en
Feedback
Continuous Learning_Startup & Investment

Continuous Learning_Startup & Investment

Open in Telegram

We journey together through the captivating realms of entrepreneurship, investment, life, and technology. This is my chronicle of exploration, where I capture and share the lessons that shape our world. Join us and let's never stop learning!

Show more
2 291
Subscribers
-324 hours
-167 days
-4530 days
Posts Archive
β€œMachine learning costs, talent and chip shortages… any AI and machine learning company faces at least one of these challenges, and most face a few at a time,” Pekhimenko told TechCrunch in an email interview. β€œThe highest-end chips are commonly unavailable due to the large demand from enterprises and startups alike. This leads to companies sacrificing on the size of the model they can deploy or results in higher inference latencies for their deployed models.” With spending on AI-focused chips expected to hit $53 billion this year and more than double in the next four years, according to Gartner, Pekhimenko felt the time was right to launch software that could make models run more efficiently on existing hardware. β€œTraining AI and machine learning models is increasingly expensive,” Pekhimenko said. β€œWith CentML’s optimization technology, we’re able to reduce expenses up to 80% without compromising speed or accuracy.” β€œFor one of our customers, we optimized their Llama 2 model to work 3x faster by using Nvidia A10 GPU cards,” CentML isn’t the first to take a software-based approach to model optimization. It has competitors in MosaicML, which Databricks acquired in June for $1.3 billion, and OctoML, which landed an $85 million cash infusion in November 2021 for its machine learning acceleration platform. β€œThe CentML platform can run any model,” Pekhimenko said. β€œCentML produces optimized code for a variety of GPUs and reduces the memory needed to deploy models, and, as such, allows teams to deploy on smaller and cheaper GPUs.”

