Sam Altman在斯坦福大学的全面演讲解析：详细探讨GPT4设定的AI新标准和对GPT5的期待，以及人工智能的未来社会影响和商业模式变革

老范讲故事
28 Apr 202421:20

Summary

TLDRIn a recent YouTube channel feature, the host discusses a closed-door meeting at Stanford University where Sam Altman, a prominent Silicon Valley entrepreneur and the figurehead behind OpenAI, shared his insights. Altman, who famously dropped out of Stanford to pursue entrepreneurship, touched on several topics including the rapid development of artificial intelligence, the role of GPT-4 in setting industry standards, and the potential of GPT-5 to redefine those benchmarks. He also addressed the debate around open-source versus proprietary models, advocating for a free, ad-free GPT model to democratize AI services. Altman's vision includes using AI to eliminate inequalities and prepare society for the swift pace of technological change. He emphasized that while AI can augment human capabilities, it's crucial for society to evolve alongside these advancements to prevent chaos and ensure that the benefits of AI are accessible to all, albeit with the caveat that the actual participants in this innovation might remain a select group.

Takeaways

  • 🚀 **Innovation in AI**: The rapid development of AI, particularly with GPT4 setting a new standard for the industry to follow and surpass.
  • 🎉 **Celebrating Achievements**: Sam Altman, a prominent Silicon Valley entrepreneur, was celebrated for his birthday, highlighting his contributions to the tech industry.
  • 📚 **Education to Entrepreneurship**: Altman's story parallels other successful entrepreneurs like Bill Gates and Mark Zuckerberg, who also left their studies at Stanford to pursue business ventures.
  • 📈 **Scaling AI Models**: The effectiveness of the scaling law, where increasing model size and data lead to better performance, was emphasized with examples like the Llama and Tongyi models.
  • 💡 **Open Source vs. Free Access**: OpenAI's stance on open sourcing their models was questioned, with the argument that providing free, ad-free access to AI might be more beneficial.
  • 🌐 **Global AI Services**: Altman's vision for AI services to be cheap and widely available globally, potentially disrupting the current business models of AI companies.
  • 💰 **Funding and Burning**: A discussion on the financial model of sustaining AI development, with the concept of 'burning money' to create societal value and finding funds to support this.
  • 🛠️ **Innovation and Entrepreneurship**: Advice against targeting current AI deficiencies for innovation, as newer models like GPT5 are expected to obsolete current solutions.
  • 🎮 **Convergence of Media**: Mention of Sora, a platform that aims to blend movies and games, suggesting new directions for创业 (entrepreneurship/innovation).
  • 👑 **AI and Human Interaction**: The exploration of the relationship between humans and AI, and the societal roles they will each play, drawing examples from chess and mental health counseling.
  • 🏛️ **Organizational Structure**: The importance of organizational structure being subservient to the company's vision and mission, with adaptability being key to achieving goals.

Q & A

  • What was the context of the meeting at Stanford University where Sam Altman spoke?

    -Sam Altman spoke at a closed-door meeting at Stanford University, where he discussed various topics including AI development, the future of OpenAI, and the societal implications of rapid technological advancements.

  • What did Sam Altman mention about the development of AI and GPT models?

    -Sam Altman mentioned that AI is developing rapidly, with GPT4 setting a new standard for the industry. He also hinted at the upcoming GPT5, suggesting it would be very powerful and set new benchmarks.

  • What was the significance of the DGX H200 gift to Sam Altman?

    -The DGX H200 was likely a birthday gift to Sam Altman, who was celebrating his birthday around the time of the event. It's a high-performance AI computing system, indicating the respect and recognition for his work in the AI field.

  • What is Sam Altman's view on the open-source model for AI development?

    -Sam Altman expressed that he does not believe open-source is the best path for AI development. Instead, he advocates for a model where AI services are freely available without ads, suggesting that this approach could be more effective in achieving widespread adoption and use.

  • How does Sam Altman envision the role of AI in reducing inequality?

    -Altman believes that by making AI services widely available and inexpensive, it can help reduce inequality. However, the speaker of the transcript expresses skepticism about the ability of tools alone to eliminate social inequalities.

  • What did Sam Altman say about the future of AI and its impact on jobs?

