Wonderful Tech @Taiwan

李志銘 也來談談KMT版的小橘書 民國六十八年（1979）在國民黨主政下，由國防部總政治作戰部編印的《揭穿中共統戰陰謀答問》 這本小冊子裡雖然只有短短7頁8題，但卻字字珠璣，尤其放到今天來看，更是完全凸顯了中國國民黨從反共到舔共的事實。 . 譬如其中第三題問：：國共會有兩度合作、一次和談的歷史，爲什麼不能再談？ 答：我們就因爲過去每次都上了中共的當，最後失去了大陸，所以現在不能再和他們談了。 第一次是民國十三年的「容共」。中共聲稱服膺三民主義，參加國民革命，但他們却發展自己的組織，分化革命陣營，使北伐革命幾乎失敗。 第二次在民國廿六年的所謂「聯合抗日」。中共趁日本向我國侵略，聲稱接受政府領導，擁護三民主義，取消叛亂政權和紅軍名義，共同抵抗日本。實際上他們却擴張自己勢力，並勾結日本偷襲國軍，打下了他們擴大叛亂的基礎。 最後一次是戰後的「國共和談」。經過美國的調處，中共以邊談邊打的策略，以「談判」保護自己，以軍事行動擴張地盤，並在此談談打打的過程中，挑撥中美關係，動搖我民心土氣，最後終於竊據大陸。我們有了這些經驗，知道和談就是解除自己武裝向他們投降，所以再不能和中共談判了。 . 又譬如其中第七題問：中共現在已不講「解放臺灣」「血洗臺灣」，而講「回歸祖國、完成統一」是不是他們已放棄使用武力？ 答：共產黨最善於在名詞上玩魔術，我們千萬不能上當，一定要找出其所用名詞的真正涵義。基本上，「解放臺灣」已訂入了中共的「憲法」，目標已定，正如中共自己所說的，十年、二十年，甚至一百年、一千年，總要達到目標。所以併吞臺灣這個目標是不會改變的。 . . 《揭穿中共統戰陰謀答問》全書PDF電子檔下載 https://reurl.cc/6b5zvM

台積電的關鍵優勢與不可取代性 台積電是全球半導體產業的關鍵角色，其領先的製程技術與產能布局，使其成為全球科技發展的核心驅動力。台積電董事長暨總裁魏哲家在台大EMBA百川講座中，以幽默風趣的方式，闡述了台積電的不可取代性，並點出其最新技術無法輕易被移轉至其他國家。 全球產業依賴台積電 魏哲家指出，台積電的存在對全球經濟至關重要，若沒有台積電，蘋果手機將無法更新，甚至電視、冰箱、汽車等日常用品的生產也會受到嚴重影響。他強調：「如果沒有台積電，全球經濟將陷入停滯。」更進一步，他表示，2026年後的自動駕駛技術也將因台積電的缺席而消失，顯示出台積電對科技未來發展的關鍵影響力。 台積電技術無法輕易複製 市場曾擔憂台積電赴美設廠後，是否會導致台灣失去技術優勢。然而，魏哲家指出，建立一條新的生產線需要2.5年，但前提是必須具備充足的土地、水電及人才，並擁有先進的技術能力。此外，若要建立完整的3奈米製程生態系統，至少需要5年時間。即使其他國家擁有理想的基礎設施，仍難以複製台積電的成功模式。 美國設廠挑戰重重 美國亞利桑那州廠的建設進度不如預期，魏哲家幽默地形容：「在亞利桑那州，我一把鼻涕、一把眼淚，受盡各種訓練。」他點出了三大挑戰： 1. 基礎建設不足 當地缺乏半導體廠建設經驗，即使美國擁有知名的半導體公司，但多年來人才流失嚴重，導致台積電不得不從德州調派建築工人來支援。 2. 法規與行政效率 在台灣，政府與台積電共同制定法規，以便快速推進建廠計畫；然而，在美國，台積電需自行出資聘請專家來制定規則，並與當地政府協商，光是法規制定便花費3,500萬美元，產生18,000多條規定，導致流程複雜且冗長。 3. 供應鏈與成本問題 美國本地供應商無法提供符合台積電標準的化學材料，若當地生產，成本將是台灣的五倍。因此，台積電選擇從台灣運送硫酸至美國，即便包含運輸成本，仍比美國生產更具成本效益。 此外，台積電還面臨當地工會文化與行政流程過於繁瑣的問題，影響建廠效率。美國繁複的審批機制，使得技術每次升級時，都需重新繪製設計圖、申請許可，導致生產線調整速度遠遜於台灣。 台積電的核心競爭力—根留台灣 綜合以上挑戰，魏哲家直言，台積電的最新技術無法輕易移轉至美國或其他國家，因為台灣擁有完整的供應鏈、靈活的行政支援、以及高效的人才培育機制，這些條件讓台積電在全球半導體產業中保持領先地位。 台積電不僅是全球...

