1000 object community

Good idea to use German words. I used words from about seven languages in my images (with dictionaries), but I don’t think there are any German words in my system since I didn’t know how to pronounce German back then.

Thanks for the link, London. For now I just want the first half of the system so I can do something other than PAO for cards that could also be used in multi-deck (so not 52/52). The future beyond that is muddy.

Where can we see your lists?

are they Creative Common, so I could use them in a piece of software?

I had forgotten about this thread…

Maybe I can shed some light on why this thread, and others like it, have died.

Before you have a 3-digit system, it appears that the main challenge to surmount in order to use a 1000-object system is to come up with 1000 objects that you like that fit cleanly into the system of your choice. With 1-card systems, and 2-digit object systems, this is true, With 1000+ object systems, the challenge is a little bit different. It is about really really knowing and loving your images, so that they can be slapped down at a similar speed as would be done with a smaller system, with no added difficulty to memorization, so that little extra distance can be squeezed out of the method.

I would contest that this latter objective, completely apart from the naming of the objects, is more than 95% of the actual challenge to be surmounted. It also takes far more time. If you had all 1000 objects handed to you, there would be nothing you could do with any efficiency until you had grokked each and every last one. The reason people to type out their 1000 object systems, or Ben Systems, is because it isn’t worth the effort for either party. Some of the best images I have came from when I was first trying to play with the digits, after they had all been named, but only some had been memorized. 774 would pop up, and I would think “Kakarot,” which wasn’t my initial image, so I would shake my head, go back to my list, and say “Ok, Lance, next time you see 774, think cougar.”

“Kakarot.” “No.”
774.
“Kakarot.” “No.”

Eventually, I gave up on cougar, which is the right thing to do in that situation.

The amount of time it will take you to REALLY know each your images is a lot longer than it will take to merely name them. So by using someone else’s list, you wouldn’t actually be saving any time, and may even supplant personal, potentially creative, solutions with manufactured ones.

Take a look at those Ben System 200-299 above and try to understand what I mean.

1 Like

I completely forgot that I made this thread. I remember now making a promise to help others that I did not keep.

I am now willing and able to help, but here’s a quick tangent first if you will allow it:

If you want to use the Ben System, I can’t help you. But there are a couple options. One is my 2-card system called the Shadow System, (Come on guys, that’s marketable and you know it). I don’t know if it’s better than Ben’s. At first I was convinced of the advantages, but now I see that it is high-maintenance. I broke the 35 second barrier with cards after about six months, but a score like that is far from typical. Ola is better than me at every event, usually by a huge margin, and using the Ben System, it took him a year to meet his old PAO PB of 1:02 that he had already set when he switched to the Ben System, and using SS, I memorized a deck in almost half the time, (34.8 seconds) in almost half the time (just over 6 months) Ben himself improved to my level relatively quickly with the Ben System. The difference between he and me is that he just kept getting better. Anyway, if you want to be one of the 10 fastest card memorizers in the world, you’re going to have to pick a 2-card system eventually.

But the 2-card system I recommend to you all isn’t Ben’s, and it isn’t mine. It’s a very slight modification of Johannes Mallow’s. I only modified it because I can’t figure out exactly how he covers 2704 combinations with only 1000 images. I don’t get it. So it uses 1352 objects instead of 1000. Anyway, one advantage of adopting this system is that if you use it now and choose to adopt SS later, you’re well over half way there as far as the image-naming is concerned. One other advantage is that you can break a minute with it in only a few months. You could do that with PAO also, but if you can get sub-0:40 decks with PAO, you’ll be one of the only people who ever have been able to do that with consistency.

Make 1352 objects and have a pair that begins with a red card to match every pair that begins with a black card. Club/Diamond is the same image as Diamond/Club.

Version 1: When you memorize a deck, keep linking cards that begin with a red suit in one locus until you get to an image with a black card first. Memorize that one in the following loci and keep linking black-first images until you get to a red-first card. Move to the next locus and repeat. During recall, you can use the first card of the last image you memorized and review back through the loci, differentiating which version of the image you used by whether it was in a “red-first” or “black-first” locus.

Version 2: Pick either red-first or black-first. From now on, that type of image will be the last image in every locus. Let’s say that you pick red-first as your ‘locus-ender.’ Keep linking red-first images in a locus until you get a black-first image. Stick the black-first image at the end of the locus and move on to the next one. If you get another black-first image, it will be the ONLY image in the next locus. Put it in there and move on. The problem with version two is that it provides no context for whether the last image was red or black. So if you forget that, you’ll be screwed 50% of the time.

To fill out 1352 images, use the SS codification of the major system if you don’t want to learn a new phonetic system. Trust me, it works just fine.

The point of all of this is that I will help anyone with the drive to make a 1000 object list because I want to see more of them. And if you do make a 1000 object list, you should make a 2-card system I think.

By the way, Mallow’s method averages out to 12-13 loci per deck and almost always falls between 9-16 loci.

Everyone will tell you that you should come up with your own images when making an object list. But some number combinations are just a pain. So if you’re reluctant to make a 1000 object list on account of spending an inordinate amount of time on a small percentage of images, I will be here to fill in the gaps you post.

My only request is that you do not post a list of a whole bunch of numbers in a row. It suggests that you haven’t spent enough time trying to come up with original images for those numbers, which I was guilty of when I made this thread. Use too many of my images and you’re cheating yourself.

