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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How businesses are using AI: An interactive guide

77% of companies using #cognitive tech and #AI use them to innovate products and services.

  • The organizations already apply cognitive technology to accomplish targeted business goals
  • We looked closely at a subset of advanced users – organizations using two or more cognitive technologies for at least one year.
  • We surveyed 600 early adopters of cognitive technologies and wanted to share our learnings through an interactive visual .
  • How businesses are using AI: An interactive guide
  • Many of the advanced users are embedding a full spectrum of AI technologies – including machine learning, natural language processing and more – into their processes and products.

Today’s most advanced cognitive technology users offer a glimpse into the possibilities and tangible benefits of creating intelligent businesses.
Continue reading “How businesses are using AI: An interactive guide”

Machine Learning for Designers

[FREE] Report Download: #MachineLearning for Designers @PatrickHebron

  • Machine learning is no longer just a tool for data scientists.
  • The O’Reilly report not only introduces you to contemporary machine learning systems, but also provides a conceptual framework to help you integrate machine-learning capabilities into your user-facing designs.
  • Stay up to date with advancements in the field and spot emerging opportunities for machine learning-aided design
  • You’ll learn how recent advancements in machine learning can radically enhance software capabilities through natural language processing, image recognition, content personalization, and behavior prediction.
  • Using tangible, real-world examples, author Patrick Hebron explains how machine-learning applications can affect the way you design websites, mobile applications, and other software.

Machine learning is no longer just a tool for data scientists. By taking advantage of recent advances in this technology, UI and UX designers can find ways to better engage with and understand their users. This O’Reilly report not only introduces you…
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Teaching an AI to write Python code with Python code • Will cars dream?

Teaching an #AI to write Python code with Python code  #MachineLearning #DeepLearning

  • So we want to train a neural net to write some Python code.
  • We can now write our code to train a LSTM network on Python code.
  • Teaching an AI to write Python code with Python code
  • The network takes a few hours to train.
  • You will be able to write code directly in your browser and have it run on your instance.

OK, let’s drop autonomous vehicles for a second. Things are getting serious. This post is about creating a machine that writes its own code. More or less.
Continue reading “Teaching an AI to write Python code with Python code • Will cars dream?”

LG Electronics to Heavily Invest on Artificial Intelligence and The Internet of Things : Tech : koreaportal

LG Electronics heavily into IOT and AI #iot #internetofthings

  • South Korean Conglomerate LG Electronics announced that it will heavily invest in robot technology and artificial technology according to a report by Reuters Sunday.
  • LG did not elaborate on how much it plans to invest in its push or when it expects to launch robotic products, but the firm said it is exploring a variety of options through the combination of technologies including autonomous driving and artificial intelligence.
  • LG, Samsung’s rival, is seeking to take advantage of recent advances in artificial intelligence which have the potential of creating sophisticated machines that can perform mundane everyday human tasks.
  • LG Electronics to Heavily Invest Artificial Intelligence and Internet of Things (Photo by Jung Yeon Je , Getty Images)
  • “We will prepare for the future by aggressively investing in smart home, robots and key components and strengthen the home appliances business’s capabilities,” said Jo Seung-jin, head of LG’s appliances business, in the statement.

South Korean Conglomerate LG Electronics announced that it will heavily invest in robot technology and artificial technology according to a report by Reuters Sunday.
Continue reading “LG Electronics to Heavily Invest on Artificial Intelligence and The Internet of Things : Tech : koreaportal”

Teaching an AI to write Python code with Python code • Will cars dream?

Teaching an #AI to write Python code with Python code  #MachineLearning #DeepLearning

  • So we want to train a neural net to write some Python code.
  • We can now write our code to train a LSTM network on Python code.
  • Teaching an AI to write Python code with Python code
  • The network takes a few hours to train.
  • You will be able to write code directly in your browser and have it run on your instance.

Read the full article, click here.


@MikeTamir: “Teaching an #AI to write Python code with Python code #MachineLearning #DeepLearning”


OK, let’s drop autonomous vehicles for a second. Things are getting serious. This post is about creating a machine that writes its own code. More or less.


