Learn Japanese daredevil • 6 months ago • 100%

久しぶりですね。皆さんは元気だと希望します。じゃあ、日本語を勉強しましょうか？ 14.I.B [#genki2textbook](https://kbin.social/tag/genki2textbook) [#japanese](https://kbin.social/tag/japanese) [#learnjapanese](https://kbin.social/tag/learnjapanese) [#japanesepractice](https://kbin.social/tag/japanesepractice) B. Items marked with O are what you wanted when you were a child, and items marked with ✗are what you did not want. Make sentences using ほしい。 > > > Example: > O・子供の時、本がほしかったです。 > ✗・子供の時、マフラーがほしくなかったです。 > > 1. O・テレビーゲーム 子供の時、テレビーゲームがほしかったです。 2. ✗・指輪 子供の時、指輪がほしくなかったです。 3. ✗・腕時計 子供の時、腕時計がほしくなかったです。 4. O・玩具 子供の時、玩具がほしかったです。 5. ✗・花 子供の時、花がほしくなかったです。 [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 7 months ago • 100%

14.I.A [#genki2textbook](https://kbin.social/tag/genki2textbook) [#japanese](https://kbin.social/tag/japanese) [#learnjapanese](https://kbin.social/tag/learnjapanese) [#japanesepractice](https://kbin.social/tag/japanesepractice) I. 日本がほしいです。 A. Items marked with O are what you want, and items marked with X are what you do not want. Make sentences using ほしい。 > > > Example: > [O] 本・本がほしいです。 > [X] マフラー・マフラーがほしくないです。 > > 1. [ｏ] お金・お金がほしいです。 2. [ｘ] セーター・セーターはほしくないです。 3. [ｘ] パソコン・パソコンはほしくないです。 4. [ｏ] バイク・バイクがほしいです。 5. [ｘ] ぬいぐるみ・ぬいぐるみはほしくないです。 [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 8 months ago • 100%

13.VII.B [#genki2textbook](https://kbin.social/tag/genki2textbook) [#japanese](https://kbin.social/tag/japanese) [#learnjapanese](https://kbin.social/tag/learnjapanese) [#japanesepractice](https://kbin.social/tag/japanesepractice) B. Talk about part-time jobs 1. アルバイトをしたことがありますか。 > > > はい、ことがありました。 > > 1. いつしましたか。 > > > 先年です。 > > 1. どんなアルバイトでしたか。 > > > 日本レストランで給仕をしました。日本語練習ができるので、面白いアルバイトだと思いました。 > > 1. 一週間に何日働きましたか。 > > > 一週間三まで四日働きました。 > > 1. 一週間にいくらもらいましたか。 > > > 多分千ドルごろだけ。でも働くの後で、無料食べ物をくれます。悪くなかったです。 > > 1. どんなアルバイトがしてみたいですか。どうしてですか。 > > > 分かりません。今仕事が好きなので、あまりこのことについて考えりません。ラッキですよね。 > > [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 8 months ago • 100%

15.4.I [#genki2wb](https://kbin.social/tag/genki2wb) [#learnjapanese](https://kbin.social/tag/learnjapanese) [#japanese](https://kbin.social/tag/japanese) [#japanesepractice](https://kbin.social/tag/japanesepractice) I. Make sentences using the cues. 1. 食堂があります。 > > > これは食堂がある建物です。 > > 1. 私は先生に借りました。 > > > これは私が先生に借りた辞書です。 > > 1. 父は私にくれました。 > > > これは父が私にくれたです。 > > 1. 友達は住んでいます。 > > > これは友達が住んでいるです。 > > 1. 最近で来ました。 > > > これは最近で喫茶店に来たです。 > > [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 8 months ago • 100%

15.3.II [#genki2wb](https://kbin.social/tag/genki2wb) [#learnjapanese](https://kbin.social/tag/learnjapanese) [#japanese](https://kbin.social/tag/japanese) [#japanesepractice](https://kbin.social/tag/japanesepractice) 1. 来週、大きい台風が着ます。何しておきますか。 > > > お金を下ろしたり、食べ物を買ったり、服を準備しておきたりなどです。 > > 1. 来週、試験があります。何をしておきますか。 > > > 教科書を復習したり、先生に聞いておきたりなどです。 > > 1. 今度の休みに富士山に登ります。何をしておかなければいけませんか。 > > > 水を忘れなかったり、厚い服を持っていておかないといけません。 > > [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 8 months ago • 100%

15.3.I [#genki2wb](https://kbin.social/tag/genki2wb) [#learnjapanese](https://kbin.social/tag/learnjapanese) [#japanese](https://kbin.social/tag/japanese) [#japanesepractice](https://kbin.social/tag/japanesepractice) I. Read the first half of the sentences carefully. Then choose from the list what you will do in preparation and complete the sentences, using 〜ておきます。 1. あの店ではカード(Credit card)が使えないので、\_\_\_\_ > > > お金を下ろしておきます。 > > 1. 来週、北海道を旅行するので、 > > > 旅館に予約しておきます。 > > 1. 電車で東京に行くので、 > > > 電車予定を調べておきます。 > > 1. 今度の週末、友達とカラオケに行くので、 > > > 新しい歌を練習しておきます。 > > 1. 週末デートをするので、 > > > 素敵レストランを探しておきます。 > > [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 8 months ago • 100%

