Shadowing Practice: Inside a warehouse run by AI robots - Learn English Speaking with Video
Ders oluşturuluyor...
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We're enabling the next generation of Amazon to really grow
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and realize their full potential and driving the economy forward because this is the future of logistics.
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I'm Andre, Chief Growth Officer at BrightPick,
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and we're developing the next generation of warehouse robotics.
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Our mission is really to enable any warehouse,
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large or small, to fully automate their order fulfillment in a matter of weeks.
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So right now we're standing in one of our installations
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where we pretty much automated the entire fulfillment process using close to 50 BrightPick Autopicker robots.
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I'm going to show you around so you can see how it looks.
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So our flagship robot is called BrightPick Autopicker
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and it's actually the only mobile robot in the world that not only transports items but can also robotically pick them.
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And the big advantage with that is it actually does the pick directly in and out.
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And we actually took a lot of inspiration from the way humans do picking because humans,
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they go directly from one pick to the next and that is actually the most efficient way to pick orders.
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Basically, what we did is you can think of BrightPick Autopicker
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as almost like a human with a cart moving from one location in the warehouse to the next
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and doing the picks as it goes on.
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In fact, we're getting pretty close to human level performance and at a fraction of the cost.
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So the way the robotic picking process works is the robots,
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they retrieve a storage tote from the shelving,
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they scan the storage tote,
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create a 3D model of the tote.
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Then we have an AI engine which tells the robot what item to pick based on probability of success,
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and then the robot picks that item from the storage toad into the order toad.
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The thing with robotic picking is that inevitably the robots will not be able to pick some items some of the time.
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I think anyone who tells you they can pick all items 100% of the time are lying, frankly.
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It's a big challenge in robotic picking in terms of what do you do as a fallback in that scenario.
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We're actually not entirely relying on robotic picking here.
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We incorporated a couple of goods-to-person stations into this installation,
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both as a fallback in case the robots can't pick the items,
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but also for items that aren't ideally suited for robotic picking.
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So let's say items that are heavier or that have a changing center of gravity,
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like liquids, for example.
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So this is our goods to person station right here.
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It actually works on the same principle as the robotic picking.
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So each auto picker brings both the storage tote and the order tote to a human operator.
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There's a tablet that tells him exactly how many items and
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which items he needs to pick and then the operator picks it from one tote to the other tote.
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So it's super simple, pretty ergonomic.
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The robots they raise both totes to waist height.
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They actually have four different sides.
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So what that enables us to do is to feed the human operator from four sides at the same time.
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So during peak hours when it's really busy,
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there's basically four robots at the station at any given point in time,
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which means there's like zero idle time in between fixed.
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A really important part of our philosophy is product simplicity and cost.
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You can see like we use a pretty simple SCAR arm on the robots.
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It's two axes, the end effector is pretty flexible
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and we could have of horse stuck like an expensive six-axis arm on the robot,
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but that would have basically doubled the cost for an extra 10% of performance.
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There's no point in doing that
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when basically what we do in those 10% of the edge cases is we take those items to a human operator,
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which you would anyways need because even if you have the most expensive robotic picker in the world,
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there's still going to be some items when the robot can't pick them.
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So you anyways have to solve for that.
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And I think that's I think that's a really important part to understand about the whole BrightBix system is
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it's designed with simplicity in mind.
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So there's a lot of super complicated features,
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AI, you know, the software orchestration behind it.
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But the actual process of working with the robots and installing it in the warehouse,
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it's super simple, right?
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You see I'm like walking around with the robots.
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Of course, usually we all want people to do that because it slows down the system.
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But it's perfectly safe, you know,
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you don't need any safety fencing.
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There's no QR codes on the floor for navigation.
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We use LiDARs and AI.
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The shelving, it's like very cheap.
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It's basically the same shelving you can buy in Home Depot,
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which also means like you can install in a matter of weeks and even move the shelving from one warehouse to another,
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which, you know, it's pretty important.
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You don't want to build like a monument in your warehouse that you're stuck with for the next 10 years.
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That's actually the reason we purposefully don't use any conveyors because,
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you know, once you build a conveyor good luck moving that.
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That's basically why we developed the system is to enable any retailer to automate their fulfillment in a matter of weeks.
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This is really like a decade of development behind this.
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I mean first we developed the 3D scanner which is actually from our sister company Photo Neo.
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We then developed the AI picking engine.
