Learning through human feedback

Learning through human feedback  #DeepLearning #AI #ArtificialIntelligence

  • That is why DeepMind co-founded initiatives like the Partnership on AI to Benefit People and Society and why we have a team dedicated to technical AI Safety.
  • Research in this field needs to be open and collaborative to ensure that best practices are adopted as widely as possible, which is why we are also collaborating with OpenAI on research in technical AI Safety.
  • One of the central questions in this field is how we allow humans to tell a system what we want it to do and – importantly – what we don’t want it to do.
  • This is increasingly important as the problems we tackle with machine learning grow more complex and are applied in the real world.
  • The first results from our collaboration demonstrate one method to address this, by allowing humans with no technical experience to teach a reinforcement learning (RL) system – an AI that learns by trial and error – a complex goal.

A central question in technical AI safety is how to tell an algorithm what we want it to do. Working with OpenAI, we demonstrate a novel system that allows a human with no technical experience to teach an AI how to perform a complex task, such as manipulating a simulated robotic arm.
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A Designer’s Guide To The $15 Billion Artificial Intelligence Industry

A designer's guide to the $15 billion artificial intelligence industry  (from 2016)

  • The best designers know that they need to study human behavior if they want to make the right choices for their users.
  • It allows designers to cater to, and anticipate, individual users’ needs.
  • With AI, products and services aren’t just performing basic functions; they’re emotionally aware, letting designers create the best experience for each user.
  • Psychology: The way an AI system communicates with users at 2 p.m. should be different from the way it talks to them at 2 a.m., taking into account the unusually late time and understanding that the users are likely frustrated because they can’t sleep, playful because they’ve been drinking, or panicked because there’s been an emergency.
  • Designers have to understand the many ways users might react in different scenarios and how they will express their intention depending on factors like their mood, location, and what they ate that day.

As artificial intelligence gains ground, designers will need to adapt. Here’s how to get started.

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3 guiding principles for ethical AI, from IBM CEO Ginni Rometty

.@IBM 's CEO Ginni Rometty sums up the principles for ethical #AI into three words

  • For IBM, the purpose of AI will be to aid humans, not replace them. “
  • Google uses DeepMind AI to reduce energy use at data centers and save money (TechRepublic)
  • We say cognitive, not AI, because we are augmenting intelligence,” Rometty said. “
  • Microsoft’s new breakthrough: AI that’s as good as humans at listening…
  • You must be clear as you build AI platforms how they are trained, and what data was used in training. “

At the World Economic Forum on Tuesday, IBM CEO Ginni Rometty laid out three principles to guide technologists for responsible AI use as cognitive abilities continue to develop.
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A Designer’s Guide To The $15 Billion Artificial Intelligence Industry

A designer's guide to the $15 billion artificial intelligence industry

  • Sociology: Designers will need to consider when and if AI systems should be considered a part of society.
  • The best designers know that they need to study human behavior if they want to make the right choices for their users.
  • First a word on why designers should embrace artificial intelligence in the first place.
  • AI has the potential to fundamentally change how society functions .
  • With AI, products and services arent just performing basic functions; theyre emotionally aware, letting designers create the best experience for each user.

As artificial intelligence gains ground, designers will need to adapt. Here’s how to get started.
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ecosystem/marathon at master · tensorflow/ecosystem · GitHub

Run @tensorflow on @ApacheMesos with @dcos!

  • The section covers instructions on how to write your training program and build your docker image.
  • Write your own Docker file which simply copies your training program into the image and optionally specify an entrypoint.
  • Write your own training program.
  • An example is located in docker/Dockerfile or docker/Dockerfile.hdfs if you need the HDFS support.
  • The Marathon config is generated from a Jinja template where you need to customize your own cluster configuration in the file header.

ecosystem – Integration of TensorFlow with other open-source frameworks
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Microsoft Ventures out to Democratize AI

Microsoft Ventures out to Democratize AI  #AI #Microsoft

  • Launched in early 2016, Element AI enables organizations to develop their own AI solutions by implementing an “AI-First” strategy.
  • “Microsoft is committed to democratizing AI with guiding principles to drive positive impact.
  • Element AI, a Canada-based AI incubator, was the first recipient of funding from this new fund.
  • Element AI shares our approach and philosophy.”
  • “We all know ‘You’re only as good as your tools’ and now Element AI is getting supercharged with Microsoft Ventures,” says Jean-François Gagné, CEO, Element AI. “

Microsoft is taking big steps to make its mark in the Artificial Intelligence (AI) sector.
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