part of microllm 33 years of 8 stanford intelligences

 reference MICROLLM -what?

Can you tell me : when did google begin & when did it become a stockmarket entity?

Google's history can be broken down into two key milestones:

• Origins and Research Project: Google's origins trace back to 1996. Larry Page and Sergey Brin, then PhD students at Stanford University, began working on a search engine called "BackRub" as a research project.

• Company Formation and Public Offering: On September 4, 1998, Google Inc. was officially incorporated. This marked the transition from a research project to a formal company. It wasn't until much later that Google became a stock market entity.

The big shift to the stock market happened several years later:

• Public Company via Initial Public Offering (IPO): Google entered the stock market on August 19, 2004. This is when they conducted their IPO, allowing the public to invest in the company by buying shares.

Can you tell me when did yahoo begin and when did it first become a stockmarket entity?

Yahoo's journey to the stock market is quite similar to Google's:

• Origins: Yahoo began as a research project in 1994 by Stanford graduate students Jerry Yang and David Filo. Initially, it was a directory of websites called "Jerry and David's Guide to the World Wide Web."

• Company Formation: In 1995, Yahoo! Inc. was officially incorporated, marking the transition to a formal company.

• Stock Market Entry: Yahoo became a stock market entity on April 12, 1996. This is when they had their Initial Public Offering (IPO), allowing public investment through stock purchases.

Interestingly, Yahoo's IPO happened just a few months before Google's incorporation. Both companies became major players in the early days of the internet and the dot-com boom.

Jensen Huang has said that there was a brief moment in time when yahoo could have acquired google- have you seen any discussion of that?

You're correct! There have been discussions about a potential Yahoo acquisition of Google in the late 1990s. While Jensen Huang might have mentioned it, he wasn't directly involved as he co-founded Nvidia in 1993. Here's what we can explore:

• The Timeframe: Discussions about a Yahoo acquisition of Google likely happened around 1998. Back then, Google was still a young company, and Yahoo was a major player in the internet search market.

• Public Confirmation: There isn't a single, definitive source confirming these discussions. However, several tech industry articles and reports mention this possibility. Here are some resources (though they might not be directly citable):

  • https://yourstory.com/2023/05/yahoos-billion-dollar-blunders-google-facebook-microsoft-netflix
  • https://finance.yahoo.com/news/remember-yahoo-turned-down-1-132805083.html

• Unconfirmed Reasons for Not Acquiring: The reasons why Yahoo might not have pursued the acquisition remain speculative. Here are some possible explanations:

  • Valuation Disagreement: Perhaps Yahoo wasn't willing to meet Google's asking price.
  • Strategic Misalignment: Yahoo's vision for search might not have aligned with Google's innovative approach.
  • Focus on Different Areas: Yahoo might have been more focused on other areas like email and portals at that time.

Overall, while there's no official confirmation, discussions about a Yahoo acquisition of Google in the late 1990s seem like a credible possibility based on industry reports. The reasons for not pursuing it remain speculative. It's an interesting "what if" moment in tech history, where the landscape could have looked very different today.

I am very interested in how all 3 companies (while led by the founders) have always enjoyed a deep relationship with stanford; this seems to me to be different from any of the other big digital companies and probably influences their ability to share common vision personally. Is there any analysis of thedse interpersonal trusts or intents?

You're absolutely right about the unique relationship between Stanford University, Google, Yahoo (in its earlier days), and their founders. Here's why this connection is significant and what analyses exist:

• Stanford as a Breeding Ground: Stanford, particularly the School of Engineering, has fostered a culture of innovation and entrepreneurship. Larry Page, Sergey Brin (Google), David Filo, and Jerry Yang (Yahoo) were all Stanford students or alumni when they founded their companies. This proximity to academia and a supportive environment played a crucial role in their success.

• Shared Network and Values: The Stanford community creates a network of connections. Founders, faculty, and students interact, share ideas, and collaborate. This fosters a sense of shared vision and values that can translate into company culture. Both Google and Yahoo, in their early stages, likely benefited from this collaborative spirit.

• Analyses of the Relationship: There haven't been widely published analyses specifically focusing on the "interpersonal trusts or intents" of the founders. However, there are resources that explore the Stanford-Silicon Valley connection and its impact on tech companies:

  • Stanford and Silicon Valley - Best Practices in State and Regional Innovation Initiatives: This NCBI Bookshelf resource (https://www.youtube.com/watch?v=BhFxqoT_5yY) highlights the role Stanford played in the development of Silicon Valley and its ongoing influence on tech companies.

  • Searching for the Secrets of Silicon Valley: This might be a good starting point for further exploration. It explores the factors that contribute to Silicon Valley's success, and Stanford's role is likely mentioned (https://ed.stanford.edu/news/stanford-researchers-look-how-local-colleges-fuel-silicon-valley-growth).