Plus, my images are in my noggin, and I don’t want to type them all out.

One word of advice: cheat sometimes. For really hard ones, just cheat. You’re going to review these a bunch of times - it’s not like you’re going to forget what the image is over and over and over. If there are two digits in a row, and you don’t like that, just cheat. For me 233 is “Gnome,” a garden gnome. Wasn’t that easy? 223 is “Anenome.” The actual animal is called an “anemone,” but that word is so weird anyway that I just started to pronounce it wrong and it’s just as good as any other image I have. Better than some. 565 is “Leechal” It’s just a leech, but it was easier to imagine that the word was “Leechal.” Easy, right?

K, so if you’re honestly building a list and you have some numbers that you’re stuck on, just let me know by posting them here. But you might find that you don’t like them, because I have cheated on many of the tricky ones… I’ll try to remember to do one other thing, too, over time. This is my 595th post, so I’ll post my image and another option or two that I have considered:

595 = Label (labelgun/labelmaker)
Lapel

Just dropping a link to Bateman’s blog here for people who find this thread in the future :slight_smile:

I just noticed that I had made this thread 50 weeks ago…I started making that list 360 days ago, but it seems so recent.

Hi, here is my full answer to Lociln The Sky. I know, it has been a while since the question was asked but this answer may help others. If anyone wants my full 1000, I’d give that too.

453 Rolling lime, Harlem Globe trotters

.457 relic of berlin wall
.459 Loopy ear ring

.462 razor machine (urgent sticker)
.463 Horse Gym
.465.hair Gel

466.Chouchou railway

467 Artichoke
.468 Chef’s Refrigerator
.469 Recording Chip

.487 fog raincoat.

489.Fabulous Road runner (meep-meep)

253 Lame nutcracker
.258 in love engrave (on tree)
.267 no-frills jack
.278 natural cave stalagmite
.283 fame :Einstein
.284 fire engine
.289 fabulous Santa
.293 Intersection Bum
.296 Beach Sunscreen
.298 Peeve Insect
.219 needle tip (for pin board)
.223 venimous snake
.225 narcotic inhalation
.228 infantry knife
.229. Nab snake, non-venomous

237wanted mug
.244.rower’s anchor

381 fat swimmer
.383mix foam (hair washing)
.387 fog umbrella

.388 fifi smile (Fifi a mischievous girl that cheers me so the smile logo)
.393 main beam a house under construction beam only stage
.398 pavement making sidewalk making preparation
.362 Machine Madvac, road vacuum
.363.Gym Mass

761 Gadget spring bike seat
764,catcher (that’s not really a though one for baseball lovers)
766 chouchou coke (bbq charcoal)
,772, Christmas Cane
793 Bum’s cardboard

802 vicinity phone booth
,803 Homo females
,805 fossil
,806 physician
,807 viscous substance, or water heater
,808 save vault
,812 vanity tan lamp
,814 feather
,815 vital water gourd
,816 touch Velcro
,834 femur
,835 female underwear
,836 flood damage wood frame stand
,838 moving van
855 lowly floor wood floor strips
,871 fact marker
,873 football game ball (the oblong ball, not soccer)
,877 Kick a furnace
,878coffe filter
,882 vertical vine
,883 fame Van Hallen’s belt
,886 flying fish
,889,fab Fanfreluche (tv character)
891 flower pot
,892 frying pan
,893 Photo album
,897 bike frame
,898 peeve flood light
,899 effervescent pop

  1. siege chariot
    607 shrink sack
    .608 sofa chesterfield
    613.generous dime
  2. Shuttle (space)
    616 Shallow ditch.
    622 jet canon (my image is a child ride in a mall)
    .623 numb jaws from the movie Jaws
    .626 change room
    .628 jungle knife
    .629 chew nibs
    .631 mud jam (wheel spinning)
    .633 chubby mom (pregnant)
    .634 Mayor’s chamber (city hall Toronto)
    .635.male jock with small weights
  3. show homage
    637 Jamaica papaya
    .638 movie jock small flash light
    .644 rare gene (double helix, no not you)
    .645 cheerleader
    .647 shark
    .648 sheriff
    .651 shield of motorbike
    .652.balloon ship
  4. juggling Lama
  5. shut eyelash
  6. giant globe
    661 Chasing Cheetah
    .662 jack hammer machine
    .663.Gym jockstrap
  7. Jammed Jar
    665 shinny Jell-O
    .667.Chic Chandelier
    668 Achieve shorthand, a steno
    .669 Chop chard
    . finally,671 Jacket
    -699 chief pope

Thank you, Simon! I did finish that list about a year ago :smiley: but I know that those number combinations can be very tricky for anyone who’s starting to build a list.

Simon, could you post your whole 1000 object list?

Hi Bateman,

Here it is. Thanks for asking.

It isn’t a particularly good list as it is “only” my first 1000 of several thousands.
If wanted to rebuild a single list of 1000 objects using the best of what I’ve got, it would be somewhat better. If you are not sure what image I have in mind by reading this list, then I may or may not want to explain it. Some images, such as Fanfreluche and Bobino will most likely mean nothing to most people here and it would not be a good idea for you to use those images. I’m just putting up my list as a sample of an edited 1000 images.
By edited I mean that there are no repeats of images under a slightly different handle.
Again, I have memorized all this by putting all these images on grids #s which I imagine on walls of specific loci as I’ve explained in my Less L. thread. However, I’ve recently slightly altered this posting method and updated this in one of my last post on the Less L. thread.

