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
What would be the impact of quantum computing in AI technologies? That’s seems like a scary proposition to think about. If today, the world is concerned with the rapid acceleration of AI technologies, can you imagine what would happen if AI models have a virtually unlimited computation playground to grow?
The computation limitations of existing infrastructures impose tangible limitations in the ability of AI algorithms to learn new concepts fast. Theoretically, quantum computing seems like an ideal complement to AI as it expands the computation surface removing many of the limitations of existing models. However, those assumptions are just a conjecture as AI techniques haven’t been proven to work on quantum computing infrastructures. This week, researchers from IBM decided test some of those theories by testing some basic classification models in quantum computers. The results were certainly encouraging but largely inconclusive. Maybe the entire space of machine learning will have to re-imagined for quantum models or maybe there will be an easier transition. Once thing is for certain, the intersection of AI and quantum computing offers a blank canvas to imagine new machine intelligence applications that are inconceivable today.
Now let’s take a look at the core developments in AI research and technology this week:
Facebook launched a new blog dedicated to AI research which includes interviews with some of the top minds in the space.
Google partnered with Stanford and Brown University to publish Snorkel DryBell, a new model that leverages organizational knowledge to label training datasets.
IBM Researchers took an initial step to test machine learning algorithms in quantum computing infrastructures.
Cool Tech Releases
Uber announces DBEvents, a framework for high quality data ingestion pipelines.
Google open sourced TensorFlow Privacy, a library to enforce privacy policies on training datasets.
Machine learning marketplace Algorithmia launched new release with an improved user experience.
AI in the Real World
Microsoft launches a new business school focused on AI strategies.
Stanford University launched a new initiative for Human-Centered AI.
The Economist published a masterful piece about the internal battle between Google and DeepMind for AI initiatives.