Crazy Wisdom

Introduction In this exciting episode of the Crazy Wisdom podcast, we are joined by Tim Wood Powell, an innovator, catalyst, author, and speaker whose motto is "Let's make our Knowledge work!" Tim is the founder of the Knowledge Agency and author of the book The Value of Knowledge. This episode is packed with insightful discussions around the realm of knowledge, its role and value in business, and the challenging aspects of measuring intangibles. Notes Understanding Knowledge The discussion kicks off by probing the question, 'What is knowledge?' An intangible asset with no weight, its definition and measure become particularly complex in a business setting. Tim explores his insights from his experience in the music business and recounts a copyright dispute over a song. The Benefits and Challenges of Knowledge Tim shares his views on how knowledge benefits us by bringing in perspectives from psychology and philosophy. But in the business world, where there's a constant pursuit to measure the immeasurable, knowledge can be a conundrum. The current accounting systems are designed to measure tangible assets, but they fall short when it comes to intangibles. This poses challenges, especially in today's knowledge-driven work environment. Tangible to Intangible: The Journey With real-world examples, Tim illustrates how we've moved from tangible to intangible assets and discusses their role in creating business value. From IP sales of bankrupt companies to branding strategies for products like tobacco, Tim provides insightful commentary on the value and paradox of intangibles. Knowledge and Business Performance Tim delves into how companies must create their own metrics to assess intangibles despite existing accounting systems. He speaks about the role of knowledge in buffering business risks, managing uncertainty, and aiding decision-making processes. He discusses the importance of decision-making in a world that is increasingly algorithmic. The Role and Value of Knowledge Management (KM) Tim narrates the ups and downs of knowledge management through various business cycles. He explains the concept of 'time value of knowledge' and how the value of an asset is always changing. The conversation then moves towards understanding the value dynamics in a business and the role of KM in managing these dynamics. What do KM Workers do? The discussion then shifts towards understanding the role of KM workers and the challenges they face. He talks about the shift from information search to knowledge resources management and the difficulties faced due to lack of standardization and resources. He also gives insights into how KM can help organizations deal with uncertainty and manage complexity. Technologies for Sharing Information Tim discusses the benefits and challenges of technologies used for sharing information. He talks about issues related to governance, the importance of standardization, and the role of network and relationships in implementing technologies. Findability on Enterprise Search Towards the end, Tim shares his experiences as a client and how the needs of users have evolved due to Google. He stresses the importance of knowing what resources are available and what are needed, and how generative AI might help in the future. Websites/Books Mentioned Tim Wood Powell's Website The Value of Knowledge High Tech Marketing Machine Knowledge Value Chain Team of Teams book People Mentioned Fritz Maclow Professor Sid Winter Don't forget to check out Tim's book and his work at the Knowledge Agency to delve deeper into the fascinating world of knowledge management and business strategy!

Episode Introduction: Welcome to another insightful episode of Crazy Wisdom, where we delve into fascinating discussions around philosophy, technology, and everything in between. Today, we are delighted to host Saman Farid, a visionary who is working on an ambitious project of supplying the world with a robot workforce through his company, Formic. In this episode, we navigate through a range of topics from the evolution of societies to robotics, AI, industrial revolutions, and the changing face of human labor. Show Notes: Formic's Foundation: Formic, named after the Latin word for ants, is a reflection of Saman's philosophy of collective efficiency and productivity. Influence of Literature: Saman drew parallels between Formic's mission and elements from Orson Scott Card's "Ender's Game" which is where the name Formic is drawn from Human Progress & AI: The conversation delves into the history of human progress and the implications of AI, drawing from phases like the Paleolithic era, agricultural and industrial revolutions, to the current digital age. Labor Shifts: Saman touches on the shift from manpower-heavy jobs to more digital and AI-related roles. He addresses the fear surrounding job loss and the need to fill