13.VII.A [#genki2textbook](https://kbin.social/tag/genki2textbook) [#japanese](https://kbin.social/tag/japanese) [#learnjapanese](https://kbin.social/tag/learnjapanese) VII. まとめの練習 A. Answer the following questions 1. 子供の時に何ができましたか。何ができませんでしたか。 子供の時本が読めれたが、夜は外で一人で遊べませんでした。 1. 百円で何が買えますか。 多分ノートが買えます。 1. どこに行ってみたいですか。どうしてですか。 日本語を勉強するのが有益なので、日本に行ってみたいですよ。 1. 子供の時、何がしてみたかったですか。 時々漫画を書いてみたかったです。 1. 今、何がしてみたいですか。 もっと日本語が上手になりたいです。 1. 一日に何時間ぐらい勉強しますか。 最近、一時間まで二時間ぐらい勉強します。けど、すぐもっと練習したいです。お互い頑張りましょうか。 1. 一週間に何回レストランに行きますか。 最近、一週間に三まで四回に行きます。多分行くすぎると思います。 1. 一か月にいくらぐらい使いますか。 だけ少し使います。 [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 8 months ago • 100%

久しぶりですね。皆さんは元気だと希望します。このごろすごくいそがしいので、すみません皆さんと一緒に話せませんでした。さて、日本語を練習しましょうか。 13.VI.A [#genki2textbook](https://kbin.social/tag/genki2textbook) [#japanese](https://kbin.social/tag/japanese) [#japanesereview](https://kbin.social/tag/japanesereview) A. Look at the following pictures and make sentences as in the example. > > > Ex. Twice a day > 一日に二回食べます。 > > 1. Brush teeth three times a day. 一日三回歯を磨きます。 2. Sleep seven hours a day. 一日七時間寝ます。 3. Study three hours a day. 一日三時間勉強します。 4. Clean room once a week. 一週間一回部屋で掃除する。 5. Do laundry twice a week 一週間二回洗濯をします。 6. Working part-time three days a week. 一週間三回バイトで働きます。 7. I go to school 5 days a week. 一週間五日学校へ行きます。 8. I watch a movie once a month. 一ヶ月一回映画を見ます。 [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

commandline daredevil • 9 months ago • 98%

terminaltrove.com

Terminal Trove showcases the best of the terminal, Discover a collection of CLI, TUI, and more developer tools at Terminal Trove.

Video Game Music daredevil • 9 months ago • 87%

www.youtube.com

イニシエノウタ/デボル · SQUARE ENIX MUSIC · 岡部 啓一 · MONACA NieR Gestalt & NieR Replicant Original Soundtrack Released on: 2010-04-21

Learn Japanese daredevil • 9 months ago • 100%

B. Answer the following questions. Use \~なら whenever possible. > > > Example: > Q: スポーツをよく見ますか。 > A: ええ、野球なら見ます。/ いいえ、見ません。 > > 1. Q: 外国語ができますか。 A: ええ、ちょっと日本語ができます。 2. Q: アルバイトをしたことがありますか。 A: ええ、バイトならしたことがありました。 3. Q: 日本の料理が作れますか。 A: 中国の料理なら作れるが、日本語の料理は作れません。 4. Q: 有名人に会ったことがありますか。 A: ええ、有名人なら会ったことがありました。 5. Q: 楽器ができますか。 A: ええ、バイオリンならできます。 6. Q: お金が貸せますか A: ええ、お金なら貸せます。

Technology daredevil • 9 months ago • 93%

arstechnica.com

On Monday, Mistral AI announced a new AI language model called Mixtral 8x7B, a "mixture of experts" (MoE) model with open weights that reportedly truly matches OpenAI's GPT-3.5 in performance—an achievement that has been claimed by others in the past but is being taken seriously by AI heavyweights such as OpenAI's Andrej Karpathy and Jim Fan. That means we're closer to having a ChatGPT-3.5-level AI assistant that can run freely and locally on our devices, given the right implementation. Mistral, based in Paris and founded by Arthur Mensch, Guillaume Lample, and Timothée Lacroix, has seen a rapid rise in the AI space recently. It has been quickly raising venture capital to become a sort of French anti-OpenAI, championing smaller models with eye-catching performance. Most notably, Mistral's models run locally with open weights that can be downloaded and used with fewer restrictions than closed AI models from OpenAI, Anthropic, or Google. (In this context "weights" are the computer files that represent a trained neural network.) Mixtral 8x7B can process a 32K token context window and works in French, German, Spanish, Italian, and English. It works much like ChatGPT in that it can assist with compositional tasks, analyze data, troubleshoot software, and write programs. Mistral claims that it outperforms Meta's much larger LLaMA 2 70B (70 billion parameter) large language model and that it matches or exceeds OpenAI's GPT-3.5 on certain benchmarks, as seen in the chart below. A chart of Mixtral 8x7B performance vs. LLaMA 2 70B and GPT-3.5, provided by Mistral. The speed at which open-weights AI models have caught up with OpenAI's top offering a year ago has taken many by surprise. Pietro Schirano, the founder of EverArt, wrote on X, "Just incredible. I am running Mistral 8x7B instruct at 27 tokens per second, completely locally thanks to @LMStudioAI. A model that scores better than GPT-3.5, locally. Imagine where we will be 1 year from now." LexicaArt founder Sharif Shameem tweeted, "The Mixtral MoE model genuinely feels like an inflection point — a true GPT-3.5 level model that can run at 30 tokens/sec on an M1. Imagine all the products now possible when inference is 100% free and your data stays on your device." To which Andrej Karpathy replied, "Agree. It feels like the capability / reasoning power has made major strides, lagging behind is more the UI/UX of the whole thing, maybe some tool use finetuning, maybe some RAG databases, etc." ### Mixture of experts ### So what does mixture of experts mean? As this excellent Hugging Face guide explains, it refers to a machine-learning model architecture where a gate network routes input data to different specialized neural network components, known as "experts," for processing. The advantage of this is that it enables more efficient and scalable model training and inference, as only a subset of experts are activated for each input, reducing the computational load compared to monolithic models with equivalent parameter counts. In layperson's terms, a MoE is like having a team of specialized workers (the "experts") in a factory, where a smart system (the "gate network") decides which worker is best suited to handle each specific task. This setup makes the whole process more efficient and faster, as each task is done by an expert in that area, and not every worker needs to be involved in every task, unlike in a traditional factory where every worker might have to do a bit of everything. OpenAI has been rumored to use a MoE system with GPT-4, accounting for some of its performance. In the case of Mixtral 8x7B, the name implies that the model is a mixture of eight 7 billion-parameter neural networks, but as Karpathy pointed out in a tweet, the name is slightly misleading because, "it is not all 7B params that are being 8x'd, only the FeedForward blocks in the Transformer are 8x'd, everything else stays the same. Hence also why total number of params is not 56B but only 46.7B." Mixtral is not the first "open" mixture of experts model, but it is notable for its relatively small size in parameter count and performance. It's out now, available on Hugging Face and BitTorrent under the Apache 2.0 license. People have been running it locally using an app called LM Studio. Also, Mistral began offering beta access to an API for three levels of Mistral models on Monday.

