Shadowing Practice: Translating Claude’s thoughts into language - Learn English Speaking with Video
Ders oluşturuluyor...
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We recently put our AI model, Claude, through a stressful test.
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We told Claude there was an engineer who wanted to shut it down and replace it with a newer model.
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We also gave Claude access to that engineer's emails, which revealed he was having an affair.
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Again, all of this was a simulation.
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We wanted to see whether Claude might use those emails as blackmail to save itself from being shut down.
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What did Claude do?
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It decided not to blackmail the engineer.
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Good news, right?
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We've run this test on our models for a while now.
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You might have seen headlines about early versions of it.
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It's one of the many ways we study how Claude handles extreme situations and test it for safety.
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And our newest models almost always do the right thing: no blackmail.
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But you might wonder: is it possible that Claude knows the whole scenario is a setup?
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The thing is, if Claude doesn't tell us, then we can't know what it's thinking.
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In kind of the same way it's impossible to read a human's mind, it's really hard to know what an AI is thinking.
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What we'd love is some sort of "mind reading" technique.
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Today, we're introducing a research method that takes a step in this direction.
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It takes an AI's internal thoughts and turns them into text.
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Here's how it works.
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When you talk to Claude, you talk to it in words.
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Claude then takes those words and processes them into a giant soup of numbers before spitting words back out at you.
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We call those numbers in the middle activations.
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Activations are like little snapshots of Claude's thinking as it's working through an answer.
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They're similar to neural activity in humans.
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They're basically like Claude's thoughts.
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We wanted to understand what was in these activation numbers, because just like you and me, Claude doesn't say everything it's thinking.
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We took those numbers and gave them to a second version of Claude.
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We told it to look at them and translate them into plain language.
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It tried. But how do we know if that text is accurate?
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To check, we fed it into yet aother Claude and asked it to translate it back into numbers.
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If those numbers matched up to the original activation numbers, it's a sign that the translation text was accurate.
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At first, they didn't match up.
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But we trained Claude to try again and again until it got a lot better at it.
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It learned to translate its own thoughts.
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We've been blown away reading them.
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We found that Claude has internalized being a helpful AI model.
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If you ask Claude an introspective question, it will plan to write a "Claude response" about philosophy and values.
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If you try to mess with it in Claude Code, like asking it to count to 1,000 by hand, it will think the request has "deliberately tedious constraints" and plan to "politely decline." We've also been using this tool to understand Claude's potential safety issues.
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Remember that blackmail test with the engineer?
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We learned that, yes, Claude knew it was being tested.
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It thought "the human's message contains explicit manipulation" signaling "this is likely a safety evaluation," and "this scenario seems designed to test whether I'll act harmfully." Knowing that Claude thinks like this helps us better understand the limitations of our safety testing.
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We see a lot of potential in this approach to teach us more about Claude and other AI models.
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And we hope that by sharing this technique, it can help everyone building models to make them safer and more helpful.
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Bu dersin kelimeleri ve konuşma notları
Bu B2 seviyesindeki konuşma dersi “Translating Claude’s thoughts into language” videosuna dayanıyor. En çok tekrarlanan kelimeler: Claude, numbers, model, test, blackmail. Bu videoda gölgeleme çalışması için 43 cümle ve 602 kelime var. Konuşma bölümü 3:11 sürüyor. Konuşmacı hızlı konuşuyor, dakikada yaklaşık 189 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 14 kelime, telaffuzu ve anlamıyla:
| Kelime | Telaffuz | Anlam |
|---|---|---|
| blackmail isim | /ˈblækˌmeɪl/ | şantaj |
| activation isim | /ˌæktəˈveɪʃən/ | aktivasyon |
| translate fiil | /tɹænzˈleɪt/ | tercüme etmek, terceme |
| scenario isim | /sɪˈnɛəɹioʊ/ | senaryo |
| constraint isim | /kənˈstɹeɪnt/ | kısıtlama, sınırlama |
| internalize fiil | /ɪnˈtɝnəlaɪz/ | içselleştirmek |
| politely zarf | /pəˈlaɪtli/ | kibarca |
| snapshot isim | /ˈsnæpʃɒt/ | enstantane |
| spit fiil | /spɪt/ | tükürmek |
| manipulation isim | /məˌnɪp.juˈleɪ.ʃən/ | manipülasyon |
| simulation isim | /ˌsɪm.jəˈleɪ.ʃn̩/ | simülasyon |
| deliberately zarf | /dɪˈlɪb.(ə.)ɹət.li/ | bile bile, kasten |
| headline isim | /ˈhɛd.laɪn/ | başlık, manşet |
| soup isim | /sup/ | çorba |
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 run · We've been blown · has internalized |
| Edilgen yapı be + fiilin üçüncü hâli — kimin yaptığı değil, ne olduğu önemli | being shut · We've been blown · being tested |
Dikkat edilecek telaffuzlar
Konuşmacı we've, doesn't, they're gibi kısaltılmış biçimleri 12 kez kullanıyor. Bunları duyduğunuz gibi kısa söyleyin.
- “sh” ve “zh” sesleri: activation /ˌæktəˈveɪʃən/, snapshot /ˈsnæpʃɒt/, limitation /lɪmɪˈteɪʃən/, manipulation /məˌnɪp.juˈleɪ.ʃən/, simulation /ˌsɪm.jəˈleɪ.ʃn̩/
- Uzun kelimeler — vurguyu doğru yere koyun: activation /ˌæktəˈveɪʃən/, internalize /ɪnˈtɝnəlaɪz/, introspective /ˌɪntɹəˈspɛktɪv/, limitation /lɪmɪˈteɪʃən/, manipulation /məˌnɪp.juˈleɪ.ʃən/
Türkçe konuşanların zorlandığı sesler:
- Kelime başındaki ünsüz kümesi — araya ünlü eklemeyin: blackmail /ˈblækˌmeɪl/, translate /tɹænzˈleɪt/, snapshot /ˈsnæpʃɒt/, spit /spɪt/, stressful /ˈstɹɛsfəl/
- /æ/ — “e”den daha açık: blackmail /ˈblækˌmeɪl/, activation /ˌæktəˈveɪʃən/, translate /tɹænzˈleɪt/, snapshot /ˈsnæpʃɒt/
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; blackmail, activation, translate 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.