0 sauya sause

  1. tie

  2. noah

  3. mah

  4. rye

  5. ale

  6. shoe

  7. cow

  8. Ivy

  9. Bee

  10. Toes

  11. Statue Liberty

  12. Tuna

  13. Time watch

  14. Tire swing

  15. Towel

  16. Dish

  17. Tack

  18. Tofy

  19. Tub

  20. Nose

  21. Net

  22. Nun

  23. Name tag

  24. Nowhere island

  25. Nail

  26. Snatch zipper

  27. Neck display

  28. Knife (steak Knife)

  29. Nob

  30. Mouse

  31. Mat

  32. Semen

  33. Mommy (sarcophagus)

  34. Mower

  35. Mule

  36. Match

  37. Mug

  38. Movie seat

  39. Mop

  40. Rose

  41. Rod

  42. Rain

  43. Rome coliseum

  44. Rower

  45. Rail

  46. Roach

  47. Rag

  48. Roof (bus vent)

  49. Rope

  50. Lice

  51. Lot (marks)

  52. Lion

  53. Elm

  54. Lure (plastic duck)

  55. Lilly

  56. Leash

  57. Lake

  58. Leaf stem

  59. Lip

  60. Cheese pizza

  61. Sheet Metal

  62. Chain

  63. Chum

  64. Cherry

  65. Jail (sniper tower)

  66. Chouchou

  67. Check

  68. Chef stove

  69. Chop stick

  70. Case (suitcase)

  71. Cat

  72. Can

  73. Comb

  74. Car (2 doors)

  75. Kale

  76. Cage (hamster’s))

  77. Coca box

  78. Scaffold

  79. Cab (top sign)

  80. Fuse

  81. Foot

  82. Phone

  83. Fume (portable gaz tank)

  84. fire hose

  85. file cabinet

  86. fish on ice

  87. fog house (light house)

  88. fifi brin d’acier (French character)

