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Musk will drop Twitter deal if data on bots not provided

In a new letter, Elon Musk threatens to walk away from $44 Billion Twitter deal if the management doesn’t provide more data on total bot counts.

According to a letter sent by Elon Musk’s legal team to Twitter, “Twitter refused to provide the information that Mr. Musk has repeatedly requested since May 9, 2022 to facilitate his evaluation of spam and fake accounts on the company’s platform” and “It’s effort to characterize it otherwise is merely an attempt to obfuscate and confuse the issue”.

The letter also reminded that Musk does not believe the company’s lax testing methodologies are adequate so he must conduct his own analysis and “The data he has requested is necessary to do so”. The letter also said “Mr. Musk is entitled to seek, and Twitter is obligated to provide information and data”.

Automatic debugging of software

Circa 2016


Computer programs often contain defects, or bugs, that need to be found and repaired. This manual “debugging” usually requires valuable time and resources. To help developers debug more efficiently, automated debugging solutions have been proposed. One approach goes through information available in bug reports. Another goes through information collected by running a set of test cases. Until now, explains David Lo from Singapore Management University’s (SMU) School of Information Systems, there has been a “missing link” that prevents these information gathering threads from being combined.

Dr Lo, together with colleagues from SMU, has developed an automated debugging approach called Adaptive Multimodal Bug Localisation (AML). AML gleans debugging hints from both bug reports and , and then performs a statistical analysis to pinpoint program elements that are likely to contain bugs.

“While most past studies only demonstrate the applicability of similar solutions for small programs and ‘artificial bugs’ [bugs that are intentionally inserted into a program for testing purposes], our approach can automate the debugging process for many real that impact large programs,” Dr Lo explains. AML has been successfully evaluated on programs with more than 300,000 lines of code. By automatically identifying buggy code, developers can save time and redirect their debugging effort to designing new features for clients.

Axon halts plans to make a drone equipped with a Taser

Axon has paused work on a project to build drones equipped with its Tasers. A majority of its artificial intelligence ethics board quit after the plan was announced last week.

Nine of the 12 members said in a resignation letter that, just a few weeks ago, the board voted 8–4 to recommend that Axon shouldn’t move forward with a pilot study for a Taser-equipped drone concept. “In that limited conception, the Taser-equipped drone was to be used only in situations in which it might avoid a police officer using a firearm, thereby potentially saving a life,” the nine board members wrote. They noted Axon might decline to follow that recommendation and were working on a report regarding measures the company should have in place were it to move forward.

The nine individuals said they were blindsided by an announcement from the company last Thursday — nine days after 19 elementary school students and two teachers were killed in a mass shooting in Uvalde, Texas — about starting development of such a drone. It had an aim of “incapacitating an active shooter in less than 60 seconds.” Axon said it “asked the board to re-engage and consider issuing further guidance and feedback on this capability.”

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