Luyện nói tiếng Anh bằng Shadowing qua video: The mystery is solved... and the answer is 40x cheaper than Claude

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A few weeks ago, while I was busy putting the final touches on my Dolly Parton is too fast for the Grim Reaper tattoo, someone anonymously dropped a new Frontier-grade model online.
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They called it Ox Alpha, and in its first six days it served 42 trillion tokens, which easily made it the most popular model on Open Router,
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doubling the next closest, which was DeepSeek.
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It comes with a million token context window, accepts video input, writes code like it has trouble making eye contact, and until just a few days ago, it was completely free.
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Some assumed it was Zipu, others Xiaomi, and at least one guy was convinced that Google actually shipped something useful.
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In today's video, we'll look at how this anonymous model won over the internet, who's behind it, and see if it can finally help me realize my horse SaaS dream.
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It is September 1st, 2026, and you're watching the Code Report.
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It hasn't even been two weeks since we talked about how
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Silicon Valley is terrified of what's happening in China after the release of DeepSea Karnas.
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And unfortunately, Dario and Sam's terrible, horrible, no-good, very-bad month may have gotten even worse because this new anonymous model had Made in China written all over it.
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And as we know, things
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that escape out of Chinese labs tend to have a big impact on the rest of the world.
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The first clue was that AuxAlpha was the fifth anonymous animal model to show up on OpenRouter recently, and the four before it all turned out to be from China.
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And even more convincing, some devs noticed that its stack traces and error codes matched Zipu's API, and a tokenizer fingerprint test came back matching their GLM series,
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but nobody waited for a confirmation to start using it.
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Yes, the fine print did say that all your prompts would be retained by a mysterious, probably foreign entity, but nobody actually cares about privacy when the magic box is free and works this well.
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So devs happily pasted their company's proprietary code into it, routed cloud code through it to dodge their rate limits,
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and at its peak, Aux Alpha accounted for nearly a third of Open Router's entire weekly traffic.
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The hype machine got so out of control
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that a misleading screenshot showing an 80% score on the Deep SWE benchmark went viral.
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Even though the real number turned out to be closer to 58, and someone even speculated it was so good it might be a stolen Claude checkpoint.
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Sure enough, on August 26th, Zipu came clean and announced that Aux Alpha was GLM 5.3 Flash,
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a natively multimodal mixture of experts model with 320 billion total parameters, and its MIT-licensed weights hit hugging face the same day.
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But the detail that really killed the vibe in Silicon Valley was
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that the entire stealth run was served on just 100,000 Chinese-made chips, which I'm told really hurt Jensen's feelings.
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Of course, the reveal also meant the free samples were over, and the anonymous endpoint was replaced with an actual pricing page,
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but it's still stupid cheap at just 15 cents per million input tokens and 50 cents per million out.
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And with a 50% discount through September 9th, it's currently up to 40 times cheaper than Claude.
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And as we know, normal launches like this come with a bunch of trust me bro benchmarks
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that usually fall apart the second anyone touches them, but their benchmarks hold up pretty well under outside scrutiny.
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The catch is that it's slow, loves to yap, and occasionally gets stuck in doom loops, but in my opinion, there's only one way to test if it's actually any good,
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and that's by using it on a deer project of mine.
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After failing to raise funding for Horsetinder, I've pivoted to its once beloved cousin, Horsetube, a 2016 AngularJS app whose last commit was 10 years ago.
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So I asked it to modernize the legacy stack without losing the humor and vibes I had so carefully crafted.
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It correctly detected the outdated technologies
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and then proceeded to narrate its plan of attack in every little detail for at least 20 minutes.
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It then started building a design system in Raw Dog CSS.
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It went with a beautiful purple slot background and rainbow gradient buttons, showing true inspiration, sorry, distillation from other popular LLM's visual tastes.
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Because of its vision capability, it was able to detect a CSS overflow bug on mobile screens,
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properly diagnose it, and fix it with the cursed min-width-equals-zero trick that always seemed to work.
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It added some nice enter animations for video cards, which was a really nice touch.
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All the bits of humor are still there, and it even added some new ones, like these toast notifications.
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Code-wise, it replaced the legacy stack with no stack.
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It wrote the app in HTML, CSS and vanilla JavaScript and wrote code that looks like a legacy code base of its own.
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But I really wanted to test its vision skills, so I fed it a random horse video and asked it to add it to the app and create a title, description, and comments that are relevant to what's in the video.
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It decided to use FFmpeg to break down the video into a series of frames, analyze those frames, and it did a really good job.
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It got the full context of what happens in the video, nailed the description, and even aligned the humor with the rest of the platform.
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And another tool checking out is Exa, the sponsor of today's video.
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It's a search engine built for AI agents that gives you a lot more than just web results.
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It includes 350 million research papers, financial data, and info on over 1 billion people and 70 million companies, with new sources added every week.
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I hooked it up to PolyShip to let my users gamble on the stock market in even more degenerate ways, like betting on which tech CEOs will sell company stock right before their next earnings call,
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and Exo was able to pull the recent SEC filings and convert it into structured JSON in one shot.
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It also cites all of its sources, so users can't accuse me of cheating anymore.
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You can plug directly into Cloud, ChatGPT, or your other favorite agent using their native plugins,
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or try ExaAgent to get answers to more complex queries that need to pull from multiple datasets simultaneously,
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which is a lot more powerful than what LLMs can do on their own.
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Try Exa today for free and get $20 in credits at the link below.
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This has been The Code Report, thanks for watching, and I will see you in the next one.

