Here are five important AI stories from the week.
Microsoft invests $1 billion in the A.I. research lab founded by Elon Musk and headed now by the former head of Y Combinator Sam Altman. OpenAI’s successes to date include releasing a very impressive language model called GPT-2; OpenAI made headlines earlier this year when it chose NOT to release the code because it feared releasing the code would lead bad actors to disseminate false information using the model. OpenAI also designed an AI to beat the world’s best players at a complex strategy-based video game called Dota 2.
According to Sam Altman, OpenAI will focus on building a quantum computer next. What does Microsoft capture from the deal? A portion of profits. Microsoft also will eventually become the sole provider of cloud infrastructure for OpenAI. Fortune also did a great job covering this transaction.
A few years after launching its initial $100 billion Vision Fund, SoftBank is at it again, expecting to raise $108 billion for this second Vision Fund. Other likely investors include Apple, Microsoft, Foxconn, and several major financial giants. Its mission this time: to “facilitate the continued acceleration of the AI (artificial intelligence) revolution through investment in market-leading, tech-enabled growth companies.”
Autonomous vehicles perform very well when they do not encounter abnormal situations such as cars or cyclists or pedestrians running lights or inclement weather. Although autonomous vehicles perform well in most driving conditions, they struggle with the edge cases. And since driving poorly has potentially fatal consequences, autonomous vehicles cannot yet drive on open roads. In other words, self-driving cars are almost here but not quite yet.
Two weeks ago, a photo-transforming app went viral; users were able to upload photos of their face and see “aged” versions of themselves, courtesy of synthetic image generation powered by machine learning. The app almost magically transformed faces, adding in wrinkles and graying hair. But, users of the app eventually realized the app had been developed by a mysterious Russian firm, creating some paranoia about what would happen to the data they had made available to the Russian firm. Concerns over data privacy are on the rise as users become more aware of how their data is being used.
Google released BERT late last year, and many firms such as StitchFix are rapidly adopting the model for use in their core business. At StitchFix, stylists use notes provided by consumers to find the most suitable clothes. Instead of relying on just humans, StitchFix has an array of machine learning solutions to narrow down the search for stylists. With BERT, StitchFix is able to extract information from text and automatically map text to clothes that the consumers will like with considerably less human involvement. Here is just how it all works.
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