The news: Facebook is open-sourcing a new AI language model called M2M-100 that can translate between any pair among 100 languages. This is in contrast to previous multilingual models, which heavily rely on English as an intermediate. A Chinese to French translation, for example, typically passes from Chinese to English and then English to French, which increases the chance of introducing errors. Data curation: The model was trained on 7.5 billion sentence pairs. In order to compile a data set that large, the researchers relied heavily on automated curation.
Facebook has developed an artificial intelligence capable of accurately translating between any pair of 100 languages without relying on first translating to English, as many existing systems do. The AI outperforms such systems by 10 points on a 100-point scale used by academics to automatically evaluate the quality of machine translations. Translations produced by the model were also assessed by humans, who scored it as around 90 per cent accurate. Facebook's system was trained on a data set of 7.5 billion sentence pairs gathered from the web across 100 languages, though not all the languages had an equal number of sentence pairs. "What I really was interested in was cutting out English as a middle man. Globally there are plenty of regions where they speak two languages that aren't English," says Angela Fan of Facebook AI, who led the work.
What kind of projects are you working on in an R&D department in data science or AI field? It is the reality of Superhuman #AI, what guides all my projects, to prove the assumptions which are behind a superhuman intelligence: - AI is already getting smarter than us, at various domains, at an exponential rate. Elon Musk, Stuart Russell, Ray Kurzweil, Demis Hassabis, Sam Harris, Nick Bostrom, David Chalmers, Bart Selman, Jaan Tallinn and Max Tegmark all agreed that superhuman intelligence was inevitable and not far away. I do my best to build a digital superintelligence model as a global AI platform within 10 years showing that the Superhuman AI is a not a myth or religious belief, but a reality, today's reality.
Previously, facial recognition technology was reserved for the movies and was a thing of fiction. However, much like other biometric solutions that have seen improvement and progress, facial recognition technology also steadily became a reality. Over the past decade, it has not only been developed and perfected; it is being deployed around the world as well. However, not as rapidly as other biometric technologies did – which include fingerprint, iris recognition, hand geometry, and DNA. Before we discuss the history and gradual evolution of facial recognition technology, there is a need to have an understanding of how this technology works and why there was a need for it in the first place?
I've lost friends over this because a denial of consciousness undermines a final refuge of the arrogance of selfhood: universal consciousness. But even most normal people are strongly insistent that consciousness is a real thing, a special thing, and that they possess it. The problem I have is that there's not only no evidence for it, but what people seem to be referring to as consciousness is explainable as an effect no more unusual, no less materialistically explainable, than water flowing downhill. Now I'm not going to get too far into the metaphysics of non-separation. At least initially, I'm not going to try to explain that, on one level, consciousness, being an aspect of the illusion of a subject/object separation of the wholeness, is itself illusory.
Snapchat's augmented reality dreams might be starting to look a bit more realistic. The company has been subtly improving its AR-powered Lenses every year, improving the technical odds-and-ends and strengthening its dev platform. The result is that today, more than 170 million people -- over three-quarters of Snap's daily active users -- access the app's augmented reality features on a daily basis, the company says. Two years ago, Snap shared that creators had designed over 100,000 lenses on the platform; now Snap says there have been more than 1 million lenses created. The goofy filters are bringing users to the app and the company is slowly building a more interconnected platform around augmented reality that is beginning to look more and more promising.
Have you ever watched a video or movie because YouTube or Netflix recommended it to you? Or added a friend on Facebook from the list of "people you may know"? And how does Twitter decide which tweets to show you at the top of your feed? These platforms are driven by algorithms, which rank and recommend content for us based on our data. If you want to know when social media companies are trying to manipulate you into disclosing information or engaging more, the answer is always.
What rules would you give artificial intelligence? I was just pointing out with the anthill analogy that #AI does not need to hate us to destroy us. In a sense, that if it decides that it needs to go in a particular direction and we're in the way then it would without no hard feelings it would just roll over us. We would roll over an anthill that's in the way of a road. I think that we really need to think of intelligence as really not being uniquely confined to humans.
Decisions on where to send police patrol cars, which foster parents to investigate, and who gets released on bail before trial are some of the most important, life-or-death decisions made by our government. And, increasingly, those decisions are being automated. The last eight years have seen an explosion in the capability of artificial intelligence, which is now used for everything from arranging your news feed on Facebook to identifying enemy combatants for the U.S. military. The automated decisions that affect us the most are somewhere in the middle. A.I.'s big feature is essentially pattern matching.