Every week, my team at Invector Labs publishes a newsletter that covers the most recent developments in AI research and technology. You can find this week’s issue below. You can sign up for it below. Please do so, our guys worked really hard on this:
From the Editor: What AlphaStar Means for AI
Earlier this year, artificial intelligence(AI) powerhouse DeepMind unveiled an earlier version of AlphaStar, a reinforcement learning agent that could challenge the top world players in StarCraft II. This week, DeepMind published an update showing that AlphaStar can now play the full game at a Grandmaster level under professionally approved conditions. Specifically, AlphaStar was able to raise to at Grandmaster level in all StarCraft modalities overperforming 99.8% of human players.
Even though AlphaStar is focused on a gaming scenario, the development can have profound implication for general-purpose AI solutions. StarCraft is a strategy game in which agents need to collaborate, cooperate, explore new environment and make decisions in the absence of complete information. From self-driving vehicles to economic planning, the principles behind AlphaStar can become foundational to a new generation of AI applications.
Now let’s take a look at the core developments in AI research and technology this week:
Playing StarCraft Without Any Restrictions
DeepMind published a new research describing AlphaStar II, the first AI that plays StarCraft at a Grandmaster level.
Transferring Knowledge Across Languages
Amazon researchers published a paper proposing a method to reduce the data required for transfer learning in natural language understanding models.
Learning to Assemble and Disassemble Objects
Google published a research paper outlining a new method for training a robot to disassemble and assemble objects.
Cool AI Tech Releases
A Dataset to Train Conversational Assistants
Google released a dataset for training AI agents on task-oriented conversational dialogs.
TensorFlow Gets Collaborative
Google launched TensorBoard.dev, a new environment for sharing machine learning experiments.
Parallel Neural Network Training
Microsoft Research open source PipeDream, a new framework for scaling the training of deep learning models.
AI in the Real World
AI and the Future of Work
IBM and MIT published a study about how AI is impacting specific jobs.
Solving a Famous Math Problem 100 Million Times Faster
AI researchers form the University of Edinburgh build a series of neural networks that solved the famous three-body problem 100 million times faster than previous attempts.
US DOE Gets Serious About AI
The US Department of Energy is pushing a multi-billion AI initiative to improve scientific discoveries.