    -Altman suggested that while AI will surpass human capabilities in certain areas, such as playing chess, people will still enjoy human interactions and activities. He also mentioned that new AI tools will enable more significant innovations from humans, rather than stifling them.

  • What is the 'scaling law' that Sam Altman referred to?

    -The 'scaling law' or 'Grading low' that Altman mentioned refers to the principle that as the scale of AI models increases, with more data and computational power, the performance and outcomes of these models continue to improve.

  • How did Sam Altman address the criticism regarding OpenAI's business model and funding?

    -Altman indicated that the focus of OpenAI is on creating social value and achieving its vision of AGI (Artificial General Intelligence), rather than following traditional business logic. He suggested that they are willing to 'burn money' to achieve their goals and find funding to support their operations.

  • What was the birthday gift sent to Sam Altman by '老黄' (Huang)?

    -The birthday gift sent to Sam Altman by '老黄' was a DGX H200, a high-end AI supercomputer, which is indicative of the close ties between the tech community and Altman.

  • What is the relationship between Sam Altman's educational background and his entrepreneurial journey?

    -Sam Altman is a Stanford dropout, similar to other notable Silicon Valley entrepreneurs like Bill Gates and Mark Zuckerberg. His decision to leave Stanford to pursue entrepreneurship is part of a trend among tech founders who have chosen to forego formal education to start their companies.

  • How does Sam Altman view the future of AI products and services?

    -Altman envisions a future where AI services are globally available, extremely cheap, and widely accessible. He also discusses the importance of society preparing for technological advancements to prevent chaos and ensure a smooth integration of AI into daily life.

Outlines

00:00

🎤 Introduction to Sam Altman's Stanford Talk

The video introduces Sam Altman's recent talk at Stanford University, discussing the content of a closed-door meeting where only snippets of information are available online. It mentions a gift sent to Altman, a DGX H200, and a group photo with Huang Renxun and Greg. The talk focused on AI development, with Altman emphasizing the rapid progress in the field, particularly with GPT-4 setting a new standard for the industry to follow. Altman also touched on his background as a Stanford dropout and the significance of the scaling laws in AI, suggesting that larger models with more data will continue to improve performance.

05:00

🤖 AI's Rapid Development and Open Source Debate

This paragraph delves into the advancements in AI, particularly the impact of models like Lama 3 and the upcoming GPT-5, which is expected to set new benchmarks. It contrasts the traditional business model of earning and reinvesting profits with Altman's approach of seeking funds to create social value. The paragraph also addresses the open-source debate, where Altman argues that providing free, ad-free AI services is more beneficial than open-source code, which is utilized by a smaller audience. Furthermore, it discusses the potential for AI to eliminate inequalities and the speaker's ambition to make AI services globally affordable and accessible.

10:01

🚀 Disrupting Traditional Business Models

The speaker challenges traditional business logic by focusing on finding funds to sustain operations rather than earning profits through conventional means. It reflects on the experience of dealing with Google's business practices and the realization that even a seemingly open company like Google has its rules and boundaries. The paragraph also warns against trying to fix current GPT models, as future iterations will naturally surpass them. It briefly mentions Sora, a platform that aims to integrate movies and games, and questions its viability based on OpenAI's unconventional commercial understanding.

15:02

🧲 AI and the Future of Entrepreneurship

The speaker advises against exploiting the weaknesses of current AI models, as they will soon be obsolete with the release of newer models like GPT-5. It emphasizes the importance of adhering to business principles despite OpenAI's disruptive approach. The paragraph also explores the relationship between humans and AI, using examples such as people's preference for watching human chess games and青少年 (youth) preferring AI therapists. It stresses the need to consider the roles and boundaries of humans and AI in product and service design.

20:03

🌐 Preparing Society for AI Advancements

The speaker discusses the social implications of AI, emphasizing that society must prepare for rapid technological progress. It acknowledges concerns about the speed of AI development and its potential to disrupt jobs, suggesting that society needs time to adapt. The paragraph also addresses the evolution of OpenAI's organizational structure to align with its vision and mission, and refutes criticisms by stating that the structure will continue to change as needed. Lastly, it asserts that new tools, like advanced AI, will not stifle human innovation but rather enable higher levels of creativity and innovation.

