Clearview says its software lets authorities plug in photos of people suspected of involvement in crimes and search for other images of their faces from the internet. The company has compiled a massive database of photos by scraping websites, including social-media platforms. Some of the platforms have accused Clearview's scraping efforts of violating their terms of service. Facebook Inc., Twitter Inc. and Microsoft Corp.'s LinkedIn are among those that have sent the startup cease-and-desist orders. Civil libertarians have raised concerns broadly about the use of facial-recognition by law enforcement, and specifically about Clearview.
Google's influence in our lives is overwhelming, which is perhaps one of the reasons the Department of Justice and several state attorney generals banded together to file an anti-trust lawsuit against the company. But just how wide is Google's reach? We decided to take a look, and the results may surprise you. Start with the fact that Google ads are all over the Internet, and despite the initial stated goal of "organizing the world's information," the Alphabet unit is designed to have more ads appear, to keep the earnings up. In its most recent earnings, Alphabet reported $38.30 billion for Google.
The global economic climate has prompted several organizations to make a strategic move towards automation and AI. Unsurprisingly, there has been an upsurge in AI and automation investments. This broad adoption of AI has reimagined business operations across the globe. Due to its myriad of benefits, researchers and data scientists are continually striving to create new benchmarks in the AI world. Toolbox shares significant breakthroughs in AI this week.
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.