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The backstory of Two Graduates Recreating OpenAI’s Risky code which was not meant to be released.

, The backstory of Two Graduates Recreating OpenAI’s Risky code which was not meant to be released., Tech chums
Source: Singularity Hub

An artificial intelligence lab co-founded by Elon Musk, OpenAI, informed In February that its latest breakthrough was so risky that they decided not to release it to the public. The OpenAI expressed shocking news that it had made language software so consistent at generating text that can be manipulatively used to crank out fake news or spam.

Two recent master’s graduates in computer science, Aaron Gokaslan, 23, and Vanya Cohen, 24, as per Wired, released a re-creation of OpenAI’s withheld software onto the internet open to download and use saying that they aren’t out to cause havoc and instructing the general public not to believe on such software poses many risks to society yet.

The duo claims that their release was purely intended to show that you don’t have to be an elite lab rich in dollars and PhDs to create this kind of software: They used an estimated $50,000 worth of free cloud computing from Google, which hands out credits to academic institutions. Further extending their argument, they state that setting their creation free can help others explore and prepare for future advances which have both positive and negative aspects.

“This allows everyone to have an important conversation about security and researchers to help secure against future potential abuses,”

Vanya Cohen

says Cohen, who notes language software also has many positive uses.

“I’ve gotten scores of messages, and most of them have been like Way to go.”

Vanya Cohen

The pair’s experiment, like OpenAI’s, involved releasing out machine learning software text from a number of webpages gathered by cultivating the links shared on Reddit. When the software succeeded in internalizes patterns of language from the text, it adapted to tasks such as translation, powering chatbots, or generating new text in response to a prompt. The text that Gokaslan and Cohen’s software generates can be “impressively fluid”  in the structure of adaptation. When the research hub gave it the prompt

“The problem with America is that, because everything is a narrative, we’re all imprisoned in our own set of lies.”

A few sentences later it praised Donald Trump for being able to give voice to those who had been left voiceless.

That text showed similarities to what the research post saw when playing with the (ultimately withheld) model OpenAI developed earlier this year, called GPT-2. That one riffed about interlinking between Hilary Clinton and George Soros. Both versions of the software show the signs of training on content linked from Reddit, where political debates can be heated.

But none of the projects can generate perfect prose: Machine learning software generally picks up the statistical patterns of language, which is why it leads to no true understanding of the world.

The generated artificial text from both the original and wannabe software often makes “nonsensical leaps” if put in simple words. They cannot be directed to include particular facts or points of view either.

Those disadvantages generated out of misinterpretation in working have caused some AI researchers to greet OpenAI’s claims of an imminent threat to society with derision. Humans can write more potent misleading text in the light of it and no doubt they do it.

OpenAI released a report saying it was aware of more than five other groups that had replicated its work at full scale, but that none had released the software. The report also said that a smaller version of GPT-2 OpenAI had released was roughly as good as the full withheld one at creating fake news articles. (You can try that smaller version online.)

Gokaslan and Cohen took the report’s data to mean that their own software wouldn’t be significantly more dangerous than what OpenAI had already released if it was dangerous at all.

They wanted to show the world that similar projects are now within reach of anyone with some programming skills and motivation. “If you gave a high school student guidance, they could probably do it,” Gokaslan says.

On the point of how dangerous the software the pair released might be, Miles Brundage, who works on policy at OpenAI, remains silent. According to him, No one has had time to properly test it, even though the pattern of the figures released by Gokaslan and Cohen suggest that it is slightly less powerful than the full GPT-2.

OpenAI would like to release that full version in the future, according to Brundage, provided that they feel “comfortable” that there won’t be negative consequences. Brundage also acknowledges that Gokaslan and Cohen have shown how widening access to powerful computers and AI skills is increasing the number of people who can do such work.

However, He still believes anyone working on something similar should proceed with caution and talk through their release plans with OpenAI. “I encourage people to reach out to us,” he adds.

As an important AI safety lesson from this episode comes the fact to always read your email. Gokaslan and Cohen tried to inform OpenAI about their project and operation by reaching out to the lead author on the lab’s technical paper about GPT-2. They say they never heard back, causing them to miss out on whatever OpenAI advises other researchers about the risks of software like its own.

A spokesperson for OpenAI reported that the researcher Gokaslan and Cohen have tried to contact through a lot of emails and that the lab’s policy team has been monitoring a dedicated email address for an extended discussion about GPT-2  which was previously published in blog posts. Gokaslan and Cohen did make contact with OpenAI after a tweet announcing their release began circulating among AI researchers. They say they’re looking forward to discussing their work and its implications.

They’re also working on a research paper describing their project and they plan to write it themselves. This was appreciable as a notice that their attempt was legal and required attention which was a lack on the part of the AI monitoring department.

After all the cautions that add up to the attempt of recreating any project or code that involves any safety threat should be taken into consideration.

Though the report did not inform us of how effectively has the pair incorporated the challenge, in terms of safety and awareness but certainly, it can be deduced that the intention behind it was larger as a cause and not as an evil plan to misuse the codes.

About the author

Nina Young

Nina is a tech enthusiast, a programmer, and a Chess player who lives in New Jersey. She deeply believes that technology now has the capability to shape the future of people if used in the right direction.

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