아이폰 μΆœμ‹œ ν›„ 첫 4~5λ…„ μ •λ„λŠ” 앱을 μΆœμ‹œν•˜λŠ” κ²ƒλ§ŒμœΌλ‘œλ„ μœ μ €μ˜ wowλ₯Ό μ΄λŒμ–΄ λ‚Ό 수 μžˆμ—ˆλ˜ μ‹œμ ˆμ΄ μžˆμ—ˆλ‹€. μ΄λ™ν•˜λ©° 인터넷도 ν•  수 있고 ν„°μΉ˜μŠ€ν¬λ¦°μ„ ν™œμš©ν•  수 μžˆλŠ” μŠ€λ§ˆνŠΈν°μ—μ„œ ꡬ동이 λœλ‹€λŠ” κ²ƒλ§ŒμœΌλ‘œλ„ wow μ˜€λ˜ 것이닀. κ·Έ 이후 κΈ°μ‘΄ λ ˆκ°€μ‹œ μ‚°μ—…μ˜ νŒ¨λŸ¬λ‹€μž„μ„ λ°”κΎΌ μ„œλΉ„μŠ€λ“€μ΄ λ“±μž₯ν•˜μ—¬ wow λ₯Ό μ„ μ‚¬ν–ˆλ‹€. 유투브/λ„·ν”Œλ¦­μŠ€λŠ” TV/λ―Έλ””μ–΄ 산업을 λ°”κΏ¨κ³ , 페뢁/ꡬ글은 λ―Έλ””μ–΄/포털산업을 λ°”κΏ”λ†“μ•˜μœΌλ©°, μ•„λ§ˆμ‘΄μ€ μ‡Όν•‘/μ„œλ²„μ‹œμŠ€ν…œμ„, ν…ŒμŠ¬λΌλŠ” μžλ™μ°¨ 산업을, μš°λ²„λŠ” νƒμ‹œ 산업을, 에어비엔비λ₯Ό ν˜Έν…” 산업에 큰 영ν–₯을 쀬닀. μœ„μ™€ 같은 2000λ…„ 초반 이후 κ²©λ™μ˜ 20λ…„ 정도λ₯Ό κ²ͺ으며, ν˜„λŒ€μ‚¬νšŒμ˜ λ§Žμ€ μ‚¬λžŒλ“€μ€ λͺ¨λ°”일 및 μ›Ή μ€‘μ‹¬μ˜ μ„œλΉ„μŠ€μ— κ½€ 많이 μ΅μˆ™ν•΄μ§„ λ“― ν•˜λ‹€. κ·Έλž˜μ„œ, μƒˆλ‘œ μΆœμ‹œλ˜λŠ” 앱을 봐도 κ·Έ 감ν₯이 κ³Όκ±° λŒ€λΉ„ λ¬΄λŽŒμ§€κ³  μžˆμŒμ„ λŠλ‚€λ‹€. 였히렀, μš”μ¦˜μ€ κ³Όκ±°μ—λŠ” λ§Œμ‘±ν•˜λ©° μ‚¬μš©ν•˜λ˜ Big Tech μ‚¬μ˜ μ„œλΉ„μŠ€ 쑰차도 슬슬 'μ§€κ²¨μ›Œμ§„λ‹€' λŠλΌλŠ” 뢄듀이 μ¦κ°€ν•˜λŠ” λ“―ν•˜λ‹€. λ™μ‹œμ— 'κ³Όκ±°λΆ€ν„° 많이 μ΄μš©ν•˜λ˜ μ„œλΉ„μŠ€λ“€μ΄ μ΅œκ·Όμ—λŠ” μ˜ˆμ „λ§Œ λͺ»ν•΄μ„œ 싀망감이 크고, μ–΄μ©” 수 없이 μ΄μš©ν•˜κ³  μžˆλ‹€'κ³  λ§ν•˜λŠ” 뢄듀도 λ§Žμ•„μ§€λŠ” λ“―ν•˜λ‹€. OpenAI κ°€ chatGPT λ₯Ό μΆœμ‹œν•˜λ©° μƒˆλ‘œμš΄ ν™œλ ₯을 λΆˆμ–΄λ„£κ³  μžˆμ§€λ§Œ, κ·Έ νŒŒκΈ‰λ ₯이 과거의 아이폰 λͺ¨λ©˜νŠΈμ²˜λŸΌ μ—„μ²­λ‚˜μ§€ μ•Šμ€ 것도 사싀이닀. (chatGPTλŠ” μ†ŒλΉ„μž λ³΄λ‹€λŠ” μŠ€νƒ€νŠΈμ—…μ— ν™œλ ₯을 λΆˆμ–΄λ„£κ³  μžˆλŠ” λ“―ν•˜λ‹€. κ·Έλž˜μ„œ 걱정이기도 ν•˜λ‹€. μ†ŒλΉ„μžκ°€ λ°˜μ‘ν•˜μ§€ μ•ŠμœΌλ©΄ κ²°κ΅­ imapct κ°€ μ œν•œμ μΌ μˆ˜λ°–μ— μ—†κΈ° λ•Œλ¬Έμ΄λ‹€) μš”μ¦˜μ€ μœ μ €λΆ„λ“€μ΄ λŒ€λ‹€μˆ˜ μ„œλΉ„μŠ€μ— κ³Όκ±° λŒ€λΉ„ λœ¨λœ¨λ―Έμ§€κ·Όν•œ λ°˜μ‘μ„ λ³΄μ΄λŠ” μ‹œκΈ°μΈ 것 같기도 ν•˜λ‹€. λ‹€λ§Œ, μœ μ €λ“€μ€ μ—¬μ „νžˆ 더 λ‚˜μ€ 삢을 μ‚΄κ³  μ‹Άμ–΄ν•˜λŠ” μš•κ΅¬κ°€ κ°•ν•˜λ‹€. 