Shadowing Practice: The Truth About How Data Centers Use Water And Power To Keep Cool - Learn English Speaking with Video
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So here we can see all of the liquid cooling infrastructure for the Grace Blackwell Rack.
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Inside this Equinix data center in San Jose, California, there are hundreds of server racks,
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some executing massive AI compute tasks for the company's renting space here to run thousands of graphics and sensor processing units.
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There are eight GPU racks in here
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and each rack has 72 GPUs inside of it
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and all those chips get hot under heavy workloads server can boil your eggs
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they are like raining at 80 degree celsius the chips themselves would melt down
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if they weren't continuously cooled and keeping these chips cool requires a lot of water and power
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which is a major reason why there's a national backlash against
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ai data centers backlash against data centers is growing across the country.
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71 % of respondents said they would oppose the construction of a data center in their local area.
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Backlash is also growing around power, water costs, who pays, local and state leaders are hitting pause on new projects.
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The rate payers, both electrical and water, have seen their rates be shot up.
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They don't wanna have to pay for these data centers to be there.
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The largest data centers can use up to five million gallons per day.
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That's what a small town of up to 50 ,000 might use.
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A few data centers are using that much water, but most communities in the U .S.
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don't have the infrastructure to support that demand.
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But not all data centers and ways of keeping them cool are created equal.
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These servers are liquid -cooled in a closed -loop system, but liquid cooling is only the start of the water
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and power equation because the facility still has to get rid of the heat that's been absorbed by the liquid.
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How a data center does that is what really determines consumption rates.
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This closed -loop system itself doesn't necessarily mean the data center doesn't use water.
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How do we reject the heat from the closed -loop to the ambient environment?
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That's where the water usage comes in.
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From dry cooling to evaporative cooling towers and hybrid solutions in between, we visited data centers around the country and chip plants
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that need even more water to find out how data centers really use water, what liquid cooling looks like,
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and where the companies running the biggest AI workloads have room to improve.
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Inside data centers with closed loop systems, hyperscalers often label their cooling systems as using zero water for a majority of the year.
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What they're not taking into account is once that heat is moved off the chip, it has to get moved out of the building.
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And that part takes water and power.
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In fact, saving water often means using more power for cooling.
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There's no sort of silver bullet, but at some point you need to eject that heat out to the atmosphere, and that's where those tradeoffs occur.
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But inside the servers that zero water use is largely right.
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Once a closed loop system is filled up, no more water is consumed in this part of the process, keeping those chips inside the servers cool.
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This is one of the 18 compute trays.
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the gpus sit underneath these copper cold plates
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that have liquid running through them to remove the heat from the system
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this is amd's helios the only real competitor to nvidia's industry leading racks vera rubin
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and grace blackwell and both companies designed their latest systems
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so they can be entirely liquid cooled this is a cooling distribution unit
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that takes chilled water in from the facility filters it pumps it
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and distributes it to all of the helios racks keeping them cool
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we're doing about 750 gallons per minute of chilled water
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but unlike some cooling systems this one is completely closed loop and so it's not a drain upon the resources
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the biggest advantage of liquid cooling however comes from just how quickly it can bring chip temperatures down
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so they can get back to work.
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Water is about 3 ,000 times more effective than air at removing heat from the chips.
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Therefore, you're able to increase the density in the same footprint.
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There's giant gigawatt plus sites built to run AI workloads for single huge companies like SpaceX AI, OpenAI, Google, Meta, and Amazon.
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Then there's co -location data centers like this one.
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Equinix, a big beneficiary of the AI boom, provides the building, power, network connections, and cooling to companies renting space for their server racks like
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these NVIDIA Blackwell racks owned by NVIDIA -backed AI software startup Alembic.
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So we went to an Equinix data center where these servers
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are running real workloads today to see how this looks when the systems are powered on.
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So these white pipes that are coming in are coming from our facility.