Technology daredevil • 9 months ago • 100%

arstechnica.com

On Monday, Mistral AI announced a new AI language model called Mixtral 8x7B, a "mixture of experts" (MoE) model with open weights that reportedly truly matches OpenAI's GPT-3.5 in performance—an achievement that has been claimed by others in the past but is being taken seriously by AI heavyweights such as OpenAI's Andrej Karpathy and Jim Fan. That means we're closer to having a ChatGPT-3.5-level AI assistant that can run freely and locally on our devices, given the right implementation. Mistral, based in Paris and founded by Arthur Mensch, Guillaume Lample, and Timothée Lacroix, has seen a rapid rise in the AI space recently. It has been quickly raising venture capital to become a sort of French anti-OpenAI, championing smaller models with eye-catching performance. Most notably, Mistral's models run locally with open weights that can be downloaded and used with fewer restrictions than closed AI models from OpenAI, Anthropic, or Google. (In this context "weights" are the computer files that represent a trained neural network.) Mixtral 8x7B can process a 32K token context window and works in French, German, Spanish, Italian, and English. It works much like ChatGPT in that it can assist with compositional tasks, analyze data, troubleshoot software, and write programs. Mistral claims that it outperforms Meta's much larger LLaMA 2 70B (70 billion parameter) large language model and that it matches or exceeds OpenAI's GPT-3.5 on certain benchmarks, as seen in the chart below. The speed at which open-weights AI models have caught up with OpenAI's top offering a year ago has taken many by surprise. Pietro Schirano, the founder of EverArt, wrote on X, "Just incredible. I am running Mistral 8x7B instruct at 27 tokens per second, completely locally thanks to @LMStudioAI. A model that scores better than GPT-3.5, locally. Imagine where we will be 1 year from now." LexicaArt founder Sharif Shameem tweeted, "The Mixtral MoE model genuinely feels like an inflection point — a true GPT-3.5 level model that can run at 30 tokens/sec on an M1. Imagine all the products now possible when inference is 100% free and your data stays on your device." To which Andrej Karpathy replied, "Agree. It feels like the capability / reasoning power has made major strides, lagging behind is more the UI/UX of the whole thing, maybe some tool use finetuning, maybe some RAG databases, etc." ### Mixture of experts ### So what does mixture of experts mean? As this excellent Hugging Face guide explains, it refers to a machine-learning model architecture where a gate network routes input data to different specialized neural network components, known as "experts," for processing. The advantage of this is that it enables more efficient and scalable model training and inference, as only a subset of experts are activated for each input, reducing the computational load compared to monolithic models with equivalent parameter counts. In layperson's terms, a MoE is like having a team of specialized workers (the "experts") in a factory, where a smart system (the "gate network") decides which worker is best suited to handle each specific task. This setup makes the whole process more efficient and faster, as each task is done by an expert in that area, and not every worker needs to be involved in every task, unlike in a traditional factory where every worker might have to do a bit of everything. OpenAI has been rumored to use a MoE system with GPT-4, accounting for some of its performance. In the case of Mixtral 8x7B, the name implies that the model is a mixture of eight 7 billion-parameter neural networks, but as Karpathy pointed out in a tweet, the name is slightly misleading because, "it is not all 7B params that are being 8x'd, only the FeedForward blocks in the Transformer are 8x'd, everything else stays the same. Hence also why total number of params is not 56B but only 46.7B." Mixtral is not the first "open" mixture of experts model, but it is notable for its relatively small size in parameter count and performance. It's out now, available on Hugging Face and BitTorrent under the Apache 2.0 license. People have been running it locally using an app called LM Studio. Also, Mistral began offering beta access to an API for three levels of Mistral models on Monday.

