Major Job Opportunities for young people – Resellers collaborate with the library to temperory loan out tech products and others. Youtubers could make a 2 weeks loan on it to do a video. Earn money for themselves and the resellers. Library could be a job creator. Wow tech // Per
You can calculate everything with machine learning as long as you know a relevant truth. Just to do experiments that the matrix function model then has to adapt to. Assume all
input data can affect the virus. Then you insert a truth in the process that becomes label = 1 and without label = 0. Then train the model so that it grasps when something has been
inserted. It corresponds to 0.0.93,1.22, -0.01,1.01,1,0.1,0 from random mix of data. Remove the manual deposit and see what the model classifies for similar problems.
Idea – You can measure magnetic field noise and the time it takes for the virus to die in a hot water saline solution and in a hot water solution. It will be label 1 for saline and
label 0 for hot water only. Collect a lot of data X_train and y_train = 0,0,0, … 1,1,1 … which is a label truth> 1 min. Randomly mix data and then practice the ML function.
Then run the model on any substance in water to calculate the probability it takes before the virus dies.
Quantum Computer = Function(raspberrypi) – guess – Noise is music to atoms. So different atoms will respond differently to different noise. Assume correct results means the atom liked the noise. Classify different noise functions to different atom # id’s. Then use only good fun.
Machine Learning Math – Adapt a initial Quantum Particle Matrix so that a zoom in series reduction get the true temperure value. Testing…
Playing on the Raspberry – guess idea – With a hdmi capture card usb3 dongle connect a google chromecast ultra stadia to the pi4 and play through that. @EbenUpton
Math guess – If all points in a graph are true you don’t do a linear approximation function. Since its a line between two points that is the thing. Draw other lines so you don’t need to change the point locations. Then what properties? All multi line coeffients are define trusted
Super Home Treatment – White point cabbage + sea salt. For the brain. // Per
Black hole information paradox – If an object is digitialized in 0’s and 1’s you can imagine the logic of super position travel. If a particle changes between 1 and 0 you can do inf. particle add(a,b) when its 0 since the result is 0. So you need particle memory and 0 capability.
WOW – Machine Learning NEW MLP model – Insert another question to the outputs get perfect results back. map_rnd2 = np.random.permutation(np.arange(10)) y_train2_hot = lb.transform(map_rnd2[y_train]).astype(np.float32) // Per Lindholm 98.8% on a MLP 200 element wide.
Machine Learning idea – Large Paint On Models – Paint the x output from each layer with a starter model function. What would it look like 1000x larger. Then do an invers calulation on the weight matrix. And you get a much larger model. // Per
Machine Learning – Self Hacking Math Function – y = f(t) but at time t = 0 you change y.array = y.array*0+1 . Without any rules other than that. So could this lead to something similar to self learning by optimizer. Self hacking function. The dy suddenly differs from y. // Per
Infinite Processing Speeds – Everything are functions – You can input different things to atom functions. Like what would happen if you made a calculating diamond. Put a CPU inside a Diamond. The CPU iterates its own max processing speed. Wow if it works. // Per
Super Intelligence – Machine Learning bug searching numbers. Plot a series list comprehension function of the number and a sloping curve. If its not smooth something is wrong. Verified pi but not sqrt, log // Per Wow
Theory guess – Draw a circle many time around the nucleus by hand and you see you cant get it 100% right. The number of circles don’t overlap 100%. This is a general problem. So this loss problem gives an update assignment to the quantum particles. Leave or join the nucleus and take some energy with you. The probability is the function field from a machine learning function. Whereby the nucleus can nearfield ?teleport the electron to the right position with the quantum particles as input data. // Per
Why don’t MIT put some research on making rain clouds. To put down wild fires. It was not difficult. Boil salt+water. Cool down. Fill a spray bottle. Spray from an elevated position. Watch rain clouds form. We need water for everything. Perfect civilization rescued. // Per
Salt has an immediate on the throat when feeling the covid19 in that area. Take a seasalt flake right away the same time you feel a virus in the throat. Keep with you seasalt at all times.
Use business for good. Home delivery of covid19 adapted natural foods. Free or with almost free. Gov politics made easy. Make very much sense. 90% of the cure is food? // Per
You need to do steam inhalation from a boiling pot with salt+water. Salt is an active ingridient. Also wash floors with salt + water. If feeling the throat eat a sea salt flake at the same time. Gargle with cooled down boiled salt+water+glarlic cloves also if you feel the throat.
Machine Learning Math – Invent problems. Like getting a value in a differential equation to jump to another field line. This leads to large jumps that would occur in a spiral galaxy like andromeda. // Per wiki image
Super Genius – From newtons gravity law. G*m1*m2/r^2 = F and a known limit sin(x)/x you can argue that the equation has two limits. The realworld is a number and the real singularity is dimensionless. (sin(x)/x) * (1/r). Gravity is the dimensionless space that is modeled. // Per L
Black holes have large gravity so it has to do with 1/r^2. When r->0 we have a singularity problem. That problem has to do with chaos. Then there is a known limit for x/sin(x)=1,x->0. Replace 1/r² with f() then the secret of the black hole is how r goes to zero with inf. safety.
Gravity!!! – From f = ma we get f/a = m then what if a is 0. You get an insight from a = sin(x) and f = x the limit x/sin(x)=m. So mass is the limit and acceleration oscillates around zero most of the time then a force must be created to follow acceleration so mass exist. // Per
Super Intelligence Mathematics – Dual math functions. Every function(x,Xworld) has at least two inputs. Since calculation is based on causality you can assign kinship to variables this way. y1 = f(x,Xworld) and y2=f2(x,Xworld) // Per Lindholm