Crazy Wisdom – Détails, épisodes et analyse

In this episode of the Crazy Wisdom podcast, Stewart Alsop speaks with Diego Fernandez, co-creator of QuarkID and the Secretary of Innovation for Buenos Aires. They discuss the future of innovation in Buenos Aires, focusing on how technology can simplify citizen interactions with the government and empower individuals through control over their identity with Web3. The conversation explores the potential of decentralized technologies like blockchain to transform government services and create new opportunities for innovation, especially in Argentina's unique economic landscape.

In the episode Stewart forgot the name of something about the innovation of digitizing real world assets in Argentina, see this tweet about the deregulation of warrants so that they can be handled online.

And for more on QuarkID, visit www.quarkid.org.

Check out this GPT we trained on the conversation!

Timestamps

00:00 Introduction to the Crazy Wisdom Podcast

00:13 Innovation in Buenos Aires: A Vision for the Future

01:34 The Role of Technology in Government

02:37 Web3 Technologies: Closing the Gap

05:29 Argentina's Unique Economic Resilience

08:53 Crypto Adoption in Argentina

11:25 The Impact of Inflation and Crypto Solutions

17:41 Argentina's Potential in the Web3 Era

27:40 Crypto Scene in San Francisco

28:20 Buenos Aires: A Hub for Crypto Innovation

29:04 Aleph's Pop-Up City and Economic Vision

31:04 Regulatory Changes and Crypto Opportunities

32:09 Decentralization and the Future of Money

32:47 The Role of Governments in the Digital Age

34:50 The Evolution of Money and Technology

38:02 Real-World Crypto Applications: Morphy Token

41:09 Decentralized Platforms and Censorship

41:57 QuarkID: Revolutionizing Digital Identity

45:21 The Future of Digital Identity and Privacy

51:22 Conclusion and How to Learn More About QuarkID

Key Insights

1. Innovation in Buenos Aires: Diego Fernandez emphasizes that the future of innovation in Buenos Aires is centered around making government services seamless and empowering citizens. He envisions a "WiFi-like" government where the state's presence is only noticed when something goes wrong, with a primary focus on streamlining interactions between citizens and government through technology.
2. The Role of Web3 in Identity: Web3 technologies, particularly decentralized identifiers (DIDs) and verifiable credentials, are set to revolutionize how individuals manage their identities. With QuarkID, citizens will have control over their digital identities, securely storing documents and credentials on their own devices. This shifts control from centralized entities like governments or tech giants to individuals.
3. Argentina’s Economic Resilience: Fernandez expresses optimism about Argentina’s future, calling its citizens "economic Navy Seals" due to their experience in dealing with decades of economic instability. He believes that Argentina's hardships have made its population more entrepreneurial, adaptable, and uniquely positioned to embrace blockchain and Web3 technologies to overcome economic challenges.
4. Web3’s Impact on Global Financial Systems: The episode highlights how Web3 technologies are poised to disrupt traditional financial systems by enabling peer-to-peer transactions of value and identity. In Argentina, where economic crises have pushed citizens to adopt cryptocurrencies, the use of decentralized financial tools is not only growing but also fostering innovation in industries like tokenization of real-world assets.
5. The Leapfrogging Potential of Argentina: Fernandez believes that Argentina has the potential to "leapfrog" other nations in developing new financial systems and infrastructure based on decentralized technologies. The country’s lack of entrenched financial systems, combined with its thriving blockchain ecosystem, provides an opportunity to build future-proof solutions that could serve as a model for other emerging economies.
6. Blockchain Startups Flourishing in Argentina: Argentina has become a hotspot for blockchain innovation, with notable startups like Decentraland, Ripio, and numerous others being created within the country. Fernandez is bullish on the growth of both centralized and decentralized financial products, as well as advancements in deep tech, especially in cryptography and zero-knowledge proofs.
7. Decentralization and Government’s Role: Fernandez draws a parallel between the separation of church and state and the future separation of money from the state. He argues that just as governments no longer control religion, they will eventually lose their control over money as decentralized platforms take hold. This change, driven by technological advancements, could fundamentally reshape governance and public services.