더 μ„±μž₯ν•˜κ³  μ‹Άμ–΄ν•˜κ³ , 더 ν–‰λ³΅ν•œ 삢을 μ‚΄κ³  μ‹Άμ–΄ν•˜κ³ , 더 즐거운 μ‹œκ°„μ„ 보내고 μ‹Άμ–΄ ν•œλ‹€. 본인 인생에 κ°•λ ¬ν•˜κ²Œ λ‹€κ°€μ˜¬ 수 μžˆλŠ” μ„œλΉ„μŠ€λ₯Ό λ§Œλ‚˜, ν•΄λ‹Ή μ„œλΉ„μŠ€μ™€ ν•¨κ»˜ 더 만쑱슀러운 삢을 μ‚΄κΈ°λ₯Ό ν¬λ§ν•˜λŠ” 뢄듀이 κ½€ μžˆλ‹€. κ·Έλž˜μ„œ, λ―Έλž˜μ—λŠ” μ–΄λ–€ μ„œλΉ„μŠ€κ°€ λ§Žμ€ μœ μ €λ‘œλΆ€ν„° wowλ₯Ό μ΄λŒμ–΄ λ‚Ό 수 μžˆμ„μ§€... κΆκΈˆν•˜λ‹€. μœ μ €μ˜ μ„±μž₯κ³Ό λ§Œμ‘±μ— 더 많이 μ§‘μ°©ν•˜λŠ” μ„œλΉ„μŠ€κ°€ κ·Έ wow λ₯Ό μ΄λŒμ–΄ λ‚Ό 수 있으리라 λ―Ώμ§€λ§Œ, κ³Όκ±° λŒ€λΉ„ μœ μ €μ˜ wow λ₯Ό μ΄λŒμ–΄ λ‚΄κΈ° μœ„ν•œ λ‚œμ΄λ„κ°€ λ†’μ•„μ Έμ„œ κ³Όκ±° 만큼 'κΈ‰μ„±μž₯ν•˜λŠ” μŠ€νƒ€νŠΈμ—…'이 많이 λ‚˜μ˜¬ 것 κ°™μ§€λŠ” μ•Šλ‹€. κ·Έλž˜λ„, 이런 λ‚œμ„Έλ₯Ό μ΄κ²¨λ‚΄λŠ” κ°€μž₯ 쒋은 방법은 '더 νž˜λ“€μ–΄μ§€λŠ” ν™˜κ²½'에 λ°˜μ‘ν•˜κΈ° λ³΄λ‹€λŠ” 'μœ μ €'에 μ§‘μ€‘ν•˜μ—¬ ν•˜λ£¨ ν•˜λ£¨ 더 쒋은 μ„œλΉ„μŠ€λ₯Ό λ§Œλ“€μ–΄ λ‚΄λŠ” 것이라 μƒκ°ν•œλ‹€. λ¬Όλ‘  κ³Όκ±°μ—λŠ” 1λ…„ λ…Έλ ₯ν•˜λ©΄ λ§Œμ‘±μ„ μ΄λŒμ–΄ λ‚Ό 수 μžˆμ—ˆλ‹€λ©΄, μ΅œκ·Όμ—λŠ” 3~5λ°°λŠ” 더 ν•΄μ•Όν•˜λŠ” 어렀움이 μ‘΄μž¬ν•˜μ§€λ§Œ 말이닀. κ·Έλž˜μ„œ μš”μ¦˜ 같은 μ‹œλŒ€λŠ” Why? κ°€ 더 μ€‘μš”ν•΄μ§€λŠ” 것 κ°™λ‹€. μ™œ μ‹œμž‘ν–ˆλŠ”μ§€? 무엇을 μœ„ν•΄ μ„œλΉ„μŠ€λ₯Ό λ§Œλ“€μ–΄ λ‚΄κ³  μžˆλŠ”μ§€?에 λŒ€ν•œ λͺ…ν™•ν•˜κ³  μ†”μ§ν•œ 닡을 κ°€μ§€κ³  μžˆλŠ”μ§€κ°€ 더 μ€‘μš”ν•΄μ§€λŠ” μ‹œλŒ€κ°€ μ™”λ‹€. κ·Έ μ΄μœ μ— λŒ€ν•œ 닡을 전체 νŒ€μ΄ κ³΅μœ ν•˜κ³  μžˆμ–΄μ•Ό, wow λ₯Ό λ§Œλ“€μ–΄ λ‚΄κΈ° μœ„ν•œ λ…Έλ ₯/μ‹œκ°„μ΄ μ¦κ°€ν•œ μ‹œλŒ€λ₯Ό 묡묡히 μ΄κ²¨λ‚˜κ°ˆ 수 있기 λ•Œλ¬Έμ΄λ‹€. μ„œλΉ„μŠ€λ₯Ό μ΄μ–΄λ‚˜κ°€κ³  μžˆλŠ” 본질적 μ΄μœ λŠ” 무엇인가? 우리 μ„œλΉ„μŠ€λŠ” λˆ„κ΅¬λ₯Ό μœ„ν•΄ μ‘΄μž¬ν•˜λ©° μ™œ μ‘΄μž¬ν•΄μ•Ό ν•˜λŠ”κ°€? κΉŠμ€ λ°€, 링글을 더 μ„±μž₯μ‹œμΌœ λ‚˜κ°€κΈ° μœ„ν•œ 방법을 κ³ λ―Όν•˜λ‹€κ°€, 원둠적인 μ§ˆλ¬Έμ— λŒ€ν•΄ λ‹€μ‹œ ν•œ 번 생각해본닀.