  89. fab 4

  90. bus

  91. bat

  92. bone

  93. bum

  94. bear

  95. bell

  96. beach

  97. book

  98. puff

  99. pipe

  100. Disease (elephantism)

  101. Toast

  102. Design (architect table)

  103. Aim Dart board

  104. Taser gun

  105. Diesel car

  106. Dosage spoon

  107. Task (unplug toilet)

  108. Save Dessert (fruit salad)

  109. Spa Straw

  110. Dad’s beard

  111. Sweet date

  112. Trumpet tune

  113. Totem

  114. Deter scarecrow

  115. Toilet tile

  116. Stitches

  117. Attack Doberman

  118. Dolphin Dive

  119. Toilet tap

  120. Tennis net

  121. Scent detergent

  122. Water canon

  123. Dynamo (bike’s)

  124. Tenor

  125. Tunel

  126. Three punch holes

  127. Tonic ginseng

  128. Dagger knife

  129. Trailer nob

  130. Mouse trap

  131. Tomato

  132. Women head dress(all covered)

  133. Mom’s tampon

  134. Tumor on plant

  135. Tamil

  136. Damaged Dirigible

  137. Stomach

  138. Movie DVD

  139. Temperature hail

  140. Dress

  141. Dart

  142. Drain

  143. Trimmer

  144. Drawer

  145. Drill

  146. Austrich

  147. Truck (construction heavy load)

  148. Trophy

  149. Drape

  150. Stalls (horse’s)

  151. Toilet water

  152. Balloon toy

  153. Gloomy stop

  154. Taylor tape

  155. Lowly decoltee (French)

  156. Door latch

  157. Tongue lick

  158. Hot lava

  159. Tulip

  160. Chess timer

  161. Disgusting sheet (toilet sheet)

  162. Double chin

  163. Gym trampoline

  164. Cherry tattoo

  165. Jail tray (hard tray)

  166. Chouchou steam pot

  167. Water jug

  168. Chef hat

  169. Wood Chip

  170. Dogs’ treat

  171. Dashing skates

  172. Token

  173. Tee ball game stand

  174. Tiger

  175. Store scale

  176. Baggage ticket

  177. Kick hat (shreiner’s)

  178. Coffee Thermos

  179. Dentist cup

  180. Devise “s” shape hold

  181. Devide scissors

  182. Define dictionary set

  183. Defamous davinchy drawing

  184. Hydrant fire

  185. Devil

  186. Fish statue

  187. Defog head light (bike)

  188. Fifi hair stile (see 88)

  189. Fabulous tintin

  190. Space star patern

  191. Tree pot

  192. Ban stunt (bag used to go over falls)

  193. Athletic beam

  194. Prey dinosaur

  195. Delicious apple

  196. White page

  197. Tooth pick

  198. Pave tar, sticky tar substance used in road constr.

  199. Tobacco pipe

  200. Nameless ass (African ass)

  201. Nest

  202. Insane woman

  203. Inseam

  204. Knight sir, a knight chess

  205. Nasal hair

  206. Noxious sewage

  207. Niska (artist paint)

  208. Save newspaper (inside plastic)

  209. Inuit soap

  210. Nudity tease

  211. Tooth incisive

  212. Nipple tune instrument bike

  213. Newborn dome

  214. Nitro seal (seal of bottle)

  215. Noodles

  216. Unafraid hostage

  217. Tuke nylon (winter hat)

  218. Native dress

  219. Needle tip (for boards)

  220. Nasa uniform (space suit)

  221. Naphta scent balls

  222. Antique canon

  223. Venomous snake (eastern Diamondback)

  224. Near neighbor

  225. Inhale narcotic

  226. No nudge (rocking chair)

  227. Nock nock device

  228. Infentery knife

  229. Nab snake (ribbon snake)

  230. Nosy moose

  231. Nomad (with large backpack)

  232. Cinnamon

  233. Animated mime

  234. AnnaMarie

  235. Windmill

  236. Intersection damage

  237. Wanted mug

  238. Nymph of mosquito

  239. Damp newsstand (paper box)

  240. Nurse

  241. North Pole

  242. running neuron

  243. Romeo and (balcony)

  244. Rower anchor

  245. Rolindex

  246. Enrage (shrink’s couch)

  247. Natural rock (menhir)

  248. Nevrve back spine

  249. Rip nightclothes

  250. Snails

  251. Nailed chair

  252. Woolen napkin

  253. Lame nut cracker

  254. Nacre layer

  255. Lowly sandpiper

  256. Window ledge

  257. Incredible hulk

  258. Inlove engrave

  259. Snowy slope

  260. Jazz note

  261. Noble chateau

  262. China snake

  263. Gym wrongs

  264. Injury charley horse

  265. Angel

  266. Chouchou engine(fireplace tools)

  267. No-frills jack

  268. Indian chef (feather hat)

  269. Chopped onion

  270. Snacks (mountain mix in bag)

  271. Needle kit

  272. Nuisance coin (penny)

  273. Coma num

  274. Negro hair

  275. Snuggle a pillow

  276. Baggage sandal

  277. Kick window screen

  278. Natural Cave stalagmite

  279. Cupboard Nailclipper

  280. Infuse tee device

  281. Invade window

  282. Invent fire detector

  283. Fame Einstein

  284. Fire engine

  285. File instrument

  286. Angel fish

  287. Nutritious fig

  288. Fifi honey (This French character is a honey)

  289. Santa fabulous

  290. Necessary pass (bus pass)

  291. Pit instrument (takes core off apples)

  292. Ban snowmobile

  293. Intersection bum

  294. Snipper viewfiner

  295. Nipples cow’s

  296. Beach sunscreen

  297. Bike handlebars

  298. Peave insect

  299. Newborn baby

  300. Moon size

  301. Mist spray

  302. Snow man

  303. Homo males

  304. Miserable (movie scene)

  305. Muscle truck’s lift

  306. Massage

  307. Mask

  308. Massive elephant

  309. Spy minicamera

  310. Mitts

  311. Matted king

  312. Madona

  313. Time mountain

  314. Metro (subway)

  315. Metal lingo

  316. Attach motorcycle

  317. Medic

  318. Motif cardigan

  319. Metabolism tube (dr’s)

  320. Nasa missile

  321. Minth

  322. Nanobe microbes

  323. Enemy monster (child movie character)

  324. Minor

  325. Manual harmonica

  326. Manage pocket

  327. Maniac (mass killer)

  328. Margarine knife

  329. Nab merlin

  330. Mass mixture (beer maker)

  331. Home maid

  332. May man (a fly)

  333. Mom’s umbilical cord

  334. Mesh armor

  335. Mammal muskrat

  336. Medal damage

  337. Smoke smoke

  338. Movie image (cardboard dummie)

  339. Montreal Map

  340. Morse

  341. Heart emergency (machine heart)

  342. Submarine

  343. Army market cap

  344. Mirror

  345. Meat grill

  346. March majorette

  347. Morgue

  348. Smurf

  349. Troupe members

  350. Molasses

  351. Mold

  352. Melon

  353. Lame model

  354. Magnetic layer

  355. Lowly board piece (mini plane)

  356. Mileage counter

  357. Milk bag

  358. Maple leaf

  359. Cement slab

  360. Midges

  361. Midget

  362. Madvac machine (street vaccum)

  363. Gym Mass

  364. Cheer Mascot

  365. Jail mate

  366. Chouchou mini

  367. Magic cards

  368. Achieve macramé

  369. Chip monk

  370. Mucus

  371. Maggot

  372. Metal cane

  373. Monopoly game

  374. Meager muffin

  375. Smuggle (small spray can)

  376. Cage hamster wheel

  377. Kick ambulance

  378. Cave man

  379. Cup musk skunk

  380. Match fuse

  381. Fat swimmer

  382. Mini van

  383. Foam mixing (hair washing)

  384. Meditation Fair

  385. Muffle removal (car snow brush)

  386.  Minnow fish
    
  387. Fog humbrella

  388. Fifi Smile (logo)

  389. Fab pumpkin

  390. Military base barbed wire

  391. Moped

  392. Marshmallows bun

  393. Main beam construction stage

  394. Disappear magician

  395. Cymbals the pits

  396. Swim badge

  397. Bike magazine

  398. Cement pavement sidewalk preparations

  399. Pipe man

  400. Uranus size

  401. Rust vent

  402. Reasoning brain

  403. Racism Mandela

  404. Razor

  405. Harp seal

  406. Horseshoe

  407. Risk pogo stick

  408. Receive santa’s red bag

  409. Raspberry

  410. Roots dandelion

  411. Rated rook

  412. Written notes (parachuted from sky)

  413. Redeem walking on cloud

  414. Radar dish

  415. Retail defence (on front window)

  416. Radish

  417. Arctic aries

  418. Deafen siren (police’s car top)

  419. Deep rig (for loading)

  420. Harness (climber’s)

  421. Ravine newt

  422. Canon round

  423. Numb arm

  424. Air banner

  425. Arsenal catapult

  426. Syringe

  427. Real knocker (puppets)

  428. Round knife

  429. Nab earthworm

  430. Swarms flies

  431. Remote control

  432. Roman candles

  433. Mom’s relick (art belonging to mom)

  434. Armor tank

  435. Airmail letter

  436. Hair damage (hair loss)

  437. Rudimentary hammock

  438. Remove dust pan

  439. Ramp

  440. Rice cereal

  441. Sewer rat

  442. Ruin remains

  443. Rotating rim

  444. Rower oar

  445. Restaurant Grill (outdoor pick nick table)

  446. Rich residence

  447. Road reck

  448. Aerial roof (mobile platform)

  449. Rhubarb

  450. Rolls die

  451. Roulette lottery

  452. Airline

  453. Rolling lime

  454. Ruller

  455. Lowly raccoon

  456. Relish

  457. Air leak tube

  458. Red pine leaf

  459. Loopy earing

  460. Arches (Arch of Triumph)

  461. Searched hut

  462. Razor machine

  463. Gym horse

  464. Hair chair

  465. Hair gel

  466. Chouchou rail

  467. Artichoke

  468. Chef refrigerator

  469. Chip recording

  470. Circus

  471. Pingpon racket

  472. Hurricane satellite photo

  473. Racketball game

  474. Rigor mortis dead bird

  475. Ring bill gull

  476. Royal Cash 10 $

  477. Kick a Hockey ring

  478. Cave art

  479. OCAP Rally (legislature statue)

  480. Effacer

  481. Rivet

  482. Ravine

  483. foam surfing board

  484. river

  485. rifle

  486. fish reef (aquarium prop)

