Every week, my team at Invector Labs publishes a newsletter to track 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
A new year has started and with that all sorts of predictions and expectations about artificial intelligence(AI). What should we expect from AI in 2019? Certainly, there are no lack of optimistic predictions about massive adoptions of AI in this new year. At Invector Labs, we believe this is going to be another year of infrastructure building and small progress towards mainstream adoption of AI technologies.
Based on what we are seeing with our customers, we certainly hope for some improvements in the platforms that are used to implement AI solutions in the real world. Specifically, better stacks for training and interpretability of machine learning models are desperately needed. One area that we are particularly excited is reinforcement learning. At the moment, reinforcement learning applications are a privilege of AI powerhouses such as OpenAI or DeepMind. The recent work of AWS in this area and some other developments indicate that we are close to simplify and streamline the adoption of reinforcement learning in real world applications.
Certainly, 2019 promises to be an exciting year for AI and we are happy to be sharing this journey with you.
Happy New Year!
Now let’s take a look at the core developments in AI research and technology this week:
Microsoft Research summarized some of their most successful AI accomplishments of 2018
Researchers from the University of Western Ontario published a paper introducing a technique called dynamic planning networks(DPN) which allow reinforcement learning agents to construct dynamic plans that test different hypotheses.
Researchers from Cambridge University in the United Kingdom published a paper that tries to shade some light into how visual question-answering agents develop a notion of quantifiers
Researchers from the Partnership on AI published a fascinating paper that digs deeper into the relationship between uncertainty and value functions in AI systems.
AI Researchers from Salesforce.com published a paper that proposes a method for question-answering models that gather evidence across different documents.
AI in the Real World
Uber hosted a charter of the Women in Statistics, Data, Optimization and Machine Learning group to celebrate some of the achievements of women working in AI at Uber.
Finland started an audacious plan to train its population in artificial intelligence.
Bloomberg published a great article about how artificial intelligence is being used to study and adapt to hacker’s behaviors.