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I think we've done close to a billion picks by now to train our AI.
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We then developed a mobile platform,
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all the software orchestration that goes with that.
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We actually had a goods-to-person solution before this,
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but then ultimately we brought it all together inside the Autopicker.
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And now this robot can do everything you need for order fulfilling, right?
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Like robotic picking, goods-to-person picking,
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pallet picking, order buffering, consolidation, dispatch, replenishment.
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When we think of BrightPick Autopicker as basically a humanoid in all but name,
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If you think about what a human picker does in a warehouse,
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it's basically the same, except auto pickers are able to do it much faster, more efficient.
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It's literally a tenth of the cost of a humanoid.
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We don't believe in technology for technology's sake.
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Why do you need a human form factor when you can basically achieve human level performance at a fraction of the cost?
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So a common misconception that people have about robotics is that we're taking away people's jobs,
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but the reality is actually completely opposite because pretty much every customer that buys our solution,
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they're dealing with massive labor shortages,
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whether it's in logistics or in manufacturing,
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and there's simply not enough people to meet demand because we have a shrinking labor force.
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These are physically tough jobs.
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Imagine walking two marathons a week just to pick orders,
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and there's not enough people to fill the demand, basically.
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For example, this customer right here,
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they had to actively turn off their marketing spend because they didn't have enough people in their warehouse to pick orders.
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And now after they installed our solution,
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they're able to grow it 100%.
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It was basically like three people servicing our entire system.
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Whereas before they would have needed 20, 30 people here.
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Another feature that's unique to BrightPick is what we call pallet picking.
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And this is actually, imagine you have items that are fast movers.
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So let's say you're putting in samples or you're basically selling products that go into every order or every second order.
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It doesn't really make sense to put those items into the system
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because you're going to be replenishing them almost as fast as you're taking them out.
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So what we developed, what we call these pallet picking positions,
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where basically human operators are able to pick directly from pallets or from cases,
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which you see stored behind them,
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and place them onto the order tote at the robot.
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So that basically makes the replenishment process super easy,
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where all you do is you stick a pallet there or you throw a case there,
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and then the robot pulls up,
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tells the human operator on the tablet what item to pick,
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and the human can pick that item and place it onto the robot.
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So you really get that flexibility of robotic picking,
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GTP picking, and pallet picking,
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all as part of one system.
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You really don't need any other picking.
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So this right here is the buffer area,
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and actually this is a 24-7 operation,
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so the robots are working even at night when there's practically no one in the warehouse.
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and what they're doing is after they pick the orders,
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they buffer them in this area.
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And then once the morning shift comes in,
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they take them out, deliver them to pack out to be packed and shipped.
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Another use case is imagine you have an order that consists of 10 picks,
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but only nine of them are robotically pickable.
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So the robots are gonna pick those nine items overnight,
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buffer them, and then when the morning shift comes in,
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it's gonna do that last 10th pick using the goods to person or pallet station.
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And basically then the order is complete.
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So because we have such a high level of automation,
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we're able to easily operate at night because you practically don't need anyone to run the system.
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We're now in a hyper-growth mode.
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We're really focused on ramping up our manufacturing because we already get more demand than we can meet for our solution.
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So now it's really about laying down the groundwork to make
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sure we can manufacture as many of these robots as possible and really ensure that they're as reliable as possible.
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We understand that these are mission critical processes,
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so we make sure that each robot can really operate five,
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10 years without breaking down.
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This is one of many installations that we've already done.
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We have many more in the pipeline,
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so right now it's rolling up our sleeves and getting to work.
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Bu dersin kelimeleri ve konuşma notları
Bu C1 seviyesindeki konuşma dersi “Inside a warehouse run by AI robots” videosuna dayanıyor. En çok tekrarlanan kelimeler: robot, pick, picking, item, robotic. Bu videoda gölgeleme çalışması için 149 cümle ve 1712 kelime var. Konuşma bölümü 8:24 sürüyor. Konuşmacı hızlı konuşuyor, dakikada yaklaşık 204 kelime; bu yüzden birbirine bağlanan ve zayıflayan sesler duyacaksınız. Kelimelerin %83’i İngilizcede en sık kullanılan 3.000 kelime arasında; geri kalanına başlamadan önce bakmakta fayda var.