arstechnica.com

On Monday, Mistral AI announced a new AI language model called Mixtral 8x7B, a "mixture of experts" (MoE) model with open weights that reportedly truly matches OpenAI's GPT-3.5 in performance—an achievement that has been claimed by others in the past but is being taken seriously by AI heavyweights such as OpenAI's Andrej Karpathy and Jim Fan. That means we're closer to having a ChatGPT-3.5-level AI assistant that can run freely and locally on our devices, given the right implementation. Mistral, based in Paris and founded by Arthur Mensch, Guillaume Lample, and Timothée Lacroix, has seen a rapid rise in the AI space recently. It has been quickly raising venture capital to become a sort of French anti-OpenAI, championing smaller models with eye-catching performance. Most notably, Mistral's models run locally with open weights that can be downloaded and used with fewer restrictions than closed AI models from OpenAI, Anthropic, or Google. (In this context "weights" are the computer files that represent a trained neural network.) Mixtral 8x7B can process a 32K token context window and works in French, German, Spanish, Italian, and English. It works much like ChatGPT in that it can assist with compositional tasks, analyze data, troubleshoot software, and write programs. Mistral claims that it outperforms Meta's much larger LLaMA 2 70B (70 billion parameter) large language model and that it matches or exceeds OpenAI's GPT-3.5 on certain benchmarks, as seen in the chart below. The speed at which open-weights AI models have caught up with OpenAI's top offering a year ago has taken many by surprise. Pietro Schirano, the founder of EverArt, wrote on X, "Just incredible. I am running Mistral 8x7B instruct at 27 tokens per second, completely locally thanks to @LMStudioAI. A model that scores better than GPT-3.5, locally. Imagine where we will be 1 year from now." LexicaArt founder Sharif Shameem tweeted, "The Mixtral MoE model genuinely feels like an inflection point — a true GPT-3.5 level model that can run at 30 tokens/sec on an M1. Imagine all the products now possible when inference is 100% free and your data stays on your device." To which Andrej Karpathy replied, "Agree. It feels like the capability / reasoning power has made major strides, lagging behind is more the UI/UX of the whole thing, maybe some tool use finetuning, maybe some RAG databases, etc." ### Mixture of experts ### So what does mixture of experts mean? As this excellent Hugging Face guide explains, it refers to a machine-learning model architecture where a gate network routes input data to different specialized neural network components, known as "experts," for processing. The advantage of this is that it enables more efficient and scalable model training and inference, as only a subset of experts are activated for each input, reducing the computational load compared to monolithic models with equivalent parameter counts. In layperson's terms, a MoE is like having a team of specialized workers (the "experts") in a factory, where a smart system (the "gate network") decides which worker is best suited to handle each specific task. This setup makes the whole process more efficient and faster, as each task is done by an expert in that area, and not every worker needs to be involved in every task, unlike in a traditional factory where every worker might have to do a bit of everything. OpenAI has been rumored to use a MoE system with GPT-4, accounting for some of its performance. In the case of Mixtral 8x7B, the name implies that the model is a mixture of eight 7 billion-parameter neural networks, but as Karpathy pointed out in a tweet, the name is slightly misleading because, "it is not all 7B params that are being 8x'd, only the FeedForward blocks in the Transformer are 8x'd, everything else stays the same. Hence also why total number of params is not 56B but only 46.7B." Mixtral is not the first "open" mixture of experts model, but it is notable for its relatively small size in parameter count and performance. It's out now, available on Hugging Face and BitTorrent under the Apache 2.0 license. People have been running it locally using an app called LM Studio. Also, Mistral began offering beta access to an API for three levels of Mistral models on Monday.

Learn Japanese daredevil • 9 months ago • 100%

**II. Complete the dialogue, using the volitional + と思っています。** かな：1. (What do you intend to do for the next holiday?) ::: spoiler answer 来休みはどうするつもりですか？ ::: ジョン: 2. \_\_\_\_\_\_\_\_ ので、3.\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_。 ::: spoiler answer 最近家族をあまり見ないので、会うつもりです。 ::: かな：いいですね。 ジョン：かなさんは？ かな：4.\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_。 ::: spoiler answer 先学期の成績は良くないので、よく勉強するつもりです。 ::: ジョン：そうですか。

Learn Japanese daredevil • 9 months ago • 100%

### 15-2 Volitional Form + と思っています ### **I. Read the first half of the sentences carefully. Then, choose what you are going to do from the list and complete the sentences, using the volitional + と思っています。** * ボランティア活動に参加する * 両親にお金を借りる * 練習する * お風呂に入って早く寝る * 保険に入る * 花を送る 1. 将来病気になるかもしれないので、 ::: spoiler spoiler 保険に入れると思っています。 ::: 2. お金がないので、 ::: spoiler spoiler 両親にお金を借りられると思っています。 ::: 3. 一日中運動して疲れたので、 ::: spoiler spoiler お風呂に入って早く寝られると思っています。 ::: 4. 夏休みに時間があるので、 ::: spoiler spoiler 練習できると思っています。 ::: 5. 母の日に、 ::: spoiler spoiler 花を送れると思っています。 ::: 6. 自転車に乗れないので、 ::: spoiler spoiler ボランティア活動に参加できないと思っています。 :::