Mindmap

Keywords

💡Sam Altman

Sam Altman is a well-known entrepreneur and investor, recognized for his role in the development of artificial intelligence. In the video, he is the central figure who shares insights on AI's rapid development and its implications for society. His perspective on AI's trajectory and its potential to reshape various industries is a key theme.

💡Artificial Intelligence (AI)

AI refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The video discusses the rapid advancements in AI, particularly focusing on the developments of models like GPT-4 and the expectations surrounding GPT-5. AI is portrayed as a transformative force that will continue to evolve and set new standards.

💡GPT-4

GPT-4 represents the fourth generation of the Generative Pre-trained Transformer, a large language model developed by OpenAI. The script mentions GPT-4 as a benchmark that other AI models are striving to surpass. It has set a standard in the field of natural language processing, influencing the direction of future AI research and development.

💡Scaling Laws (Grading low)

Scaling laws, also referred to as 'Grading low' in the transcript, pertain to the principle that as the scale of a system increases, typically through more data or computational power, its performance also improves. The video uses this concept to discuss how increasing the scale of AI models leads to better performance and outcomes, as exemplified by the progression from 72B to 370B models.

💡Open Source

Open source refers to a philosophy of software development where the source code is made available to the public, allowing anyone to view, use, modify, and distribute it. The video discusses the debate around whether open sourcing AI models is the best approach, with the speaker suggesting that providing free, ad-free access to advanced AI models might be more beneficial than open sourcing the code.

💡AGI (Artificial General Intelligence)

AGI, or Artificial General Intelligence, is the hypothetical ability of an intelligent machine to understand or learn any intellectual task that a human being can do. The video mentions AGI as the ultimate goal of OpenAI, highlighting the organization's focus on creating machines that can think and solve problems like humans.

💡

💡Innovation and Entrepreneurship

The video touches on the topic of innovation and entrepreneurship in the context of AI. It suggests that instead of focusing on the shortcomings of current AI models, entrepreneurs should look forward to the new opportunities that will be presented by upcoming models like GPT-5. This underscores the importance of forward-thinking and adaptation in the face of rapid technological change.

💡Sora

Sora is mentioned as a concept that aims to blend movies and games, potentially indicating a new direction for创业 (entrepreneurship). However, the speaker expresses skepticism about whether this fusion will be practical without a clear workflow and cost model, reflecting on the challenges of commercializing innovative ideas in the tech industry.

💡Commercialization

Commercialization refers to the process of turning an invention or idea into a good or service that can be sold for a profit. The video discusses the commercialization of AI technologies, contrasting the non-traditional approach of OpenAI, which focuses on creating societal value and finding funding, with the more traditional business models that emphasize profit and shareholder returns.

💡Social Impact of AI

The social impact of AI is a central concern in the video, as it discusses the potential for AI to disrupt job markets and the need for society to adapt to rapid technological advancements. The speaker argues that while AI can lead to higher levels of innovation, it may also exacerbate inequality unless society is prepared to address the challenges it presents.

💡Technological Unemployment

Technological unemployment is the loss of jobs caused by the introduction of new technologies that change the way tasks are performed, allowing machines to replace human workers. The video briefly touches on this concept with the example of professions like lawyers and doctors potentially being replaced by AI, emphasizing the need for society to prepare for such shifts.

Highlights

Sam Altman, a prominent Silicon Valley entrepreneur, spoke at Stanford University, discussing various topics including AI development and its societal implications.

Altman mentioned that GPT-4 has set a new standard for AI, prompting other companies to catch up and potentially surpass it.

He touched on the Scalability Law, suggesting that as AI scales up with more data and computational power, performance will continue to improve.

Altman discussed the potential for GPT-5 to establish new benchmarks and standards in the field of AI.

He expressed skepticism about open-source as the best path for AI development, emphasizing the importance of creating value for society.

Altman suggested that OpenAI's goal is not to be open-source but to achieve AGI (Artificial General Intelligence).

He indicated that free and ad-free access to advanced AI models like GPT could be more beneficial than open-source code.

Altman shared his vision of making AI services extremely cheap and widely available globally, possibly leading to GPT-4 being offered for free.

He addressed the criticism regarding OpenAI's organizational structure and its mission, stating that the structure serves the vision and is subject to change.

Altman argued that society needs to prepare for rapid technological advancements to avoid chaos and ensure smooth integration.

