Elon Musk-backed AI Company Claims It Made a Text Generator That’s Too Dangerous to Release

The OpenAI researchers found that GPT-2 performed very well when it was given tasks that it wasn’t necessarily designed for, like translation and summarization.

AdvertisementThe researchers used 40GB of data pulled from 8 million web pages to train the GPT-2 software.

Photo: GettyResearchers at the non-profit AI research group OpenAI just wanted to train their new text generation software to predict the next word in a sentence.

That’s ten times the amount of data they used for the first iteration of GPT.

Elon Musk has been clear that he believes artificial intelligence is the “biggest existential threat” to humanity.

The dataset was pulled together by trolling through Reddit and selecting links to articles that had more than three upvotes.

Rather than releasing the fully trained model, it’s releasing a smaller model for researchers to experiment with.

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How AI is revolutionising drug industry by cutting pharmaceutical development time, says leading company

Founded by Alex Zhavoronkov in 2014, the enterprise uses AI and deep learning – a subset of machine learning that imitates the workings of the human brain in processing data – for drug discovery and ageing research.

Zhavoronkov says AI can speed up and reduce costs for drug development which – involving several phases of clinical trials, government approval and licensing – can last more than a decade.

“Moving to Hong Kong is the first step for us to go to China. The future for AI is in China as AI is about data and China has more data than any other country. The [Chinese] government also supports AI more than any other country,” he says.

With 66 staff, more than half of whom are deep-learning scientists, Zhavoronkov says they will hold a second round of private financing and a hackathon in Science Park later this year to recruit AI talent.

Zhavoronkov says AI can save up to “Two years in pharmaceutical research and development time”, and that the current development process is “Very inefficient”.

“The pharmaceutical drug discovery and drug development process consists of the many phases and often takes decades. The probability of failure is very high at every stage. In pre-clinical phases the failure rates are over 99 per cent and in human clinical trials about 90 per cent of the molecules fail,” he says.

“Western pharmaceutical companies are still very sceptical of the potential of AI and are not willing to change and upgrade. Fortunately, the Chinese government and companies prioritise the investment in AI and are very likely to enjoy the benefits and come up with innovative medicines faster.”

This article was summarized automatically with AI / Article-Σ ™/ BuildR BOT™.

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