude. Small models do great on basic tasks.


2. Push for environmental labels on AI products.
Like food nutrition labels—users deserve to know what they’re consuming.


3. Reward transparency.
Open-source models should be championed when they publish energy use.


4. Make sustainability a design goal—not an afterthought.




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🙋‍♀️ FAQs: AI and Energy

Q: Does training an AI model consume more energy than using it?
Yes, significantly. Training GPT-3 reportedly used the equivalent of powering a U.S. home for over 300 years. Inference (everyday use) is less intensive—but still adds up with scale.

Q: Is ChatGPT energy-efficient?
Depends on the task. For short queries, it may be fairly efficient. For long, image-heavy, or deeply reasoning tasks—it’s much less so. And we don’t have full numbers from OpenAI.

Q: Are there "green" AI models available?
Yes. Some models are designed to be energy efficient, and a few companies now share emissions data. But they are still the minority.

Q: Will AI companies be forced to disclose emissions in the future?
Possibly. Regulatory pressure is building in Europe and California. But so far, there’s no global standard.


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🌍 Final Thoughts: We Can’t Afford to Stay in the Dark

AI is powerful. But if it’s going to be everywhere—helping us write, search, build, and dream—it must also be accountable.

> We need clarity over convenience, and transparency over performance hype.



If we treat carbon emissions like a hidden tax on progress, we’re not just building intelligent systems—we’re building unsustainable ones.

It’s time AI becomes not just smart, but responsible too.




Ready to be part of the change? Share this. Ask questions. Demand data. Because intelligence, without awareness, is just arrogance in disguise.

Label: AI & Sustainability
Hashtags: #AI #EnergyConsumption #SustainableTech #GreenAI #AIandEnergy #ClimateImpact #CarbonEmissions #OpenAI #LLMs #EthicalAI

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