He highlighted the importance of considering the relationship and boundaries between humans and AI in the design of future AI products and services.

Altman suggested that while AI has surpassed humans in games like chess, people still prefer to watch human players, indicating a continued desire for human interaction.

He pointed out that contrary to chess,青少年 (youth) prefer chatting with AI therapists, showing a shift in human-AI interaction preferences.

Altman warned against focusing on current GPT-4's shortcomings as future iterations like GPT-5 will render those efforts obsolete.

He emphasized that AI startups should adhere to established business principles, unlike OpenAI's disruptive approach.

Altman shared insights on the fusion of movies and games, hinting at new entrepreneurial directions with platforms like Sora.

He concluded by expressing optimism that new tools like advanced AI models will enable higher levels of human innovation, rather than stifling it.

Transcripts

00:00

大家好

00:00

歡迎收聽老範講故事的YouTube頻道

00:02

今天咱們來講一講

00:03

前幾天山貓奧特曼

00:04

到底在斯坦福大學裏說了些什麼

00:07

大家注意啊

00:08

這是一個閉門會議

00:09

我們現在所能夠看到的資訊

00:12

都是網上流傳的

00:15

各種隻言片語

00:17

有照片但是呢

00:18

並沒有看到全文

00:19

什麼視頻啊

00:21

我反而是沒看到了

00:22

以及根據這些隻言片語做的各種總結

00:27

4月25號上午呢

00:30

應該是黃教主考去送禮去了

00:33

送的是DGX H200

00:36

山貓奧特曼啊

00:37

黃仁勳以及Greg

00:39

他們三個人合了一張影

00:41

下午呢

00:41

就應該跑到斯坦福去做活動去了

00:44

斯坦福大學創業思想領袖講壇

00:49

這樣的一個活動

00:50

山姆奧特曼

00:50

號稱自己是這樣的一個領袖

00:52

應該沒有任何毛病了

00:53

上千人參加

00:55

而且呢還有給他的生日祝賀啊

00:59

說祝山姆奧特曼生日快樂

01:01

那你說

01:02

上午老黃是不是也去送生日禮物了呢

01:06

呃嚴格來說不算

01:08

但是稍微寬泛一點來說呢

01:10

問題不大

01:11

山姆奧特曼呢

01:12

是1985年4月22號生的

01:14

到4月25號呢

01:16

差個兩三天

01:17

給你補份生日禮物

01:19

補一份生日祝福

01:21

應該也算是應有之意吧

01:25

山毛特曼呢

01:26

算是一個非常根紅苗正的矽谷創業者

01:31

為什麼這麼講呢

01:32

他是在大二的時候

01:33

從斯坦福大學輟學的

01:36

比爾蓋茨輟學了啊

01:38

紮克伯格我印象裏好像也是輟學了

01:41

很多的創業者都輟學過

01:44

斯萊姆奧特曼斯坦福輟學啊

01:46

你輟學呢

01:47

就是聲明你能考得上斯坦福

01:49

否則你怎麼有機會從斯坦福輟學呢

01:51

讓了一半就突然創業

01:53

熱情熊熊燃燒

01:55

不能再念下去

01:56

了我要去創業

01:58

我原來也碰到過一位輟學創業的朋友

02:00

啊就是編程貓的創始人啊

02:03

他呢

02:04