  487. fog raincoat

  488. Uranium symbol (I don’t remember why)

  489. Fabulous road runner

  490. Ropes for training

  491. Rabbit

  492. Harpoon canon

  493. Vynil pocket (recording album)

  494. Robber

  495. Rubble

  496. Hair peach

  497. Repack socket

  498. Pave roller

  499. Orange pip

500 Leases bowling alley
501 Last icicle
502 Listen student desk
503 Wholesome store cashier plastic bag holder
504 Laser
505 Lawful seal
506 Siege ladder
507 Alaska igloo
508 Lessive (French, tray inside dish washer)
509 Liquid soap
510 Lights (stage lights)
511 Lighted lighter
512 Latin species pined insects
513 Ultimo calendar
514 Liter container
515 Little lectern
516 touch linesman
517 think library shelves
518 stiff olive
519 Deep see life fish
520 lenses magnifier
521 lint from screen of drying machines
522 noon lunch box
523 numb leg
524 linear triangle music
525 solar panel
526 lynch stand
527 neck lace
528 long knife sword
529 line-up super market
530 maze labyrinth
531 limit flag soccer
532 lemon
533 Alps mommy frozen
534 lemur
535 lotto mall booth
536 sledge damage
537 electronic mike
538 move lawn rolled grass
539 lamp shade
540 walrus
541 Alert
542 long runway
543 alarm bell red
544 lord prayer cross
545 trail lynx
546 large bobsleigh
547 leaf rake
548 larva caterpillar
549 lofty ruby
550 Lilies
551 salad lettuce
552 laundry line
553 lame holder candle stick’s
554 aluminum layer
555 lowly alligator
556 slippery algae on rock
557 slack elevator
558 leaf littering bum (guy who litter the streets with free papers)
559 loolahoop a circle for swinging around waist
560 leeches
561 lumber shed
562 laundry machine
563 gym locker
564 electric chair
565 isolation jail cell
566 chouchou wheel
567 yellow chick
568 Chief woolves alpha and betta
569 chop helicopter
570 littering goose
571 liquide lubricant 9
572 lagoon like shaped transistor
573 legume been pod
574 loggerhead
575 galley labor
576 luggage
577 lumpy gag
578 loony goofy
579 lock up bike lock
580 law office reception desk
581 low lift lifter’s power bar
582 ceiling fan
583 love him (give him a G-string underwear)
584 leaver (bike tire repair)
585 level
586 fish lobster
587 fog lightening
588 Fifi elastic Mischievous girl slings elastics
589 fabulous Luck Luke cartoon
590 peace logo
591 lipid spoon (with hole in it so you can lose weigthd)
592 pin wheel fire work
593 stamp album the plastic strip used to hold the stamps in the album
594 wheelbarrow
595 label on shirt
596 beach life guard chair
597 bike helmet
598 peave holes (a bin full of holes I used to own)
599 pipe line
600 Jupiter size
601 just woman the washroom sign
602 switch is on a lever switch
603 miawo’s chow cat’s bowl
604 chasing zoro
605 chisel
606 siege chariot western
607 shrink sack windbreaker as a belt pouch
608 sofa chesterfield
609 sugar maple sap container
610 shades
611 toad shrimps
612 judo dan belt
613 generous dime
614 shooter volleyball
615 shuttle space
616 shallow ditch
617 zodiac Sagittarius
618 chef d’oeuvre mountain of bike art
619 gel tip of tooth paste
620 Chance joker character
621 chant ear muffs
622 jet canon kid mall ride
623 numb jaws from movie Jaws
624 chalk banner
625 channel western bar like double swing doors
626 change room
627 unique jersey Vince Carter’s
628 Jungle knife
629 Chew nib
630 Ash moss (tree leaf)
631 mud jam
632 chimney
633 chubby mum pregnant
634 mayor chamber city hall
635 male jock exercising with small weights
636 show homage
637 Shoe Mountain Equipment Coop (MEC) shoe stand
638 movie jock small flash light
639 chimpanzee
640 Raise a Javelin
641 Shredded paper
642 journalist’s station logo on mike
643 germinating avocado
644 rare gene double helix model
645 cheerleader
646 church
647 shark
648 sheriff
649 Shrub
650 shoe lace
651 shield for motorbike
652 balloon ship
653 juggling lama
654 jade layer
655 lowly checkers
656 shut eye lash
657 shylock’s security bank window
658 shelf brace
659 giant globe
660 chachas’ ball disco ball
661 chasing cheetah
662 jack hammer machine
663 gym jackstrap
664 jammed jar
665 shinny Jell-O
666 Judge’s jewelry
667 chic chandelier
668 Achieve shorthand steno
669 chop chard
670 Jingle keys
671 jacket
672 sugar cane
673 jig saw game (puzzle)
674 sugar bag
675 chuckle mike’s stand comedy
676 baggage journal
677 kick a G-I Joe
678 shopper’s coffee
679 Aged cob
680 shrub vase
681 shaft
682 fine chocolate
683 fame shoplifter (a politician)
684 chauffeur helmet
685 shovel
686 fish shit
687 vogue shirt
688 jumping hoof deer
689 fab 007
690 Space ship enterprise
691 shoulder pad
692 ban a chop board
693 bum jewel (carved soap sold on streets)
694 Giant pear
695 chapel
696 shobby pouch worn at the waist
697 shot puck
698 pave shingle
699 chief pope
700 Galaxy size constellation
701 Cast (arm plaster)
702 cousin
703 cosmos observatory
704 Sahara cactus
705 Guzzling toilet
706 massage cream pot
707 zigzagging pin ball machine
708 goalie save arm pad
709 soup crouton
710 kites
711 gobbling toad
712 guitar tune
713 time course (starting block)
714 glass cutter
715 cuddle a doll
716 caddis fly
717 tack gun
718 scuba dive snorkel
719 deep gage for oil
720 canoes
721 queen ant
722 canon on large battle ship
723 enemy ghost
724 skinner sealer with club
725 square funnel for liquids
726 carnage body parts
727 conic nuke explosion
728 knife exacto
729 nab cobra
730 gums of teeth
731 comet
732 gammon game triangles
733 crown mummy
734 camera
735 camel
736 scrimmage exit sign
