Ready Player One (2018) : Tye Sheridan, Olivia Cooke ,Ben Mendelsohn, T. J. Miller & Simon Pegg
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The Official World Politics Thread - All Breaking News here.
We need a thread to put all the election news, updates, foolishness, etc....
Sticky, please?
Sticky, please?
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Body bag thread
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The Official Marvel Cinematic Universe Phase 3 thread - Now Showing -"Thor:RAGNAROK"
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The Official Boxing Thread
Here's to hoping 2012 was as great as 2011 for the sport of boxing!!!
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Chris Brown got competition!Pop Locking Pops
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Arrest Made in 2015 Murder of Chinx
A suspect in the 2015 murder of rapper Chinx has been arrested. Quincy Homere, 32, of Long Island faces the following charges: murder, attempted murder, assault and criminal possession of a weapon.
Chinx,31, whose real name is Lionel Pickens, was gunned down in his Porsche back in May of 2015. The fatal shooting occurred in Queens at a red light near Queens Boulevard and 84th Drive, according to police.
Chinx was shot multiple times in the torso and taken to a nearby hospital where he was pronounced dead. The rapper's friend, who was also in the car, suffered gunshot wounds to his back.
Chinx,31, whose real name is Lionel Pickens, was gunned down in his Porsche back in May of 2015. The fatal shooting occurred in Queens at a red light near Queens Boulevard and 84th Drive, according to police.
Chinx was shot multiple times in the torso and taken to a nearby hospital where he was pronounced dead. The rapper's friend, who was also in the car, suffered gunshot wounds to his back.
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White Posters: Dedication
Shout out to every active white poster on the I.c. Streets.
Y’all mfs got some thick skin for real. All the race related shit posted yet y’all still contribute.
That’s dedication. That’s black power right there. Y’all know and see what your melanin deficient brethren refuses to acknowledge.
I’m surrounded by white ppl all day everyday during business hours. If only 20% of the whites I deal with had y’all level of understanding, my days would be so much easier.
Most of the Caucasian posters have fallen to the wayside but the ones that remain....salute
Y’all mfs got some thick skin for real. All the race related shit posted yet y’all still contribute.
That’s dedication. That’s black power right there. Y’all know and see what your melanin deficient brethren refuses to acknowledge.
I’m surrounded by white ppl all day everyday during business hours. If only 20% of the whites I deal with had y’all level of understanding, my days would be so much easier.
Most of the Caucasian posters have fallen to the wayside but the ones that remain....salute
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Goons of the Industry
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Side Piece tried to extort Kevin Hart and he said bump that!
Side piece tried to extort my man? Smh..
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The Official 'The Walking Dead' Season 8 Thread
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THE CHALLENGE XXX
1 million on the line...30 people
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So come to find out...
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BLACK THOUGHT incredible FREESTYLE @Flex
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Call of Duty: World War 2
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On This Day In 1992, Dr. Dre Released The Greatest Rap Album Of All Time...The Chronic
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Google AI outperforms developers in writing machine learning algorithms
https://eandt.theiet.org/content/articles/2017/10/google-ai-outperforms-developers-in-writing-machine-learning-algorithms/
A tool created by Google engineers to automate the writing of machine learning algorithms has outperformed developers in the creation of efficient machine learning systems for some tasks.
The AutoML (automated machine learning) tool was announced earlier this year by Google representatives. Its creation was motivated by the widespread skills shortage associated with coding, particularly for machine learning applications. The Google team built a machine learning system capable of rapidly creating, testing and refining machine learning architectures.
“One way we hope to make AI more accessible is by simplifying the creation of machine learning models called neural networks,” wrote Sundar Pichai, Google CEO, in a blog post.
“Today, designing neural nets is extremely time intensive, and requires an expertise that limits its use to a smaller community of scientists and engineers. That’s why we’ve created an approach called AutoML, showing that it’s possible for neural nets to design neural nets.”