是當時在法國一個學校裏面念碩士

02:08

也就是創新創業專業的一個碩士

02:11

到最後來

02:12

參加我們的這個創業比賽的時候說

02:14

哎呀再不創業就要畢業了啊

02:17

再不輟學就畢業了

02:19

當時講了這麼一句名言啊

02:20

我們記到現在

02:22

所以山伯奧特曼

02:23

是一個根紅苗正的斯坦福輟學創業者

02:27

那麼他講了幾件事呢

02:29

第一個

02:30

人工智慧的發展很快

02:33

說GPT4啊

02:34

已經指明了方向了

02:36

然後大家就去抄襲

02:38

抄襲是很容易的

02:40

他呢講的這個話並沒有說啊

02:43

穀歌抄襲了啊

02:44

還是蘋果抄襲了

02:46

而是什麼呢

02:47

GPT4啊他樹立了標準

02:50

樹立了標杆

02:51

然後呢各大廠商呢

02:53

就圍繞這些標準進行追趕

02:57

進行超越

02:58

這就是從GPT的發佈

03:00

以後的這一段時間裏頭

03:01

大家做的事情

03:03

你說我們現在做這麼多的模型測試

03:05

這個說

03:06

我今天在哪一個模型上超越GPT4了

03:08

明天在那個模型上說啊

03:10

我們在某一個特定場景裏超越GPT4了

03:12

那你說他們到底是怎麼幹的呢

03:15

其實都是有GPT4先出來了以後

03:19

然後再去在這個基礎上

03:21

設置克重的評測標準

03:23

PT4真正起到的作用呢

03:26

就是幫大家設立了一個標杆啊

03:28

你們按照GPT4的周邊

03:30

去設立評測標準啊

03:31

然後再去追趕

03:34

山奧特曼講了啊

03:35

說GPT4是一個很愚蠢的很尬的東西

03:38

你們現在不得不跟他去聊天

03:40

你說GPT5快出了嗎

03:42

GPT5會很強大啊

03:43

他已經講出這話了然

03:45

後講說這個縮放法則

03:48

也叫Grading low

03:49

依然沒有過時

03:51

依然有效

03:52

這個東西是什麼

03:53

就是隨著規模的擴大

03:55

數據的擴大

03:56

呃整個的性能或者結果

03:58

還是會繼續變好的

04:00

而人家會更嚴謹一些了啊

04:02

用我們的話講是什麼

04:03

就是當縮放法則依然成立的時候

04:06

就可以大力出奇跡

04:08

我可以堆更多的GPU

04:11

更多的數據進去

04:12

然後訓練出更好的模型

04:14

來跟大家講一個縮放法則起作用的

04:18

最現實的案例

04:20

比如說同1,000問

04:22

在拉瑪3出來以後

04:24

馬上又出了一個新的模型啊

04:27

原來統計千萬開放出來的模型是72B

04:30

但是拉瑪370B明顯的超越了

04:34

通1,000問72B

04:35

那麼通1,000問

04:36

應該就是在昨天還是前天

04:38

發了一個新模型

04:40

叫通1,000問110B

04:43

雖然我比拉瑪3的70B要大那麼一點點

04:47

但是呢

04:48

我的性能比他好啊

04:50

輸出的結果要比他強

04:51

各種的評測指標都比他好

04:53

再往後是什麼

04:54

再往後統一前面說了

04:55

我們準備出2.0

04:58

那麼在這個過程中

05:00

縮放法則到底是怎麼起作用的

05:02

你看拉瑪3出來了

05:03

70幣啊效果比我好了

05:05

那怎麼比我好的呢

05:07

拉瑪3

05:07

其實整個的訓練數據集是非常大的

05:10

就是他訓練70幣

05:12

雖然參數只有70幣

05:13

但是他數據集啊

05:15

要比現在咱們使用的正常模型都要大

05:17

非常多它的整個的訓練模型

05:20

數據品質都是很高的

05:22

它就可以得到70B

05:24

品質最好的這個開源模型

05:26

同1,000萬說不

05:27

我們即使不調整演算法

05:31

不調整數據品質

05:32

我只管增加模型參數

05:35

就可以達到拉瑪3

05:37

70幣的水準

05:38

他就出了一個110幣

05:40

而且拉瑪3說

05:42

我已經把該公開的公開了

05:43

指明方向了

05:44

你只要是用更多的數據去訓練

05:47

用更好品質的數據去訓練

05:49

你就可以訓練出像拉瑪這樣的模型來

05:52

同意千粉說

05:53

那我來了啊

