Here are the contents translated into English:

For Future Career Development

In my career, I actively explore the impact of AI or new technologies and think about how they can help my industry or work produce more value. By doing so, I can stay ahead of the competition with new competitive advantages.

Reading Literature

When reading related articles, I usually start by looking at the table of contents and then jump to key chapters or sections based on my interests. This way, I can quickly understand the main content and ensure that I don’t miss important information.

Reading Style

I tend to read literature with a problem-solving approach, which helps me better understand and remember the content I learn. When reading, I first look at graphs or tables, then gradually read the text, and finally, if necessary, carefully read related sections for more detailed information.

Thinking About the Future

For questions about AI’s impact on work, I try to find keywords related to work, profession, or robots and expand them step by step to understand their possible changes and developments. This helps me better predict future changes in the workplace environment.

Conclusion

In conclusion, I believe that AI and new technologies will have a significant impact on future career development and will bring about profound changes in work styles and professions. By grasping this information and thinking about how it can help my work, I can stay ahead of the competition.

Translation

對於未來的職涯發展

在職涯上面,我主動去了解 AI 或新科技的影響,並且思考它們如何幫助我所在產業或工作產生更多價值。這樣做,能夠讓我站在領先者的角度,掌握新的競爭優勢。

閱讀文獻

當閱讀相關文章時,我通常會先看目錄,然後根據我的興趣跳至關鍵的章節或段落。這樣可以快速了解文章的主要內容,並且確保我不錯過重要的資訊。

閱讀方式

我習慣帶著問題去讀文獻,這樣能夠幫助我更好地理解和記住所學的內容。在閱讀時,我會先看圖表或表格,然後再逐步閱讀文字。最後,如果我確實需要知道更多資訊,我才會仔細閱讀相關段落。

思考未來

對於AI對工作影響的問題,我會嘗試找出有關工作、職業或機器人等關鍵字,並且逐步往後延展,以了解它們可能帶來的改變和發展。這樣做能夠幫助我更好地預測未來職場環境的變化。

結論

對於未來的職涯發展,我認為AI和新科技將會帶來重大影響,並且會對工作方式和職業產生深遠的變革。掌握這些資訊並思考它們如何幫助我的工作能夠讓我在競爭中佔據優勢。

Reference:

https://www.youtube.com/watch?v=cCZnR4xKSUs


<
Previous Post
Apple paper: GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models
>
Next Post
Yann LeCun: LLM can never reach AGI