Models
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Models
/* How valuable are CFP grants compared to in 2022/3? */ // DESCRIPTION // OVERVIEW // We model the probability of that CFP technologies are sufficiently incubated in the US to reach commercial scale // (or in the case of nuclear, trigger a fresh wave of nuclear fission).
/* Is it a good idea for US actors to accelerate an AI arms race with China? */ // Probability that an aligned AI has good values regardless of what its creator wants, i.e., an aligned Chinese-built AI will refuse to let China take over the world. p_aligned_ai_enforces_good_values = 0.1 // Probability that China would take over the world if it could. p_china_would_take_over_the_world = 0.6
/* * EV of AI safety technical research vs. policy advocacy, in * terms of change in probability of extinction. */ @doc( "Open Phil granted $69M on AI safety in 2023; a LW post[1] says $43M of that was on technical AI safety; but most of that was not directly funding alignment research (generously, only $28M was alignment research, the rest being forecasting/field-building/etc.). There are some other philanthropic funders, plus for-profit companies do some internal safety research. Internal research is the bulk of the money but I expect most of it is bad ex ante (e.g. fake safetywashing research). It would be feasible to estimate spending on AI 'safety' research, but harder to estimate how much of that spending is real, so I kinda just made up a number range. [1] https://www.lesswrong.com/posts/adzfKEW98TswZEA6T/brief-analysis-of-op-technical-ai-safety-funding" )
/*
BOTEC model to evaluate benefits from water quality forecasts and optimal trade-off between precision and recall.
*/
@name("Model Inputs")
@doc("Key input parameters for the aquaculture prediction model")
inputs = {
@name("True Rate of Poor Water Quality")
@doc("The actual occurrence rate of poor water quality in aquaculture farms")
@format(".1%")/*
Generated by Squiggle AI. Workflow ID: dd6b98ba-7143-423f-b6bc-01f9f58d4dbf
*/
import "hub:ozziegooen/sTest" as sTest
// Model for estimating the number of C code bugs in the world
@name("Number of C Code Bugs in the World")
@doc(
"This model estimates the total number of C code bugs in the world by combining estimates of total C code lines (both public and private) with bug density estimates."
/*
Generated by Squiggle AI. Workflow ID: b93791ef-fdec-4c7d-a296-fe04d5093cf1
*/
import "hub:ozziegooen/sTest" as sTest
// AI Educational Content for Enterprise Product/Business Strategy Leaders
// Market Size Analysis (TAM, SAM, SOM)
@name("Market Size Inputs")
@doc("Key inputs for calculating market size at different levels")Calculator.make({|resident_count, liters_per_day_per_resident, filtered_fraction, home_fraction|
liters_per_gallon = 128/33.8
gallons_per_day_per_resident = liters_per_day_per_resident / liters_per_gallon
filtered_at_home_gallons_per_day_per_resident = gallons_per_day_per_resident * home_fraction * filtered_fraction
filtered_gallons_dispensed_at_home_per_year = resident_count *
filtered_at_home_gallons_per_day_per_resident *
365.25
filtered_gallons_dispensed_at_home_per_year
}, {/*
Generated by Squiggle AI. Workflow ID: a1c362d8-dd87-4bed-8e91-dfa6b85810db
*/
import "hub:ozziegooen/sTest" as sTest
import "hub:ozziegooen/helpers" as h
// Base inputs and assumptions
inputs = {
@name("🌍 Global Population")
@doc(oai_now = 350 to 500 ant_now = 250 to 350 gdm_now = 350 to 500 other_us_labs_training_staff = 500 to 700 china_labs_now = 200 to 1000 other_randoms = 200 to 1200 total = oai_now + ant_now + gdm_now + other_us_labs_training_staff + china_labs_now + other_randoms
/*
Generated by Squiggle AI. Workflow ID: 0f56af75-62c0-4c91-8d65-3d165bedc7da
*/
import "hub:ozziegooen/sTest" as sTest
// Cost-Benefit Analysis: Vasectomy Decision Model
// This model compares three scenarios: vasectomy with sperm freezing,
// vasectomy without freezing, and no vasectomy
@name("Input Parameters")/*
Climate Policy vs Innovation Effectiveness Model
This model compares the relative effectiveness of domestic policy and innovation
on reducing emissions over time, based on historical data and future projections.
*/
// ==================== INNOVATION PARAMETERS ====================
// ----- Historical Innovation Effects -----
@name("Effect of falling remenewables price (2000-2020) on future emissions")/*
Generated by Squiggle AI. Workflow ID: a63000f5-a328-4a46-924c-142397a9a0b8
*/
import "hub:ozziegooen/sTest" as sTest
// Octopus Breeding Program Cost Estimation Model
// This model estimates the cost of running an octopus breeding program for intelligence uplifting
@name("Program Parameters")
@doc("Key parameters for the octopus breeding program")calendar_time = 3/12 to 3 // years sandworm_headcount = 10 to 50 sandworm_technical_headcount_share = 0.2 to 0.6 sandworm_technical_headcount = sandworm_technical_headcount_share * sandworm_headcount triton_technical_headcount = sandworm_technical_headcount * (0.2 to 0.8)
//2015 and 2015 grid attacks calendar_time = 31/12 // years total_headcount = 10 to 50 // inc non-technical staff technical_headcount_share = 0.2 to 0.6 technical_headcount = technical_headcount_share * total_headcount time_share_on_grid_attacks = 10% to 60%
calendar_time = 0.5 to 4.5 // years technical_headcount = 20 to 50 time_share = 20% to 100% person_years_effort = time_share * technical_headcount * calendar_time
/*
* Cost-effectiveness of DOE funding based on case studies of Enhanced Geothermal Systems (EGS) and Fracking
*/
// ===== EGS Model 1 =====
@name("EGS Model 1 Inputs")
egs1_inputs = {
@name("Impact of 300GW EGS by 2050 (GT averted)")
@doc("Estimated gigatonnes of CO2 averted in a scenario with 300GW EGS deployment by 2050")
impact_300gw = normal(5, 1.24)