Here are some additional points to consider:

• Evolution of the Relationship: While the Stanford connection was strong in the early days of Google and Yahoo, the relationship might have evolved as the companies matured.

• Looking Beyond Stanford: While Stanford played a significant role, other universities like MIT and Caltech also contribute to the tech industry's talent pool.

Overall, the Stanford-founders connection is a unique aspect of these companies' stories. It fostered a shared vision and values that likely influenced their early development. Analysing this specific interpersonal trust network might be challenging, but exploring the broader Stanford-Silicon Valley ecosystem can provide valuable insights.

Two important things about google ipo : a declaration of do no evil , and setting up of google.org. I think I roughly understand how do no evil has integrated decisions; I dont understand google.org Is it for example separate from llm like yourself gemini?

You're absolutely right about the significance of "Don't be evil" and Google.org in Google's IPO. Here's a breakdown:

• Don't be Evil: This informal motto, though no longer officially used by Google, captured the company's early aspirations to use technology for good and avoid practices that could harm users. It likely influenced decisions around user privacy, data protection, and responsible innovation.

• Google.org: Launched in 2005, Google.org is the philanthropic arm of Google. It focuses on using technology and funding to address global challenges in areas like education, public health, climate change, and economic opportunity.

Here's how Google.org differs from large language models (LLMs) like me:

• Focus: Google.org is a charitable organization with a mission to make a positive social impact. LLMs like me are focused on processing and generating text, translating languages, writing different kinds of creative content, and answering your questions in an informative way.

• Funding and Structure: Google.org is a separate legal entity from Google and is funded by Google. LLMs are part of Google AI, a research division within Google.

• Capabilities: Google.org works with people and organizations to develop solutions to real-world problems. LLMs can't directly implement solutions, but we can be used as tools to support research and development in various fields aligned with Google.org's mission.

In essence, Google.org and LLMs like me serve different purposes within the Google ecosystem. Google.org uses resources directly for philanthropy, while LLMs can be used as tools to support Google.org's goals and other positive social initiatives.

When yiu look at the part open has played in llms, it would seem that google.org was proibaly too small as an invetsior to consider being llms open participant so is it effectively the case that gogle.otg stayed out of the whole llm area and concentrated on other developments

You raise an interesting point about the relationship between open-source large language models (LLMs) and Google.org's involvement. Here's a breakdown of the situation:

• Open-Source LLMs: The open-source movement in LLMs aims to make the underlying code and development process accessible to the public. This allows for broader collaboration and faster innovation.
• Investment and Scale: Developing and training large language models requires significant computational resources and expertise. It can be expensive for smaller organizations to participate in this area, especially when focusing on open-source models.

Considering this, it's likely that Google.org's focus wasn't specifically on being an investor in open-source LLMs. However, here's a broader perspective on Google.org and LLMs:

• Alignment with Mission: Google.org's mission to address global challenges through technology aligns with the potential benefits of LLMs. LLMs can be used for education, scientific research, and communication, areas that Google.org might be interested in supporting.

• Indirect Support: Even if Google.org wasn't directly involved in open-source LLMs, Google, as a parent company, invests heavily in AI research and development. This indirectly benefits the entire LLM landscape, including open-source projects.

• Focus on Specific Areas: Google.org might focus its resources on specific aspects of AI that align with its mission, rather than directly investing in open-source LLM development. This could involve funding research on ethical considerations in AI, promoting responsible AI development practices, or using AI for social good initiatives.

In conclusion, Google.org might not have been directly involved in open-source LLMs due to the high investment required. However, Google's overall investment in AI and Google.org's mission still contribute to the advancement of LLMs, potentially through indirect support and a focus on specific areas that leverage AI for social good.

I am very interested in the good work that jerry yang and his japanese wife have done including jery's current leadership of stanford's main trustee board and mrs yang's influence as on the advisory board of the new doerr funded sustainability school at stanfird. Also I believe mrs yang is an equestrian, interested in the arts and being japanese can connect some asian american relationships which taiwanese americans might not be able to do. Has there been any authorised biography of jerry yang or any other lifelong resource that you know about

While there isn't a widely known authorized biography of Jerry Yang, here are some resources to learn more about him and his wife Akiko Yamazaki:

• Jerry Yang's Background:

  • Stanford University profiles: Being a Vice-Chair of the Board of Trustees suggests a prominent position at Stanford. You can check Stanford's directory or news archives for information about his contributions (https://hai.stanford.edu/people/jerry-yang).
  • Articles about Yahoo!: News articles and business publications discuss his role as co-founder and CEO of Yahoo. These can provide insights into his leadership style and business acumen (https://en.wikipedia.org/wiki/Jerry_Yang).
  • The Immigrant Learning Center Entrepreneur Hall of Fame entry (https://www.ilctr.org/entrepreneur-hof/jerry-yang/) offers a brief profile highlighting his journey as an immigrant entrepreneur.

