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Simple, scalable, and sustainable: A methodical approach to AI adoption

O'Reilly Radar - Thu, 2019/04/18 - 13:00

Rajendra Prasad explains how leaders in large enterprises can make AI adoption successful.

Continue reading Simple, scalable, and sustainable: A methodical approach to AI adoption.

Categories: Technology

Applied machine learning at Facebook

O'Reilly Radar - Thu, 2019/04/18 - 13:00

Kim Hazelwood discusses the hardware and software Facebook has designed to meet its scale needs.

Continue reading Applied machine learning at Facebook.

Categories: Technology

Artificial intelligence: The “refinery” for data

O'Reilly Radar - Thu, 2019/04/18 - 13:00

Nick Curcuru explains how Mastercard is using AI to improve security without sacrificing the customer experience.

Continue reading Artificial intelligence: The “refinery” for data.

Categories: Technology

Decoding the human genome with deep learning

O'Reilly Radar - Thu, 2019/04/18 - 13:00

How can machine learning decode the mysteries of life? Olga Troyanskaya explores this and other big questions through the prism of deep learning.

Continue reading Decoding the human genome with deep learning.

Categories: Technology

Making real-world distributed deep learning easy with Nauta

O'Reilly Radar - Thu, 2019/04/18 - 13:00

Carlos Humberto Morales offers an overview of Nauta, an open source multiuser platform that lets data scientists run complex deep learning models on shared hardware.

Continue reading Making real-world distributed deep learning easy with Nauta.

Categories: Technology

Software 2.0 and Snorkel

O'Reilly Radar - Thu, 2019/04/18 - 13:00

Christopher Ré discusses Snorkel, a system for fast training data creation.

Continue reading Software 2.0 and Snorkel.

Categories: Technology

Automation of AI: Accelerating the AI revolution

O'Reilly Radar - Thu, 2019/04/18 - 13:00

Ruchir Puri discusses the next revolution in automating AI, which strives to deploy AI to automate the task of building, deploying, and managing AI tasks.

Continue reading Automation of AI: Accelerating the AI revolution.

Categories: Technology

Four short links: 18 April 2019

O'Reilly Radar - Thu, 2019/04/18 - 04:05

Geospatial Feature Engineering, 3D Reconstruction, Fast NLP, and Learning the Zork Interpreter Language

  1. Geomancer -- a geospatial feature engineering library. It leverages geospatial data such as OpenStreetMap (OSM) alongside a data warehouse like BigQuery. You can use this to create, share, and iterate geospatial features for your downstream tasks (analysis, modeling, visualization, etc.).
  2. Meshroom -- a free, open source 3D Reconstruction Software based on the AliceVision framework.
  3. BlingFire -- A lightning fast finite state machine and regular expression manipulation library. [...] We use Fire for many linguistic operations inside Bing such as tokenization, multi-word expression matching, unknown word-guessing, stemming / lemmatization, just to mention a few. cf NLTK.
  4. Learning ZIL -- what the Infocom games were written in, decades before Inform. Andrew Plotkin wrote an intro that explains how it sits in the universe. (Note: this is useless but historically interesting.)

Continue reading Four short links: 18 April 2019.

Categories: Technology

Toward ethical AI: Inclusivity as a messy, difficult, but promising answer

O'Reilly Radar - Wed, 2019/04/17 - 13:00

Kurt Muehmel explores AI within a broader discussion of the ethics of technology, arguing that inclusivity and collaboration are necessary.

Continue reading Toward ethical AI: Inclusivity as a messy, difficult, but promising answer.

Categories: Technology

Is AI human-ready?

O'Reilly Radar - Wed, 2019/04/17 - 13:00

Aleksander Madry discusses roadblocks preventing AI from having a broad impact and approaches for addressing these issues.

Continue reading Is AI human-ready?.

Categories: Technology

How AI adaptive technology can upgrade education

O'Reilly Radar - Wed, 2019/04/17 - 13:00

Joleen Liang explains how AI and precise knowledge points can help students learn.

Continue reading How AI adaptive technology can upgrade education.

Categories: Technology

Fast, flexible, and functional: 4 real-world AI deployments at enterprise scale

O'Reilly Radar - Wed, 2019/04/17 - 13:00

Gadi Singer discusses the major questions organizations confront as they integrate deep learning.

Continue reading Fast, flexible, and functional: 4 real-world AI deployments at enterprise scale.

Categories: Technology

Automated ML: A journey from CRISPR.ML to Azure ML

O'Reilly Radar - Wed, 2019/04/17 - 13:00

Danielle Dean explains how cloud, data, and AI came together to help build Automated ML.

Continue reading Automated ML: A journey from CRISPR.ML to Azure ML .

Categories: Technology

Data fueling AI of the future

O'Reilly Radar - Wed, 2019/04/17 - 13:00

Thomas Henson considers how AI will shape the experiences of future generations.

Continue reading Data fueling AI of the future.

Categories: Technology

Highlights from the O'Reilly Artificial Intelligence Conference in New York 2019

O'Reilly Radar - Wed, 2019/04/17 - 13:00

Watch highlights from expert talks covering AI, machine learning, deep learning, ethics, and more.

People from across the AI world came together in New York for the O'Reilly Artificial Intelligence Conference. Below you'll find links to highlights from the event.

AI and the robotics revolution

Martial Hebert offers an overview of challenges in AI for robotics and a glimpse at the exciting developments emerging from current research.

Applied machine learning at Facebook

Kim Hazelwood discusses the hardware and software Facebook has designed to meet its scale needs.