Learn Japanese daredevil • 9 months ago • 100%

またちょっと練習しました。多分この練習がもうしたと思ういます。しかし、復習はいい習慣だと思います。 13.V.A Answer the questions as in the example > > > Example > Q: メアリーさんは今朝、コーヒーを飲みましたか。 > A: (O tea X coffee) --\> 紅茶なら飲みましたが、こーひーは飲みませんでした。 > > 1. Q: メアリーさんはバイクに乗れますか。 A: (O bicycle X motorbike) --\> 自転車なら乗れるが、バイクは乗れなかったです。 1. Q: メアリーさんはニュージランドに行ったことがありますか。 A: (O Australia X New Zealand) --\> オーストラリアなら行ったことがあるが、ニュージランドにことがありませんでした。 1. Q: メアリーさんはゴルフをしますか。 A: (O tennis X golf) --\> テニスならするが、ゴルフをしませんでした。 1. Q: けんさんは日本の経済に興味がありますか。 A: (O history X economics) --\> 日本の歴史なら興味があるが、経済が興味がありませんでした。 1. Q: けんさんは彼女がいますか。 A: (O friend X girlfriend) --\> 友達ならいるが、彼女がいませんでした。 1. Q: けんさんは土曜日に出かけられますか。 A: (O Sunday X Saturday) 日曜日なら出かけられるが、土曜日が出かけられません。

Learn Japanese daredevil • 10 months ago • 100%

久しぶりですね〜皆さんは元気だったと希望しますよ。今日はちょっと違い物を試します。/kbinのユーザーはよくスレのほうがmicroblogより好きなので、スレで日本語の練習を作りました。 ところで、今週は新しい仕事を始まったので、最近すごくいそがしいですよ。すごく面白いと思っていました。じゃあ、ちょっと日本語を練習しましょうか？ Respond to the following sentences using \~てみる > > > Example > A: この服は素敵ですよ。 > B: じゃあ、着てみます。 > > 1. A: 経済の授業は面白かったですよ。 B: じゃあ、取ってみます。 1. A: あの映画を見て泣きました。 B: じゃあ、見てみます。 1. A: この本は感動しました。 B: じゃあ、読んでみます。 1. A: このケーキは美味しいですよ。 B: じゃあ、食べてみます。 1. A: 東京は面白かったですよ。 B: じゃあ、旅行してみます。 1. A: このＣＤは良かったですよ。 B: じゃあ、聞いてみます。 1. A: この辞書は便利でしたよ。 B: じゃあ、読んでみます。

Learn Japanese daredevil • 10 months ago • 100%

13.III.B [#genki2textbook](https://kbin.social/tag/genki2textbook) [#japanesereview](https://kbin.social/tag/japanesereview) [#japanese](https://kbin.social/tag/japanese) B. Look at the pictures in [A](https://kbin.social/m/LearnJapanese/p/3316395/13-III-A-genki2textbook-japanesereview-japanese-Describe-the-following-pictures-using-sou-Example-kono-shou-siha-mei-weishisoudesu) and make sentences as in the example. > > > Example > 寿司 -\> 美味しそうな寿司です。 > > 1. ケーキ 甘そうなケーキです。 2. カレー 辛そうなカレーです。 3. 服 古そうな服です。 4. 先生 厳しそうな先生です。 5. 時計 新しそうな時計です。 6. ヤクザ 怖そうなヤクザです。 7. 男の人 寂しそうな男の人です。 8. 女の人 嬉しそうな女の人です。 9. おじいさん 元気そうなおじいさんです。 10. おばあさん 意地悪そうなおばあさんです。 11. 女の人 優しそうな女の人です。 12. 弁護士 頭がよさそうな弁護士です。 13. 学生 眠そうな学生です。 14. セーター あたたかそうなセーターです。 15. 子供 悲しそうな子供です。 [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 10 months ago • 100%

13.III.A [#genki2textbook](https://kbin.social/tag/genki2textbook) [#japanesereview](https://kbin.social/tag/japanesereview) [#japanese](https://kbin.social/tag/japanese) Describe the following pictures using \~そう。 > > > Example この寿司は美味しそうです。 > > 1. ケーキ (sweet) - このケーキは甘そうです。 2. カレー (spicy) - このカレーは辛そうです。 3. 服 (old) - この服は古そうです。 4. 先生 (strict) - この先生は厳しそうです。 5. 時計 (new) - この時計は新しそうでs。 6. ヤクザ - このヤクザは怖そうです。 7. 男の人 - (lonely) この男の人は寂しそうです。 8. 女の人 - (glad) この女の人は嬉しそうです。 9. おじいさん (energetic) - このおじいさんは元気そうです。 10. おばあさん (mean) - このおばあさんは意地悪そうです。 11. 女の人 (kind) - この女の人は優しそうです。 12. 弁護士 (smart) - この弁護士は頭がやさそうです。 13. 学生 (sleepy) - この学生は眠そうです。 14. このセーターはあたたかそうです。　 15. 子供 (sad) - この子供は悲しそうです。 [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 10 months ago • 100%