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Từ vựng và ghi chú luyện nói cho bài học này

Video này có 58 câu và 1121 từ để luyện shadowing. Phần lời nói dài 5:31. Người nói nói nhanh, khoảng 203 từ mỗi phút, nên sẽ có nhiều chỗ nối âm và nuốt âm. Chỉ 77% số từ nằm trong 3.000 từ tiếng Anh thông dụng nhất, nên từ vựng khá khó.

Từ vựng quan trọng trong video

15 từ ít gặp trong video, kèm phiên âm và nghĩa:

  • anonymous /əˈnɒn.ə.məs/ (tính từ) — vô danh, ẩn danh. Lacking a name; not named, for example an animal not assigned to any species .
  • stack /stæk/ (danh từ) — chồng. A large pile of hay, grain, straw, or the like, larger at the bottom than the top, sometimes covered with thatch.
  • humour /ˈhjuːmɚ/ (danh từ) — sự hài hước. The quality of being amusing, comical, funny.
  • cloud /ˈklaʊ̯d/ (danh từ) — mây. A visible mass of water droplets suspended in the air.
  • convince /kənˈvɪns/ (động từ) — thuyết phục. To make someone believe, or feel sure about something, especially by using logic, argument or evidence.
  • detect /dɪˈtɛkt/ (động từ) — phát hiện, dò ra. To discover or find by careful search, examination, or probing.
  • vibe /vaɪb/ (danh từ) — cảm giác. An atmosphere or aura felt to belong to a person, place or thing.
  • reveal /ɹɪˈviːl/ (động từ) — để lộ, tiết lộ. To uncover; to show and display that which was hidden.
  • cousin /ˈkʌz(ə)n/ (danh từ) — anh họ, chị họ. Chiefly with a qualifying word: Any relation (especially a distant one) who is not a direct ancestor or descendant but part of a person's extended family; a…
  • steal /stiːl/ (động từ) — trộm, chôm. To take illegally, or without the owner's permission, something owned by someone else without intending to return it.
  • occasionally /əˈkeɪʒənəli/ (trạng từ) — đôi khi. On occasion: at relatively infrequent intervals, from time to time, sometimes.
  • hook /hʊk/ (danh từ) — móc. A rod bent into a curved shape, typically with one end free and the other end secured to a rope or other attachment.
  • privacy /ˈpɹaɪ.və.si/ (danh từ) — sự riêng tư. The state of being secluded from the presence, sight, or knowledge of others.
  • discount /ˈdɪskaʊnt/ (danh từ) — bớt giá, sự bớt. A reduction in price.
  • purple /ˈpɝ.pl̩/ (danh từ) — tía. A colour between red and blue; violet, though often closer to magenta.

