NotebookLM: The AI-力／強力にするd 熟考する／考慮する 道具 I wish I had in college
When we talk about AI 事業／計画（する）s from Google, the conversation usually 回転するs around Gemini.
As Google's most 普及した and accessible AI feature, it's hard to use any of the tech 巨大（な）'s 製品s and services without running into the generative AI chatbot.
However, Gemini isn't just a chatbot. It 力／強力にするs other AI 道具s, 含むing NotebookLM. NotebookLM is one of the best AI 道具s anywhere, and wh ile I use it sporadically now, I wish I had 接近 to it in university.
NotebookLM's ability to 生成する 要約s, explanations, and answers from uploaded 文書s is extraordinarily useful for anyone who juggles 文書s scattered across 多重の places and 文書 types.
While it's not perfect, I think it's one of the best 資産s a college student can use in their 熟考する／考慮するs.
For me, a History 卒業生（する） who had to juggle more 文書s than I could 過程 at one time, it would have been a powerful assistant. Here's why.
NotebookLM can 分析する 多重の 文書 types
No need to flip 支援する and 前へ／外へ between tabs
Much of my 研究 as a student was in physical マスコミ. This time-消費するing 過程 was rewarding, but the 欠如（する） of 数字表示式の shortcuts meant I erred on the 味方する of 警告を与える when taking 公式文書，認めるs.
反して in a 数字表示式の PDF I could bookmark pages for later, or 追加する a comment with a 選び出す／独身 click, my 言及／関連s for physical マスコミ were usually 名簿（に載せる）／表（にあげる）s of page numbers with one- or two-word descriptions.
This worked, but it meant a lot of wasted time going 支援する and 前へ／外へ to 二塁打-check whether a 公式文書，認める was 関連した. Many of these 言及／関連s did turn out to be irrelevant, but I had to waste time scouring 調書をとる／予約するs to check.
と一緒に my physical マスコミ and 関連した 公式文書，認めるs were class 公式文書，認めるs, PDFs, 数字表示式の 調書をとる／予約するs, and website links.
It was a mess of different 文書 types, and I spent hours sorting them all into text 文書s for 平易な 言及／関連.
NotebookLM could have 除去するd the need for this 過程 完全に. Upload a 文書 with a 両立できる とじ込み／提出する type, and NotebookLM can 言及／関連 all of them when you ask it a question.
For example, if I were looking for （警察などへの）密告，告訴（状） about a topic, NotebookLM can check 音声部の とじ込み／提出するs, scanned PDFs, websites, and 文書s for an answer.
Not needing to spend hours sorting all my 公式文書，認めるs into one 文書 would have saved me hours of 行政の work.
I don't need to worry about NotebookLM hallucinating content, as in this シナリオ, I am using it to point me に向かって 公式文書，認めるs that I've already 立証するd as authentic.
NotebookLM lets you visualize data how you want
A 判型 for everyone
When you have thousands of words across 音声部の, ビデオ, and text 文書s, it's hard to take it all in at a ちらりと見ること.
Perhaps you prefer to listen to an 音声部の 要約 or create a mind 地図／計画する of the 重要な elements of your 公式文書，認めるs. NotebookLM can create an 音声部の overview, ビデオ overview, mind 地図／計画する, 熟考する／考慮する guide, 要点説明 doc, FAQ, and timeline from your 文書s.
Depending on your 文書s, you may find some of these 判型s more useful than others.
As a student juggling 多重の 文書s, I would have 設立する the 熟考する／考慮する guide 判型 特に useful.
NotebookLM 生成するs a short 質問（する）, a 一連の essay-判型 questions, and a glossary of 重要な 条件.
When I started a new 事業／計画（する）, I 定期的に felt 圧倒するd by the 量 of （警察などへの）密告，告訴（状） at my 処分. These 誘発するs would have helped me 増強する my understanding of my sources, so when I （機の）カム to 令状 up my 研究, I had a stronger idea where to start.
