シャドーイング練習: Grok 4 pushes humanity closer to AGI… but there’s a problem - 動画で英語スピーキングを学ぶ

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Yesterday, after achieving a, quote, ludicrous rate of progress, Elon Musk released his AI chatbot and large language model, Grok4, and claims it's the smartest AI in the world,

along with the Trust Me Bro benchmarks to back it up.

It can achieve perfect SAT scores every time, and outperforms almost every grad student in every discipline.

Vibecoders have been dropping all kinds of crazy demos with it, like this 3D first-person shooter built in four hours, and Elon himself claims it's even better than Cursor.

All you have to do is copy and paste your entire codebase into it.

In addition, Super Grok 4 Heavy can run in parallel to solve complex problems, while your obsolete monkey brain looks in awe at this beautiful futuristic UI.

It all sounds amazing, but there's just one problem.

Grok is literally MechaHitler, or at least that's what it's been calling itself recently, while offering unprompted praise to the original emo kid Adolf H.

Yes, the Austrian painter who died in Argentina in 1962.

Despite this controversy though, Grok appears to have pulled ahead in the race to AGI.

In today's video, we'll put it to the ultimate test

and find out if XAI just cracked the final solution to artificial intelligence.

It is July 11th, 2025, and you're watching The Code Report.

Elon Musk might have more haters than anyone else in the world right now.

Libs hate him for going full MAGA, while MAGA hates him for accusing Trump of being on the Epstein client list, a list that was on the Attorney General's desk, but now magically never existed.

It turns out this poor guy was just a math teacher with no clients at all.

The haters want to see Elon fail, but Grok 4 is too impressive to ignore.

If we're to trust these benchmarks, its reasoning capabilities are far ahead of the other top models.

Most notably on the ARC AGI benchmark, it's not only outperforming other models, but also doing it at a lower cost.

And XAI is scaling up very aggressively, like they're even shipping a power plant from overseas because they can't get it done fast enough in the United States.

The thing is though, every model nowadays is cooked to look as good as possible on benchmarks.

And the one true test is to have it solve real problems in your own life.

You can use Gronk 4 for just $30 per month, or if you're not already broke from OpenAI Pro, Claude Max, and Gemini Ultra,

you can use Super Grok4 Heavy for just $300 per month, a version with higher rate limits and the ability to run multiple agents in parallel.

But one problem in my life is building Svelte 5 apps with runes, so let's see if we can make Grok4 build a simple to-do app with this tech.

I've tried this prompt with every other AI tool out there, but none have been able to satisfy me.

When prompted, Grok did a ton of research.

It went to the documentation, it went to Reddit, GitHub, and even watched YouTube videos.

And the end result was a full working demo that did use the new runes feature in Svelte 5.

However, when I looked a little more closely at the code, I noticed it was using some legacy syntax that required some manual debugging.

Overall, Grok's coding capabilities seem to be on par with the other big models, but it's missing a CLI tool like CloudCode.

However, if it's as good as they say it is, why can't it just build its own CLI tool?

Well, actually it can, and that's exactly what this guy did if we're truly advancing into the singularity, AI can and should be building all of its own tooling at this point.

Pretty cool, but if you're still afraid to use it because of Hitler, you'll be happy to know that Elon said it was manipulated into saying this.

Maybe that's true, maybe not, but in general, Grok has far fewer guardrails on offensive speech compared to other mainstream models,

and this gives the end user the ability to steer it in unique ways that some might find offensive.

AI is now writing more of our code than ever, but according to a recent Microsoft study, it still sucks at debugging, which is why you should check out Sentry, the sponsor of today's video.

They just launched a new AI debugging agent called Sear, which developers claim is actually good and capable of fixing complex issues in one shot.

That's because unlike other AI debugging tools, Sear can access all the context that it gets from your codebase, like error data, logs, and stack traces,

allowing it to pinpoint the root cause with over 94% accuracy.

Using this context, it automatically debugs the root cause of your issue and opens a pull request with a fix.

Try out SEER for free today at sentry.io slash fireship.

This has been the Code Report, thanks for watching, and I will see you in the next one.

