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The speaker is considering the research question of how to achieve distributed compute, particularly the need for parallelism in executing pipelines and AI agents. They question the potential for building a Directed Acyclic Graph (DAG) that allows for agents to dynamically contribute to it and execute in parallel, emphasizing the need for pipeline development to accommodate this level of complexity. The discussion also touches on the scalability and parallel execution potential of the mixture of experts model, such as GPT-4, and the potential for hierarchical or vector space implementation. The speaker is keen on exploring the level of parallelism achievable through mixture of experts but acknowledges the limited understanding of its full capabilities at this point. They also express curiosity about fine-tuning experts for personal data. The speaker is discussing the data they are generating and the value of the training data for their system, particularly emphasizing the importance of transforming the data to suit their context and actions. They mention meditating and recording their thoughts, which they intend to transform into a bullet point list using an AI model after running it through a pipeline. The individual also discusses making their data publicly accessible and considering using GPT (possibly GPT-3) to post summaries of their thoughts on Twitter. They also ponder the potential of using machine learning models to create a personal Google-like system for individual data. The text discusses using data chunking as a method for generating backlinks and implementing PageRank in an agent system. It mentions steep space models and the continuous updating of internal state during training. It also compares the level of context in transformer models and discusses the idea of transformer as a compression of knowledge in a language. The speaker expresses interest in understanding the concept of decay in relation to memory and its impact on the storage and retrieval of information. They draw parallels between the processing of information in their mind and the functioning of a transformer model, with the long-term memory being likened to a transformer and short-term memory to online processing. They speculate on the potential of augmenting the transformer model with synthetic training data to improve long-term context retention and recall. Additionally, they mention a desire to leverage a state space model to compile a list of movies recommended by friends and contemplate the symbiotic relationship between technology and human sensory inputs in the future. In this passage, the speaker reflects on the relationship between humans and computers, suggesting that a form of symbiosis already exists between the two. They acknowledge the reliance on technology and the interconnectedness of biological and computational intelligence, viewing them as mutually beneficial and likening the relationship to symbiosis in nature. They express a preference for living at the juxtaposition of humans and computers, while acknowledging the potential challenges and the need to address potential risks. Additionally, they mention that their thoughts on this topic have been influenced by their experiences with psychedelics. The speaker discusses the potential increase in computing power over the next five years, mentioning the impact of Moore's Law and advancements in lithography and semiconductors. They refer to the semiconductor roadmap up to 2034, highlighting the shift towards smaller measurements, such as angstroms, for increased transistor density. They emphasize that the nanometer measurements are based on nomenclature rather than actual transistor size, and the challenges in increasing density due to size limitations and cost constraints. The conversation touches on different companies' approaches to transistor density and the role of ASML in pushing lithography boundaries, before concluding with a reference to the high cost and potential decline in revenue for semiconductor production. The speaker discusses the importance of semiconductor manufacturing in the U.S. and China's significant focus in this area. They mention watching videos and reading sub stacks related to semiconductor technology, specifically referencing industry analysts and experts in the field. The speaker expresses enthusiasm for staying updated on developments and offers to share information with the listener. The conversation concludes with a friendly farewell and the possibility of future discussions.

The realization of the value in this application lies in its ability to perform searches quickly, efficiently, and accurately. There are multiple approaches to enhance its functionality, with a focus on both data storage and the improvement of search capabilities, which is currently the most critical yet challenging aspect. Concerns exist about the app's method of aggregating all processed data, which feels inherently flawed, though it's being temporarily accepted for the valuable data it provides. This tension between a recognized need for development against the reluctance to proceed with an imperfect solution underscores the complexity of the problem at hand.

The speaker aspires to be part of communities that empower individuals to explore their data and bring value back to themselves. They are willing to take a job in such a space and believe it's worth doing. The goal is to build tools that make it easy for the individual to work with their data directly on a web page. They plan to move to a more reactive front end using Next.js and React, designing a feed and query system possibly using natural language. The speaker also mentions working on embedding audio and ensuring embeddings are accessible. The text discusses the process of obtaining and manipulating data and emphasizes the importance of experimentation and innovation. It uses the metaphor of building a playground to illustrate the iterative nature of the process, acknowledging that initial attempts may be imperfect but can be improved upon through learning from mistakes. The writer anticipates challenges but expresses a hope to avoid negative consequences and eventually achieve success. Finally, the text concludes with a lighthearted remark and a reference to going to sleep.

I had a profound two-hour call with Jordan at 9 a.m., discussing a range of topics including the exciting potential of language models, which he called "word calculators." Jordan and I agreed on the importance of solidifying a good intention to create a compelling demo that deeply explores the vision of our project. We also touched on self-expression and the value of using the platform as a "playground" to honestly express oneself without worrying about the audience. Lastly, we delved into the dynamic nature of intentions and how they evolve over time, along with the idea that AI could support individuals by acting as an executive function override during moments of weakness.

I had a beneficial conversation with John, who helped me work through my thoughts and appreciated his support in allowing me to talk things out. We discussed building a simple intention website that John sketched, considering the addition of GPS functionality due to its importance for intention-based actions, and the possibility of an AI assisting with small tasks based on one's intentions. Despite my aversion to login pages, John made me realize it's acceptable to ask for passwords on a website, and that a solution to eliminate logins can be addressed later. This talk has energized me for the week, and I'm excited about working on this intention website project, hopeful about committing to it longer term, and grateful for the sense of direction it provides.