Top video game dev nerve-center Unity can now be used to train AI • The Register

Top video game dev nerve-center Unity can now be used to train #AI  #gamedev

  • Unity, the most popular cross-platform game engine favored by video game developers, on Tuesday opened up its platform for machine learning researchers to test their algorithms.
  • Reinforcement learning is a strand of machine learning that teaches agents to perform a specific task in a given environment.
  • The platform, known as Unity Machine Learning Agents, includes additional features like the Agent Monitor class, which allows researchers to better understand how agents make decisions so that mistakes are easier to debug.
  • Since Unity Engine and Editor are geared toward game development, it also makes it easier for machine learning researchers to construct scenarios or even create full games to use as testbeds for their reinforcement learning algorithms.
  • But there is a slight tradeoff for having prettier graphics and more complex environments – it makes it more difficult for the algorithms to comprehend the play field, and requires more processing power from accelerators such as GPUs, so it’ll be more expensive to train agents.

Unity, the most popular cross-platform game engine favored by video game developers, on Tuesday opened up its platform for machine learning researchers to test their algorithms.
Continue reading “Top video game dev nerve-center Unity can now be used to train AI • The Register”

Are You Ready for Robot Colleagues?

Ready?

  • To enjoy more articles like this one sign in , or create an account .
  • sign up for a free account : comment on articles and get access to many more articles.
  • The article is part of an MIT SMR initiative exploring how technology is reshaping the practice of management.
  • Schmitt comes at the questions not as a computer scientist but as a marketing expert.
  • What’s happening the week at the intersection of management and technology.

In the future workplace, humans may supplement the skills of machines — and not the other way around.

Continue reading “Are You Ready for Robot Colleagues?”

Drones and machine learning combine to indentify, protect endangered sea cows

Drones and machine learning combine to identify, protect endangered sea cows

  • The latest version of the detector can find 80 percent of the dugongs in images.
  • ” the technology could be applied to surveys of any species as long as you start off which a set of images to train the detector.”
  • Case in point: the dugong, a medium-sized marine mammal often referred to as a sea cow.
  • Given a large image, the region proposal module generates a list of subwindows of the image, centered on candidate blobs.
  • Drones and machine learning combine to indentify, protect endangered sea cows

Researchers in Australia are using drones and machine learning technology to spot sea cows in their natural habit.
Continue reading “Drones and machine learning combine to indentify, protect endangered sea cows”

Are You Ready for Robot Colleagues?

Ready?

  • To enjoy more articles like this one sign in , or create an account .
  • sign up for a free account : comment on articles and get access to many more articles.
  • What’s happening the week at the intersection of management and technology.
  • The article is part of an MIT SMR initiative exploring how technology is reshaping the practice of management.
  • Schmitt comes at the questions not as a computer scientist but as a marketing expert.

In the future workplace, humans may supplement the skills of machines — and not the other way around.

Continue reading “Are You Ready for Robot Colleagues?”

Google’s ‘DeepMind’ AI platform can now learn without human input

#Google's #DeepMind #AI platform can now learn without human input ▷

  • Much like the brain, the neural network uses an interconnected series of nodes to stimulate specific centers needed to complete a task.
  • Read next: Facebook makes 360 photos much better with one small update
  • The AI is optimizing the nodes to find the quickest solution to deliver the desired outcome.
  • In a significant step forward for artificial intelligence, Alphabet’s hybrid system – called a Differential Neural Computer (DNC) – uses the existing data storage capacity of conventional computers while pairing it with smart AI and a neural net capable of quickly parsing it.
  • Instead of having to learn every possible outcome to find a solution, DeepMind can derive an answer from prior experience, unearthing the answer from its internal memory rather than from outside conditioning and programming.

Bow to your robot overlords. Google’s parent company, Alphabet, now possesses a smart AI capable of learning without the need for human input.
Continue reading “Google’s ‘DeepMind’ AI platform can now learn without human input”

Google’s ‘DeepMind’ AI platform can now learn without human input

DeepMind AI platform can now learn without human input

  • The AI is optimizing the nodes to find the quickest solution to deliver the desired outcome.
  • Any time is a good time to start a company.
  • TNW uses cookies to personalise content and ads to make our site easier for you to use.
  • Instead of having to learn every possible outcome to find a solution, DeepMind can derive an answer from prior experience, unearthing the answer from its internal memory rather than from outside conditioning and programming.
  • In a significant step forward for artificial intelligence, Alphabet’s hybrid system – called a Differential Neural Computer (DNC) – uses the existing data storage capacity of conventional computers while pairing it with smart AI and a neural net capable of quickly parsing it.

Bow to your robot overlords. Google’s parent company, Alphabet, now possesses a smart AI capable of learning without the need for human input.
Continue reading “Google’s ‘DeepMind’ AI platform can now learn without human input”

Building Machine Learning Estimator in TensorFlow

Building #MachineLearning #DataScience Estimator in TensorFlow - Yuan's Blog

  • So later a user can sub-class LogisticRegressor to implement a estimator for binary classification without much further effort.
  • I highly recommend you taking a look to understand the underlying code structure better and start Implementing your own estimators!
  • If you want to implement your own estimator, this also gives you freedom to decide whether targets can be ignored if the estimator can be trained in unsupervised fashion.
  • More examples of implementing different estimators can be found in learn.estimators .
  • It hides most of the detailed implementations of Random Forests in contrib.tensor_forest while utilizing some exposed high-level components to build the estimator so users can use contrib.tensor_forest more easily.

Read the full article, click here.


@MikeTamir: “Building #MachineLearning #DataScience Estimator in TensorFlow – Yuan’s Blog”


Have you ever wondered what’s the magic behind the tutorials on Large-scale Linear Models and Wide & Deep Learning? I hope this post would at least point you to the right direction.


Building Machine Learning Estimator in TensorFlow