13.II.B [#genki2textbook](https://kbin.social/tag/genki2textbook) [#japanesereview](https://kbin.social/tag/japanesereview) [#japanese](https://kbin.social/tag/japanese) Answer the following questions and add reasons for your answer. > > > Example: > Q: 日本の生活は楽しいですか。 > A: はい、楽しいです。友達がたくさんいるし、みんなは親切だし。 > > 1. Q: このごろ忙しいですか。 A: はい、忙しいです。よく平日は日本語を勉強するし、/kbinの雑誌を養うし、最近新しい仕事に準備しているし、などです。このごろあまり時間がありません。残念で、まだもっと物をしたいので。 1. Q: 今、幸せですか。 A: はい、幸せです。日本語がまだ上手じゃなくて、けど今は時々悪くないと思うし、いいプロジェクトを働くし、などです。 1. Q: 来学期も日本語の授業を取りますか。 A: いいえ、授業が卒業したし、今は一人で日本語を勉強しています。 1. Q: 日本に住みたいですか。 A: 絶対住みたいですよ。しかし、仕事だし、近い将来に住めれません。残念ですよ。。。 1. Q: 日本語の授業は大変ですか。 A: あまり大変じゃないです。日本語は面白くて、綺麗な言語だと思うし。日本語のほうが英語より好きです。それにアニメが見られて、わかられるのがすごくエキサイティングだと思うし。ゲームと音楽も。 [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 10 months ago • 100%

L13 [#genki2](https://kbin.social/tag/genki2) [#japanese](https://kbin.social/tag/japanese) [#japanesepractice](https://kbin.social/tag/japanesepractice) [#kanjipractice](https://kbin.social/tag/kanjipractice) [#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 10 months ago • 100%

13.II.A [#genki2textbook](https://kbin.social/tag/genki2textbook) [#japanesereview](https://kbin.social/tag/japanesereview) [#japanese](https://kbin.social/tag/japanese) Answer the following questions using \~ し \~ し。Examine the ideas in the cues and decide whether you want to answer in the affirmative or in the negative. > > > Example > Q: 日本に住みたいですか。 > A: (物価が高いです。人がたくさんいます。) > \--\> 物価が高いし、人がたくさんいるし、住みたくないです。 > > 1. 今週は忙しいですか。 (試験があります。宿題がたくさんあります。) 宿題がたくさんあるし、今週は忙しいです。 2. 新しいアパートはいいですか。 (会社に近いです。静かです。) 会社に近いだし、静かだし、新しいアパートはいいです。 3. 経済の授業を取りますか。 (先生は厳しいです。長いレポートを書かなきゃいけません。) 先生は厳しいだし、長いレポートを書かなきゃいけないし、経済の授業を取りません。 4. 旅行は楽しかったですか。 (食べ物が美味しくなかったです。言葉が分かりませんでした。) 食べ物が美味しくなかっただし、言葉が分かりなかったし、旅行は楽しくなかったです。 5. 今晩、パーティーに行きますか。 (風邪を弾いています。昨日もパーティーに行きました。) 風邪を弾いているし、昨日もパーティーに行ったし、今晩パーティーに行きません。 6. 日本語の新聞が読めますか。 (感じが読めません。文法が分かりません。) 感じが読めないし、文法がわからないし、日本語の新聞が読めません。 7. 一人で旅行ができますか。 (日本語が話せます。もう大人です。) 日本語が話せるし、もう大人だし、一人で旅行ができます。 8. 田中さんが好きですか。 (嘘を付きます。約束を守りません。) 嘘を付くし、約束を守らないし、田中さんが好きじゃないです。 単語を復習しなければいけません。。。最近すごく忙しいし、面倒くさいですね。でも、しょうがないですよね。まだ頑張りますよ。 [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

markets.businessinsider.com

The key to ThinkCERCA's approach is the incorporation of linguistic principles. Designed to provide adolescent students with instruction related to phonetic concepts and decoding, the program follows a science of reading approach in providing systematic and explicit instruction to fill in foundational gaps that secondary struggling readers will not close on their own or in a Language Arts classroom.

Learn Japanese daredevil • 10 months ago • 100%

13.I.A [#genki2textbook](https://kbin.social/tag/genki2textbook) [#japanese](https://kbin.social/tag/japanese) [#japanesereview](https://kbin.social/tag/japanesereview) A. Change the verbs into potential forms 1. 話す - 話せる 2. する - できる 3. 行く- 行ける 4. 寝る - 寝られる 5. 来る - 来られる 6. 見る - 見られる 7. 辞める - 辞められる 8. 分かる - 分かれる 9. 飲む - 飲める 10. 待つ - 待てる 11. 泳ぐ - 泳げる 12. 働く - 働ける 13. 編む - 編める ちゃんと学びたいので、今日は前課を復習しました。来週、筆跡とヒアリングの練習するつもりです。ここで練習しないかも知れないんです。じゃあ、また来週ですね。 [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 10 months ago • 100%

皆さん、すみません。めっちゃ忙しいので、最近練習ができなかったです。明日は練習したいつもりです。また明日ね。 [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

news.yahoo.com

Discovery helps reveal how a long-lost empire used multiculturalism to achieve political stability

Learn Japanese daredevil • 10 months ago • 100%

最近の課がちょっと難しいとまだ思うので、今日はげんきの教科書を復習するつもりです。別にcomprehensible inputも勉強するつもりです。だから今日はげんきのワークブックを勉強しないかもしれません。多分皆さんも勉強したくて、下に日本語comprehensible inputのリンクがあります。さて、お当該頑張りましょうね。 [https://kbin.social/m/LearnJapanese/t/621990/Japanese-Comprehensible-Input-YouTube-channels#comments](https://kbin.social/m/LearnJapanese/t/621990/Japanese-Comprehensible-Input-YouTube-channels#comments) [\#japanese](https://kbin.social/tag/japanese) [#learnjapanese](https://kbin.social/tag/learnjapanese) [#comprehensibleinput](https://kbin.social/tag/comprehensibleinput) [#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Learn Japanese daredevil • 10 months ago • 100%

