IJustCame.org offers porn for the greater good. This website donates a penny to charity each time you get off. The new porn website is where you can watch adult videos and masturbate for a good cause. But here’s the catch; each user is limited to 2 pornos per day with 15-minute breather between each video.
Stanford University undergrads Adam Lee and James Cook came up with the idea for the porn website after they spent “a drunk night partying at frats.” Lee told the Huffington Post, “Originally, we were trying to build a Tinder for lunch, for people who didn’t want to eat alone.” So basically, it was a full 180 switch from a lunch date to porn for a good cause.
Lee said that before they officially launched the website, they anonymously tested it and “in a very short time” raised over $1,000. “You can do the math on how many scenes were viewed, but that gave us the confidence to move forward.”
Currently, the duo is funding the donations from their own pockets but according to Cook, IJustCame.org will get sponsors soon. And Lee believes that their website could potentially donate millions of dollars to charity every year if everything goes according to plan.
The following charities split the masturbation money:
1. Movember Foundation – global charity that funds testicular cancer programs.
2. Ovarian Cancer Research Fund – charity in the US that funds ovarian cancer research to better diagnose, treat, and ultimately cure ovarian cancer.
3. Joyful Heart Foundation – an organisation whose mission is to heal, educate and empower victims of sexual assault, domestic violence and child abuse.
So remember that you can make a difference just by getting off. Will you make this world a better place?
3 Responses
To create the label set for a picture, we consider all potential ordered pairs of object proposals for that picture as candidates for
the common visible relationship. It exploits local and non-local picture cues to be
taught this illustration and hence recovers the occlusion relation. Generally, all the notations are the identical as JDTM, aside from the subject probabilities,
that are represented by embeddings. J lead-specific topics, that are solely represented
by the leading corpus. V words. With the three varieties of matters, the leading corpus and lagged corpus not only share some similarities,
however also have their own content traits. POSTSUPERSCRIPT for the three forms of
matters. To consider different strengths of lead-lag relationship, we alter the numbers of three
varieties of topics to mimic the scenario of no lead-lag relationship, weak lead-lag
relationship and robust lead-lag relationship.
For instance, (Rudolph and Blei, 2018) develops dynamic
embeddings, which build on exponential family to capture how the meanings of words change over time.
To acquire the subject embeddings and phrase embeddings, we comply with (Dieng et al, 2019) to apply DETM on the ACL dataset with
a total of fifty subjects. To train the model, a novel dataset is
collected and annotated, consisting of six manipulation relationship courses and thirteen device classes.
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