Bu videodaki önemli kelimeler
Videodaki en ileri düzey 15 kelime, telaffuzu ve anlamıyla:
| Kelime | Telaffuz | Anlam |
|---|---|---|
| robotic sıfat | /ɹoʊˈbɑtɪk/ | robotik |
| warehouse isim | /ˈwɛə(ɹ)haʊs/ | antrepo, depo |
| humanoid sıfat | /ˈhjuːmənɔɪd/ | insansı |
| robotics isim | /ɹoʊˈbɑ.tɪks/ | robotik |
| simplicity isim | /sɪmˈplɪsɪti/ | basitlik |
| logistics isim | /ləˈd͡ʒɪstɪks/ | lojistik |
| automobile isim | /ˈɔː.tə.məˌbil/ | otomobil, araba |
| fraction isim | /ˈfɹæk.ʃən/ | bölüm, fraksiyon |
| tablet isim | /ˈtæblət/ | levha |
| scanner isim | /ˈskænə/ | tarayıcı |
| retrieve fiil | /ɹɪˈtɹiːv/ | geri almak |
| idle sıfat | /ˈaɪd(ə)l/ | aylak, boş |
| flagship isim | /ˈflæɡʃɪp/ | amiral gemisi, bayrak gemisi |
| dispatch fiil | /dɪˈspæt͡ʃ/ | göndermek, sevk etmek |
| axe isim | /æks/ | balta |
Duyacağınız deyimsel fiiller
| Kelime | Telaffuz | Anlam |
|---|---|---|
| roll up fiil | dürmek | |
| slow down fiil | yavaşlamak | |
| take away fiil | /ˌteɪk əˈweɪ/ | götürmek |
| turn off fiil | kapamak |
Tekrar etmeye değer cümleler
Videodan, günlük konuşmada yeniden kullanabileceğiniz kısa ve tam cümleler:
- We're actually not entirely relying on robotic picking here.
- You see I'm like walking around with the robots.
- We don't believe in technology for technology's sake.
- You really don't need any other picking.
- We're now in a hyper-growth mode.
Bu videodaki dil bilgisi
Konuşmacının en çok kullandığı yapılar, videodaki sözcüklerin aynısıyla:
| Yapı | Videoda |
|---|---|
| Present perfect have/has + fiilin üçüncü hâli — geçmişte olan ama şimdi de önemli olan bir eylem | we've done · we've already done |
| Edilgen yapı be + fiilin üçüncü hâli — kimin yaptığı değil, ne olduğu önemli | is called · be packed |
| İlgi cümlecikleri who / which + cümle — bir kişi ya da şey hakkında ek bilgi | anyone who tells · scanner which is |
Dikkat edilecek telaffuzlar
Konuşmacı we're, don't, you're gibi kısaltılmış biçimleri 36 kez kullanıyor. Bunları duyduğunuz gibi kısa söyleyin.
- “sh” ve “zh” sesleri: shelve /ʃɛlv/, fraction /ˈfɹæk.ʃən/, misconception /ˌmɪs.kənˈsɛp.ʃən/, replenish /ɹɪˈplɛn.ɪʃ/, consolidation /kənˌsɑləˈdeɪʃən/
- Uzun kelimeler — vurguyu doğru yere koyun: simplicity /sɪmˈplɪsɪti/, automobile /ˈɔː.tə.məˌbil/, misconception /ˌmɪs.kənˈsɛp.ʃən/, purposefully /ˈpɝ.pəs.fə.li/, consolidation /kənˌsɑləˈdeɪʃən/
Türkçe konuşanların zorlandığı sesler:
- /w/ — dudaklar yuvarlak, /v/ değil: warehouse /ˈwɛə(ɹ)haʊs/, anyways /ˈɛn.iˌweɪz/, groundwork /ˈɡɹaʊndˌwɜːɹk/, waist /weɪst/
- Kelime başındaki ünsüz kümesi — araya ünlü eklemeyin: humanoid /ˈhjuːmənɔɪd/, fraction /ˈfɹæk.ʃən/, groundwork /ˈɡɹaʊndˌwɜːɹk/, scanner /ˈskænə/, flagship /ˈflæɡʃɪp/
- /æ/ — “e”den daha açık: pallet /ˈpælɪt/, fallback /ˈfɔːl.bæk/, fraction /ˈfɹæk.ʃən/, tablet /ˈtæblət/, scanner /ˈskænə/
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; robotic, warehouse, humanoid 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.