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So it's our chilled water infrastructure and then it goes across a heat exchanger plate.
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So that's how we're able to maintain the temperature and flow of the stainless steel piping that's distributed to the
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This Equinix data center in San Jose is on a closed -loop system, but it does still consume water.
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Like many data center operators, Equinix doesn't disclose water consumption at individual sites like this.
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In 2025, though, all Equinix operations consumed 1 .2 billion gallons of water, up 10 % from 2024.
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We're in 77 metros
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and you know our entire global water footprint is the equivalent
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of about 16 18 -hole golf courses in the southwestern United States.
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One of the leading suppliers of liquid cooling equipment to giants like NVIDIA and AMD is CoolIT.
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All the cold plates, the heat exchangers, and the connecting tissue between them.
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We've done that for 25 years.
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COOL -IT was acquired by water treatment company Ecolab for $4 .75 billion in July,
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as AI drives huge demand for an especially efficient system called direct -to -chip cooling.
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Direct -to -chip cooling uses a coolant that includes glycol to help stop corrosion, freezing, or biological growth inside the highly sensitive systems,
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but it's still primarily made of water.
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Legacy data centers were often air -cooled, in which large, noisy fans push cool air through heat exchangers to carry the heat away.
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Air -cooled is for, let's say, CPU -based servers, cloud servers, storage servers, networking equipment.
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They only need air -cooled because their heat density is much lower than GPUs.
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And for GPUs, due to the high power density, air -cooled system is not enough.
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They run at such a high wattage, a high temperature.
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You would need nearly hurricane -force winds to actually cool them down if you were just using air, which is why water is so effective.
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Still, the sheer scale of this data center build -out has many residents worried.
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More than 2 ,000 new data centers are planned in communities all across the country, on top of nearly 1 ,400 already in operation.
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In many places, the water supply simply can't support up to 8 million daily
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gallons needed at peak times for a 1 -gigawatt site like MEDA's in Lebanon, Indiana.
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Because in reality, there's a big way water is still used, even when it's a closed -loop system.
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That water has to get cooled back down using external cooling, a separate step from closed -loop systems inside the building.
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And it turns out the less water you use for this, the more power you need.
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So let's talk about the options.
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The simplest approach is just use the outside air.
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And it works pretty well in the wintertime when the air is cold.
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Using ambient air is indeed the least water -intensive method.
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Known as dry cooling, large fans blow air across heat exchangers, using that outside air to cool it down.
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Those fans don't work so well when the outside temperature is high.
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And that's when power -hungry cooling units, similar to household AC, need to kick on.
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That's a very power -intensive process.
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And that's exactly why we have power shortages in the summer, because everybody else turns on their AC.
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Evaporative cooling is the most water -intensive method because water is lost in evaporation.
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The hot water circulates through cooling towers or over wet pads that are exposed to air,
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and the portion that evaporates carries the heat away with it.
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In between those two extremes, hybrid methods are common as companies try to find a balance,
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such as dry cooling in the colder months and evaporative cooling when it's hot outside,
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or a fine mist of water is sprayed to cool the incoming air before it passes through the dry cooling system.
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There are data centers in Texas and in Phoenix, you know, where's 100 degrees during the day.
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They have the land to provide to the data centers, but they really are not the environment the data center should be in.
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Companies often build water treatment plants to help treat and recycle the necessary water, like one promised by Elon Musk in Memphis
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that's meant to turn treated municipal wastewater into cooling water for SpaceX AI's Colossus data centers.
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While Colossus 1 came online rapidly back in 2024, construction on the water treatment plant has stalled.
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Colossus is allocated up to 1 .28 million gallons of water per day, and reports indicate it uses an average of 800 ,000 gallons per day.
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As more data centers turn to water -efficient cooling methods, more power is needed.
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That's in addition to the power needed to run all the servers and equipment.
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It's why new data centers will account for most of the projected increase in electricity demand over the next decade,
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and why tech companies are building their own power plants, which also use a lot of water.
