SenseTime Group has raised $600 million from Alibaba Group Holding (baba) and other investors at a valuation of more than $3 billion, becoming the world’s most valuable artificial intelligence startup.
Source: fortune.com
There are a lot of neat things going on in deep reinforcement learning. One of the coolest things from last year was OpenAI and DeepMind’s work on training an agent using feedback from a human rather than a classical reward signal. There’s a great blog post about it at Learning from Human Preferences, and the original paper is at Deep Reinforcement Learning from Human Preferences.
Read More
Like private credit scores, a person’s social score can move up and down depending on their behaviour. The exact methodology is a secret — but examples infractions include bad driving, smoking in non-smoking zones, buying too many video games and posting fake news online.
Read More
Neural networks, which underlie many of Uber’s machine learning systems, have proven highly successful in solving complex problems, including image recognition, language understanding, and game-playing. However, these networks are usually trained to a stopping point through gradient descent, which incrementally adjusts the connections of the network based on its performance over many trials. Once the training is complete, the network is fixed and the connections can no longer change; as a result, barring any later re-training (again requiring many examples), the network in effect stops learning at the moment training ends.
Read More