Hi folks, I’m new here. I’m an amateur researcher and recently stood up a non-profit aimed at scientific exploration of consciousness. One of the areas that’s interesting to me is psi, or MMI. I’m broadly familiar with research in these areas, and like the summary here. I’m particularly motivated by experiments performed by Helmut Schmidt and also Dean Radin.
I’ve done a number of experiments to try to get even moderately consistent results with using focused intention to impact physical reality in measurable ways, primarily with emphasis on influencing random number generators in particular directions. I’ve so far iterated through a few different types of RNGs. First, I tried using once that produces random numbers on-demand in real-time by measuring the quantum fluctuations of the vacuum (more details). Not getting the results I hoped for, and not seeing what appeared to be sufficient randomness, I moved on to a hardware-based TrueRNG3, which uses the Avalanche effect of a diode to generate the raw random bits. At that point still not getting the results I wanted, I opted to make an investment in using the same type of random number generator used by Helmut Schmidt in his many successful experiments over the decades - a Geiger counter connected to a computer that was constantly scrolling through a list of numbers. Whenever the Geiger counter detected particle decay, the computer would stop and select whichever number it happened to be on at that time. A limitation of this approach is that particle decay from background radiation is usually only detected about once a minute, which means one random number per minute, but by placing a few chunks of radioactive uranium ore directly next to the RNG’s Geiger counter I increase this to a number every couple of seconds.
My experiments are performed using Python code I’ve written. It basically uses the Binomial Test to determine the probability (p) and gives real-time feedback of the probability of randomness, both via a constantly-updated line-chart and via an audio tone that increases in frequency as the p value decreases. We aim to get a p-value less than or equal to 0.05 with some consistency. The code also has the ability to generate pre-run sets of random numbers whose outcomes are respectively both observed and unobserved, and then both sets are intermixed with random numbers generated in real-time while being presented to the influencer. Though the influencer cannot distinguish between the various sets during the experiment, their influence on each of the different sets (pre-run observed, pre-run unobserved, real-time generated) are measured distinctly for post-experiment analysis. The hypothesis here builds on existing experiments (example) suggesting that unobserved results should be as influenceable as results generated in real-time.
Mostly I am performing these experiments myself, meaning using my own intention, but do have a woman that regularly participates as well. Frankly probably neither of us have actually invested the amount of time and effort that it may take to build these abilities sufficiently.
Regardless, in the end, I have not been able to achieve consistently positive results. Occasionally I get a very positive outcome, but not with the consistency I’d need to show that it wasn’t due to random chance.
I’ve spent some time reading through Scott’s various papers, patents, and the content on this forum. I’m excited about efforts to dramatically enhance the effect of MMI through new software and/or hardware techniques. As far as I can tell though, and please correct me if I’m wrong, despite a lot of effort and approaches that seem to have some tentative potential, there haven’t been significant and consistent successes. Do I have that right?
Basically I’m really interested in finding ways to get more successful and consistent experiment outcomes. If there are algorithms or different types of RNGs or approaches I can be trying here I would love to do so. (side note, I’ve tried installing the METrainer and QNG360 but am getting errors in Windows - perhaps related to the fact that I am using Parellels to run a Windows 11 VM on a Macbook Pro with an M2 chip - but would love to get some assistance on that. I get errors about DLLs failing to load when installing QNG360, but it installs. Despite that when I try to run either of the .exes, even in various compatibility modes, a window pops up and immediately goes away).
One idea - I have an Emotiv Epoch on hand and am aware of research that has shown a correlation between various brainwave states and success with MMI (psi, pk, etc). (examples: 1, 2, 3, 4). Perhaps constraining analyzed results to those correlated with one of these brainwave states helps reduce noise. But, I have enough experience with EEGs in the past to know how difficult it is to get usable data from them due to so much fluctuation across different frequency bands in different parts of the brain, and many factors influencing those fluctuations.
There seem to be a variety of factors impacting PK (MMI) ability. It sounds like it may even be useful to build a Faraday cage to shield factors such as geomagnetic activity that seem to mute any psi/pk/telekinetic/MMI ability.
I’ve even contemplated using Kozyrev Mirrors in conjunction with these experiments, or Holotropic Breathwork.
There also may be some potential in trying to influence biological systems rather than non-biological (1), as some evidence suggests greater ease of influence in that domain.
I guess I’m just looking for some guidance and/or inspiration on how to proceed with this stuff. I’d love to start seeing some more promising results. Lastly, as an aside, I do have another area of active research, which relates to quantum physics and designing and executing an experiment meant to test and ideally validate the Von Neumann–Wigner interpretation that consciousness causes collapse of the quantum wave function. I’m excited and tentatively optimistic there, but recognize it’s out of scope for this forum.