> The user is asking for instructions on how to get a valid YouTube link from the official Android app that will work with me (Gemini). They are experiencing issues with links generated by the "share" function. I need to provide clear, step-by-step instructions for obtaining a valid YouTube URL from the Android app, focusing on methods that are likely to produce standard, accessible links. > Plan: > * Provide step-by-step instructions for getting a valid YouTube URL from the Android app using methods other than the "share" button if it's causing issues. > * Suggest methods like copying the link directly from the video page or sharing to another app and then copying. > * If those methods are not feasible or still produce problematic links, suggest using the YouTube website in a mobile browser as an alternative. > * Emphasize the importance of a standard YouTube URL format (e.g., youtube.com/watch?v=... or youtu.be/...). >    回應 You'r...

AppWorks, a venture capital firm based in Taiwan, has invested in several companies during their Series A rounds. Notable investments include: 1. **Carousell** (2018, Series C): A classifieds marketplace for buying and selling items. 2. **Concept Art House** (2021): Specializes in NFTs and video game art creation. 3. **Cyber Sierra** (2021): Offers cyber risk solutions and insurance. 4. **Dapper Labs** (2019): Creator of NBA Topshot and the Flow blockchain. 5. **Dappio** (2022): Aggregates yields across DeFi and NFTs. 6. **Dcard** (2020, Series C): A forum-based social platform. 7. **Deep Sentinel** (2018, Series A): AI-based home protection. 8. **Docosan** (2021, Series Seed): A healthcare marketplace. 9. **Eden Farm** (2021, Series A): A B2B agritech startup. 10. **EMQ** (2017, Series A): A financial technology company focusing on remittances. 11. **Fandora** (2014, Series A): Online seller of illustration merchandise. For more information on AppWorks and their investments, you can v...

 Designing an autocomplete feature for a search engine involves understanding user behavior, optimizing for speed and relevance, and ensuring the system can handle a large number of requests. Here's a step-by-step guide on how you might approach this: 1. **Requirement Gathering (需求收集)**    - **User Experience (用戶體驗)**: Understand the latency requirements. Autocomplete suggestions need to be fast, typically returning in under 100 milliseconds.    - **Scale (規模)**: Predict the number of requests per second during peak times. This will help determine infrastructure needs.    - **Relevance (相關性)**: Ensure the suggestions are relevant to the users. 2. **Data Collection (數據收集)**    - Gather a list of commonly searched queries from the search logs.    - Monitor user interactions with the autocomplete feature to refine and improve over time. 3. **Trie Data Structure (Trie數據結構)**    - Use a Trie (or Prefix Tree) which is especially...

Designing a video streaming server involves multiple technical aspects and intricate architectural decisions. Here's a high-level consideration and recommended steps from a system design perspective: 1. **Define Requirements (確定需求)**:    - **Throughput (吞吐量)**: How many client connections does your server need to support simultaneously?    - **Latency (延遲)**: How quickly should the streaming begin to play?    - **Video Quality (視頻質量)**: Are you supporting resolutions like 4K, 1080p, 720p, etc.?    - **Streaming Type (串流類型)**: Do you need to support live streaming or VOD (Video on Demand)? 2. **Choose Appropriate Protocols (選擇適當的協議)**:    - **HLS (HTTP Live Streaming)** and **DASH (Dynamic Adaptive Streaming over HTTP)** are popular streaming protocols today. Both support Adaptive Bitrate Streaming (ABR), adjusting video quality dynamically based on a user's network condition.    - **RTMP (Real-Time Messaging Protocol)**: Though...

### HMD Global and Nokia: Assessing the Past, Present, and Future of Their Partnership Since 2016, Nokia and HMD Global have successfully maintained a collaborative relationship that has revitalized the Nokia brand through a range of mobile and tablet devices. The partnership has been structured around a brand licensing agreement that facilitates the global sale of devices bearing the Nokia brand. But recent developments suggest a potential shift in strategy for HMD Global, raising several questions about the future of the partnership. #### **Historical Background of the Partnership** The collaboration between Nokia and HMD Global blossomed out of a mutual objective to resurrect the once iconic Nokia brand. The agreement was founded on a well-defined business model encompassing brand licensing, shared technologies, and revenue-sharing parameters that aligned with the vision to rejuvenate the Nokia brand while ensuring a strategic business growth. #### **A New Era with HMD’s Own Brand**...