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At the end of the day, cooling the massive projects needed to supply the AI boom currently requires either a large amount of water or power.
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There are, however, companies working hard on ways to make it better.
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One idea? make the chips themselves run less hot.
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We provided over 25 degrees Celsius difference, or 40 degrees Celsius difference in the temperature, I mean, the thermal characteristics.
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Lokwon Kim's South Korean chip startup, DeepX, makes a low -power AI processor that runs so cool, it doesn't even melt butter placed on top,
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as shown in a demo filmed by DeepX.
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We gave the same AI workload, and then we just put the butter on them.
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Every chip melted each butter, except for the best chip.
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Hyundai Motor Group Robotics Lab has announced that this year, their first commercialized robots will use our chips.
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Lower heat chips are also in the works at SK Hynix, the world's leading maker of high bandwidth memory crucial for AI.
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Its next generation iHBM is designed specifically to reduce heat generation, which would lower the water or power needed for cooling.
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We developed IHBM with ICE technology.
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ICE stands for integrated cooling element and we can reduce the thermal resistance by 30%.
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At Cool IT, it's working on getting the liquid even closer to the chips.
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There's some really cool instances of water almost in the chip or just on top of the chip.
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That's all about being able to deliver even warmer water to the data center
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and continuing this ride towards ever more efficient use of liquid cooling in data centers.
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And at data centers like Equinix, efficient water use is crucial as AI workloads and business from customers continues to grow.
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At Equinix, we take it very, very seriously.
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Communities rightly have begun to ask the right questions.
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Data centers consume energy, they consume resources like water, but they also provide a very critical function to modern society.
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Bu dersin kelimeleri ve konuşma notları
Bu konuşma dersi “The Truth About How Data Centers Use Water And Power To Keep Cool” videosuna dayanıyor. En çok tekrarlanan kelimeler: center, cooling, chip, heat, liquid. Bu videoda gölgeleme çalışması için 99 cümle ve 1919 kelime var. Konuşma bölümü 11:44 sürüyor. Konuşmacı dakikada yaklaşık 163 kelimeyle, günlük konuşmaya yakın doğal bir hızda konuşuyor. Kelimelerin yalnızca %78’i İngilizcede en sık kullanılan 3.000 kelime arasında, bu yüzden kelime dağarcığı zorlayıcı.
Bu videodaki önemli kelimeler
Videodan öğrenmeye değer 15 kelime, telaffuzu ve anlamıyla:
| Kelime | Telaffuz | Anlam |
|---|---|---|
| chip isim | /t͡ʃɪp/ | çip |
| server isim | /ˈsɝvɚ/ | sunucu, server |
| liquid isim | /ˈlɪk.wɪd/ | sıvı, likit |
| loop isim | /luːp/ | ilik |
| rack isim | /ɹæk/ | askılık |
| gallon isim | /ˈɡælən/ | galon |
| consume fiil | /kənˈsum/ | kullanmak, harcamak |
| efficient sıfat | /ɪˈfɪʃənt/ | verimli |
| infrastructure isim | /ˈɪnfɹəˌstɹʌkt͡ʃə/ | altyapı, enfrastrüktür |
| butter isim | /ˈbʌtɚ/ | tereyağı, yağ |
| density isim | /ˈdɛn.sə.ti/ | yoğunluk |
| melt fiil | /mɛlt/ | erimek |
| consumption isim | /kənˈsʌmp.ʃən/ | tüketim |
| pipe isim | /ˈpaɪp/ | düdük, kaval |
| distribute fiil | /dɪˈstɹɪbjuːt/ | dağıtmak, paylaştırmak |
Duyacağınız deyimsel fiiller
| Kelime | Anlam |
|---|---|
| find out fiil | anlamak, ortaya çıkarmak |
Bu videodaki dil bilgisi
Konuşmacının en çok kullandığı yapılar, videodaki sözcüklerin aynısıyla:
| Yapı | Videoda |
|---|---|
| Edilgen yapı be + fiilin üçüncü hâli — kimin yaptığı değil, ne olduğu önemli | weren't continuously cooled · be shot · are created |
| Present perfect have/has + fiilin üçüncü hâli — geçmişte olan ama şimdi de önemli olan bir eylem | have seen · that's been absorbed · We've done |
Dikkat edilecek telaffuzlar
Konuşmacı doesn't, don't, we're gibi kısaltılmış biçimleri 14 kez kullanıyor. Bunları duyduğunuz gibi kısa söyleyin.
