Commercially viable quantum computing could be here sooner than you think, thanks to a new innovation that shrinks quantum tech down onto a chip: a cryochip.

Seeker explains:

It seems like quantum computers will likely be a big part of our computing future—but getting them to do anything super useful has been famously difficult. Lots of new technologies are aiming to get commercially viable quantum computing here just a little bit faster, including one innovation that shrinks quantum technology down onto a chip.

Malte Pietsch delivers this keynote on “Transfer Learning – Entering a new era in NLP” at PyData Warsaw 2019

Transfer learning has been changing the NLP landscape tremendously since the release of BERT one year ago. Transformers of all kinds have emerged, dominate most research leaderboards and have made their way into industrial applications. In this talk we will dissect the paradigm of transfer learning and its effects on pipelines, modelling and the engineers mindset.

Seeker examines a leaked paper from Google claimed that a quantum computer demonstrated “quantum supremacy.”

But what does that mean exactly?

Quantum computers’ potential and the advantages they promise over classical computers all remain largely theoretical, and hypothetically speaking, it is predicted that quantum computers will be able to solve problems that are beyond the reach of the classical computers we use today. Passing such a threshold will be considered proof of what we call “quantum supremacy.”

Unlike traditional software development, as you progress further in data science and AI, you will encounter more and more advanced mathematics. Given the sad state of how math is taught in schools today (at least in the US), learning math quickly can dramatically impact the quality of your life and your career options.

Fortunately, Siraj Raval has got our back and, in this video, he offers up tips on how to learn math more quickly.