The Inkhaven Residency

The Blogroll

Today, 12 out of 41 residents have published

A.G.G. Liu
Latest Post: Europe's Hidden Buddhist Mongolian Republic
Adrià Garriga Alonso
Latest Post: Nvidia rules ML because its products are cost-effective
Alex Altair
Latest Post: What would my 12-year-old self think of agent foundations?
Amanda Luce
Latest Post: Dear Beaufort
Angadh Nanjangud
Latest Post: New Attachments
Ben Goldhaber
Latest Post: Are there examples of communities where AI is making epistemics better now?
Ben Steinhorn
Latest Post: Library as a Memory
Camille Berger
Latest Post: San Francisco is just a place is not just a deepity
Claire Wang
Latest Post: Some things I recommend
Croissanthology
Latest Post: Should we Automate Discussion about Utopia?
Daniel Paleka
Latest Post: The concepts of "AI lab" and "model" will converge
David Gros
Latest Post: Dev Notes 12: Blog Improvements and Playing With Wikidata Prompts
Eneasz Brodski
Latest Post: SFF Review - The Blacktongue Thief
Harri Besceli
Latest Post: C5: FTX
Hauke Hillebrandt
Latest Post: Causes of the industrial revolution
Human Invariant
Latest Post: Novel Interface Designs for Prediction Markets
Jenn
Latest Post: Social Dynamics at Arm's Length
Joanna Bregan
Latest Post: My 5 favorite items of clothing
Justin Kuiper
Latest Post: The time Weird Al went too far
Justin Miller
Latest Post: The Mnemonic Drift
Linch Zhang
Latest Post: Inconvenient Facts
Lucie Philippon
Latest Post: To Bay or not to Bay. Act 1
Lydia Nottingham
Latest Post: Mutual Information in Probabilistic Graphical Models
Mahmoud Ghanem
Latest Post: Follow up to Hintikka on the analytic/synthetic distinction - some thoughts on proof depth, logical omniscience and tractability
Margarita Lovelace
Latest Post: Relationship Contract to Be A Cat
Markus Strasser
Latest Post: Hidden Post
Michael Dayah
Latest Post: AI Flatters with Fidelity
Michael Dickens
Latest Post: Not-Discovered-Here Syndrome
Mikhail Samin
Latest Post: Hidden Post
Nikola Jurkovic
Latest Post: Transparency improves AI safety
Raye
Latest Post: Post 17
Rob Miles
Latest Post: Answering Questions about The System
Sasha Putilin
Latest Post: My Ethical Conundrum Around Writing About Meditation (16/30)
Sean Carter
Latest Post: Betaveros' Website Hides a Secret
Simon Lermen
Latest Post: AI 2025 - Last Shipmas
Skyler
Latest Post: Mixed Feelings On Social Munchkinry
Tomás Bjartur
Latest Post: Lobsang's Children
Tsvi Benson-Tilsen
Latest Post: Constructing and coordinating around complex boundaries
Vasco Queirós
Latest Post: Why we fight
Vishal Prasad
Latest Post: Unambitious (v3)
William Friedman
Latest Post: BYZ 103.2: Reflections On Zeno

Contributing Writers, Coaches & other Chroniclers

Abram Demski
Latest Post: Wiki AI
Ben Pace
Latest Post: Mediators: a different route through conflict
Daniel Reeves
Latest Post: Mnemonic Exposition
Justis Mills
Latest Post: Expecting The World Quintile
Kave Rennedy
Latest Post: Beware Compounding Resource X
Oliver Habryka
Latest Post: Close open loops
Ozy Brennan
Latest Post: Book Review: Plasticosis
Raymond Arnold
Latest Post: One Shot Singalongability is an attitude, not a skill, or song-difficulty-level.
Robert Mushkatblat
Latest Post: Why is American mass-market tea so terrible?
Ruben Bloom
Latest Post: The skills and physics of high-performance driving, Pt. 2
Sacha Witt
Latest Post: Hidden Post
Vaniver
Latest Post: Cetaganda

Latest Posts

November 16, 2025

November 15, 2025

November 14, 2025

November 13, 2025

November 12, 2025

November 11, 2025

November 10, 2025

A Thesis Regarding The Impossibility Of Giving Accurate Time Estimates, Presented As An Experiment On Form In Which The Essay Solely Consists Of A Title; In Which The Thesis States That, If Task Times Follow A Pareto Distribution (With The Right Parameters), Then An Unknown Task Takes Infinite Time In Expectation; And Therefore, In The General Case, You Cannot Provide An Accurate Time Estimate Because Any Finite Estimate Provided Will Not Capture The Expected Value; And, More Precisely, Every Estimate Will Be An Underestimate, Because Every Number Is Smaller Than Infinity; And This Matches With The General Observation That, When People Estimate Task Times, They Usually Underestimate The True Time; However, In Opposition To This Thesis Are At Least Two Observations; First, That Even If Tasks Take Infinite Time In Expectation, The Median Task Time Is Finite, And An Infinite-Expected-Value Task-Time Distribution Does Not Preclude The Possibility That Time Estimates Can Overestimate As Often As They Underestimate, But People Fail To Do This; Second, That Certain Known Biases That Result In People Underestimating The Difficulty Of Tasks, Such As Envisioning The Best-Case Scenario Rather Than The Average Case; However, In Defense Of The Original Thesis, Optimism Bias And The Pareto-Distributed Problem Space May Be Two Perspectives On The Same Phenomenon; But Even If We Reconcile The Second Concern With The Thesis, We Are Still Left With The First Concern, In Which An Unbiased Estimate Of The Median Time Should Still Be Possible, But People Are Overly Optimistic About Median Task Times; Thus, Ultimately Concluding That The Thesis Of This Essay--Or, More Accurately, The Thesis Of This Title--Is A Faulty Explanation Of People's General Inability To Provide Accurate Time Estimates; Then Following Up This Thesis With The Additional Observation That We Can Model Tasks As Turing Machines; And The Halting Problem States That It Is Impossible In General To Say Whether A Turing Machine Will Halt, And As A Corollary, It Is Impossible In General To Predict How Long A Turing Machine Will Run For Even If It Does Halt; So Perhaps The Halting Problem Means That We Cannot Make Accurate Time Estimates In General; However, It Is Not Clear That The Sorts Of Tasks That Human Beings Estimate Are Sufficiently General For This Concern To Apply, And Indeed It Seems Not To Apply Because Some Subset Of People Do In Fact Succeed At Making Unbiased Time Estimates In At Least Some Situations, At Least Where 'Unbiased' Is Defined Relative To The Median Rather Than The Mean; It Is Difficult To Say In Which Real-Life Situations The Halting Problem Is Relevant Because It Is Not Feasible To Construct A Formal Mathematical Proof For Realistic Real-Life Situations Because This Would Require Creating A Sophisticated Model In Which The State Of The Universe Is Translated To A Turing Machine, Which Would Be An Extremely Large Turing Machine And Probably Not Feasible To Reason About; Leading To The Conclusion That This Essay's Speculation Led Nowhere

November 9, 2025

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