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Sam Altman’s leap of faith | TechCrunch
Continued Altman, “We’ve made a soft promise to investors that, ‘Once we build a generally intelligent system, that basically we will ask it to figure out a way to make an investment return for you.'” When the crowd erupted with laughter (it wasn’t immediately obvious that he was serious), Altman himself offered that it sounds like an episode of “Silicon Valley,” but he added, “You can laugh. It’s all right. But it really is what I actually believe.”
Trend  OpenAI  VC  AI  ML 
7 days ago by euler
Sam Altman’s leap of faith | TechCrunch
Earlier this year, founder-investor Sam Altman left his high-profile role as the president of Y Combinator to become the CEO of OpenAI, an AI research outfit that was founded by some of the most prominent people in the tech industry in late 2015. The idea: to ensure that artificial intelligence is “developed in a way […]
artificial-intelligence  openai  sam-altman  ai  ycombinator 
7 days ago by aagd
OpenAI unveils multitalented AI that writes, translates, and slanders - The Verge
The success of these newer, deeper language models has caused a stir in the AI community. Researcher Sebastian Ruder compares their success to advances made in computer vision in the early 2010s. At this time, deep learning helped algorithms make huge strides in their ability to identify and categorize visual data, kickstarting the current AI boom. Without these advances, a whole range of technologies — from self-driving cars to facial recognition and AI-enhanced photography — would be impossible today. This latest leap in language understanding could have similar, transformational effects.

One reason to be excited about GPT-2, says Ani Kembhavi, a researcher at the Allen Institute for Artificial Intelligence, is that predicting text can be thought of as an “uber-task” for computers: a broad challenge that, once solved, will open a floodgate of intelligence.

“Asking the time or getting directions can both be thought of as question-answering tasks that involve predicting text,” Kembhavi tells The Verge. “So, hypothetically, if you train a good enough question-answering model, it can potentially do anything.”

Take GPT-2’s ability to translate text from English to French, for example. Usually, translation algorithms are fed hundreds of thousands of phrases in relevant languages, and the networks themselves are structured in such a way that they process data by converting input X into output Y. This data and network architecture give these systems the tools they need to progress on this task the same way snow chains help cars get a grip on icy roads.
natural-language-processing  openAI  machine-learning  rather-interesting  to-write-about  representation 
february 2019 by Vaguery

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