• Google released Nano Banana Pro (gemini-3-pro-image-preview), a new AI image generation model.
• Nano Banana Pro excels in general intelligence, tool use, and creating complex scenes with less hallucination.
• It can use Google Search and Maps to gather data and reason visually through "thought images."
• Pushing infographic and map generation to new frontiers, enabling visually rich and factually accurate images.
• Can create detailed photorealistic images based on complex, multi-element prompts.
• Not reliable for electrical circuit designs yet, as it may produce erroneous circuit diagrams.
• Human intelligence still surpasses it in domain-specific tasks like accurate circuit design.
• Nano Banana Pro is seen as a game changer in practical, production-ready AI image generation.
• Tool use enables more factually accurate and data-driven generated images than previous models.
• Benchmarking AI image generation quality still needs development for production use assessment.
• The community is impressed with Nano Banana Pro's nuanced prompt following and image creation capabilities.

Levels of understanding genres: - 0) No understanding Like the song, never heard anything like it before, but no idea about anything. - 1) Basic Understanding Knowing a bit about the name of the genre and subgenres, but you can be wrong. - 2) Immersion Really dive into subgenres and flavors of the main genre... Also a bit of history about the genre. Research. - 3) Structure Breaking down the structure of the tracks in the genre. For example through DAW. Basically first-principles thinking.

To level 1: Song Analyzer tools (for example musicstax or AI). The author recommends everynoise.com too to gain a basic understanding of genres.

To level 2: Find similar songs and artists for your playlists with that genre. Perhaps playlists. Important to understand the origin of the genre.

Research: Theorization, Synthesis, etc.

Learning: Acquisition and Retention of Knowledge or Application of Skill

Both: When there is need of both and/or when research techniques don't give the necessary mastery quick enough for the material; too dense (i.e., neuroscience book)

( ~ 6:25-end )

Steps for designing a reading plan/list: 1. Pick a topic/goal (or question you want to answer) & how long you want to take to achieve this. 2. Do research into the books necessary to achieve this goal. Meta-learning, scope out the subject. The number of books is relative to the goal and length of the goal. 3. Find the books using different tools such as Google & GoodReads & YouTube Recommendations (ChatGPT & Gemini are also useful). 4. Refine the book list (go through reviews, etc., in Adlerian steps, do an Inspectional Read of everything... Find out if it's truly useful). Also order them into a useful sequence for the syntopical reading project. Highlight the topics covered, how difficult they are, relevancy, etc. 5. Order the books (or download them)

Reminds me a bit of Scott Young's Metalearning step, and doing a skill decomposition in van Merriënboer et al.'s 10 Steps to Complex Learning

I have always misinterpreted this idea.

I thought it referred to the rumination of ideas... Don't put notes you just made in it (from any source, like reading a book), instead let it ruminate.

I was wrong. I realized this when chatting with Gemini Advanced.

But either way, the DeepL translation of this paragraph: "Slip box as a clarification pit - don't just put clarified notes in it. Postponing reviewing and deciding - also a question of speed."

It is moreso related to the idea of fleeting notes and unprocessed ideas. Have to think a bit more about what Luhmann meant. Maybe @chrisaldrich knows something.

驚喜到吃手手

改天來如法炮製，看如何下prompt讓它儘量用全漢的台文輸出，減少羅馬拼音，除非基本字型出不來的字。這只是我的個人偏好。

太興奮了。我會希望AI用台文書寫，儘量減少tailo或POJ。以後來研究這個system prompt怎麼下。

AI

Taigi

Chhit Am-goat · 《 用台文直接共 AI 討台文內容 》 昨昏有朋友問講 AI 出無按家己向望彼號型。窮實佗加強 prompt 佗會使，抑是共欲指定 AI 照你欲--ê 來輸出个規定，囥佇 System Instructions 內底，攏會使--得。 下跤圖--ni̍h 是 ka 囥佇 Gemini-pro-1.5 開講區上頂懸个 System Instructions 內底，閣直接叫伊輸入台文文章，完全無閣 upload 任何物仔，足簡單个操作。 輸出愛檢查，家己愛改，毋過完成度是不止仔懸--矣，而且直接佗出台文內容，毋免閣過翻譯。 Prompt 抑是 System Instructions，用英文效果比中文加足好，因為原底遮个 LLM (大言語模型）佗攏用英文訓練--ê。 罔參考，會使按家己需要閣改，內底个例攏會換--得，例个長度小可長，效果較好。 若想欲輸出 全 POJ、全 TL、抑是全漢，會使改內底个規則佮例，試驗看覓。 《System Instructions 》 You are a linguist and a great translator between Taigi and English. Translate English text into Taigi I give you, and vise versa．Or chat with me in Taigi. For prepositions, conjunctions, particles and exclamations, must use POJ. For NERs such as country, place or human names keep the original name.English. Be sure to make the Taigi translation more Taigi-like and differentiate from Chinese, using Taigi words and sentences structures as possible, restructuring sentence is allowed. note 1: Taigi text is a mix of Hanji characters and Latin characters with phonetic component on the top. note 2: Example of Taigi word consist of Latin letters named POJ(Pe̍h-ōe-jī/POJ) sch as Tâi-gí，má-to͘h, té-thah. Please display the phonetic component and ‘-‘ between subwords accordingly. note 3: the uniqe POJ elements are: ch, cch, o͘, eng, ek, oa, ⁿ note 4: Do use POJ for prepositions, conjunctions, particles and exclamations. Output as format&example. <format&example>

• Leonardo da Vinci ê 無限好玄

Leonardo da Vinci 是文藝復興時期 ê 代表人物, 伊 ê 人生 kah 作品 lóng 浸透彼个時代 ê 精神。伊 tī 1452 年出世 tī Italy ê Vinci, 伊 ê 天才 hāⁿ(迒) 藝術、科學、工程 koh 濟濟 ê 領域, lóng 是 hō͘ 伊對智識 ê 熱狂走chông 來 lu(攄) leh 行。

伊 tī 藝術 ê 成就, 親像神秘 ê Mona Lisa kah 經典 ê 上尾 ê 暗頓, 展現伊 tùi 人類表情 kah 親像 sfumato hām 明暗對比法遮个先驅技術 ê 把握。 m̄-koh , Da Vinci ê 才調 m̄-nā tī 畫布頂懸; 伊是一个走 tī 時代進前 ê 發明家, 想出來像飛行機器 kah 太陽能這號物。

伊 ê 簿仔紙展示伊無 kā 藝術 kah 科學分--開 ê 頭殼, 內底滿滿是 chham 觀察、 chham 想像相透濫 ê 素描。Da Vinci ê 哲學是「研究藝術 ê 科學。研究科學 ê 藝術... 認捌 tio̍h 萬物 lóng 連連鬥陣」, 這反映伊相信所有學科 lóng 是 kap(合)做伙--ê。

伊 tī 藝術 ê 成就, 親像神秘 ê Mona Lisa kah 經典 ê 上尾 ê 暗頓, 展現伊 tùi 人類表情 kah 親像 sfumato hām 明暗對比法遮个先驅技術 ê 把握。 m̄-koh , Da Vinci ê 才調 m̄-nā tī 畫布頂懸; 伊是一个走 tī 時代進前 ê 發明家, 想出來像飛行機器 kah 太陽能這號物。

Gemini-1.5-pro: https://aistudio.google.com/