In this episode of Crazy Wisdom, Stewart Alsop chats with Ian Mason, who works on architecture and delivery of AI and ML solutions, including LLMs and retrieval-augmented generation (RAG). They explore topics like the evolution of knowledge graphs, how AI models like BERT and newer foundational models function, and the challenges of integrating deterministic systems with language models. Ian explains his process of creating solutions for clients, particularly using RAG and LLMs to support automated tasks, and discusses the future potential of AI, contrasting the hype with practical use cases. You can find more about Ian on his LinkedIn profile.

Check out this GPT we trained on the conversation!

Timestamps

00:00 Introduction and Guest Welcome

00:32 Understanding Knowledge Graphs

02:03 Hybrid Systems and AI Models

03:39 Philosophical Insights on AI

05:01 RAG and Knowledge Graph Integration

07:11 Challenges in AI and Knowledge Graphs

11:40 Multimodal AI and Future Prospects

13:44 Artificial Intelligence vs. Artificial Linear Algebra

17:50 Silicon Valley and AI Hype

30:44 Defining AGI and Embodied Intelligence

32:29 Potential Risks and Mistakes of AI Agents

35:04 The Role of Human Oversight in AI

38:00 Understanding Vector Databases

43:28 Building Solutions with Modern Tools

46:52 The Future of Solution Development

47:43 Personal Journey into Coding

57:25 The Importance of Practical Learning

59:44 Conclusion and Contact Information

Key Insights

1. The evolution of AI models: Ian Mason discusses how foundational models like BERT have been overtaken by newer, more capable language models, which can perform tasks that once required multiple models. He highlights that while earlier models like BERT still have their uses, foundational models have simplified and expanded AI’s capabilities.
2. The role of knowledge graphs: Knowledge graphs provide structured, deterministic ways of handling data, which can complement language models. Ian explains that while LLMs are great for articulating responses based on large datasets, they lack the ability to handle logical and architectural connections between pieces of information, which knowledge graphs can provide.
3. RAG (Retrieval-Augmented Generation) systems: Ian delves into how RAG systems help refine AI output by feeding language models relevant data from a pre-searched database, reducing hallucinations. By narrowing down the possible answers and focusing the LLM on high-quality data, RAG ensures more accurate and contextually appropriate responses.
4. Limitations of language models: While LLMs can generate plausible-sounding responses, they lack deep architectural understanding and can easily hallucinate or provide inaccurate results without carefully curated input. Ian points out the importance of combining LLMs with structured data systems like knowledge graphs or vector databases to ground the output.
5. Vector databases and embeddings: Ian explains how vector databases, which use embeddings and cosine similarity, are crucial for narrowing down the most relevant data in a RAG system. This modern approach outperforms traditional keyword searches by considering semantic meaning rather than just text similarity.
6. AI’s impact on business solutions: The conversation highlights how AI, particularly through tools like RAG and LLMs, can streamline business processes. For instance, Ian uses AI to automate customer service email drafting, breaking down complex customer queries and retrieving the most relevant answers, significantly improving operational efficiency.
7. The future of AI in business: Ian believes AI’s real-world impact will come from its integration into larger systems rather than revolutionary standalone changes. While there is significant hype around AGI and other speculative technologies, the focus for the near future should be on practical applications like automating business workflows, where AI can create measurable value without over-promising its capabilities.

In this episode of Crazy Wisdom, host Stewart Alsop is joined by Zach Rynes, known online as "Chainlink God," a community liaison for Chainlink. The conversation explores the critical role of Chainlink as a decentralized oracle network that connects blockchain-based smart contracts to real-world data, enhancing their functionality and enabling applications in DeFi, cross-chain interoperability, and beyond. The episode also touches on the broader implications of smart contracts for the legal system and the potential for blockchain technology to revolutionize financial markets globally, with a focus on developing countries and regions like Hong Kong. You can connect with Zach on Twitter at ChainLinkGod.

Check out this GPT we trained on the conversation!