undesired roles through robotics. Revitalizing Manufacturing: Discusses the potential resurgence of manufacturing through advanced technology like GPT and robotics. Challenges of Robotics Adoption: Saman shares insights on the low adoption rate of robotics in factories and the hurdles that prevent companies from leveraging this technology. Role of Robotics: Details the functionalities of the robots being built at Formic, including tasks such as palletizing, inspection, and machine welding. Redefining Labor & Purpose: The conversation explores the moral and societal implications of automating repetitive jobs and how it might impact individuals' sense of purpose and identity. Individual and Collective Purpose: Saman discusses the dichotomy between individual and collective purposes, arguing for a balance of individuality and unity. Motivations behind Formic: The journey and vision behind Formic, from the excitement of building something new to the satisfaction of seeing the products in use. Humanity and Tool Use: The conversation examines the idea of humans as tool users and the role of technology in shaping human identity and experience. Fears and Hopes for the Future: The dialogue closes with Saman's thoughts on future shifts in societal perspectives, changes in labor dynamics, and the role of engineers in creating utopian futures. Media Mentioned: Bloomberg Article: "The US is building factories, but who will work there?" Book: "Project Hail Mary" by Andy Weir. Company Website: Formic Saman's Twitter

Introduction Welcome to this deep dive into the world of Large Language Models (LLMs) and vector databases for the Crazy Wisdom Podcast. Our guest today is Eden Marco (follow him on Twitter), a Customer Engineer at Google Cloud and a best-selling Udemy instructor with a passion for General Artificial Intelligence (GenAI). In this episode, we unpack the complexities and intricacies of LLMs, explore the role of vector databases, and discuss the future of autonomous agents and machine learning. Key Discussion Points Vector Databases & Similarity Search: Vectors play a critical role in similarity searches, a common use case in vector databases. These databases are pivotal in developing LLMs and help in getting the right context to prompts. They are also used to truncate long pieces of text into paragraphs for vector outputs. Understanding LLMs and Context: How does an LLM answer questions about things it hasn't been trained on? The answer lies in in-context learning. We delve into the main problems LLMs face in understanding context and the role of vector stores in this process. LLMs and Long Term Memory: We discuss the concept of coreference resolution in LLMs, the issue of growing queries due to token limitations, and techniques to handle these challenges. Eden explains the human-like behavior of LLMs and how autonomous agents interact with other agents using memory as context. Prompt Engineering & Autnomous Agents: What is sophisticated prompt engineering? It's the art of getting the LLM to do what you want. We explore autonomous agents with Langchain, the process of augmenting prompts, and the growing importance of prompt engineering. Human Simulation & Machine Learning: Despite advancements, a real human simulation remains distant. We touch upon the statistical nature of machines and humans and discuss whether machine learning could be considered a parasite in the digital ecosystem. Twitter API & Coding: We discuss the implications and challenges of using Twitter's API for scraping tweets, and how coding can be used to overcome limitations and navigate permissions. Chroma - A Vector Database: An introduction to Chroma, a vector database that facilitates in-context learning and filtering. Eden sheds light on the competitive vector database market, the benefits of using managed servers, and the potential of combining vector databases with relational ones for enhanced utility. Long Term Memory and Scaling Databases: We discuss the potential of using vector databases for long term memories, the importance of cataloging memories, and the ease of scaling databases with cloud services. People to Follow: Hari Sanchez, co-founder, and creator of the Langchain framework, is a must-follow for anyone interested in long-term memory and LLMs. The Gap in Machine Learning: We wrap up the discussion with insights into how the gap between machine learning programmers, data scientists, and PhDs has been bridged, and the potential future of open-source models in the face of state-of-the-art LLMs. Websites & Resources Mentioned Chain of Thought Paper: A resource that describes how LLMs think. Eden Marco's Udemy Class: A comprehensive course by Eden Marco on GenAI. Langchain by Hari Sanchez: A groundbreaking framework for autonomous agents. Eden Marco's Twitter Profile: Stay updated with Eden's latest insights and work.  