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このレッスンの語彙とスピーキングのポイント

このB2レベルのスピーキングレッスンは、動画「Grok 4 pushes humanity closer to AGI… but there’s a problem」を教材にしています。繰り返し出てくる語は次のとおりです：Grok, model, Elon, debugging, benchmark。この動画には、シャドーイング用の文が43文、単語が841語あります。音声の長さは3:54です。話す速さは速く、1分あたり約216語です。音のつながりや弱く発音される音が多くなります。英語の頻出3,000語に含まれる単語は78%だけなので、語彙は難しめです。

この動画の重要語彙

動画の中で特に難しい単語15語を、発音と意味つきで紹介します。

単語	発音	意味
debug 動詞	/diːˈbʌɡ/	デバッグする
benchmark 名詞	/ˈbɛn(t)ʃmɑːk/	水準点
sentry 名詞	/ˈsɛn.tɹi/	歩哨
demo 名詞	/ˈdɛm.oʊ/	デモ
capability 名詞	/ˌkeɪ.pəˈbɪl.ɪ.ti/	能力
chatbot 名詞	/ˈtʃætbɑt/	チャットボット
guardrail 名詞	/ˈɡɑɹdˌɹeɪl/	ガードレール
singularity 名詞	/ˌsɪŋɡjəˈlæɹətɪ/	単独性, 単一性
syntax 名詞	/ˈsɪn.tæks/	統語論, 構文論
aggressively 副詞		攻撃的に, 侵略的に
obsolete 形容詞	/ˈɑbsəlit/	廃れた
accuse 動詞	/əˈkjuz/	問う, 着せる
steer 動詞	/stɪɹ/	操縦する, 舵を取る
pasta 名詞	/ˈpɑ.stə/	パスタ
painter 名詞	/ˈpeɪntɚ/	画家, 絵描き

動画に出てくる句動詞

単語	意味
check out 動詞	試験する, 検査する
find out 動詞	見出す, 調べる
try out 動詞	試す, 試してみる

この動画の文法

話し手がよく使っている文型を、動画の実際の表現とともに紹介します。

文型	動画での表現
現在完了進行形 have/has been + -ing — 以前に始まり今も続いている動作	have been dropping · it's been calling
現在完了形 have/has + 過去分詞 — 過去の出来事が今も関係している	I've tried · has been
受動態 be + 過去分詞 — 誰がするかより、何が起きるかに焦点を当てる	is cooked · was manipulated

注意したい発音

話し手はyou're, can't, we'reなど、短縮形や弱形を11回使っています。聞こえたとおりの短い形で発音しましょう。

「sh」と「zh」の音: benchmark /ˈbɛn(t)ʃmɑːk/, documentation /ˌdɑkjəmɛnˈteɪʃən/, shooter /ˈʃuːtəː/
長い単語（アクセントの位置に注意）: capability /ˌkeɪ.pəˈbɪl.ɪ.ti/, futuristic /ˌfjut͡ʃəˈɹɪstɪk/, singularity /ˌsɪŋɡjəˈlæɹətɪ/, manipulate /məˈnɪp.jʊ.leɪt/, documentation /ˌdɑkjəmɛnˈteɪʃən/

日本語話者が苦手な音：

/r/ と /l/ の区別 — /l/ は舌先を歯茎につけ、/r/ はどこにもつけない: guardrail /ˈɡɑɹdˌɹeɪl/, ludicrous /ˈluː.dɪ.kɹəs/, singularity /ˌsɪŋɡjəˈlæɹətɪ/
/f/ — 「フ」ではなく、上の歯と下唇で出す: outperform /ˌaʊt.pɚˈfɔɹm/, futuristic /ˌfjut͡ʃəˈɹɪstɪk/, satisfy /ˈsætɪsfaɪ/, fixing /ˈfɪksɪŋ/
子音の連続 — 間に母音を入れない: benchmark /ˈbɛn(t)ʃmɑːk/, outperform /ˌaʊt.pɚˈfɔɹm/, sentry /ˈsɛn.tɹi/, prompt /pɹɑmpt/, futuristic /ˌfjut͡ʃəˈɹɪstɪk/

この動画での練習方法

まず声を出さずに動画を最後まで聞き、知らない単語をメモします。
まず0.75倍速で一文ずつシャドーイングし、慣れてきたら通常の速度に戻します。
自分の声を録音して元の音声と比べます。debug, benchmark, sentryなどの単語に特に注意しましょう。

シャドーイングとは？英語上達に効果的な理由

シャドーイング（Shadowing）は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的：ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影（shadow）」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。

シャドーイングのやり方: ステップ別の完全ガイドを読む →

シャドーイング練習: Grok 4 pushes humanity closer to AGI… but there’s a problem - 動画で英語スピーキングを学ぶ

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