737 smoke cone
738 move cadence (tempo keeper device)
739 camper towed
740 grease
741 shopping cart
742 crane
743 groom from top of wedding cake figurine
744 courier van
745 coral
746 crutch
748 scarf
749 grips on a bike
750 claws of bird
751 cloud
752 clown
753 clam
754 clairvoyant’s crystal bowl
755 Galileo’s binoculars
756 clutch birds
757 clock dial
758 gloves
759 paper clip
760 coaches’ corner Don Cherry
761 Gadget bike seat spring
762 keyboard machine
763 cut gems
764 catcher
765 jail camisole
766 chouchou coke
767 choke exhaust (truck’s)
768 shave crop blade
769 ketchup
770 cocos
771 comic kid Charlie Brown
772 Christmas cane
773 hockey game (stick)
774 go-cart
775 goggle (swimmer’s)
776 baggage socks
777 kick aquarium
778 coffee grinder
779 cupboard garlic
780 vice grips
781 ski lift seat
782 coffin
783 fame Socrates’ drink
784 Car cover
785 Gavel
786 Squid fish
787 Kangaroo ■■■■!
788 Fifi’s school play ground revolving play ball on stand
789 Fabulous Gaston (cartoon character)
790 booze caps
791 ink spot
792 Cabin cruiser
793 bum’s cardboard
794 copper glass
795 battery cables
796 cabbage
797 bike cable housing
798 pave garage door
799 baby sucker
800 Venus size
801 fist
802 vicinity phone booth?
803 homo females
804 fissure on dam (this one not correct as fissure should be 864 but it still works)
805 fossil
806 physician
807 viscous liquid for photography in trays
808 save vault
809 vegetarian soup
810 fetus
811 fetida bin a worm bin (see my handle)
812 vanity tan lamp for tanning
813 time avalanche
814 feather
815 vital water gourd
816 touch Velcro
817 ■■■■■■■ dick (this is not obscenity, it represent a ball kicking person I once briefly heard)
818 Flying dove
819 deep foundation
820 fans
821 faint microscope
822 violent canine
823 venomous frog
824 vinegar
825 funnel
826 finch
827 unique fire ball WTC
828 folding knife
829 nab a fox
830 moss verdure
831 vomit
832 famine ( a paper famine measure used on starving kids’ arms)
833 mom vibrator
834 femur
835 female underwear
836 flood damage wood work frame as base
837 mock fire device inside fire place
838 moving van
839 damp vitamin cotton inside new bottle
840 frozen ice-cream
841 grapefruit
842 fern
843 farm field
844 rower’s vest safety
845 food roll
846 fractured ridge
847 fork
848 fair ref
849 refurbished leg stand
850 fleece jacket
851 football field
852 violin
853 flame thrower
854 flower
855 lowly floor wood strips
856 flash bulb
857 flag
858 Presta valve (narrow bike valve)
859 floppy disc
860 fudges
861 fidget fountain
862 ■■■■■■■ vagina (not obscene, if represent a guy scared of the ball as per ■■■■■■■ dick)
863 Gym vault
864 folding chair
865 Jelly fish
866 fair judge
867 fishhook
868 fake chefs protest
869 ship vessel a dinghy
870 gas filter mask
871 fact marker
872 vegan wide out door steps at the vegan food fair
873 football game (oblong ball not soccer)
874 figurine lawn
875 fickle weather cock
876 baggage voodoo dull
877 kick a furnace
878 coffee filter
879 cupboard floss
880 office fax
881 vivid red light
882 vertical vine
883 fame Van Hallen belt (just a belt)
884 fever thermometer
885 fuel facilities (pumps)
886 flying fish
887 fog fender
888 fluty flute fife a small flute
889 fabulous Fanfreluche TV character
890 booze flask
891 flower pot
892 frying pan
893 photo album
894 flying prey (flying squirrel)
895 feeble flight (first, Rights bothers)
896 beach flippers
897 bike frame
898 peeve flood light
899 effervescent pop
900 Pluto size
901 past tombstone
902 basin for children playing
903 asthma spay medication
904 Bizarre clothing
905 puzzle block 3D
906 sage spice
907 soak sprout bag
908 passive beetle
909 soap bar
910 winter boots
911 potato
912 beaten stretcher
913 Dim button round switch
914 potter
915 pedal
916 touch a porcupine
917 bulldog
918 dive board
919 black tape, electrical
920 pins
921 paint
922 banana
923 venomous spider
924 banner (happy birthday)
925 panel discussion
926 punched black eye
927 bionic pirate with missing arm and a hook to replace it
928 box knife
929 snap button
930 bemuse pause of thinker statue
931 permit in elevator
932 open mine back hoe bulldozer
933 mummy pyramids
934 bummer guitar case for donations
935 mail box
936 match box
937 smoke pyrotechnics
938 movie popcorn
939 pump bike
940 price sticker
941 bread
942 prune
943 broom
944 payer host (the round bread at the church)
945 pearl
946 hair brush
947 brake system, bike
948 professor black board
949 probe dental
950 place hooks for coats on the back of doors
951 bald head
952 plane (delta plane not to mix with 452)
953 plumb for fish line
954 pillar
955 lollypop
956 whiplash, a whip
957 plug electric
958 believe in fairy
959 bulb 60 watts
960 patches bike
961 bed sheet
962 bank machine
963 gym bag
964 baby chair in restaurants
965 jelly beans
966 judge’s pot
967 chick pea
968 chef’s pepper
969 potato chip
970 pigs
971 picket strike
972 can opener
973 basketball game
974 poker hand
975 bagel
976 courier package
977 kick a bungalow
978 coffee bean
979 cupboard
980 office building
981 pivot for doors
982 bovine face
983 Presley fame
984 beaver
985 biting flea
986 fish penguin
987 for boots (waterproof)
988 bee hive
989 fabulous Bobino TV character
990 baseball base
991 bibbit lady bug (bibbit is French, I think. I think it means critter. puppet instead?)
992 Ban bullets
993 bum blanket
994 bar bouncer
995 pebble
996 police badge
997 bike spoke
998 pave brick
999 plastic pipe

