OpenAI technical goals

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OpenAI's technical goals include measuring progress, building a household robot, creating an agent with natural language understanding, and solving various games with a single agent

intermediate Published 20 Jun 2016
Action Steps
  1. Define a metric for intelligence to measure progress
  2. Develop a household robot that can perform basic housework
  3. Create an agent with useful natural language understanding
  4. Solve a wide variety of games using a single agent
Who Needs to Know This

AI researchers and engineers can benefit from understanding OpenAI's technical goals, as they provide a roadmap for developing and testing AI capabilities, and can inform their own research and development efforts

Key Insight

💡 OpenAI's technical goals are focused on developing and testing AI capabilities in a range of environments, with a focus on safety and widespread benefits

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🤖 OpenAI's technical goals: measure progress, build a household robot, create an NLU agent, and solve games with a single agent #AI #OpenAI

Key Takeaways

OpenAI's technical goals include measuring progress, building a household robot, creating an agent with natural language understanding, and solving various games with a single agent

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# OpenAI technical goals | OpenAI

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Table of contents

* [Goal 1: Measure our progress](https://openai.com/index/openai-technical-goals#goal-1-measure-our-progress)
* [Goal 2: Build a household robot](https://openai.com/index/openai-technical-goals#goal-2-build-a-household-robot)
* [Goal 3: Build an agent with useful natural language understanding](https://openai.com/index/openai-technical-goals#goal-3-build-an-agent-with-useful-natural-language-understanding)
* [Goal 4: Solve a wide variety of games using a single agent](https://openai.com/index/openai-technical-goals#goal-4-solve-a-wide-variety-of-games-using-a-single-agent)

June 20, 2016

[Safety](https://openai.com/news/safety-alignment/)

# OpenAI technical goals

OpenAI’s mission is to build safe AI, and ensure AI’s benefits are as widely and evenly distributed as possible.

![Image 1: OpenAI Technical Goals](https://images.ctfassets.net/kftzwdyauwt9/8cc38227-f20b-4003-f73183e87387/6c34592b7471e4f1ec22705f67dff543/OpenAI_technical_goals.png?w=3840&q=90&fm=webp)

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We’re trying to build AI as part of a larger community, and we want to share our plans and capabilities along the way. We’re also working to solidify our organization’s governance structure and will share our thoughts on that later this year.

### Our metric

Defining a metric for intelligence is tricky, but we need one to measure our progress and focus our research. We’re thus building a living metric which measures how well an agent can achieve its user’s intended goal in a wide range of environments.

## Goal 1: Measure our progress

The metric will consist of a variety of[OpenAI Gym⁠(opens in a new window)](https://gymlibrary.dev/)environments with a unified action and observation[space⁠(opens in a new window)](https://gym.openai.com/docs#spaces)(so a single agent can run across all of them), including games, robotics, and language-based tasks. Our implementation will evolve over time, and we’ll keep the community updated along the way.

### Our research

A significant fraction of our research bandwidth is being spent on fundamental research. We’ll always be developing and testing new ideas, especially those that don’t fit neatly into our current worldview. This is important—our current ideas will not be enough to achieve our long-term goal.

We’ve also formed teams around specific projects. The intention isn’t just to solve these problems, but to develop general learning algorithms in the process. These algorithms will, in turn, help us build agents that are more capable according to our metric. These projects are:

## Goal 2: Build a household robot

We’re working to enable a physical robot (off-the-shelf; not manufactured by OpenAI) to perform basic housework. There are[existing⁠(opens in a new window)](https://en.wikipedia.org/wiki/Simultaneous_localization_and_mapping)[techniques⁠(opens in a new window)](https://en.wikipedia.org/wiki/Motion_planning)for specific tasks, but we believe that learning algorithms can eventually be made[reliable⁠(opens in a new window)](http://www.bloomberg.com/features/2015-preschool-for-robots/)[enough⁠(opens in a new window)](http://www.theverge.com/2016/3/9/11186940/google-robotic-arms-neural-network-hand-eye-coordination)to create a general-purpose robot. More generally, robotics is a good testbed for many challenge
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