Decoding the human genome with deep learning

How can machine learning decode the mysteries of life? Olga Troyanskaya explores this and other big questions through the prism of deep learning.

Computational propaganda

Sean Gourley considers the repercussions of AI-generated content that blurs the line between what's real and what's fake.

Software 2.0 and Snorkel

Christopher Ré discusses Snorkel, a system for fast training data creation.

Is AI human-ready?

Aleksander Madry discusses roadblocks preventing AI from having a broad impact and approaches for addressing these issues.

Machine learning for personalization

Tony Jebara explains how Netflix is personalizing and optimizing the images shown to subscribers.

Checking in on AI tools

Ben Lorica and Roger Chen assess the state of AI technologies and adoption in 2019.

Fast, flexible, and functional: 4 real-world AI deployments at enterprise scale

Gadi Singer discusses the major questions organizations confront as they integrate deep learning.

Making real-world distributed deep learning easy with Nauta

Carlos Humberto Morales offers an overview of Nauta, an open source multiuser platform that lets data scientists run complex deep learning models on shared hardware.

Automated ML: A journey from CRISPR.ML to Azure ML

Danielle Dean explains how cloud, data, and AI came together to help build Automated ML.

Toward ethical AI: Inclusivity as a messy, difficult, but promising answer

Kurt Muehmel explores AI within a broader discussion of the ethics of technology, arguing that inclusivity and collaboration are necessary.

How AI adaptive technology can upgrade education

Joleen Liang explains how AI and precise knowledge points can help students learn.

Artificial intelligence: The “refinery” for data

Nick Curcuru explains how Mastercard is using AI to improve security without sacrificing the customer experience.

Automation of AI: Accelerating the AI revolution

Ruchir Puri discusses the next revolution in automating AI, which strives to deploy AI to automate the task of building, deploying, and managing AI tasks.

Simple, scalable, and sustainable: A methodical approach to AI adoption

Rajendra Prasad explains how leaders in large enterprises can make AI adoption successful.

Data fueling AI of the future

Thomas Henson considers how AI will shape the experiences of future generations.

Teaching a computer to read

Desiree Gosby shares lessons learned while applying computer vision to seeing and reading complex financial documents.

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Continue reading Highlights from the O'Reilly Artificial Intelligence Conference in New York 2019 .

Categories: Technology

Checking in on AI tools

O'Reilly Radar - Wed, 2019/04/17 - 13:00

Ben Lorica and Roger Chen assess the state of AI technologies and adoption in 2019.

Continue reading Checking in on AI tools.

Categories: Technology

AI and the robotics revolution

O'Reilly Radar - Wed, 2019/04/17 - 13:00

Martial Hebert offers an overview of challenges in AI for robotics and a glimpse at the exciting developments emerging from current research.

Continue reading AI and the robotics revolution.

Categories: Technology

Machine learning for personalization

O'Reilly Radar - Wed, 2019/04/17 - 13:00

Tony Jebara explains how Netflix is personalizing and optimizing the images shown to subscribers.

Continue reading Machine learning for personalization.

Categories: Technology

Four short links: 17 April 2019

O'Reilly Radar - Wed, 2019/04/17 - 04:05

Infocom Source, Twitter Design, New Ways of Seeing, and Software Blowouts

  1. Infocom Source Code Uploaded -- with some version control (retroactively manufactured from different versions of the source code). Uploaded from a hard drive of Infocom material copied at the time of the acquisition. Jason Scott described the contents. See also DECWAR source.
  2. I Kind of Hate Twitter (Jason Lefkowitz) -- a very good product analysis of why Twitter drives unproductive behaviour. Example: Push delivery makes it hard to ignore what people are saying about you. If someone’s talking about you on the web, you have to go into Google and search to find that out. If someone’s talking about you on Twitter, though, it’s very likely right in your face. This can be flattering if people are saying nice things, but if they’re not, it can feel embarrassing and/or painful; and people who are embarrassed or wounded tend to do stupid things, like lash back at the person who did the wounding, that they regret later when the pain has worn off.
  3. New Ways of Seeing -- new BBC show from James Bridle which looks to be great. (via The Guardian)
  4. Why Software Projects Take Longer Than You Think—a Statistical Model -- A reasonable model for the “blowup factor” would be something like a log-normal distribution. If the estimate is one week, then let’s model the real outcome as a random variable distributed according to the log-normal distribution around one week. This has the property that the median of the distribution is exactly one week, but the mean is much larger [...]

Continue reading Four short links: 17 April 2019.

Categories: Technology

Four short links: 16 April 2019

O'Reilly Radar - Tue, 2019/04/16 - 03:55

Data Brokers, AI Research Ethics, Overclaimed Science, and Hardware for ML

  1. Facebook Transparency Tool (Buzzfeed) -- A transparency tool on Facebook inadvertently provides a window into the confusing maze of companies you’ve never heard of who appear to have your data.
  2. Microsoft’s AI Research with Chinese Military University Fuels Concerns (SCMP) -- “The new methods and technologies described in their joint papers could very well be contributing to China’s crackdown on minorities in Xinjiang, for which they are using facial recognition technology,” said Helena Legarda, a research associate at the Mercator Institute for China Studies, who focuses on China’s foreign and security policies.
  3. @justsaysinmice -- points out bogus science claims by adding "in mice" where appropriate. Genius.
  4. What Machine Learning Needs from Hardware (Pete Warden) -- More arithmetic; Inference; Low Precision; Compatibility; Codesign.

Continue reading Four short links: 16 April 2019.

Categories: Technology

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