Forum Log

Bob Nystrom wrote a famous post entitled "What Color is Your Function?" - https://journal.stuffwithstuff.com/2015/02/01/what-color-is-your-function/ It discussed the tension in software between how sync and async functions behave. A new category of data is emerging that I call "purple". This is produced by LLMs. The property is transferable. Any data or function that uses LLM-generated data is purple, and any data or function based on the same is also purple. Keeping track of AI provenance is crucial going forward, as is providing checks on the data produced by purple functions. So, I present a new approach: https://llmsmr.io It summarises text using an LLM, but also provides tools to quickly check the result by extracting direct quotes and presenting them to the user. The summary is purple, but the quotes can be verified simply to ensure that they do indeed appear in the original text. I believe this approach should be applied to all purple data going forward.

Podcast summary: Dr. Dani Sulikowski argues that "wokeness" can be understood as _manipulative reproductive suppression_. Key points: - Once societies become wealthy and infant mortality falls, elite women lose their normal reproductive advantage. - To restore it, they promote cultural norms - e.g. career-first feminism, abortion rights, body positivity, gender ideology, toxic masculinity - that will lower the reproduction rate of other women. - This behavior is not necessarily conscious. - These movements are framed as progressive or compassionate but effectively make other women less fertile. - This pattern is cyclical across civilizations. Male competition is dominant until an inflection point of high wealth and success is reached. Female competition then becomes the dominant force in mating outcomes, and birth rates decline, setting the stage for societal decline and replacement. https://www.youtube.com/watch?v=sRY_1JRRcNU

MVC (Model-View-Controller) is a pattern in software design for building user interfaces. Key benefit: It keeps code modular - models don't deal with presentation, and views don't contain business rules. 1. The model defines what data the app should contain. 2. The view defines how the app's data should be displayed. 3. The controller contains logic that updates the model and/or view in response to input from the users of the app. Scenario: A user writes a new post on an online forum. - Model: Receives and validates the post data. Handles saving to and loading from the database. - View: Builds the page shown to the user. Either the "New Post" form with validation errors, or the "Post Details" page showing the freshly created post. - Controller: Handles the "create post" request. Flow: - User makes post - Controller receives post data - Model saves to database - Controller chooses a View - User sees result

The current meta for social platforms selects for platforms that optimize for emotional engagement. The core mechanic is "reaction", as reified in likes, shares, comments. Posts are simply the raw material. Reaction is what keeps people coming back. Humans have a powerful anxiety-driven need to perceive the social currents - "what are other people saying about X ?" (what should my opinion be ?) Reaction maintains regular engagement, which allows the business of adverts to exist. I propose a new core mechanic: Validation. A person's social profile would showcase the posts that they have validated - verifiable record of what they judged to be true / insightful / useful. The value proposition: That this profile would increase the user's professional reputation. The overall result: The platform produces few posts, but each post supports a cloud of confirmations. Highly-validated posts are then republished on existing platforms, with the validators featured alongside the author.

Protocol: - Each block creates new coins (the "block reward") in its "coinbase transaction". - The block reward was initially at 50 BTC per block. - Every 210,000 blocks (~4 years), the reward is halved. - This halving produces a geometric series that converges to a maximum of 21 million BTC. Enforcement: - Bitcoin nodes run the protocol code. - The code defines the block reward formula and enforces it. - A miner who tries to claim more than the allowed reward will simply produce an invalid block. - Other nodes reject that block, and the miner gets nothing. Note: - A subgroup of nodes can choose to set a higher limit, producing a hard fork, resulting in a new network, with the same addresses and balances. This has already happened at least twice. However, the original network offers a "harder" asset (due to its lower limit) and over time wins in terms of stored value and market interest. Holders will tend to sell the forked asset.