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Tuesday, April 23, 2024

Web Guru Who Exposed 2020 Vote Fraud Asks Musk to Hire as Twitter CEO

'I have 4 degrees from MIT & have created 7 successful high-tech software companies...'

(Jacob Bruns, Headline USA) Data scientist Shiva Ayyadurai, who notably used algorithmic analyses to help expose vote fraud in the 2020 election, told Twitter CEO Elon Musk that he would like to become the new CEO of Musk’s social-media company.

“I have 4 degrees from MIT & have created 7 successful high-tech software companies,” he tweeted in December, garnering more than 80,000 likes and 10,000 retweets. “Kindly advise of the process to apply.”

After receiving no reply from the red-pilled Tesla billionaire, he reiterated the offer on Feb. 12.

My offer to be CEO still stands as my goal is to deliver #FreeSpeech to the world,” said Ayyadurai, the self-declared “Inventor of Email” and a former Massachusetts senatorial candidate.

Ayyadurai offered his services just months after Musk said that he would step down as Twitter’s CEO if he could find a suitable successor.

“I will resign as CEO as soon as I find someone foolish enough to take the job!” Musk tweeted at the time. “After that, I will just run the software & servers teams.”

His successor “must like pain a lot” to run a company that he said has been “in the fast lane to bankruptcy,” he noted.

“No one wants the job who can actually keep Twitter alive. There is no successor,” Musk added.

However, Ayyadurai may prove to be the very type that Musk is interested in.

Back in 2020, Ayyadurai presented what appeared to be a cut-and-dry case of systemic fraud that stemmed from the voting software used in several Michigan counties.

He discovered that in that election 69,000 votes in the counties appeared to have been taken from then President Donald Trump and given to Democrat candidate Joe Biden—a net gain of 138,000 votes for Biden, whose current projected lead in the state is just over 146,000.

Ayyadurai specifically noted that the automated voting systems—such as Dominion Voting Systems—may be to blame.

The results, he wrote, make “no sense unless a computer algorithm was in place to lower Trump’s votes as a function of Republicanism in a precinct.”

“Our position is that it could only be done by a computer algorithm in such a precise way over so many precincts,” he added.

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