### The Revival of Nokia: An Insight into the Nokia-HMD Global Partnership In a dynamic and fiercely competitive mobile device market, alliances and partnerships are not uncommon. One such notable collaboration is between Nokia, a veteran in the telecommunications industry, and HMD Global, a relatively new player aiming to make significant strides in the market. Here we delve deep into the partnership between these two Finnish companies, exploring the synergy that brings Nokia’s legacy into the modern smartphone era. #### **Background** **Nokia**, with its rich history stemming from a paper manufacturing venture to becoming a leader in the telecommunication equipment and mobile communications devices, was a global giant in the mobile manufacturing sector during the early 2000s. However, with the advent of smartphones, Nokia's market share gradually dwindled. **HMD Global**, founded in 2016, came into existence with the primary goal to create and market mobile phones and tablets und...

### The Revival of Nokia: An Insight into the Nokia-HMD Global Partnership In a dynamic and fiercely competitive mobile device market, alliances and partnerships are not uncommon. One such notable collaboration is between Nokia, a veteran in the telecommunications industry, and HMD Global, a relatively new player aiming to make significant strides in the market. Here we delve deep into the partnership between these two Finnish companies, exploring the synergy that brings Nokia’s legacy into the modern smartphone era. #### **Background** **Nokia**, with its rich history stemming from a paper manufacturing venture to becoming a leader in the telecommunication equipment and mobile communications devices, was a global giant in the mobile manufacturing sector during the early 2000s. However, with the advent of smartphones, Nokia's market share gradually dwindled. **HMD Global**, founded in 2016, came into existence with the primary goal to create and market mobile phones and tablets und...

Kaggle itself provides some great free resources and online courses, which can help you prepare for their contests. Here are a few: 1. **Kaggle Learn**: Kaggle's own "Learn" platform has a number of free, fast-paced courses designed to get you up to speed with the most important tools and techniques used in data science:    - **Python**: Teaches the basics of Python programming and data science.    - **Intro to Machine Learning**: Covers the fundamental concepts required to get started with machine learning.    - **Intermediate Machine Learning**: Introduces more complex machine learning models, including handling missing values and categorical variables, and using pipelines.    - **Data Visualization**: Teaches how to create beautiful and informative visualizations.    - **Pandas**: Introduces the Pandas library, which is fundamental for data analysis and manipulation in Python.    - **Deep Learning**: Covers the basics of dee...

Yes, Kaggle is a popular platform for data science competitions, but there are several others that you might be interested in as well. Here are a few: 1. **Zindi**: Zindi is a platform for data scientists in Africa to connect and compete. They run competitions (both for profit and non-profit) focused on solving Africa's most pressing problems. 2. **DrivenData**: DrivenData hosts competitions that aim to address some of the world's biggest social challenges. The challenges range from health, education, climate, and more. 3. **CodaLab Competitions**: CodaLab is an open-source web platform that enables researchers, developers, and data scientists to collaborate. They have a section dedicated to competitions. 4. **CrowdANALYTIX**: CrowdANALYTIX hosts data science and AI-related contests and also has an active community of data scientists. 5. **DataScienceGlobal Impact Challenge**: This is an annual competition aimed at data scientists and non-profits. The goal is to showcase how da...

Exploratory Data Analysis (EDA) is a critical step in any data science project. It involves understanding the data you're working with, discovering patterns, identifying anomalies, testing hypotheses, and checking assumptions using statistical summaries and graphical representations. Here's a bit more detail: 1. **Understanding the Data**: Start by checking what each column represents, the types of values (categorical, numerical, binary, etc.), and get a general sense of the data structure. 2. **Summary Statistics**: Pandas provides a `describe()` function that gives a useful summary of the numerical columns. It shows the mean, standard deviation, min, max, and quartiles. For non-numeric data, you can use the `value_counts()` method to see the distribution of categories. 3. **Visualizing the Data**: Graphical representations can help you understand the data better. Histograms and box plots are useful for visualizing distributions, scatter plots can show relationships between va...