---- Navigating "corporate speak" isn't easy. Here's a helpful guide I put together: "Let me check with my team" = No "Possibly" = No "On my roadmap" = Not happening "This will be done in Q4" = This will be done in Q2 next year "Disagree and commit" = I hate you "Per my last email" = Try reading, for once in your life "Challenging landscape" = We're going out of business, quickly "Digital transformation" = We're going out of business, slowly "Let's circle back" = We'll never speak of this again "Take it offline" = We'll never speak of this again "30,000 foot view" = I don't know what I'm saying "Low hanging fruit" = Easy promotion "Open up the kimono" = HR violation "We use AI" = We don't use AI "We use machine learning" = We don't use machine learning "All hands on deck" = Let's actually try for once, please πŸ˜‚

β€œμ°½μ—…κ°€μ˜ 길에 λ“€μ–΄μ„œλ©΄ νšŒμ‚¬κ°€ μ—¬λŸ¬λΆ„μ˜ 가쑱보닀 μ€‘μš”ν•΄μ Έμš”. κ°€μ‘±λ“€μ˜ λŒ€μ†Œμ‚¬λ₯Ό μ±™κΈΈ 수 μ—†κ³ , μžλ…€λ“€μ—κ²Œ κ΅Ώλ‚˜μž‡ ν‚€μŠ€λ₯Ό ν•  수 μ—†κ²Œ 될 κ±°μ˜ˆμš”. 또 ν˜„κΈˆ μžμ‚°μ΄ ν•„μš”ν•΄ 쒋은 μ§‘κ³Ό 쒋은 μ°¨λŠ” 포기해야할 κ±°κ³ μš”. μΉœκ΅¬λ‚˜ 지인듀은 μ—¬λŸ¬λΆ„μ„ μ΄ν•΄ν•˜μ§€ λͺ»ν•˜κ³ , μΈμƒμ—μ„œ 길을 μžƒκ³  λ°©ν™©ν•œλ‹€κ³  생각할 κ±°μ˜ˆμš”. λΆ€λ”” 방황이 μ§§μ•„μ•Όν•  텐데 ν•˜κ² μ£ .” β€œνŒ€μ›λ“€μ˜ 월급을 쀄 수 μ—†λŠ” μ‹œκΈ°κ°€ 올 κ±°μ˜ˆμš”. 이 μ—¬μ •μ—μ„œ λˆ„κ΅°κ°€λŠ” λ‹Ήμ‹ (μ°½μ—…κ°€)을 κ³ μ†Œν•  κ±°μ˜ˆμš”. μ—¬λŸ¬λΆ„μ„ κ³ μ†Œν•˜λŠ” μ‚¬λžŒμ΄ 곡동 μ°½μ—…μžμΌ μˆ˜λ„ 있고 투자자일 μˆ˜λ„ μžˆμ–΄μš”. 또 자주 틀릴 것이고, 이 λ¬Έμ œλ“€μ„ νŒ€μ›λ“€μ΄ λ‹€ 보게 될 κ±°μ˜ˆμš”. μͺ½νŒ”λ¦° 단계λ₯Ό λ„˜μ–΄μ„œλ©΄ λ‚΄κ°€ ν•˜λŠ” 게 λ§žλ‚˜, (λŒ€ν‘œμ§μ—μ„œ) λ‚΄λ €μ™€μ•Όκ² κ΅¬λ‚˜λΌλŠ” 생각도 λ“€κ²Œ 되죠. νŒ€μ›λ“€λ„ 계속 μ—¬λŸ¬λΆ„μ„ μ‹€λ§μ‹œν‚¬ ν…Œμ§€λ§Œ, κ·ΈλŸΌμ—λ„ 계속 예수처럼 μ‚¬λž‘μ„ νΌμ€˜μ•Ό ν•΄μš”. νŒ€μ›λ“€μ„ μœ„ν•΄ 격리 μ‹œμΌœμ•Ό λ§ˆλ•…ν•œ μ§μ›μ—κ²Œλ„ 웃어야 ν•˜λŠ” μ‹œκΈ°κ°€ μžˆμŠ΅λ‹ˆλ‹€.” (이승건 비바리퍼블리카 λŒ€ν‘œ, μ •μ£Όμ˜ μ°½μ—…κ²½μ§„λŒ€νšŒ 데λͺ¨λ°μ΄ 2023) 정말 λ¦¬μ–Όν•œ μ°½μ—…μžμ˜ μ‚Ά. μ§€κΈˆ 상황이 λ„ˆλ¬΄ νž˜λ“ λ° 무슨 λΆ€κ·€μ˜ν™”λ₯Ό λˆ„λ¦¬κ² λ‹€κ³  이걸 ν•˜λ‚˜ μ‹Άμ§€λ§Œ 또 λ‚˜λ¦„μ˜ μ΄μœ κ°€ μƒκ²¨μ„œ μ§€μ†ν•˜λŠ” 것이죠. κ°œμΈμ μœΌλ‘œλŠ” 이 삢이 λ‹Ήμ—°ν•˜κΈ°λ³΄λ‹€λŠ” 점차 κ°œμ„ λμœΌλ©΄ μ’‹κ² μŠ΅λ‹ˆλ‹€. μ°½μ—…μžμ— λŒ€ν•œ 쑴쀑과 λ³΄ν˜Έλ„ 컀져야 ν•˜κ³ μš”.

