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1. Gwern.net newsletter (Substack subscription page)

2. ​ February 2021 News

3. ​ ‘newsletter’ directory

4. ​ Changelog

5. Gwern Branwen Creating Essays on Gwern.net

6. 2021-03-28-gwern-gwernnet-annotations-mobilepopins-darkmode.png

7. 2021-04-01-gwern-gwernnet-annotations-popups-recursivewikipediapopups.png

8. Multimodal Neurons in Artificial Neural Networks [CLIP]

9. CLIP: Connecting Text and Images: We’re introducing a neural network called CLIP which efficiently learns visual concepts from natural language supervision. CLIP can be applied to any visual classification benchmark by simply providing the names of the visual categories to be recognized, similar to the ‘zero-shot’ capabilities of GPT-2 and GPT-3

10. The New CLIP Adversarial Examples Are Partially from the Use-Mention Distinction. CLIP Was Trained to Predict Which Caption from a List Matches an Image. It Makes Sense That a Picture of an Apple With a Large ‘IPod’ Label Would Be Captioned With ‘IPod’, Not ‘Granny Smith’!

11. Apple or IPod? Easy Fix for Adversarial Textual Attacks on OpenAI’s CLIP Model!

12. 2021-radford-clip-figure4-promptengineering.png

13. Pixels Still Beat Text: Attacking the OpenAI CLIP Model With Text Patches and Adversarial Pixel Perturbations

14. Evolving Reinforcement Learning Algorithms

15. Waymo Simulated Driving Behavior in Reconstructed Fatal Crashes within an Autonomous Vehicle Operating Domain

16. Replaying real life: how the Waymo Driver avoids fatal human crashes

17. Debugging Reinforcement Learning Systems

18. My Reinforcement Learning Learnings

19. Systems that defy detailed understanding § Deep reinforcement Learning

20. ML Scaling subreddit

21. SEER: Self-supervised Pretraining of Visual Features in the Wild

22. Self-Supervised Learning: The Dark Matter of Intelligence

23. Learning from videos to understand the world

24. Contrasting Contrastive Self-Supervised Representation Learning Models

25. Understanding Robustness of Transformers for Image Classification

26. Vision Transformer: An Image is Worth 16×16 Words: Transformers for Image Recognition at Scale

27. https://aiindex.stanford.edu/wp-content/uploads/2021/11/2021-AI-Index-Report_Master.pdf#page=41

28. ChinAI #137: Year 3 of ChinAI: Reflections on the newsworthiness of machine translation

29. The 5-Second Level

30. GPT-3: Language Models are Few-Shot Learners

31. DALL·E 1: Creating Images from Text: We’ve trained a neural network called DALL·E that creates images from text captions for a wide range of concepts expressible in natural language

32. GPT-3 Powers the Next Generation of Apps: Over 300 applications are delivering GPT-3–powered search, conversation, text completion, and other advanced AI features through our API

33. A mathematical theory of semantic development in deep neural networks

34. The Shape of Learning Curves: a Review: 6. Ill-Behaved Learning Curves: 6.1. Phase Transitions

35. An early cell shape transition drives evolutionary expansion of the human forebrain

36. Scientists discover why the human brain is so big: Molecular switch makes human organ three times larger than great apes’, study finds

37. The remarkable, yet not extraordinary, human brain as a scaled-up primate brain and its associated cost

38. Brainiacs, not birdbrains: Crows possess higher intelligence long thought a primarily human attribute

39. Behavioral and Neuronal Representation of Numerosity Zero in the Crow

40. GWAS in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color

41. Why Do Wealthy Parents Have Wealthy Children?

42. Nothing in evolution makes sense except in the light of parasites

43. Before a Disastrous Blight, the American Chestnut Was a Keystone Species in Eastern Forests. Could Genetic Engineering Help Bring It Back?