Timestamps

00:00 Introduction to the Crazy Wisdom Podcast

00:25 Understanding Chainlink's Role in Blockchain

02:40 Interoperability and Its Impact on Cryptocurrency

05:10 Tokenization and Its Benefits

07:19 Chainlink's Global Influence and Future Prospects

09:51 Chainlink's Value Proposition and Investment Case

13:16 Exploring Oracle Networks and Computation Layers

23:07 Government Adoption and Future of Web3

26:20 China's Stance on Crypto

27:14 Crypto as an Alternative Financial System

28:41 Blockchain's Role in Developing Nations

29:51 Argentina and the AI Revolution

30:26 Understanding Chainlink

31:32 Challenges in Explaining Blockchain to Governments

32:13 Chainlink's Connectivity and Interoperability

33:27 Argentina's Economic Challenges

36:09 Personal Journey into Crypto

40:12 Smart Contracts and the Legal System

46:32 Future of Crypto Regulations

49:12 Conclusion and Final Thoughts

Key Insights

1. Chainlink as a Connectivity Solution: Chainlink plays a pivotal role in the blockchain ecosystem by serving as a decentralized oracle network, enabling smart contracts to access real-world data that blockchains inherently lack. This connectivity is crucial for the functionality of decentralized finance (DeFi) applications, particularly for providing reliable price data, cross-chain interoperability, and other external inputs that smart contracts need to execute properly.
2. The Evolution of Blockchain Use Cases: While Chainlink initially focused on DeFi and price data, the platform has expanded its use cases significantly. Chainlink now facilitates cross-chain asset transfers, connects institutional systems to blockchain networks, and supports various forms of tokenization, including assets like debt and equities. This evolution highlights the broad applicability of blockchain technology beyond its original financial use cases.
3. Smart Contracts and Legal Systems: Smart contracts have the potential to transform the legal system by automating agreements that can be objectively verified through data. While not a replacement for traditional legal frameworks, smart contracts can reduce the need for court arbitration by ensuring that certain contractual conditions are met programmatically, thereby lowering transaction costs and increasing trust in digital agreements.
4. Challenges of Blockchain Adoption in Developing Countries: Developing nations, often constrained by fragmented financial systems and lack of infrastructure, stand to benefit significantly from blockchain technology. Chainlink and similar platforms offer these countries a way to leapfrog traditional financial systems by creating more liquid and accessible capital markets, facilitating international trade, and providing a more transparent and trustless system for transactions.
5. Regulatory Barriers and Institutional Involvement: The adoption of blockchain technology by institutions is currently hampered by regulatory uncertainty. Despite the clear economic benefits, such as increased liquidity and reduced operating costs, institutions are often restricted by laws that have not yet adapted to the realities of digital assets and smart contracts. The hope is that as the financial benefits become undeniable, regulations will evolve to support broader blockchain adoption.
6. The Role of Chainlink in Computation: Beyond data, Chainlink is also positioning itself as a computational resource for blockchain networks. Through its Functions service, Chainlink allows developers to run decentralized computations off-chain, which can then be integrated into smart contracts. This approach complements on-chain processing by offering privacy and efficiency benefits, making it an essential part of the blockchain infrastructure.
7. The Global Race for Blockchain Leadership: Countries like Hong Kong and Singapore are emerging as leaders in the global blockchain race, driven by more favorable regulatory environments. These regions are capitalizing on the hesitation of Western nations like the U.S., which have been slower to embrace blockchain due to regulatory challenges. As these Asian markets grow, they could set a precedent for other nations to follow, making blockchain a central pillar of the global financial system.

In this podcast episode, the host, Stewart, is talking with Zach and Matthew, co-founders of Clay, a relationship management platform.

The conversation covers various topics including:

1. The Journey to Clay: Zach and Matthew discuss their journey of conceptualizing and developing Clay. They reveal the thought process that went into creating a product that could help manage relationships without reducing them to transactional entities.

2. Exploration of Clay: They delve into the workings of Clay, its AI assistant, and how it helps users manage their relationships. Clay has the capability to remind users of their connections, keep them updated with their social interactions, and help maintain the quality of their relationships.

3. Concept of Attention Economy: They talk about the notion of the attention economy and how it can be detrimental to our relationships. They also discuss how Clay can help users regain control over their attention.

4. Relationship with Nature: Stewart discusses his personal experience with his move from San Francisco to the country, and the challenges and learning experiences that came with it. He prompts the others to share their thoughts on the relationship with nature, and how it influences our relationship with ourselves. Matthew relates this to the idea of self-discovery and the inherent need for human connection with nature.

5. Adapting to Challenges: They discuss the challenges and "curveballs" of life, especially in the startup world, and how they adapt to them. Matthew highlights the importance of having a supportive co-founder and a solid team to weather the inevitable storms.

