Artificial Intelligence will Speak Its Own Language — Soon

Artificial Intelligence will Speak Its Own Language
  #AI

  • Artificial Intelligence will Speak Its Own Language — SoonGrounded language is a new step towards Artificial Intelligence revealed by OpenAI.The article is about a system that invents a language which is tied to perception of the world.
  • In sum, the post reveals possibilities that might be opened via researches related to an artificial language.
  • At least the language will be similar to a signal language typical for animals.
  • Further languages will be evolved into more complex technologies…This article was originally published on pionic.

The article is about a system that invents a language which is tied to perception of the world. In sum, the post reveals possibilities that might be opened via researches related to an artificial…
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China wants to be a $150 billion world leader in AI in less than 15 years

#China wants to be a $150 billion world leader in #AI in less than 15 years

  • China has laid out plans to become the world leader in artificial intelligence (AI) by 2030, with the aim of making the industry worth 1 trillion yuan ($147.7 billion).
  • The State Council released its three-step roadmap on Thursday outlining the thinking behind how it expects AI to be developed and deployed in areas from the military to city planning.
  • “Artificial intelligence has become a new engine of economic development,” the State Council’s document said according to a translation.

China’s three step program outlines its aim to use AI in a number of areas from the military to smart cities.
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Google’s AI Guru Says That Great Artificial Intelligence Must Build on Neuroscience

Google’s #AI guru says that great artificial intelligence must build on neuro science

  • Demis Hassabis knows a thing or two about artificial intelligence: he founded the London-based AI startup DeepMind, which was purchased by Google for $650 million back in 2014.
  • In a paper published today in the journal Neuron, Hassabis and three coauthors argue that only by better understanding human intelligence can we hope to push the boundaries of what artificial intellects can achieve.
  • But it also points out that more recent advances haven’t leaned on biology as effectively, and that a general intelligence will need more human-like characteristics—such as an intuitive understanding of the real world and more efficient ways of learning.
  • As Hassabis explains in an interview with the Verge, artificial intelligence and neuroscience have become “two very, very large fields that are steeped in their own traditions,” which makes it “quite difficult to be expert in even one of those fields, let alone expert enough in both that you can translate and find connections between them.”
  • (Read more: Neuron, The Verge, “Google’s Intelligence Designer,” “Can This Man Make AI More Human?”)

Inquisitiveness and imagination will be hard to create any other way.
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Norway Takes Lead in Race to Build Autonomous Cargo Ships

#Norway Takes Lead in Race to Build Autonomous Cargo Ships by @CostasParis  #AI #ML

  • The vessel will cost $25 million, about three times as much as a conventional container ship of its size, but its backers say without need for fuel or crew it promises to cut annual operating costs by up to 90%.
  • Petter Ostbo,

    Yara’s head of production who leads the project, said the company would look to invest in bigger ships and use them for longer routes once international regulations are in place for crewless vessels.

  • The International Maritime Organization, which regulates maritime travel, doesn’t expect legislation governing crewless ships to be in place before 2020.
  • Shipping executives say autonomous vessels will be popular for short sea routes, but doubt they will replace oceangoing ships that move thousands of containers across continents with an average crew size of around 25.
  • The first vessels will likely be tugboats and ferries, with cargo ships that can sail through international waters to follow.

Two Norwegian companies are taking the lead in the race to build the world’s first crewless, autonomously operated electric ship, an advance that could mark a turning point in seaborne trade.
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China announces goal of leadership in artificial intelligence by 2030

China announces goal of leadership in artificial intelligence by 2030

  • BEIJING — China’s government has announced a goal of becoming a global leader in artificial intelligence in just over a decade, putting political muscle behind growing investment by Chinese companies in developing self-driving cars and other advances.
  • Artificial intelligence is one of the emerging fields along with renewable energy, robotics and electric cars where communist leaders hope to take an early lead and help transform China from a nation of factory workers and farmers into a technology pioneer.
  • Already, Chinese companies including Tencent Ltd., Baidu Inc. and Alibaba Group are spending heavily to develop artificial intelligence for consumer finance, e-commerce, self-driving cars and other applications.
  • The announcement follows a sweeping plan issued in 2015, dubbed “Made in China 2025,” that calls for this country to supply its own high-tech components and materials in 10 industries from information technology and aerospace to pharmaceuticals.
  • China has had mixed success with previous strategic plans to develop technology industries including renewable energy and electric cars.

AI is one of the emerging fields — along with renewable energy, robotics and electric cars — where communist leaders hope to take an early lead
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GitHub

A #Java Toolbox for Scalable Probabilistic #MachineLearning

  • The AMIDST Toolbox allows you to model your problem using a flexible probabilistic language based on graphical models.
  • AMIDST Toolbox has been used to track concept drift and do risk prediction in credit operations, and as data is collected continuously and reported on a daily basis, this gives rise to a streaming data classification problem.
  • As an example, the following figure shows how the data processing capacity of our toolbox increases given the number of CPU cores when learning an a probabilistic model (including a class variable C, two latent variables (dashed nodes), multinomial (blue nodes) and Gaussian (green nodes) observable variables) using the AMIDST’s learning engine.
  • As can be seen, using our variational learning engine, AMIDST toolbox is able to process data in the order of gigabytes (GB) per hour depending on the number of available CPU cores with large and complex PGMs with latent variables.
  • If your data is really big and can not be stored in a single laptop, you can also learn your probabilistic model on it by using the AMIDST distributed learning engine based on a novel and state-of-the-art distributed message passing scheme implemented on top of Apache Flink.

toolbox – A Java Toolbox for Scalable Probabilistic Machine Learning
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Train Neural Machine Translation Models with Sockeye

New on the AWS #AI Blog: Train Neural Machine Translation Models with Sockeye.

  • Sockeye, which is built on Apache MXNet, does most of the heavy lifting for building, training, and running state-of-the-art sequence-to-sequence models.
  • Sockeye provides both a state-of-the-art implementation of neural machine translation (NMT) models and a platform to conduct NMT research.
  • You can easily change the basic model architecture, including the following elements:

    Sockeye also supports more advanced features, such as:

    For training, Sockeye gives you full control over important optimization parameters.

  • If you have a GPU available, install Sockeye for CUDA 8.0 with the following command:

    To install it for CUDA 7.5, use this command:

    Now you’re all set to train your first German-to-English NMT model.

  • You also learned how to use Sockeye, a sequence-to-sequence framework based on MXNet, to train and run a minimal NMT model.

Have you ever wondered how you can use machine learning (ML) for translation? With our new framework, Sockeye, you can model machine translation (MT) and other sequence-to-sequence tasks. Sockeye, which is built on Apache MXNet, does most of the heavy lifting for building, training, and running state-of-the-art sequence-to-sequence models.
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