Show Notes In this episode of the Crazy Wisdom podcast, we are joined by Tem Nugmanov, the founder of the first-ever Notion consultancy Optemization. This enlightening discussion covers a broad array of topics, from how our lives are defined by the tools we use to the changing landscape of knowledge management. Key Discussion Points Tem's journey from moving to NYC in 2015 to study at NYU to becoming an entrepreneur and starting his fitness technology business, focusing on data optimization for weightlifting. His knack for discovering and figuring out productivity tools such as Trello, Asana, Flow, Slack, and Zapier, which led to him becoming known as the guy who "does the API." Tem's fascination with Notion since the release of its 2.0 product in 2018, which he believes puts everything into one space. He talks about the steep learning curve with Notion and how the aesthetic satisfaction from using it keeps users hooked. The rise of Notion within startups and how it replaced traditional tools by offering a simplified and unified workspace. Tem discusses his experiences hosting Notion events and migrating Confluence workspaces to Notion. The relationship between form and function in knowledge management, and how tools like Notion, Coda, and Almanic are revolutionizing the industry by making it more conducive to knowledge sharing. The transition from personal knowledge management to enterprise knowledge management, with different rules, permissions, and sharing methods. The impact of AI on knowledge management and the possibility of a new category emerging within the field. The different aspects of knowledge management, including project management and asynchronous work. Tem discusses his views on the subject, particularly disagreeing with the notion that knowledge management is solely about asynchronous work. The core concept of hierarchy within knowledge management, where beliefs about how things are done need to be nurtured and maintained. He talks about the tension between people and processes and the need for checks and balances within an organization. The challenges faced when incorporating asynchronous work into a remote workflow. Tem shares his experiences working with a startup and their struggle to redefine their remote workflow. The future vision for his Notion consultancy, which involves workspace design, workspace automation, project management, and goal management. He dreams of creating a "big four consultancy" for Notion and code. Listen to the full episode to hear all this and much more. Don't miss this insightful conversation with Tem Nugmanov, as he shares his crazy wisdom and his unique insights into the world of productivity tools, knowledge management, and the future of work.

Show Notes for the Crazy Wisdom Podcast Guest: Jared Zhao, CEO of AskEdith (https://www.askedith.ai/) Conversation: Introduction to AskEdith: Explanation of the search-driven analytics tool that enables users to access data in plain language Targeted at non-technical users Background: Jared's previous work in creating a visual editor for a data warehouse and training non-technical users Evolution of AskEdith: The journey so far and how it's still in its early stages The influence of startup circles and the emergence of large language models (LLMs) like ChatGPT from OpenAI The potential for swapping out the underlying core technology The role of English to SQL translations Future of AskEdith and Industry Insights: Thoughts on the future of core IP and the impact of open source Understanding the inference structure and use of APIs Discussion on the current competitive advantage of OpenAI The litmus test for whether we are in a technological singularity and its definition Unique aspects of the data industry, including the inability to host data Technical Aspects of AskEdith: The balance between search functionality, security, and compliance The use of a terraform module for one-click deployment into private clouds Insights into database and networking configuration AI and Society: The implications of AI on philosophy and its potential as a "silver bullet" The difference between AI replacing tasks versus jobs The historical context of automation and the Roman Empire's approach to universal basic income The potential need for universal business income today Whether AI will lead to deflation and thoughts on the economics of AI AI in Practice: The role of AI in replacing resources like Stack Overflow Challenges faced by AI in writing innovative code and the current capabilities of GPT-4 The potential for AI to predict the future and become an expert in a field The use of external data and consumer trends for benchmarking The Future of AskEdith: The vision of AskEdith as a mission control for enterprises The role of AskEdith as a search layer