Participating in Kaggle competitions is a great way to learn and apply data science techniques. Here are some steps and tips to get you started: 1. **Create a Kaggle Account**: The first step is to create a Kaggle account, if you haven't already. 2. **Find a Competition**: Browse the Competitions section on Kaggle to find one that interests you. If you're a beginner, you might want to start with one of the "Getting Started" competitions, such as the "Titanic: Machine Learning from Disaster". 3. **Understand the Problem Statement**: Read the competition details carefully to understand the problem you need to solve, the data you have to work with, and the metric on which your solution will be evaluated. 4. **Download the Data**: Download the provided datasets. Kaggle competitions usually provide a training set, which includes the target variable, and a test set, which you'll use to make predictions for submission. 5. **Explore the Data**: Use techniques su...

Yes, there are several best practices you can follow when writing code in Jupyter Notebooks for data analysis: 1. **Clear and descriptive naming**: Use clear and descriptive names for variables, functions, and so on. This makes your code easier to understand and maintain.  2. **Commenting and Documentation**: Make sure to document your code well. This includes adding comments to explain complex code blocks, and using docstrings for functions and classes. 3. **Modular and Reusable Code**: Encapsulate code that performs a specific task into a function. This makes your code more readable, reusable, and maintainable. 4. **Minimal use of global variables**: Try to avoid using global variables where possible, and pass variables to your functions instead.  5. **Consistent Coding Style**: Following a consistent coding style can make your code much easier to read and understand. You can follow the PEP 8 -- Style Guide for Python Code. In addition to these, here are some Jupyter Noteboo...

QIoT Suite 2.0.009 ( 2022/06/09 ) [Enhancements] - Renewed the code signing certificate on the application. QIoT Suite Lite 2.0.008 ( 2021/07/29 ) [Fixed Issues] - Selecting TLS 1.3 for secure connection (HTTPS) in the System Administration page would not allow users to log in to QIoT Suite. - The system would automatically delete the lxdbr0 interface. - Notification Center would not display the QIoT Suite logs. QIoT Suite Lite 2.0.005 ( 2020/12/07 ) [Fixed Issues] - Users would not be able to log in to QIoT Suite using the user account that was created using the same login credentials in both QTS and QIoT Suite application. QIoT Suite Lite 2.0.003 ( 2019/09/09 ) [New Features] - Added support for the OPC UA protocol: - QIoT OPC UA Client: connects to OPC UA servers - QIoT OPC UA Server: communicates with OPC UA clients and transfers data - QIoT OPC UA Gateway: maps data between OPC UA servers and clients - QOPCUA nodes: read, subscribe, and write to specific OPC UA tags in the QIoT ru...

Responsible AI, also known as ethical AI or trustworthy AI, refers to the development and deployment of artificial intelligence (AI) systems that prioritize fairness, transparency, accountability, privacy, and social impact. It is an approach that aims to address the potential risks and challenges associated with AI technologies while maximizing their benefits for individuals, organizations, and society as a whole. The rapid advancement of AI technologies has brought about numerous opportunities and benefits across various domains such as healthcare, finance, education, and transportation. However, these advancements also raise concerns about potential biases, discrimination, lack of transparency, and unintended consequences that can arise from AI systems. Responsible AI seeks to mitigate these concerns by integrating ethical considerations into the entire lifecycle of AI development. This involves several key principles and practices: Fairness and Avoidance of Bias: Responsible AI ai...

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  Learning Android application development in just 10 days may be challenging, but it's not impossible. Here are some suggestions to help you get started: Understand the basics: Start by understanding the basic concepts of Android development, such as the Android SDK, the development environment, and the application components. Choose a programming language: Android development is primarily done in Java or Kotlin. Choose one of these languages and learn the basics of it if you don't already know them. Learn the Android Studio IDE: Android Studio is the official integrated development environment for Android development. Learn how to use it to create, run, and debug your Android applications. Learn about layouts and views: The user interface (UI) of an Android application is created using layouts and views. Learn about different types of layouts and views, such as LinearLayout, RelativeLayout, and TextView. Work on projects: Start working on small projects, such as creating a si...

Developing proficiency in natural language processing (NLP) in just 10 days is a challenging task, but it's not impossible. Here are some suggestions to help you get started: Learn the basics: Start by learning the basic concepts and terminology of NLP, such as tokenization, stemming, lemmatization, part-of-speech tagging, and named entity recognition. You can find plenty of resources online, including tutorials, videos, and textbooks. Choose a programming language: NLP is often implemented using programming languages like Python, Java, or C++. Choose a language you are familiar with or interested in learning. Use NLP libraries: There are many libraries available for NLP, such as NLTK, spaCy, and Stanford CoreNLP. These libraries can help you perform NLP tasks quickly and easily. Practice with datasets: Practice on real-world datasets, such as news articles, reviews, or social media posts, to get familiar with different types of text data. Work on projects: Start working on small ...

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