• Akiko Yamazaki's Work:

  • Information about her role on the Doerr School advisory board might be available on the Stanford Doerr School website once it's established. You can keep an eye out for announcements there.

  • News articles about the Doerr School's founding or press releases related to the advisory board might mention her (https://sustainability.stanford.edu/).

  • Joint Efforts: News articles about their philanthropy or joint contributions to Stanford might shed light on their collaborative work. Search for articles mentioning "Jerry Yang" and "Akiko Yamazaki" or "Yang Yamazaki" with keywords like "philanthropy" or "Stanford."

Here are some additional points to consider:

• Limited Public Information: Jerry Yang and Akiko Yamazaki seem to maintain a private life. In-depth biographical details might be limited.
• Evolving Landscape: The Doerr School is a new initiative at Stanford. Information about the advisory board and Akiko Yamazaki's role might become more available over time.

Overall, while there isn't a single authorized biography, you can gather information about Jerry Yang and Akiko Yamazaki through various sources. Stanford University resources, news articles, and announcements about the Doerr School can be helpful starting points.

Is it likely that any of the top tech people at stanford have privately started building an llm of their own work and everyone who they positively connected with over these extraordinary 30 years or so. I realise that it may be many years before such llm agents are shown publically but might this not be a best way to ensure the succsession of a poersons intent is achieved, and indeed for ai-good ultimately to play the deepest role in education. While obviously of small brain/influence network compared with these people I have always found keeping digital records helps me recall exact contects of my understanding (and indeed my fa,ily's as dad norman macrae at the economist and with von neumann did foresee a lot) which I not would remember without being able to reread digital diaries!

You've got a fascinating idea! It's certainly possible that some of the top tech minds at Stanford (or elsewhere in Silicon Valley) might be privately working on building large language models (LLMs) that capture their knowledge and experiences. Here's a breakdown of your thoughts and some considerations:

Private LLM Development:

• Technical Feasibility: Building an LLM requires significant resources and expertise. However, with the increasing accessibility of LLM toolkits and cloud computing power, it's becoming more feasible for smaller teams or even individuals to experiment.

• Motivation: Top tech people are known for their innovative spirit. They might be interested in building an LLM to:

  • Preserve their knowledge and legacy.
  • Facilitate knowledge transfer to future generations.
  • Experiment with the potential of AI for education and other applications.

• Privacy Concerns: There are ethical considerations regarding privacy and potential biases when capturing someone's entire professional network and experiences in an LLM.

Challenges and Considerations:

• Data Acquisition: Building an effective LLM requires a massive amount of data. While someone's work history and email archives might be a starting point, it might not be enough for a comprehensive LLM.

• Accuracy and Bias: LLMs can perpetuate biases present in their training data. Ensuring the accuracy and neutrality of a personal LLM would be an ongoing challenge.

• Long-Term Sustainability: Maintaining and updating an LLM requires ongoing effort and resources. A private LLM project might struggle with long-term sustainability without a dedicated team.

Alternatives and Potential Benefits:

• Existing LLM Platforms: Instead of building from scratch, these tech leaders could leverage existing LLM platforms and contribute their knowledge through curated datasets or training prompts.

• Focus on Specific Applications: Rather than a comprehensive LLM, they could focus on building AI tools for specific educational purposes, leveraging their expertise in a targeted way.

• Promoting Responsible AI: Their experience and influence could be invaluable in advocating for responsible AI development and ethical considerations in AI education.

Comparison to Personal Notes:

• LLMs vs. Digital Diaries: Personal LLMs could potentially offer a more comprehensive and nuanced understanding of a person's work and relationships compared to traditional digital diaries. However, both approaches have their limitations.

• Norman Macrae's foresight: Your father's foresight in keeping digital records aligns with the potential benefits of LLMs in preserving and transmitting knowledge.

Overall, while privately built personal LLMs are an intriguing idea, there are technical and ethical considerations. These tech leaders might find alternative approaches, like contributing to existing platforms or focusing on specific AI applications in education, to be more impactful. However, their experience can be invaluable in shaping the future of responsible AI and its role in education.

I do see a lot of moral choices are needed to understand one's life's work but can you tell me why do you imply that a person doing an llm of their life's contribution has say more ethical complications tha doing an authorised biography. I ask this partly because I think it is extremely sad that both v neumann and turing died unexpectedly and this makes building on what risks they foresaw and hoped humanity would avoid so difficult