IPS PARTNERS POINTS vs AI Cash App and Data Science

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AI Cash App pays you cash for uploading images that are used to continuously train a Machine Learning model (Artificial Intelligence or AI/ML model.) The model is continuously getting trained so that it can stay up to date on the latest information including images of anything. The approach used to train the ML model is called Crowdsourced AI Training because it relies on the public for data collection and labeling. Using AI Cash App, 1. Select image: This is the data 2. Describe image: This is the label 3. Upload image: Final step of data collection 4. Get cash in days FAQ: 1. Specifically, what images are users required to upload in order to earn money? >> Any image for example it could be an image of a cat, an image of a car, an image of grass, etc. 2. How much money can a user earn by uploading an image? >> A few cents depending on the uniqueness, quality, and description of the image NOTE: >> Musicians upload their music to various music streaming services and get paid each time their music is streamed. >> AI Cash App users upload any images and get paid each time the images are used to train the Machine Learning model (Artificial Intelligence or AI/ML model.) >> AI Cash App's pay per training session is approximately $0.0005 and is subject to change anytime. So, you are paid a few cents for each image you upload and you also get paid each time the image is used to train the ML model. DATA SCIENCE In the Data Science section of the app, you can create your own Machine Learning model. The ML/AI model you can create is a high-quality time series model that can be used to predict/forecast prices for stocks, currencies, & derivatives; business sales; temperature; website visits; channel views; number of likes; etc. Unlike models based on Deep Neural Networks, this particular model is quite uncomplicated and hence, can be created within a few seconds. Nevertheless, storing it can be expensive in the long-run and for this reason, it should be deleted if it's expected to stay idol for more than an hour. To get started creating your model, you start by uploading historical data on which you want predictions/forecasts to be based. For example if there's any specific stock you like, you can upload a file containing its historical prices. You then go through a series of steps that take about a minute or so and end after a prediction/forecast is made. COMPUTE FUND ML Models use a lot of computational resources that are not free. For this reason, if you decide to create an ML model for making predictions/forecasts, it's also necessary for you to create a Compute Fund that's used to pay for the computational resources your ML model uses. Each time you use the ML model, the funds in your Compute Fund decrease by a few cents. After they decrease to zero, you're prompted to create another Compute Fund. To create one, you tap the "About Compute Fund" button and then the "Create Fund" button. Yours Truly, LogeekSoft