51% of Zendesk's revenue is international 47% of Cloudflare’s revenue is international 46% of HubSpot’s revenue is international 45% of MongoDB's revenue is international 38% of Asana’s revenue is international 34% of Twilio’s revenue is international 22% of Okta’s revenue is international Go Global as soon as you have customers there Pull ahead

이 μ‚¬λžŒμ€ μžκΈ°κ°€ ν”Œλ ˆμ΄ν•˜κ³  μžˆλŠ” κ²Œμž„μ˜ 판이 μ–΄λ–»κ²Œ μ„€κ³„λ˜μ–΄μžˆλŠ”μ§€ λΆ„λͺ…ν•˜κ²Œ μ•Œκ³  μžˆλ„€ https://www.youtube.com/watch?v=Czmkes4yAOA

Long 베이비뢀머 vs Short MZ BofA λŠ” 졜근 λ³΄κ³ μ„œμ—μ„œ Long 베이비뢀머, Short λ°€λ ˆλ‹ˆμ–Ό (MZ) 투자 아이디어λ₯Ό μ œμ‹œν•©λ‹ˆλ‹€. μ§€κΈˆμ˜ 고금리, κ³ λ¬Όκ°€ ν™˜κ²½μ—μ„œ λ―Έκ΅­λ‚΄ μ†ŒλΉ„ μ§€μΆœμ˜ μ£Όλ„κΆŒμ€ 65μ„Έ μ΄μƒμ˜ 고령측이 μ™„λ²½νžˆ μ₯κ³  μžˆμŠ΅λ‹ˆλ‹€. ν•œκ΅­μ˜ 베이비뢀머 μ„ΈλŒ€μΈ 저희 λΆ€λͺ¨λ‹˜λ“€μ„ 보더라도 λŒ€λΆ€λΆ„ μžκ°€λ‘œ 1 주택 이상을 보유 μ€‘μž…λ‹ˆλ‹€. λŒ€μΆœ 거의 μ—†μŠ΅λ‹ˆλ‹€. μžμ‚° κ°€κ²©μ˜ μΈν”Œλ ˆμ† Wealth effect λ¬΄μ‹œ λͺ»ν•©λ‹ˆλ‹€. 반면, MZ μ„ΈλŒ€λŠ” 주둜 μ“°κ³  μ£½μžλŠ” 세계관, 졜근 λͺ‡λ…„κ°„ 뢀동산 영끌쑱, 코인/주식 빚투쑱의 ν•©λ₯˜λ‘œ 뢀채 뢀담이 μƒλ‹Ήν•©λ‹ˆλ‹€. 숨만 쉬어도 이자의 Snowball effect λ₯Ό κ²½ν—˜ν•˜κ³  있죠. λ”μš±μ΄ λ² μ΄λΉ„λΆ€λ¨ΈλŠ” 돈이 λ§Žλ“  적든 μ—¬μ „νžˆ 저좕에 λŒ€ν•œ 믿음이 μžˆμŠ΅λ‹ˆλ‹€. 미ꡭ도 Cash return 이 5% λ₯Ό μƒνšŒν•©λ‹ˆλ‹€. Cash is king 인 μž‘κΈˆμ˜ 상황은 μ„ΈλŒ€κ°„ 격차λ₯Ό 되돌리기 νž˜λ“€ μ •λ„λ‘œ 벌리고 μžˆμŠ΅λ‹ˆλ‹€. μŠΉμžμ™€ νŒ¨μžκ°€ λͺ…ν™•νžˆ κ°ˆλ¦¬λŠ” κ²Œμž„μ΄λΌλ©΄, 섹터와 μ‚°μ—…λ‚΄ 투자 μ•„μ΄λ””μ–΄λ‘œ ν™œμš©ν•΄ 볼만 ν•©λ‹ˆλ‹€.