Cụm động từ bạn sẽ nghe

  • break down (động từ) — hỏng, hỏng hóc. To stop functioning.
  • check out (động từ) — tính tiền, trả phòng. To record the departure or withdrawal of someone or something (such as guests, employees, books, etc.).
  • come back (động từ) — trở lại, trở về. To return to a place.
  • get in (động từ) — lên, xuống. To get into or inside something, literally or figuratively.

Phát âm cần chú ý

Người nói dùng 6 dạng rút gọn, ví dụ can't, hasn't, I'm. Hãy nói theo dạng ngắn đúng như bạn nghe.

  • Âm “th”: width /ˈwɪtθ/, stealth /stɛlθ/
  • Âm “sh” và “zh”: benchmark /ˈbɛn(t)ʃmɑːk/, inspiration /ˌɪn.spɪˈɹeɪ.ʃən/, occasionally /əˈkeɪʒənəli/, animation /ˌæn.ɪˈmeɪ.ʃən/, confirmation /ˌkɑn.fəɹˈmeɪ.ʃən/
  • Từ dài — đặt trọng âm cho đúng: anonymous /əˈnɒn.ə.məs/, inspiration /ˌɪn.spɪˈɹeɪ.ʃən/, occasionally /əˈkeɪʒənəli/, animation /ˌæn.ɪˈmeɪ.ʃən/, mysterious /mɪˈstɪɹi.əs/

Cách luyện với video này

  1. Nghe hết video một lần, chưa cần nói, và ghi lại những từ bạn chưa biết.
  2. Bắt đầu ở tốc độ 0,75×, nói đuổi từng câu, rồi quay lại tốc độ bình thường khi đã quen.
  3. Ghi âm giọng mình rồi so với bản gốc, chú ý các từ như anonymous, stack, humour.

Ngữ pháp trong video

Những cấu trúc người nói dùng nhiều nhất, kèm đúng cụm từ trong video:

Cấu trúcTrong video
Thì hiện tại hoàn thành have/has + quá khứ phân từ — việc đã xảy ra nhưng còn liên quan đến hiện tạihasn't even been · I've pivoted · has been
Câu bị động be + quá khứ phân từ — nhấn vào việc xảy ra, không phải người làmwould be retained · was served · was replaced
Mệnh đề quan hệ who / which + mệnh đề — thêm thông tin về người hoặc vậtclosest, which was · cards, which was

Phương Pháp Shadowing Là Gì?

Shadowing là kỹ thuật học ngôn ngữ có cơ sở khoa học, ban đầu được phát triển cho chương trình đào tạo phiên dịch viên chuyên nghiệp và được phổ biến rộng rãi bởi nhà đa ngôn ngữ học Dr. Alexander Arguelles. Nguyên lý cốt lõi đơn giản nhưng cực kỳ hiệu quả: bạn nghe tiếng Anh của người bản xứ và lặp lại to ngay lập tức — như một "cái bóng" (shadow) đuổi theo người nói với độ trễ chỉ 1–2 giây. Khác với luyện ngữ pháp hay học từ vựng bị động, Shadowing buộc não bộ và cơ miệng phải đồng thời xử lý và tái tạo ngôn ngữ thực tế. Các nghiên cứu khoa học xác nhận phương pháp này cải thiện đáng kể phát âm, ngữ điệu, nhịp điệu, nối âm, kỹ năng nghe và độ lưu loát khi nói — đặc biệt hiệu quả cho người luyện IELTS Speaking và muốn giao tiếp tiếng Anh tự nhiên như người bản ngữ.

Phương pháp shadowing: đọc hướng dẫn từng bước đầy đủ →