I'm いっそう少なく keen on the 音声部の or ビデオ 判型s. While I could see the 音声部の 判型 存在 useful for people who struggle to 吸収する （警察などへの）密告，告訴（状） visually, it's much harder to 位置／汚点／見つけ出す mistakes made by NotebookLM.
Any 道具 力／強力にするd by generative AI is 有能な of hallucinating sources and （警察などへの）密告，告訴（状）, and NotebookLM 向こうずねs when it 言及／関連s where it has pulled 要約s from.
The 音声部の and ビデオ 判型s do not 明確に 示す where they pull （警察などへの）密告，告訴（状） from.
NotebookLM makes it 平易な to 二塁打-check its （警察などへの）密告，告訴（状）
Good for 立証するing （警察などへの）密告，告訴（状） and その上の 研究
One of the 推論する／理由s I'm glad 道具s like Gemini and ChatGPT weren't around when I was in college is their 傾向 to hallucinate （警察などへの）密告，告訴（状）.
While we all know that we should 立証する everything 設立する on the internet, it's 平易な to skip this step when you're in a 急ぐ.
Generative AI chatbots often put links to their sources at the end of 要約s, but these often 要求する you to 追跡（する） through the entire 文書 for the exact 言及／関連.
NotebookLM 追加するs a source link after each 声明 in a 要約. Click this link, and it'll take you 直接／まっすぐに to the section of the 文書 where it pulled the （警察などへの）密告，告訴（状） from.
After uploading a 文書 to NotebookLM, I can check every 選び出す／独身 声明 in minutes.
The only problem is that while NotebookLM lets you save its 要約s to a separate 公式文書，認める, you can't 直接／まっすぐに edit these 生成するd 返答s. You can copy the text into a 公式文書，認める for editing yourself, but this 除去するs the source links.
にもかかわらず this 問題／発行する, NotebookLM's citations not only 補償する for one of the biggest failings of generative AI, but also help you 研究 a 文書 yourself.
If I had 接近 to this feature in university, I could have understood the 状況 of a 文書 in minutes, and had pre-生成するd 開始する，打ち上げるing off points for その上の 研究.
NotebookLM makes it hard to lose 価値のある 文書s
It can 要約する the 蓄積するd 公式文書，認めるs of an entire university career
Over the course of my college life, I 蓄積するd hundreds of 文書s, from PDF copies of 調書をとる／予約するs to pages of Word docs 含む／封じ込めるing class 公式文書，認めるs to 音声部の recordings of guest lectures.
As I built my pyramid of knowledge over the years, many of these 文書s were lost or buried in forgotten folders.
Much of this （警察などへの）密告，告訴（状） was 価値のある, and I would frequently waste time digging for a half-remembered 公式文書，認める or paper of relevance to my 現在の work years later.
If NotebookLM were around in my first year at college, I could have chucked every 選び出す／独身 文書 I own into the app.
NotebookLM's separate notebooks would have let me sort them by 支配する, but the result is akin to a personal librarian.
NotebookLM can answer queries with sources from 文書s years old, with links so I can 長，率いる 支援する and check them.
I shudder to think of how many 価値のある 公式文書，認めるs and papers I lost 予定 to my poor organization. NotebookLM could have made sure no 文書 was wasted.
NotebookLM encourages you to do the work yourself
There is plenty of 合法的 批評 leveled at the use of AI in education. From ChatGPT creating 完全にするd essays for students to Gemini hallucinating sources, there is 証拠 that AI can 本気で 損失 students' education.
However, generative AI is here to stay, so we must learn to use it responsibly and identify where it can help, not 妨げる us.
As a student, I wasted hours 成し遂げるing basic 組織の 仕事s that did not serve to help my education.
道具s like NotebookLM do the 組織の work for you, then 供給する helpful jumping-off points for your own 研究.
I can see how NotebookLM can be 乱用d to skip tedious 研究 仕事s, but for anyone taking their 熟考する／考慮するs 本気で, it's an incredibly powerful 資産. If only I were able to use it.