πŸ“’ Introducing Voyage AI Founded by a talented team of leading AI researchers and me πŸš€πŸš€. We build state-of-the-art embedding models (e.g., better than OpenAI 😜). We also offer custom models that deliver 🎯+10-20% accuracy gain in your LLM products. 🧡 We think embeddings are an under-loved, but incredibly important, part of everyone’s retrieval stack. So we set out to build just better embeddings. Voyage embeddings are SOTA on MTEB and 9 held-out benchmarks covering industry domains. Learn more here: https://lnkd.in/gk59ZE-T We partnered with @LangChainAI to help enhance their official chatbot, live at chat.langchain.com. Both our base and fine-tuned embeddings improve both the retrieval and response quality, and the latter is deployed! Check out https://lnkd.in/gZ2aH4KU for more details. Try Voyage embeddings for free – your first 5000 documents are on us! Create an account at voyageai.com and check out our API docs at https://docs.voyageai.com . To fine-tune your own custom model, email βœ‰οΈ contact@voyageai.com for early access!

λ‚΄κ°€ 일본에 근무할 λ‹Ήμ‹œ λ°˜λ„μ²΄ νˆ¬μžκ°€ μ΄λ€„μ‘ŒκΈ° λ•Œλ¬Έμ— 도쿄 μ§€μ‚¬μ—λŠ” 이병철 회μž₯의 μžλ¬Έμ—­μ„ ν•΄μ£ΌλŠ” λ°˜λ„μ²΄ κ΄€λ ¨ 전문가듀이 자주 λ°©λ¬Έν–ˆλ‹€. μžλ¬Έν•œ 일본인 λŒ€ν•™κ΅μˆ˜μ—κ²Œ β€œμš°λ¦¬ 회μž₯λ‹˜μ΄ λ°˜λ„μ²΄λ₯Ό μ–Όλ§ˆλ‚˜ μ•Œκ³  κ³„μ‹­λ‹ˆκΉŒ?” 라고 λ¬Όμ–΄λ΄€λ‹€. 그뢄은 μ›ƒμœΌλ©΄μ„œ β€œμ΄ˆλ“±ν•™μƒ μˆ˜μ€€μž…λ‹ˆλ‹€β€λΌκ³  λ‹΅ν–ˆλ‹€. β€œκ·ΈλŸ°λ° μ™œ μ£Όμœ„ μ‚¬λžŒλ“€μ˜ λ°˜λŒ€λ₯Ό 무릅쓰고 λ°˜λ„μ²΄ 투자λ₯Ό λ°€μ–΄λΆ™μ΄μ‹€κΉŒμš”?