2 Likes

Thanks for that Simon.

I will be using some of these images. A lot of them (most?) seem to not conform strictly to the rules though. The consonants seem to be able to be in any position of the words, with it rarely being 1.2.3, often it seems to be x x 2 3 X 1 or something similar. A lot of them are also 2.3 1 x x x. Did you just look for any word that had any combination of the three consonants in it? With you having 10? sets of 1000 images, I don’t blame you. Interesting method by the way, seems very difficult to keep track of that amount of images in a way that you can retrieve them efficiently, but stranger things have happened.

Hi Bateman,

You are welcome. I’m glad I could help with some words.
Yes, I do give myself a lot of flexibility in my system. Take the word BeaCH for instance. When I have two consonants like that, I really like to keep them for the last two digits, X96. Then I use a first initial for another word to go with it (flippers, lifeguard). I know that I would never use the word Beach for the first digit of the 900s because I use it all over for the 96. I’m also often ignoring the first S of a word because its value is zero. For instance, in Beach suNscreen I consider the N to be the first consonant. I almost never use the first initial of a word for the last unit of a number. I found that having this system does help.

I think I have 2 German words in my list. I’d expected to have more, but didn’t really need them. I have a couple of Japanese words, too.

Hi, I want to make a 3 digit system and so far I think the best option would be the Ben system. I have a few questions for those of you who use a 3 digit system:

Do you think it is better than a two digit system?
How many images do you place per locus?
Does a 3 digit system have slower recognition than a 2 digit system?
Would you recommend it for spoken numbers?
How long did it take to learn all the images?

