Catalyst Watch: Google’s TensorFlow and Quantum Gravity!
Learn how TensorFlow could be creating a new era for the scientific computing market!
As many of our readers may know from reading popular books such as ‘The Elegant Universe’ and ‘The Nature of Space and Time’. There are quantum theories for three of the fundamental forces of nature, the electromagnetic, strong nuclear and weak nuclear forces. There is currently no complete quantum theory that also includes the force of gravity that complies with the experimental observations i.e. an accurate model of quantum gravity.
Earlier this summer, a team of Google researchers based in Zürich published an article in the Journal of High Energy Physics where they introduced novel techniques to address important problems in a modern/advanced theory of quantum gravity. Namely, M-Theory with an emphasis on the use of machine learning technologies such as TensorFlow.
Using simplifications enabled by TensorFlow, we managed to bring the total number of known (stable or unstable) equilibrium solutions for one particular type of M-Theory spacetime geometries to 194, including a new and tachyon-free four-dimensional model universe. The geometries that we studied are special in that they are still (barely) accessible with exact calculations that do not require neglecting potentially important terms.
We hope that these results will be an important step in interpreting M-theory and demonstrate how the research community can use new ML tools, such as TensorFlow, to approach other similarly complex problems. We are already applying the newly discovered methods in further theoretical physics research.
The researchers note on their blog post.
As a VC why should you care?
Well, firstly if you read our report on TensorFlow adoption and ‘The State of Open Source Machine Learning Frameworks’ - you’ll have learned that there’s a great deal of opportunities for start-ups to help bring TensorFlow to fortune 500 companies. Hence, you may consider investing early in AI/ML infrastructure & dev tooling startups that are making deep learning frameworks such as TensorFlow easy to adopt and use.
Secondly, you may have a ‘Jack of all trades’ type of AI/ML infrastructure portfolio struggling to gain traction due to a lack of focus. Perhaps you could suggest that they first focus 100% on TensorFlow!
Thirdly, this result from the Google researchers is probably one of the catalysts for a new era in the scientific computing market, which is currently dominated by companies such as: MathWorks, Maplesoft and Wolfram Research.
Do you know that we are tracking top European and US based scientists that our signals indicate may start companies in near future? Schedule a call to learn more!