05:54

我準備上通1,000問2.0

05:57

前面是我們在用的是通1,000問1.5啊

06:00

那麼2.0呢

06:01

大家可以想像

06:02

這一定會用更多的數據

06:04

更高質量的數據

06:06

就像拉瑪3那樣的數據

06:07

再去訓練

06:08

他就有可能在七十幾幣的這個模型下

06:12

可以超越拉瑪370幣

06:14

對吧

06:15

所以這個事情大家依然在同一個路上

06:17

再往前懟

06:18

或者你們管這個過程叫內卷都行

06:22

但是GPT5不一樣啊

06:23

GPT5上來以後會幹嘛

06:25

會樹立一大堆新的標杆

06:28

一大堆新的標準

06:29

在這些標準上

06:30

一開始就只有他一個人

06:31

然後再等著其他人慢慢往上追啊

06:34

這是人工智慧發展的很快啊

06:37

第二個講的是什麼呢

06:38

叫開源並不是一個好的途徑啊

06:41

因為很多人說哎

06:43

你open AI你怎麼不開源呢

06:44

特別是跟埃羅馬斯克吵了半天

06:47

埃羅馬斯克說

06:47

你應該把名字改成叫close AI

06:49

你不能叫open AI

06:51

這個肯定要回應一下了

06:54

那回應的方式是什麼呢

06:55

就是open AI的目標啊

06:57

不是開源

06:58

而是AGI叫通用人工智慧

07:01

讓機器可以像人一樣去思考問題

07:04

而我們並不認為

07:06

開源是更好的一個途徑

07:08

而是什麼呢

07:09

他認為免費

07:10

無廣告的GPT才是更好的途徑

07:13

因為什麼呢

07:14

開源了以後

07:14

真正能夠用開源代碼人

07:16

其實是很少的對吧

07:18

絕大部分人

07:19

是直接使用GPT去聊天的啊

07:21

而如果我能夠免費

07:23

無廣告的給大家用了

07:24

那麼這個不比開元效果更好嗎

07:27

他是這樣來去講這個事情

07:29

前面我去猜測過

07:30

如果GPT5出來以後

07:32

GPT4會不會免費

07:35

我覺得

07:35

從他現在講話的這個呃透的口風來說

07:40

這個可能性是存在的

07:42

而且很大

07:43

那麼GPT4一旦免費了

07:46

國內什麼文心藝言啊

07:47

這些付費的大模型

07:50

包括cloud 3這樣的模型

07:52

估計日子就不好過了

07:55

山姆奧特曼想要幹什麼呢

07:57

讓所有人都可以獲得人工智慧的服務

08:02

讓AI服務在全球範圍內

08:04

變得極其廉價和廣泛可用

08:09

我不知道這個全球範圍內

08:10

算不算中國啊

08:12

讓他立這個雄心壯志吧

08:14

那能咋辦呢

08:15

等哪天看山貓奧特曼到中國來

08:17

誰接見他吧

08:18

他應該沒來過吧

08:20

我印象裏是他沒來過啊

08:21

然後呢要消除不平等

08:24

現在很多做open AI

08:26

做AIGC的人

08:27

都在想去怎麼通過AI消除不平等啊

08:31

從這一點上來說呢

08:33

我個人表示不認可啊

08:35

為什麼我從來不認為工具的強大

08:39

可以消除不平等

08:41

工具越強大

08:42

不平等越厲害

08:44

搜索引擎出來的時候

08:46

大家就應該不會再上當受騙了

08:49

但實際上

08:50

搜索引擎對於各種的欺詐

08:52

一點碰觸都沒有

08:54

絕大部分人是不會去用的

08:56

哪怕搜索引擎是免費的啊

08:58

是每一個人都可用的

09:00

依然有很多人會去相信

09:03

各種街談巷議這樣的事情

09:06

所以我並不認為

09:07

AIGC就可以改變這個問題啊

09:10

那麼它如果免費的無廣告的

09:13

讓大家省差的GPT了

09:14

那這個錢的問題怎麼辦呢

09:16

啊他也講了

09:17

說燒錢啊

09:19

我就去燒啊

09:20

5億50億500億美金

09:22

我去燒去

09:23

無所謂啊

09:24

他覺得

09:24

我並不認為這是一個多大的事啊

09:26

那麼奧特曼也是很神奇啊

09:29

要只要我堅持下去

09:31

不斷的找錢

09:32

為社會創造價值就可以了

09:35

這個呢真的是顛覆很多人的認知

09:39

為什麼他不符合商業邏輯

09:42

他是一個反商業的過程