Teaching an AI to write Python code with Python code • Will cars dream?

Teaching an AI to write Python code with Python code • Will cars dream?

Teaching #AI to write #Python code with #Python code #DeepLearning #LSTM #MachineLearning

  • So we want to train a neural net to write some Python code.
  • We can now write our code to train a LSTM network on Python code.
  • Teaching an AI to write Python code with Python code
  • The network takes a few hours to train.
  • You will be able to write code directly in your browser and have it run on your instance.

Read the full article, click here.


@kdnuggets: “Teaching #AI to write #Python code with #Python code #DeepLearning #LSTM #MachineLearning”


OK, let’s drop autonomous vehicles for a second. Things are getting serious. This post is about creating a machine that writes its own code. More or less.


Teaching an AI to write Python code with Python code • Will cars dream?

Machine Learning for Designers

FREE Report: How #UI/#UX designers can better engage users w/#machinelearning @PatrickHebron

  • Machine learning is no longer just a tool for data scientists.
  • The O’Reilly report not only introduces you to contemporary machine learning systems, but also provides a conceptual framework to help you integrate machine-learning capabilities into your user-facing designs.
  • Stay up to date with advancements in the field and spot emerging opportunities for machine learning-aided design
  • You’ll learn how recent advancements in machine learning can radically enhance software capabilities through natural language processing, image recognition, content personalization, and behavior prediction.
  • Using tangible, real-world examples, author Patrick Hebron explains how machine-learning applications can affect the way you design websites, mobile applications, and other software.

Read the full article, click here.


@OReillyMedia: “FREE Report: How #UI/#UX designers can better engage users w/#machinelearning @PatrickHebron”


Machine learning is no longer just a tool for data scientists. By taking advantage of recent advances in this technology, UI and UX designers can find ways to better engage with and understand their users. This O’Reilly report not only introduces you…


Machine Learning for Designers

Machine Learning for Designers

[NEW] Free Report: #MachineLearning for Designers @PatrickHebron   #OReillyDesign

  • Machine learning is no longer just a tool for data scientists.
  • The O’Reilly report not only introduces you to contemporary machine learning systems, but also provides a conceptual framework to help you integrate machine-learning capabilities into your user-facing designs.
  • Stay up to date with advancements in the field and spot emerging opportunities for machine learning-aided design
  • You’ll learn how recent advancements in machine learning can radically enhance software capabilities through natural language processing, image recognition, content personalization, and behavior prediction.
  • Using tangible, real-world examples, author Patrick Hebron explains how machine-learning applications can affect the way you design websites, mobile applications, and other software.

Read the full article, click here.


@oreillydesign: “[NEW] Free Report: #MachineLearning for Designers @PatrickHebron #OReillyDesign”


Machine learning is no longer just a tool for data scientists. By taking advantage of recent advances in this technology, UI and UX designers can find ways to better engage with and understand their users. This O’Reilly report not only introduces you…


Machine Learning for Designers

[1606.03073] Convolutional Sketch Inversion

Sketch2Face: Deep Learning For Face Synthesis  #computervision #Machinlearning #science

  • We first construct a semi-simulated dataset containing a very large number of computer-generated face sketches with different styles and corresponding face images by expanding existing unconstrained face data sets.
  • In contrast to existing patch-based approaches, our deep-neural-network-based approach can be used for synthesizing photorealistic face images by inverting face sketches in the wild.
  • Abstract: In the paper, we use deep neural networks for inverting face sketches to synthesize photorealistic face images.
  • We then train models achieving state-of-the-art results on both computer-generated sketches and hand-drawn sketches by leveraging recent advances in deep learning such as batch normalization, deep residual learning, perceptual losses and stochastic optimization in combination with our new dataset.
  • We finally demonstrate potential applications of our models in fine arts and forensic arts.

Read the full article, click here.


@quantombone: “Sketch2Face: Deep Learning For Face Synthesis #computervision #Machinlearning #science”



[1606.03073] Convolutional Sketch Inversion