The AutoML approach allows for a “controller neural net” to put forward a suggestion of a basic architecture for a new machine learning algorithm, which can be subsequently trained to perform a highly specialised task. The algorithm’s performance is evaluated and this feedback is used to improve the next attempt.
After repeating these simulations thousands of times, the controller is well-informed about which architectures are likely to perform better at this task. This entire process is automated and takes a matter of hours.
Within just five months, Google has reported that AutoML has begun to generate machine learning algorithms which outperform those written by the developers themselves. An AutoML-generated algorithm proved capable of learning to recognise and categorise images – an extremely complex task – reached a record 82 per cent accuracy.
Even in complex tasks, the AutoML code outperformed code written by developers: in a task in which the system had to mark the location of various objects within an image, the developers’ machine learning software achieved 39 per cent accuracy, while the AutoML software achieved 43 per cent.
Once well-honed enough such that it could be used for practical applications, tools like AutoML could be incorporated into machines of the near future, allowing them to update themselves regularly and even create new programs to solve specific problems.
While machines outperforming humans in highly-skilled jobs remains a fantasy, the success of AutoML demonstrates the slight edge that artificially intelligent systems can have over humans in performing tedious tasks: in this case, the ability of AutoML to rapidly run through thousands of possible architectures would otherwise take months of work for a developer, whose time could be put to better use on more creative tasks.
A tool created by Google engineers to automate the writing of machine learning algorithms has outperformed developers in the creation of efficient machine learning systems for some tasks.
The AutoML (automated machine learning) tool was announced earlier this year by Google representatives. Its creation was motivated by the widespread skills shortage associated with coding, particularly for machine learning applications. The Google team built a machine learning system capable of rapidly creating, testing and refining machine learning architectures.
“One way we hope to make AI more accessible is by simplifying the creation of machine learning models called neural networks,” wrote Sundar Pichai, Google CEO, in a blog post.
“Today, designing neural nets is extremely time intensive, and requires an expertise that limits its use to a smaller community of scientists and engineers. That’s why we’ve created an approach called AutoML, showing that it’s possible for neural nets to design neural nets.”
The AutoML approach allows for a “controller neural net” to put forward a suggestion of a basic architecture for a new machine learning algorithm, which can be subsequently trained to perform a highly specialised task. The algorithm’s performance is evaluated and this feedback is used to improve the next attempt.
After repeating these simulations thousands of times, the controller is well-informed about which architectures are likely to perform better at this task. This entire process is automated and takes a matter of hours.
Within just five months, Google has reported that AutoML has begun to generate machine learning algorithms which outperform those written by the developers themselves. An AutoML-generated algorithm proved capable of learning to recognise and categorise images – an extremely complex task – reached a record 82 per cent accuracy.
Even in complex tasks, the AutoML code outperformed code written by developers: in a task in which the system had to mark the location of various objects within an image, the developers’ machine learning software achieved 39 per cent accuracy, while the AutoML software achieved 43 per cent.
Once well-honed enough such that it could be used for practical applications, tools like AutoML could be incorporated into machines of the near future, allowing them to update themselves regularly and even create new programs to solve specific problems.
While machines outperforming humans in highly-skilled jobs remains a fantasy, the success of AutoML demonstrates the slight edge that artificially intelligent systems can have over humans in performing tedious tasks: in this case, the ability of AutoML to rapidly run through thousands of possible architectures would otherwise take months of work for a developer, whose time could be put to better use on more creative tasks.
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Cheap Seats What's on your Mind thread
Fuck that nigga Chi Town. Don't derail this thread with your constant bitching
What y'all niggas doing this weekend?
What y'all niggas doing this weekend?
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The Official 2017 Food Pic thread
This spot called the Tuscan Market located north of Boston, the food was on point!
Yall share your recent culinary experiences here.
You're welcome
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PRESENTING ...........UNCLE CAIN'S QUIET STORM
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More Pages to Explore .....