6. Future Plans for Clay: Zach and Matthew hint at upcoming features in Clay, including AI advancements. They invite listeners to check out the beta preview of these features on their website.

At the end of the conversation, Matthew emphasizes the importance of investing time in our relationships, not only in a professional context but also personally. He suggests that this investment offers a high return and could significantly improve one's quality of life.

Bart is the founding Guru at GuruScan | International Knowledge Management speaker | Makes Knowledge driven business decisions and helps enable the customers to do

https://www.linkedin.com/in/bart-guruscan/

Guruscan website

https://guruscan.nl/

• What is knowledge management?
  • Knowledge is a lot more than information
  • Information is content
  • Knowledge is explicit and implicit knowledge
  • Knowledge Management strategy
    • Shell
    • Connecting people to people,
    • Connecting people to content
    • Community of practice
    • Lessons learned, what did we do and how well did we do it?
    • Forward-looking thing: how can we integrate learning and development? Learn about where we want to go
  • This makes me excited to be a part of KM
  • Skills that are really hard to make explicit
  • Fingerspettein
  • Riding a bike, talk to someone about riding a bike
  • Keep on pedaling, look forward, and find your balance, these are all processes that can't be taught
  • You can’t read how to ride a bike
  • What percentage of knowledge for business is like riding a bike?
  • Specific use cases; a lot of research
    • 20% is explicit and 80% is actually stuff people are doing
    • Then not ending up in the final
    • 95% implicit in the particular case of tacit knowledge
  • Is the role
  • Thousands of people; how do you communicate with them
  • Complex environment and things are changing in
  • Solving complex problems is when you want to get people together
  • Prehistoric groups
    • There was cross-group and collaboration
    • Strangers interacting
    • 1-2 years now for
    • 10-15 years of experience as specialist
    • After a while, its interesting to hear how people have feelings about whether things are wrong
    • Intuition says something is wrong, and then finds the thing that is wrong
    • No textbook is going to tell you what is wrong
  • Concept is called Dunbar number, robert dunbar, British anthropologist
    • 150 people; the people with you can have a meaningful relationship
    • High school friends are replaced with work friends
    • Changes over time but the limit
    • Social grooming, what their parents are doing, what are they doing
    • If you want to expand you are not going to be
    • FDR had 44,000 people in
  • The level of leadership changes, and remote work
  • As a CEO of a 20K person company
  • Methods for
    • Organizational network analysis
    • Knowledge Map of the organization
    • Connect people with very similar of knowledge.
    • Find people to really like to exchange with
    • An idea is network
  • Bart is in Amsterdam
  • Not totally remote
  • Gitlab as an example
  • Remote work as asynchronous
  • Being able to work asynchronously in productive
    • Large organizations
      • Monday morning you have the standup
    • Large organizations in tons of synchronous meetings
    • Lockdowns the whole workspace
    • Feeling productive vs not feeling productive
    • Status report
    • Alignment and updating people
    • That's the big challenge
  • The furthest in Async first
  • Async needs to be changed
  • If you can’t have that meeting, what would you do?
  • Internal organization
    • A lot of people who make money running the organization
    • IIf you are up to 60 or 70 people because there is no overhead
    • If you need to arrange something you need to
    • Staff departments at 150
    • Institutional
  • Staff departments
  • Especially, growing the company as an incentive
  • How do you work smarter, not harder?
  • Our department
  • In organizations, the hard thing is to make sure that you don’t reduce complexity,
    • If you reduce the complexity
    • Requisite variety, adapt to all the changes that are coming from the outside of the world
    • Balance exploration and exploitation
    • If you don’t exploit then you don’t the money
    • Exploration is the future of the company
    • How much money, time, effort and people?
    • How much money should we invest in R&D?
    • Insane amounts of money
    • Every company should do in more exploration
    • Changing processes is usually not considered R&D
    • Changing your organization to better fit future
  • Political aspect
  • Produce 50 or 60% of all the semiconductors
  • Flat screens
  • LED lights have semiconductors
  • European Union has different regulations
    • Huge fabrication tension of where
  • ASML
    • TSMC
    • The flow of money spent on the
    • Governed by Moore laws
    • The number of transistors on a square meter would double every year
    • Fit the developments into the computer chips
    • Pentium processors went faster than Moore’s laws
    • How many people work in semiconductors?
    • Ultraviolet lights
    • Collaborations
  • Semiconductor stuff, how to do the knowledge management?
    • Work together with SAIS, German lens company
    • SAIS maybe made an investment in that
    • Seimer integrating with the equiptment
    • Global recruiment that they do
    • Optical engineering
    • Thats the most important thing
    • With customers and suppliers
    • Crash in 2009 and 2020
    • Apple, Intel, and Samsung
    • Flagship model
    • The chain is so fragile