Hello friends. While reading and writing are great ways to study Japanese, listening comprehension and speaking are also important aspects to consider as well. As such, this post will serve to provide a list of YouTube channels for the purpose of comprehensible input. I will update this post periodically over time. [いろいろな日本語](https://www.youtube.com/@iroironanihongo) ========== A channel that uses hand-drawn pictures to narrate lessons while speaking. This channel also explains the plot to anime, and various kanji. Subtitles are only available in Japanese. Furigana is not provided. The channel is relatively new, so there is less content than some of the other channels I'll be linking. However, the creator speaks slowly, clearly, and repeats himself to help the viewer. This channel is useful for beginners. [Comprehensible Japanese](https://www.youtube.com/@cijapanese) ========== A channel that focuses on digital, hand-drawn, and live examples to narrate while speaking. Subtitles are in written in kanji and kana--furigana is not provided. This channel has been around longer than the previous channel, meaning there will be more content to consume. A bit more challenging than the previous channel as Yuki speaks at a more natural pace and does not repeat herself. [Daily Japanese with Naoko](https://www.youtube.com/@DailyJapanese) ========== A channel focused on speaking on day-to-day topics such as weather, traveling, daily tasks, etc. This channel has less videos to watch than the previous one. However, Naoko speaks at a more natural pace than the previous two, so this is probably recommended for intermediate to advanced learners. Additionally, she subtitles her videos in Japanese--this includes kana, kanji, and furigana. This will be useful if you wish to practice reading while listening simultaneously. [Nihongo-Learning](https://www.youtube.com/@nihongo-learning7582) ========== This channel focuses on grammar and how Japanese is used in daily life, similar to the previous channel. Lessons occasionally cover kanji and kana lessons, with supplemental visual aids. Yuta often creates videos while out on walks, so this also has the benefit of taking in some sights while learning. Subtitles are largely in kanji and kana. Occasionally, vocabulary is introduced in their kanji and kana forms. Yuta, the creator, takes his time to repeat phrases so that the viewer can practice both listening and imitating his pronunciation. There are nearly 100 videos, and I would say this is a very useful resource for beginners. [Japanese with Shun](https://www.youtube.com/@JapanesewithShun) ========== This channel covers a wide variety of topics, ranging from fashion, to travels, daily life, food, conversations with friends, listening exercises, and more. This channel also includes podcasts targeted at beginners. Shun also includes a brief description of how difficult the language content may be. These descriptions range anywhere from N5 --\> N2, with some descriptions used in relation to Genki (the podcasts in particular). Probably the most useful for those who wish to get a feel for their listening comprehension. Also useful for more intermediate to advanced learners. In the videos, you'll find kanji and kana. However, furigana is not provided (at least that I've seen so far). This channel is also has the largest library of content, containing 507 videos at the time of this post. [もしもしゆうすけ](https://www.youtube.com/@moshimoshi.yusuke) ========== This channel covers topics at convenience stores, recorded conversations with friends and acquaintances, dining at restaurants, daily life, and more. Yusuke's content may be on the more intermediate to advanced side of content listed here, as he speaks at a pace more suited for natural dialogue. Furthermore, as Yusuke likes to walk during some of his monologues, there may be added difficulty in practicing listening comprehension. This may prove useful for those who wish to listen to Japanese outside of an "idealistic setting" where some content creators are sitting in a noise-insulated room and can focus entirely on the clarity of their pronunciation for the viewer. These videos provide subtitles mostly in kana, with occasional instances of kanji and their associated furigana. English subtitles are also provided. [あかね的日本語教室](https://www.youtube.com/@Akane-JapaneseClass/videos) ========== * Travel vlog * Speaks clearly + slowly * Subtitles [YUYU](https://www.youtube.com/@Akane-JapaneseClass/videos) ========== * Wide variety of topics * Speaks quickly * Probably \~N2 level, recommended for more experienced learners [Japanese with Ken](https://www.youtube.com/@JapanesewithKen) ========== [Bite size Japanese Podcast](https://youtube.com/@the_bitesize_japanese_podcast?si=Q4LAjbC09KVmWUsU) ========== [tsubakiclass](https://www.youtube.com/@tsubakiclass) ========== [yukiijapanese00](https://www.youtube.com/@yukijapanese00) ========== [japarrot](https://www.youtube.com/@Japarrot_LetsLearnJP) ==========

yaledailynews.com

Since it was first offered in spring 2018, American Sign Language at Yale has grown to be the third largest language option, with over 200 students enrolled in ASL classes this semester.