Thanks!

MCEVE01, I hope others can answer your questions, but I’m going to refrain until I have more experience. One thing I will note is that a 3-digit system will definitely reduce your incidence of repetitions. Consider the task of memorizing 1000 digits in less than 1 hour to meet, for example, one of the GM norms. With a 2-digit system, you’d need 500 images, so each image you’d expect to encounter on average 5 times during the run. Maybe you can manage that, but what most people don’t consider is that that’s the average. The worst offenders (images that coincidentally repeat the most) could appear 11 times or more on a typical run, and almost all of the images (over 99%) will be seen. (I simulated this with a program.)

For a 1000 image, 3 digit system, you’d need 334 images to encode all 1000. If I run this through my program, the worst offenders repeat maybe 3-4 times, and 72% of the images won’t even appear once in any given run.

So that’s good news and bad news. The good news is that with a 1000 image system you won’t have to deal with repeated images anywhere near as much. The bad news is that normal practice (just using the system to memorize numbers) won’t exercise all of your images. You have to rehearse them systematically.

From a human experience, a lot of my new images are still surprising me, and I think that’s good. With 100 images, that doesn’t happen as much.

If you have 1000 images and one of them is Godzilla, when you finally see Godzilla it’s like “wow, Godzilla just showed up at my place and started crushing everything in sight and setting it on fire.” That’s pretty special.

If you have 100 images and one of them is Godzilla, you get used it. You see Godzilla all the time. It’s more Godzilla is your roommate you chat with all the time but still never washes the dishes. Somehow being Godzilla isn’t so interesting any more. :slight_smile:

  1. The major system is also a viable option to use for a 3 digit system, including fine options for binary and a 2-card systems as well as the Ben System. It is what I use and have found success with personally, which is why I espouse it. But the Ben System works too.

  2. Yes, there’s no question about it to me. One or two people have reached elite levels with a 2-digit system, but it’s rare, and I wouldn’t count on you or anyone else to be the third person to make that work.

  3. Different strokes for different folks. But for most of us it’s 3. I’ve had nearly equal success with 2 even though I rarely try it. Just the other day I set a PB with 2 per locus, but I think I could do it with 3/locus also. If possible, 3 is obviously better than 2 for the 33% reduction in loci used.

  4. It depends on the user. I don’t think many people can recognize their 2 digit systems as quickly as I can recognize my 3-digit one. But Wang Feng can recognize his 2-digit images faster than I will probably ever be able to. Are you the next Wang Feng? Maybe you are, but for us humans, the 3-digit systems often start getting pretty fast before long, and that doesn’t happen as often with 2-digit systems…but of course it can.

  5. For spoken numbers, it is just awesome. I love getting 3 seconds for each image.

  6. I think you can memorize them pretty quickly. It takes a lot longer to get to the point where you never have to stop and think about it. And then longer to get to the point that you feel comfortable with the details of each image. It varies from person to person, but I would say that if you would be satisfied with an above-average competence with number scores in one year from the starting point, you should definitely do it. It took me probably a quarter of that time to go from a speed numbers PB of 120 to 240, and the rest of the year to get that up to 360, tripling the starting point. I practiced a whole lot to get there though, which is why I said “a year” above. A score of 240 is well above average on its own, and you can easily move beyond that with some patience. But with a few more months practice with a 2-digit system, that starting point could probably have been much higher and you would wonder if it was even worth the effort. It’s all so relative that it’s hard to even talk about. But I DO NOT think there is anybody who has learned a 3-digit system and regrets spending the time. I for one will never use a 2-digit system again.

If you plan on sticking with memory sports for years, and you have the patience to carry out long projects, do it.

It’s really nice post, Lance. Thanks a lot :slight_smile:

Thanks, Lance. I’ve started on the Ben system for decimal and binary because I like his idea of one syllable words. I think I might use it for cards but 2704 images is a lot!

I have started my 1000 objects and am having a hard time with:

x6x
xx6
x8x

Anyone have some general tips for dealing with these 300 objects?
I like the idea of sometimes having exceptions but don’t want to confuse myself by having too many

I do feel that Loci’s estimation of 6-12 months is correct…
I will give you an update

All Major? If you are using the usual “6 = sh, soft ch, j, soft g, zh” then I understand. The truth is that combination isn’t as frequent as some others. Leading ‘n’ can also have more gaps for the same reason.

I adopt a variation where I moved the hard ‘g’ from 7 to 6 but I also allow 6 to represent the sounds above. In normal Major system, ‘g’ is grouped with ‘k’ which is logical as it is phonetically similar. However, ‘k’ by itself has enough matches to stand on its own, so I decide to move the ‘g’ to help out the ‘j’-ish sounds. I’m not saying I recommend it…in fact recently I considered undoing it because it’s less natural, but it did help with some gaps.

Whatever you do, it’s going to be a bit of a whack-a-mole exercise with 1000 images. You might make a change that makes one part of the table easier to fill in but it will make others harder. 5-10% nonsense syllables or creative cheats actually isn’t that bad.

Direct association is still possible with some of the 1000 images. For example, I noticed recently that when I look at 262 I sometimes think of a marathoner because 26.2 miles is the length of a marathon. That’s not my image, but it could be.