Matt Bunday works in crypto. He loves to rock climb, martial arts, and think about underground psychedelic therapy

1. What is the biggest problem you’ve faced with knowledge management at your companies?

   1. Slack 

   2. Dropped balls in communication

   3. LLMs might be the response

2. Why do you think slack spread so fast even though its not the best product?

   1. It was a step up from email

   2. IRC was a component

   3. More friendly for non-engineering

3. What do you think about the complexity of slack?

   1. Twist is an alternative

4. Why is information architecture such a challenge?

5. How do LLMs fit into this?

6. What would happen if slack created a LLM or plugged one in?

   1. Slack workspace plug in

7. What is a retrieval plug in?

   1. Universal adapter for any type of data

8. Who are the incumbents in the slack knowledge management space?

   1. Guru startup

9. What is the difference between information management and knowledge management?

   1. Knowledge management is a higher level synthesis

   2. Information management is siloing related types of information

      1. Data types 

      2. Group related to information around people

10. What are your thoughts on the membrane?

    1. Siloes

    2. Privacy is where LLMs can be very innovative

    3. If we were to share a LLM

    4. We can both specify a privacy policy to the LLM and it will follow it

    5. LLMs can intuit the privacy public distinction

11. Are you using LLMs to code for you?

    1. Copilot

       1. Issues with difficulty to prompt it correctly

       2. You had to write comments to prompt it

       3. Inline suggestions were not good

       4. Is it better now?

          1. Haven’t noticed a dramatic improvement

       5. Hard to prompt it to code in certain styles now

    2. GPT 4 is way better for a starting off point for projects

       1. Helpful for conversion processes

12. What are the things that GPT4 has not been helpful for you?

    1. You have to chunk it

13. What about building systems with GPT4?

14. Code completion cool called tap9

    1. Train the model against your local code

15. What are some other things about KM that we can use tools for?

    1. Shared LLM for the family

    2. Surface serendipity between users

    3. If facebook were to do this

       1. One person says they are selling a couch

       2. One person is buying one

       3. LLM connects them

16. At what point do we merge with the machines?

    1. Sufficiently high bandwidth

    2. Translation

17. Are we already cyborgs?

    1. It began with wearing shoes

    2. Horselike

18. Where do you fit in the excitement vs fear when it comes to AI?

19. What parts of knowledge work will get automated?

20. What are we losing?

21. What is your take on bodywork?

    1. 10% investment

    2. Martial arts practices, he gets beat up 

    3. Ninjiutsu

       1. Special forces for ninjas

    4. Healing and striking points on the body are the same

    5. Balance between healing/killing, if you know how to heal

    6. Unbroken transmission since 1400

    7. What is the importance 

Zohar Atkins

He is a rabbi, philosopher, blogger and podcaster. His podcast is called Meditations With Zohar