09:44

因為大家注意

09:45

這裏頭有一個很關鍵的一個字

09:47

叫什麼叫找啊

09:48

不斷找錢

09:50

穀歌是這麼幹的嗎

09:52

不是的微軟亞馬遜

09:55

任何一個互聯網巨頭或傳統巨頭

09:57

都不是這麼幹的

09:59

而現在他說我要去找錢

10:01

那麼找錢跟前面有什麼區別

10:03

前面的錢那叫賺錢

10:04

我賺了錢再去花

10:06

而且賺了錢花了以後呢

10:08

要量入而出

10:09

還要跟所有的股東去分紅

10:12

對吧這是傳統的商業模式啊

10:16

在互聯網之前

10:17

最早的商業模式是我造出一東西

10:19

你來買然後我去賺差價

10:21

或者我倒騰一東西

10:22

我從左手進右手出

10:24

我賺一差價

10:24

這是傳統的方式

10:26

互聯網呢

10:27

是已經在這個地方做了一個啊

10:29

進步了他是什麼呢

10:30

我分配流量啊

10:32

我來賺這個差價

10:33

賺這個流量費

10:34

對吧他找出一個新的到山茅

10:36

他班長說來哼

10:37

我燒錢創造社會價值

10:40

燒的錢我自己去找

10:41

最後怎麼能夠讓商業進行閉環

10:45

還是說整個商業的理論會再往前發展

10:49

讓整個的社會來為他去買單

10:51

這個事情啊

10:53

怎麼能夠讓他迴圈起來

10:54

我們還是要拭目以待這

10:56

個

10:56

確實是超出很多普通人的理解範疇了

11:01

關於創新和創業

11:03

他講了些什麼呢

11:05

啊他說

11:05

不要針對當前GPT4的缺陷

11:08

去做任何事情

11:09

在這塊去做專案的團隊

11:12

最後會被GPT5覆蓋掉的

11:15

甚至會被GPT6覆蓋掉

11:17

所以哪怕是GPT底層有什麼問題

11:19

你在這個基礎上做了些什麼東西修改

11:22

這事是不對的

11:23

跟大家講一小故事

11:24

就是我曾經有一次

11:26

跑去穀歌北京辦公室去吃早飯

11:31

當然目的不是吃早飯啊

11:32

目的是為了見穀歌大中華區

11:35

應該是香港那邊過來的

11:36

一位商業的負責人

11:39

當時在獵豹移動

11:40

給他去推薦獵豹移動相關的產品

11:43

希望能夠得到穀歌的一些扶持

11:46

啊他就問我啊

11:48

你們這個Cleanmaster是清理大師嘛

11:50

到底是清理記憶體啊

11:52

還是清理磁片啊

11:54

當然講的是英文啊

11:55

就是clean disc

11:56

oh clean memory

11:58

我們一堆人都去了

11:59

其他人沒聽懂啊

12:00

我的英文也很不好

12:01

但是我就突然反應過來了

12:03

這可能他們也在想

12:05

應該怎麼回答這個問題

12:06

其實clean master是兩個都清理的啊

12:08

但是我當時就靈機一動

12:10

一拍腦袋我就講了

12:12

我說我們只clean disc

12:13

絕對不碰memory

12:15

我們一起去的同事很詫異的看著我說

12:18

你為什麼會回答這樣的一個事情

12:20

我明明兩個都清理了

12:21

而且清理了記憶體才會有用戶體驗

12:24

才可以讓用戶覺得手機變快嘛

12:26

啊但是我就堅持說了

12:27

我們只清理硬碟

12:29

不清理記憶體

12:29

他們也不好意思來反駁我

12:31

畢竟是在外人面前嘛

12:33

哪怕是我說錯了

12:34

我在當時

12:35

級別也不高嘛

12:36

回去再收拾唄

12:38

但是呢這句話說對了

12:40

為什麼呢

12:41

穀歌的這位領導就跟我們講了

12:44

說你做的對

12:45

你就不應該去清理記憶體

12:48

那是安卓操作系統該做的事情

12:51

你不能鑒閱

12:53

如果你去清理記憶體

12:54

相當於是什麼

12:55

在安卓操作系統所控制的記憶體裏邊

12:59

去做了一些手腳

13:00

這是會對整個安卓操作系統

13:02

造成影響的

13:03

是會讓安卓系統的

13:05

整個的穩定性下降的

13:06

這事不該你管

13:08

安卓的硬碟管理是做的比較爛的

13:10

磁片管理比較爛

13:11

那麼你去把那那個清一清

13:13

這個是沒有問題的啊

13:15

所以呢當時不能叫龍顏大悅吧