I went a little crazy on the testing and my notes alone are over 10 pages but I will post a broad summary of some changes to keep the post clear.
After a lot of trailing and error I have come to the consideration of using my custom morph system. My morph system a little which is similar to the shaper system but instead you mentally convert the text/numbers you are seeing into images even if you need to distort them. The reason for this change is because there is no training time in using a system which takes the cue as the input data to produce an image. The shaper system is also equally compatible. The reason for me choosing the morph system over the shaper system in tests was as follows :
- It takes me less time to make images as I don’t have to think of suiting images but instead morph the text to be suiting to any image.
- My tests showed that if I encoded 4 digit numbers in real time with the morph system I didn’t lose track of numbers. If I do the same with the shaper system because the shape of the image in the moment isn’t precise enough (at-least for 4-5 digits) I lose digits in real time. It seems with the morph system the detail from the encoding of all digits as one is retained.
- It retains the same benefit of requiring less training to be instantaneous as the shaper system.
Alongside this I also tested :
Encoding the writing of digits on other images with memory palace
(more memorable than expected but not significant).
Placing morphed images in a memory palace
(seemed less effective for speed but was good for general storage)
Morphing shaper images rather than the digits.
(Strangely there wasn’t any confusion of using the shaper morphed images first and it improved recall but not significantly)
( had higher recall than initial shaper but was 0.1 seconds slower per digit)
( took 8-9x the time of normal shaper but had perfect recall besides 1 error)
(took 8-9x the time of normal morph but had perfect recall)
(Didn’t do well up to 20 digits but was 2.5 times faster than shaper).
(It felt strange but was unique and okay effective took 2x the time of the shaper system)
Spatial link system
( took 3x the time of the spatial system without it)
Combined spatial and shaper system
(while slower than the spatial system 1.5x, interestingly with the first time using mnemonics I was aware of the quantity of each digit in the sequence, even if I did not remember their order so well )
( interestingly took 0.06 seconds more than the shaper system and was less flexible)
Shaper in memory palace
(took around 3x normal shaper, recall was perfect but notably speed and recall was faster if the digits were closer to assume a chunk than if spread out across the loci).
I applied all of these on 1 digit systems. My rules did not permit me to use chunks. So I was evoking the recall of 1 image and then moving to the next. I realized quite a lot of things in doing this and I have the exact data as well but it would make my post overly long.
Firstly a spatial system as I defined it is essentially similar to a PAO system but it only encodes the act of movement. I was kind of curious as I knew the brain region for this was heftily involved in memory.
When I did not combine it with the image I used a random image to produce the movements, in my case I simply visualized a blade and random persons swinging it in shape per digit. As it was overly unique of an experience ( it clearly felt different and had a hint of some more things to discover ), I decided to further test on spatial things in the future.
The sound system encoded a shorter sound per digit that I was not used to using. It was slower than the sharper system which is a good indication that the sharper system is fast enough out of the box. Regardless it was very obvious that where I was losing all the time was not in recalling the digit but moving onto the next digit after recalling the previous one. There was some kind of refractory period even if I clearly knew which image was next. This also applied to all systems but was pruned on the spatial systems.
I got to a number of conclusions :
Firstly these methods would obviously work. By learning chunks you would learn how to quickly place digits after the others. The downside to this is that it takes a long time to cover all possible chunks, far more than making another 5 digit system when you get to a 3 digit one.
Parallel encoding would naturally be encoding multiple digits at a time so it would have more chunks in a single go. The downside was that this itself required training and wasn’t exempt after hitting the adequate chunks, in the end it would also suffer from fighting peripheral vision. Also, most of all, memory champions who train a lot likely do not use these 2 principles but still get their time down significantly.
As a result of this I considered really what other possibilities there were. Theoretically ‘having a stronger connection’, ‘more efficient synapse’, while it makes sense is kind of on the wrong point. What I was facing was a refractory period which either of these isn’t expected to help much with, and for a synapse learning a chunk would naturally be effective. I thought there should be another thing that can be done besides having a upgraded synapse, cross activation’s and ‘stronger connection’. The shaper system essentially has a very strong connection to the digit because it is self contained, the connection should be efficient. When I considered this it really hit me though, what I was essentially doing was evoking 1 image, stopping it and then starting the next. It’s a very logical thing we don’t usually overlap images when evoking 1 at a time but I realized 2 things here:
- I was artificially waiting for the first image to fade before I started integrating the next image.
- When I tested the spatial system It felt very different because I was not really waiting for anything to fade. This point is really logical because we can draw on paper we don’t have to wait until a line is drawn and say okay before we draw the next one. More so we don’t have to do this for every mark the pen makes on the paper.
Considering those 2 things I realized some precise ways I can reduce the time otherwise.
- Increase the speed at which I clear the image
- Place or activate an image in a way that I could equally so and easily so activate a second or third so I don’t have to wait for it to end.
To my surprise or perhaps as expected, increasing the speed at which i clear the image led to increased encoding speed and reduced time per digit proportionately to how quickly I can clear the image. Even more surprisingly when I started the process of converting images to numbers while staring at the numbers in a spatial field like visualizing the images on the screen as I encode them with my eyes open in mini version. My encoding speed essentially skyrocketed to some competitive levels. Even using a memory palace in this way was much faster. This is also for 1 digit precisely to make testing more effective. The results would be at-least 3x faster with a 3 digit system, but I could definitely encode the digits doing this faster than I could read them.
I will plan to do some speed reality checks when I extend my system, for now the 101 image morph system is complete, for digits 0-100.
Essentially I have indirectly solved the issue of fast chaining, which I will verify when I fully complete few systems. I believe it is more effective to a separate post on updated goals so I will do so shortly.
Since I have validated my decision on the system I will use I will now also apply spaced repetition as appropriate (I reintroduce anki here). With the memory capabilities of shaper and morph systems, I will likely be able to work in batches of 100 digits comfortably.
Further tests will include a structured memory palace for information but this will be post the next goals (I hope).