Show Notes

1. Who is your favorite philosopher?

2. What is non-aggressive socratic questioning?

3. Why do you like Heidegger?

   1. How was he Nazi-ism

4. How do you relate to the history of philosophy?

5. How do you walk the line between tradition and being a revolutionary?

6. What was your first experience learning for yourself instead of learning top-down?

7. What does it feel like to have a hunger for learning?

8. What happens when we decide we are going to learn everything and then run into the block of only having so much time?

9. How do you relate to patience when confronting the weird language of philosophy?

10. How do you define good communication?

11. What is the value of incomprehensibility?

12. How important is banging your head on the wall?

13. Who is a philosopher that you think is a fraud?

14. Was Jesus a philosopher?

15. Do philosophers build truth structures?

16. What is hagiography?

17. What is your philosophy of technology?

18. How is Socrates exceptional?

19. Where do philosophy and religion meet?

20. What happened to the public intellectual?

21. Was Wittgenstein religious? 

22. How was Wittgenstein obsessed with language?

23. What is your take on rationalism?

    1. What about scientism?

24. What is the job of philosophy?

25. Why are most people not interested in philosophy?

26. Who is Leo Strauss?

    1. Philosophy is opposition to the state

    2. What happens when the state get too powerful and the philosophy gets crowded out?

27. What is the dominant philosophy of the US in the 20th century?

    1. Pragmatism

28. What was the difference between philosophy and science for ancient philosophers?

29. How is philosophy a technology?

30. How is UX a strain of phenomenology?

31. What is the feedback cycle between technology and philosophy?

32. What is the problem of induction?

    1. Aristotlean is ok with doing case studies

    2. Deductionism leads to cancelling all the case studies

33. What defines the modern essence of technology?

34. What happens when humans commoditize themselves?

35. Without technology why can’t most understand leisure?

36. How does Science doesn’t think?

37. How did the original science people become more humble about the origins of science?

38. How does achievement distract from the question of meaning?

39. Why don’t you think Scientism is a big deal?

40. How is Scientism is bad for religion?

41. What is your take on new age occult stuff?

42. Irrationalism sees with a squint to what rationalism is blind

43. How can we become open to the strangeness of the universe?

44. How can we be epistemologically humble?

AJ is a software engineer interested in Urbit and data composability. 

Twitter: https://twitter.com/ajlamarc

https://www.ajlamarc.com/

Keep an eye out on Holium, and making it easier to code in Javascript for Urbit

Notes

1. What is data composability?

   1. Multiple applications sharing data and make the interfaces work together

   2. OpenAIs that both Twitter and Facebook had and then were shut down

   3. Data is the main product that these applications have

   4. You can separate the data and the code

   5. Personal AI

2. How did we get to such a fragmented application landscape?

3. Legacy internet vs New Internet?

4. What is AJ working on?

   1. TomeDB

   2. Javascript package

   3. Associated gall agent

   4. NoSQL database

   5. The front end side is the interesting part

5. What are gall agents?

   1. Standardized backend of Urbit

   2. Rules for moving data between different servers and accounts

6. What are you looking for in a backend?

7. Why are you reinventing the wheel when building a new urbit backend?

8. What is the promise of urbit?

9. What is the main draw of urbit?

10. What does it mean to be permissionless?

11. Urbit brings the best out of the past

12. How much data is stored when you host your urbit on the cloud vs your own database?

13. What are the technical limitations that an Uribit can store?

    1. 4-8 GBs can be stored and its stored in RAM

14. How long until we have video streaming on Urbit?

15. What is your take on where AI and Urbit mingle?

16. How do you have an AI work for you rather than a big corporation?

17. Urbit is creating a virtual world where you get only what you want and little of what you want

18. The success of Urbit is the apple OS with the next generation of software

19. How do you get the cost down?

    1. How do you run an urbit inside an urbit?

20. What is the main difficulty of scale for computing on the cloud?

21. If a million people join urbit tomorrow would it break?

22. What is the biggest scale that Urbit has seen?

    1. 1-2K people

23. What is the new narrative of Urbit?

24. How do you use urbit as a really simple use case that urbit can solve to start getting urbit adoption?

    1. How do you store data and transfer it between two people in a secure way?

25. Urbit as an infrastructure that can help build infrastructure

    1. There has to be the normal infrastructure that we are used to in terms of databases and networking 

    2. Urbit is mostly a backend technology

    3. Urbit could eventually have HOON native AI

26. Did you use crypto to pay for anything in El Salvador?

27. What did you learn at the Volcano Summit in El Savlador?

28. Logan’s talk on Zorp using Knock

Dave Snowden is the Chief Scientific Officer of Cynefin. Head of Knowledge Management for 30 years.