Introduction Jae Yang, the founder of Tacen, a decentralized exchange, discusses his first hire as an archivist for the company and how this unique approach to knowledge management has helped them navigate the complex world of crypto startups. Tacen's commitment to thorough documentation and keeping a permanent record of every decision made is a testament to their belief in transparency and accessibility. Topics Covered Knowledge Management and the Role of an Archivist Jae shares how his experience at various startups led him to the role of an archivist, a guardian of a company's history and knowledge, differentiating it from a librarian who curates and organizes knowledge. The importance of meeting notes and how AI is utilized in their decision support process. The evolution of their team, starting as the 3rd person on board, to now 26 members. The process of making knowledge visible across the company and its challenges. Explains their unique classification system for information security that ranges from '00' for public data to '04' for secret data. Tools Used for Knowledge Management The use of internal wikis and Urbit, a suite of software tools that provides good infrastructure level support. Transition from Notion to WikiJS for self-hosting, and the reason behind the move. The capabilities of Urbit in knowledge management, including indexing textual content and its limitations like the absence of a textual management system like Obsidian. Urbit vs Obsidian The comparison between Urbit and Obsidian, which has features like bi-directional tagging and infinite discoverability. Events Discussion of "Reassembly 2023," a conference hosted by Tacen in Cheyenne, Wyoming from August 16-18th. Company Location and Cryptocurrency Law Explanation of why Tacen was established in Wyoming, citing factors such as crypto-friendly laws like the Wyoming DAO Law, zero corporate tax, and good internet infrastructure. Comparisons to South Dakota's innovative banking regulations and credit card processing. Brazil and Cryptocurrency The situation of cryptocurrency in Brazil, including its integration in daily life with apps and its role in circumventing high inflation and tax burdens. Brief mention of cryptocurrency's role in Argentina (note: segment about stablecoins was cut out). World View and Social Change Jae's thoughts on the rapidly changing world, the social changes since the 1970s, and the impact of technology. Discussion on the falling birth rates, changing attitudes to personal rights, and the further atomization of society. His view of the internet as a powerful tool that can lead to both individual empowerment and the spread of harmful agendas. Banks and Access to Finance Concern over banks preventing people from accessing their accounts for ideological reasons. Cheyenne and Tech Startups The vibrant tech startup scene in Cheyenne and its nearby University town, Laramie. About Tacen Tacen's early struggles with information overload and automatic deletion of data on Notion, leading to a change in their documentation strategy.

Robert DT on twitter: @DeeperThrill Doctorate on biomedical engineering with a focus on AI Entrepreneur building biomedical systems with AI specifically; medical imaging The conversation centers on the role of artificial intelligence (AI) in medical imaging, with an emphasis on computer vision and the utilization of existing imaging algorithms. Transformers, a type of deep learning model, are discussed for their unique self-attention mechanism and applications in natural language processing and computer vision. The talk pivots to data cleaning, specifically anonymization and safeguarding personal identifiers in the context of healthcare. Questions arise about data storage in healthcare facilities and the process of transferring it to the cloud. The conversation broadens to encompass AI's predictive capabilities and inherent risks, including the possibility of AI predicting third-order effects of its own interventions and concerns about excessive trust in AI predictions. The potential of AI in genetic engineering surfaces, particularly regarding CRISPR technology and nanobots. The conversation explores the benefits and risks of such advancements, including the revival of extinct plants and emergence of new diseases. Finally, the conversation shifts to societal implications of AI, including job displacement, the emergence of an attention economy, and the prospects of decentralized AI. The importance of understanding the limits of AI is underscored.   Show notes We need to examine what's currently happening in the field of AI, particularly in relation to medical imaging. This involves an exploration of computer vision technologies and how pre-existing imaging algorithms are being applied. We should discuss the concept of a "transformer" in the context of artificial intelligence. A critical part of working with AI is data cleaning. This includes the process of anonymization, ensuring that we only use the person's image and not any identifiable data like their name. We must also consider the storage of this data, which is typically housed on hospital servers. Additionally, there's the question of how this data is transferred to a cloud system for further processing. Let's explore the issue of gatekeeping in the field of AI. This might involve discussing the role of clinical trials and the Institutional Review Board in ensuring ethical standards. The engineering aspect of gatekeeping also requires attention, particularly when dealing with 3D data sets for imaging. We should highlight two major changes currently happening in the field of AI. Swin Transformers represent a significant development, as they are built off the concept of transformers in AI. Let's delve into the world of language modeling and chatbots. We must also consider the potential downsides of these AI technologies. The transhumanism angle presents an interesting point of discussion, particularly in relation to the next generation of technology. For example, the development of the mRNA vaccine was a major leap forward in response to global health crises. There's also the concept of generative mRNA vaccines, which use AI to generate potential cures. However, these AI technologies also come with risks. They could inadvertently create a disease, or develop a cure that isn't effective. The ease with which technology