Resident Evil 4 Remake has been crowned PlayStation Game of the Year at The Golden Joysticks 2023 powered by Intel. Capcom's third Resident Evil remake was released in March of this year and took players back to rural Spain to confront the mysterious, and deadly, Los Illuminados cult - 18 years after we originally did on the PlayStation 2. Fans clearly loved revisiting the classic survival horror game as it managed to beat out other games in the category including Final Fantasy 16, Street Fighter 6, and Star Wars Jedi: Survivor. The other Golden Joystick Awards 2023 nominees in this category can be found below: * Final Fantasy 16 * **Resident Evil 4 Remake (winner)** * Street Fighter 6 * Humanity * Armored Core 6: Fires of Rubicon * Star Wars Jedi: Survivor

www.yahoo.com

Final Fantasy 7 Rebirth has won the Most Wanted Game category at the Golden Joystick Awards 2023 powered by Intel. Due in February of next year, Square Enix's much-anticipated follow-up marks the second part of a planned three-part modern-day reimagining of its 1997 source material. Hot on the heels of 2020's Final Fantasy 7 Remake, Final Fantasy 7 Rebirth extends the legendary story beyond Midgar – with a recent trailer teasing familiar spots such as Cid's Rocket Town, Red XIII's Cosmo Canyon, and the indelible Gold Saucer theme park. Add flashes of an introspective Sephiroth, Jenova, Junon Harbor and that thoroughfare-dominating parade, and it's easy to see why people are looking forward to this one, and, indeed, why it's come out on top of this year's Golden Joysticks' Most Wanted category. Throw in the teasiest of Emerald Weapon teasers, and… yeah, February 29, 2024 really can't come soon enough. Full credit to Final Fantasy 7 Rebirth rising to the top of its 20-game-strong category. Here's the full list of [Most Wanted Game Golden Joystick 2023 nominees](https://www.gamesradar.com/golden-joystick-awards-2023-nominations/), and as you can see Final Fantasy 7 Rebirth beat 19 other games to come out on top: * Death Stranding 2 * Star Wars Outlaws * **Final Fantasy VII Rebirth (Winner)** * Tekken 8 * Vampire: The Masquerade - Bloodlines 2 * S.T.A.L.K.E.R. 2: Heart of Chornobyl * Hades 2 * Fable * Hollow Knight: Silksong * EVERYWHERE * Frostpunk 2 * Ark 2 * Metal Gear Solid Δ: Snake Eater * Persona 3 Reload * Bulwark: Falconeer Chronicles * Suicide Squad: Kill the Justice League * Pacific Drive * Black Myth: Wukong * Banishers: Ghosts of New Eden * Warhammer Age of Sigmar: Realms of Ruin Discover the [best games of 2023](https://www.gamesradar.com/best-games-2023/) at the best prices by checking out the [Golden Joystick Awards Steam sale page](https://store.steampowered.com/sale/goldenjoystickawards)

OP: [@yukijoou](https://lemmy.blahaj.zone/u/yukijoou): > > > For those who may not know, the IPA (international phonetics alphabet) is widely used for writing out how words are spoken. It’s very useful for linguists writing research papers, and for people looking to learn new languages! As I wasn’t satisfied with most IPA keyboards available, and wanted something that integrated well with fcitx, which I already have to use for japanese input, I re-implemented parts of the [SIL IPA keyboard](https://help.keyman.com/keyboard/sil_ipa/1.8.6/sil_ipa). It’s not a one-to-one recreation (yet), because I needed somthing now rather than later, and took some shortcuts to put in all the features I personally needed, but it should be good enough for doing broad transcription of RP English. It should also be fairly trivial to hack in support for most character combinations. Feel free to check out the [git repo](https://git.kemonomimi.gay/yukijoou/fcitx5-ipa-sil)! > >

Learn Japanese daredevil • 10 months ago • 100%

To see related [#Japanese](https://kbin.social/tag/Japanese) language-learning content, consider checking out [@Japanese](https://kbin.social/m/japanese/microblog). While [@Japanese](https://kbin.social/m/Japanese) will include language-learning content, it will also include content beyond simply learning Japanese itself. This may prove useful for finding resources and content for written and spoken immersion. [@Japanese](https://kbin.social/m/Japanese) may also be updated to include content related to more general Japanese-language content as well. Regarding the [#microblog](https://kbin.social/tag/microblog) section found here in [@LearnJapanese](https://kbin.social/m/LearnJapanese), you may use this space to complete Japanese language-learning exercises, ask questions, provide answers, or find others that are inexperienced and experienced alike. However, please note that **users from Mastodon will only have their posts federated to [@LearnJapanese](https://kbin.social/m/LearnJapanese) if [#learnjapanese](https://kbin.social/tag/learnjapanese) or [#japanesepractice](https://kbin.social/tag/japanesepractice) is the first tag embedded in your post**. The way /kbin currently works is that by using [#Japanese](https://kbin.social/tag/Japanese) as the first tag in your post, your post will be sent to [@Japanese](https://kbin.social/m/japanese/microblog) instead. This section may also be useful for posts that you may feel don't necessitate its own thread. In that sense, this area can act as a "daily discussion hub" akin to the megaposts found on Reddit. That being said, though this is a space for questions and whatever else--you're still permitted and encouraged to post questions among other things as threads too. We look forward to seeing beginners and veterans alike engaging in discussion with one another. お当該頑張りましょう！ Attached below is a link to a list of recommended resources. [https://kbin.social/m/LearnJapanese/t/14796/Useful-resources](https://kbin.social/m/LearnJapanese/t/14796/Useful-resources) Please feel free to add a reply if you have a suggestion, or have critique regarding any resources I have provided. If one is providing critique, please also include an alternative. I am not perfect, but I am open to suggestions. By teaching me, you help future users that stop by to read our conversations. Thanks, and best wishes on your Japanese-language learning journey. [\#LearnJapanese](https://kbin.social/tag/LearnJapanese)

Moving to: m/AskMbin! daredevil • 10 months ago • 100%

First one that comes to my mind is having to travel with an NPC and our walk/run speeds don't match.