Author of Cynefin - Weaving Sense-Making into the Fabric of Our World (https://tinyurl.com/4958x362)

1. When did knowledge management start in the 90s?

   1. The ultimate disciplinary field

2. What is intellectual capital?

   1. Intellectual property

3. What is the anarcha book?

4. Knowledge management is information management

5. What is relevant knowledge?

6. What is messy coherence?

7. What is exaptive innovation?

8. How do you add value to organizations?

   1. Focus

9. What is the difference between teleological idealism and realism?

10. What is the KM process?

    1. Find out what is keeping middle management awake at night

    2. Do not want to be a CEO pet project

11. How do you map what a company already knows?

12. How do you map current knowledge from the things that keep people awake at night?

13. Where are we on the cycle now?

    1. At the early stage of the hype cycle

14. What is complexity theory?

15. How do you map the unknown unknowns of a company?

16. How do you create resiliency within an organization?

17. How do you build informal networks across the organizations?

18. European field guide on complexity management

19. Does getting involved with tactics take away from strategy?

20. Trying to make the cost of virtue greater than the cost of sin?

21. How has knowledge management changed with Covid and remote work?

22. How do you replicate pheromones in a remote environment?

23. What are hexis?

24. How does knowledge transfer work?

25. How do you make decisions that keep options open?

26. How do you create processes that stop ambiguity?

27. Why are stories of linear processes greatly exaggerated?

28. How do you deal with too much information?

    1. Focus on connecting people and storing information

29. Entangled trios with task from different groups

    1. Run that every three months

30. Secret is not to take an information centric approached

31. Knowledge is only ever volunteered, not conscripted

32. We always know more than we can say and we can always say more than we can write down

33. What is necessary ambiguity?

34. What is the role of narrative when it connects tacit to explicit information?

35. Narrative asks you questions that make you think differently

36. Lessons learning rather than lessons learned

37. 90% of knowledge is walking out the door

38. The danger of machine learning is dumbing down how we know things

39. THE RIGHT SOURCE DATA IS THE KEY

40. Machine learning is inductive 

41. Feed ML better training data

42. How did you get the role at IBM at knowledge management?

43. Institute for knowledge management at IBM

44. IBM center for complexity studies 

45. How do you measure knowledge management?

    1. outcome/ouput measures

       1. Fine with predictable systems

    2. Outcomes produce a perverse incentive

    3. Vector measure for intensity of effort

    4. How do you structure KPIs?

46. What are the power dynamics of exchange?

47. Fear of abuse is the main reason people seek knowledge in organizations

48. Art comes before words before human language

49. Semiotics is symbols and signs

    1. UK is the most mapped country in the world

50. We need renaissance instead of an enlightenment

51. What is catholic with a small c?

Adam is the 

• VP of engineering at Invisible Technologies and active angel investment
• If you have specific questions, send them on to Adam@invisible.co

• How do you organize information and data in order to spend most of your time on high-level work?
• How do you manage people who report to you to also do the same?
• What does knowledge management mean to you?
• What are the applications that will leverage LLMs?
  • What is an intranet?
  • Transition from card catalog to Google
• How do you take structured things and make them unstructured?
• Can LLMs do unstructured data?
• What is tabular data?
• Who is going to shine when it comes to leverage LLMs?
• How do LLMs hallucinate?
• How can we prevent LLMs from hallucinating?
• What would happen to a law firm that has an LLM that hallucinates a contract?
• What happens when NYC opened up all its APIs?
• What is data availability?
• Will LLMs have big moats? (13 minutes in might be when we get too close to OpenAI)
• What will happen with LLama from Meta?
• What has been overhyped in terms of LLMs?
• Have you started to use Copilot in your own programming?
  • Reference tool rather than programming aid
  • LLM code has a higher security risk
• What is your take on AI ethics?
  • How do you deal with collective commons type of stuff?
  • How does bias training come into play?
  • How do we think about the implicit biases that the models have been trained on?
• How does technology help us to understand ourselves?
• How is technology an amplification of human ability?
• What is the frustration of knowledge management for you?
  • Bot at Facebook that goes through and warns people when something needs to be updated
  • Finding something and its wrong
  • How do we make sure that information stays updated and relevant
• What is the curse of knowledge?
  • Onboarding is testing the system
• How should we think about knowledge leakage?
• Does Notion have an API?
• Keep metrics on how much people are writing
• What were some ways that Facebook excelled at knowledge management?
  • Investment in search tools
  • Code documentation
  • Chat bot messages
    • scale of 1-10 how do you feel
    •  
• What are the barriers that we have at invisible to implementing great search?
• What is the issue with implicit knowledge at Invisible?
• What is status hero?
• 8 or 9 engineering teams at invisible
• When there is high trust all processes work and when there is low trust no processes work
• What is the biggest problem going to be for me as knowledge management guy?
• How can we bring spaced repetition software into Invisible?