44. Broad cross-national public support for accelerated COVID-19 vaccine trial designs

45. Crystal Prison Zone: I Tried to Report Scientific Misconduct. How Did It Go?

46. Crystal Prison Zone: Smell You Later

47. The Revolution in Classic Tetris: How a younger generation used the Internet to master the falling blocks

48. ​ The Effectiveness of Unreasonable Small Groups

49. Magic, Explanations, and Evil: The Origins and Design of Witches and Sorcerers [and replies]

50. Self-blinding citizen science to explore psychedelic microdosing

51. Positive expectations predict improved mental-health outcomes linked to psychedelic microdosing

52. ​ LSD microdosing RCT

53. Placebo effects in cognitive training

54. https://www.reddit.com/r/electronic_cigarette/comments/lkhewr/usa_vape_mail_ban_newssales_megathread/

55. Can You Ever Be Too Smart for Your Own Good? Linear and Nonlinear Effects of Cognitive Ability

56. Behavioral scientists and laypeople misestimate societal effects of COVID-19

57. Training Working Memory for 2 Years—No Evidence of Latent Transfer to Intelligence

58. Real-time dialogue between experimenters and dreamers during REM sleep

59. Leroy’s elusive little people: A systematic review on lilliputian hallucinations

60. A Group of Orca Outcasts Is Now Dominating an Entire Sea: Killer whales that feast on seals and hunt in small packs are thriving while their widely beloved siblings are dying out

61. Estimation of the total saliva volume produced per day in five-year-old children

62. The esthetic-Usability Effect

63. They Might Never Tell You It’s Broken

64. The Third User, or, Exactly Why Apple Keeps Doing Foolish Things

65. Cameras and Lenses

66. Lights and Shadows

67. Large Batch Simulation for Deep Reinforcement Learning

68. ​ Computer Optimization: Your Computer Is Faster Than You Think

69. The Incredible Boxes of Hock Wah Yeo

70. Stone Walls That Stay Built: A Master Waller Shares How to Dry-Lay Stone Walls That Hold Their Ground for Centuries

71. The Use and Misuse of Income Data and Extreme Poverty in the United States

72. ​ Lizardman Constant in Surveys

73. Is economics performative? Option theory and the construction of derivatives markets

74. Whitewood under Siege

75. Coping with mortality: responses of monkeys and great apes to collapsed, inanimate and dead conspecifics

76. Wikipedia Bibliography:

    1. Stroop effect

    2. Temporal difference learning

    3. Bird intelligence

    4. 2019–2020 vaping lung illness outbreak

    5. Noble lie

    6. Parable of the broken window

    7. Mark Hofmann  :

       https://en.wikipedia.org/wiki/Mark_Hofmann

    8. Alexandra David-Néel  :

       https://en.wikipedia.org/wiki/Alexandra_David-N%C3%A9el

    9. John Harvey Kellogg  :

       https://en.wikipedia.org/wiki/John_Harvey_Kellogg

    10. Alice in Wonderland syndrome  :

        https://en.wikipedia.org/wiki/Alice_in_Wonderland_syndrome

    11. Orca

    12. Orca § Types  :

        https://en.wikipedia.org/wiki/Orca#Types

    13. Automated storage and retrieval system  :

        https://en.wikipedia.org/wiki/Automated_storage_and_retrieval_system

    14. Visual cryptography  :

        https://en.wikipedia.org/wiki/Visual_cryptography

    15. Black-Scholes model

    16. Fischer Black  :

        https://en.wikipedia.org/wiki/Fischer_Black

    17. Pallet  :

        https://en.wikipedia.org/wiki/Pallet

    18. Mautam  :

        https://en.wikipedia.org/wiki/Mautam

    19. Braitenberg vehicle  :

        https://en.wikipedia.org/wiki/Braitenberg_vehicle

    20. Reply of the Zaporozhian Cossacks  :

        https://en.wikipedia.org/wiki/Reply_of_the_Zaporozhian_Cossacks

    21. Richard Bong  :

        https://en.wikipedia.org/wiki/Richard_Bong

    22. North by Northwest  :

        https://en.wikipedia.org/wiki/North_by_Northwest

    23. Alfred Hitchcock  :

        https://en.wikipedia.org/wiki/Alfred_Hitchcock