- “th” sesleri: thermal /ˈθɜːməl/, underneath /ˌʌndɚˈniθ/, bandwidth /ˈbændwɪdθ/
- “sh” ve “zh” sesleri: efficient /ɪˈfɪʃənt/, backlash /ˈbækˌlæʃ/, consumption /kənˈsʌmp.ʃən/, crucial /ˈkɹuː.ʃəl/, tissue /ˈtɪʃ.(j)u/
- Uzun kelimeler — vurguyu doğru yere koyun: infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, necessarily /ˌnɛs.əˈsɛɹ.ə.li/, primarily /ˈpɹaɪ.mə.ɹə.li/, electricity /ɪˌlɛkˈtɹɪsɪti/, electrical /ɪˈlɛktɹɪkəl/
Türkçe konuşanların zorlandığı sesler:
- /w/ — dudaklar yuvarlak, /v/ değil: liquid /ˈlɪk.wɪd/, acquire /əˈkwaɪɚ/, equation /ɪˈkweɪ.ʒən/, bandwidth /ˈbændwɪdθ/, gigawatt /ˈɡɪɡəˌwɒt/
- Kelime başındaki ünsüz kümesi — araya ünlü eklemeyin: crucial /ˈkɹuː.ʃəl/, startup /ˈstɑɹtˌʌp/, primarily /ˈpɹaɪ.mə.ɹə.li/, cloud /ˈklaʊ̯d/, municipal /mjuˈnɪsɪpəl/
- /æ/ — “e”den daha açık: rack /ɹæk/, gallon /ˈɡælən/, backlash /ˈbækˌlæʃ/, ambient /ˈæm.bi.ənt/, atmosphere /ˈætməsˌfɪɹ/
Bu videoyla nasıl çalışılır
- Videonun tamamını konuşmadan bir kez dinleyin ve bilmediğiniz kelimeleri not edin.
- 0,75× hızla başlayın, cümle cümle tekrar edin ve kolaylaşınca normal hıza dönün.
- Kendinizi kaydedin ve orijinaliyle karşılaştırın; chip, server, liquid gibi kelimelere özellikle dikkat edin.
Gölgeleme Tekniği Nedir?
Gölgeleme, başlangıçta profesyonel tercüman eğitimi için geliştirilen ve çok dilli Dr. Alexander Arguelles tarafından popüler hale getirilen, bilim destekli bir dil öğrenme tekniğidir. Yöntem basit ama güçlüdür: ana dili İngilizce olan bir sesi dinler ve hemen yüksek sesle tekrar edersiniz — konuşmacıyı 1-2 saniye gecikmeyle takip eden bir gölge gibi. Pasif dinleme veya dilbilgisi alıştırmalarının aksine, gölgeleme beyninizi ve ağız kaslarınızı gerçek konuşma kalıplarını eşzamanlı olarak işlemeye ve yeniden üretmeye zorlar. Araştırmalar, telaffuz doğruluğu, tonlama, ritim, bağlı konuşma, dinleme anlama ve konuşma akıcılığını önemli ölçüde geliştirdiğini göstermektedir — bu da onu IELTS Konuşma hazırlığı ve gerçek dünya İngilizce iletişimi için en etkili yöntemlerden biri yapar.