β€ν•˜κ³  λ‹€μ‹œ λ¬ΌμœΌλ‹ˆ 그뢄은 β€œνšŒμž₯λ‹˜μ˜ 사업에 λŒ€ν•œ 감각은 동물적 λ³ΈλŠ₯μž…λ‹ˆλ‹€. 아무도 말릴 수 μ—†μŠ΅λ‹ˆλ‹€β€λΌκ³  λ‹΅ν•΄ ν•¨κ»˜ μ›ƒμ—ˆλ‹€. 결과적으둜 ν•œκ΅­μ˜ μ „μžμ‚°μ—…μ΄ 일본을 μΆ”μ›”ν•  수 있던 건 μ˜€λ„ˆ μœ„μ£Όμ˜ μ§€λ°°κ΅¬μ‘°μ—μ„œ μ‹ μ†ν•˜κ³  μž₯기적인 μ˜μ‚¬κ²°μ •μ„ ν–ˆκΈ° λ•Œλ¬Έμ΄λ‹€. κ³Όκ±° 이건희 회μž₯은 μ£Όμž¬μ›μ΄ κ·€κ΅­ν•  λ•Œ λ°˜λ“œμ‹œ 일본의 μ „μžμ œν’ˆμ„ ν•˜λ‚˜μ”© μ‚¬μ™€μ„œ λΆ„μ„ν•˜λΌκ³  μ§€μ‹œν–ˆλ‹€. λ‚˜μ²˜λŸΌ 기술 λ¬Έμ™Έν•œμΈ μ‚¬λžŒμ—κ²ŒλŠ” 곀혹슀러운 μΌμ΄μ—ˆλ‹€. μ‚Όμ„±μ „μžκ°€ VTR κ°œλ°œμ— λ‚˜μ„  μ΄ˆκΈ°μ—λŠ” λΆˆλŸ‰λ₯ μ΄ λ„ˆλ¬΄ λ†’μ•„ μš΄λ™μž₯에 μ œν’ˆμ„ μŒ“μ•„μ„œ λΆˆμ„ μ§€λ₯΄κΈ°λ„ ν–ˆλ‹€. λ„μ‹œλ°”μ˜ ν˜‘μ‘°λ₯Ό μ–»μ–΄ 라인의 μ‘°μž₯듀을 λ„μ‹œλ°” 곡μž₯에 보내 μ‹€μŠ΅μ„ μ‹œν‚€κΈ°λ‘œ ν•œ 적이 μžˆλ‹€. ν•œλ° μ‹€μŠ΅μ΄ μ§„ν–‰λ˜λ˜ 쀑 λ„μ‹œλ°”μ—μ„œ λ”λŠ” ν•œκ΅­μ˜ μ—°μˆ˜μƒμ„ λ°›μ§€ μ•Šκ² λ‹€κ³  ν†΅λ³΄ν–ˆλ‹€. λ„μ‹œλ°” κ°„λΆ€λ‘œλΆ€ν„° μ „ν•΄ 듀은 μ‚¬μœ λŠ” 어이가 μ—†μ—ˆλ‹€. 3μ°¨ μ‹€μŠ΅μƒλ“€μ΄λ‚˜ 1Β·2μ°¨ μ‹€μŠ΅μƒλ“€μ΄ ν•˜λŠ” 질문이 λ™μΌν•˜λ‹€κ³  ν–ˆλ‹€. 같은 질문이 λ‚˜μ˜€λŠ”λ° λΉ„μ‹Ό κ²½λΉ„λ₯Ό λ“€μ—¬ ν•΄μ™Έ μ—°μˆ˜λ₯Ό ν•  ν•„μš”κ°€ μžˆλŠλƒλŠ” μ–˜κΈ°μ˜€λ‹€. 쑰금 λͺ¨μš•μ μœΌλ‘œλ„ λ“€λ Έμ§€λ§Œ ν‹€λ¦° 지적이 μ•„λ‹ˆμ—ˆλ‹€. 개인의 이읡보닀 μ§‘λ‹¨μ˜ 이읡을 μš°μ„ μ‹œν•˜κ³ , μƒˆλ‘œμš΄ 지식은 κ³΅μœ ν•˜λŠ” 일본인의 μ‚¬κ³ λ°©μ‹μœΌλ‘œλŠ” 우리 μ—°μˆ˜μƒλ“€μ˜ 개인주의적 사고방식이 μ΄ν•΄ν•˜κΈ° 어렀웠을 것이닀. μš”μ¦˜ μ•„ν‚€ν•˜λ°”λΌ λ§€μž₯의 μ•žμžλ¦¬λ₯Ό μ°¨μ§€ν•˜κ³  μžˆλŠ” μ‚Όμ„±, LG TVλ₯Ό 보면 40λ…„ 전에 μ°½ν”Όν–ˆλ˜ κ·Έλ•Œμ˜ 일이 λ– μ˜€λ₯΄κ³€ ν•œλ‹€.

μ‹ λ™μ•„μ—λŠ” 가끔 쒋은 글듀이 μžˆλ‹€. https://shindonga.donga.com/economy/3/03/13/4503748/1