can be used in this field means that virtually anyone can make implants, leading to a new set of challenges. We should also discuss the emerging role of AI in lab-based work, such as managing petri dishes. The application of Hegelian principles to AI provides an interesting philosophical perspective. Looking ahead, we might consider what a lab kit might look like in ten years. The idea of the first version of something, and its relationship to anti-authoritarianism, is another interesting topic to explore. We have to acknowledge that AI, despite its potential, will not prevent all risks. AI can be used as a predictive tool for triaging, helping to determine whether an intervention will benefit a person. The use of CRISPR technology is another relevant point of discussion, especially considering its potential downsides, its application in nanobot technology, its use in regrowing extinct plants, the potential for new diseases arising from its use, and the systematics of finding new plant species in places like the Amazon. Let's also consider the case of the dodo and the role of technology in its extinction. With a small sample size, AI can predict certain outcomes, a feature that can be beneficial in various fields. Most plant species are discovered rather than created, and AI can potentially help in predicting where these new species might be found. The question arises: is AI better at predicting the future? It can certainly help us see larger scale patterns that we aren't aware of. However, the act of predicting the future can create its own issues, akin to the Oracle of Delphi dilemma. For instance, can AI predict the third-order effects of its own intervention? By revealing patterns, AI becomes a more effective tool. The more layers of patterns it can show us, the better. AI and Medical Imaging: AI is increasingly being used in medical imaging, particularly through deep learning techniques. These have applications in MRI, CT, and PET scans, enhancing image reconstruction, quality, and efficiency. While impressive progress has been made, the technology still needs further development before it can be widely applied in clinical settings Transformers: Introduced in 2017, transformers are a type of deep learning model used primarily in natural language processing and computer vision. They're distinguished by their use of self-attention, enabling them to process the entire input data all at once, rather than sequentially as in Recurrent Neural Networks (RNNs). This allows for more parallelization and thus reduces training times. Transformers have become the model of choice for many NLP problems, replacing RNN models such as long short-term memory (LSTM)

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: 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. 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. 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. 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. 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. 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   What is the biggest problem you’ve faced with knowledge management at your companies? Slack  Dropped balls in communication LLMs might be the response Why do you think slack spread so fast even though its not the best product? It was a step up from email IRC was a component More friendly for non-engineering What do you think about the complexity of slack? Twist is an alternative Why is information architecture such a challenge? How do LLMs fit into this? What would happen if slack created a LLM or plugged one in? Slack workspace plug in What is a retrieval plug in? Universal adapter for any type of data Who are the incumbents in the slack knowledge management space? Guru startup What is the difference between information management and knowledge management? Knowledge management is a higher level synthesis Information management is siloing related types of information Data types  Group related to information around people What are your thoughts on the membrane? Siloes Privacy is where LLMs can be very innovative If we were to share a LLM We can both specify a privacy policy to the LLM and it will follow it LLMs can intuit the privacy public distinction Are you using LLMs to code for you? Copilot Issues with difficulty to prompt it correctly You had to write comments to prompt it Inline suggestions were not good Is it better now? Haven’t noticed a dramatic improvement Hard to prompt it to code in certain styles now GPT 4 is way better for a starting off point for projects Helpful for conversion processes What are the things that GPT4 has not been helpful for you? You have to chunk it What about building systems with GPT4? Code completion cool called tap9 Train the model against your local code What are some other things about KM that we can use tools for? Shared LLM for the family Surface serendipity between users If facebook were to do this One person says they are selling a couch One person is buying one LLM connects them At what point do we merge with the machines? Sufficiently high bandwidth Translation Are we already cyborgs? It began with wearing shoes Horselike Where do you fit in the excitement vs fear when it comes to AI? What parts of knowledge work will get automated? What are we losing? What is your take on bodywork? 10% investment Martial arts practices, he gets beat up  Ninjiutsu Special forces for ninjas Healing and striking points on the body are the same Balance between healing/killing, if you know how to heal Unbroken transmission since 1400 What is the importance