Google DeepMind has urged the UK government to consider funding AI degrees (GOOG)

Postgame David Silver, Demis Hassabis, Lee Sedol

Google DeepMind

DeepMind, the artificial intelligence research lab acquired by Google for a reported £400 million in 2014, has called on the UK government to consider funding degree courses that focus on machine learning, which is a subfield of AI.

The company — cofounded by Demis Hassabis, Shane Legg and Mustafa Suleyman in 2011 — said the government needs to support the next generation of machine learning experts if it wants the UK to cement its position as a world leader in AI.

Writing in evidence submitted to a parliamentary inquiry into robotics and AI last month, DeepMind said: "The government should consider funding for machine learning masters and PhD programmes at British universities, to encourage more research in the field and nurture the next generation of scientists who will help preserve the UK’s preeminent position."

The company added: "This funding could also include direct support for modules within programmes that train machine learning researchers in the ethics of data science and increasingly autonomous decision-making, to ensure that the pursuit of beneficial outcomes is embedded in the science of machine learning at every level."

Machine learning masters degrees and PhDs can cost individuals upwards of £10,000 at the top universities. 

Machine learning is an area of computer science that gives computers the ability to learn without being explicitly programmed. Google is one of several large tech companies carrying out research in the space, with the search giant recently announcing a new machine learning research team in Europe. Apple, Facebook, Amazon, and Microsoft are also investing heavily in the field.

The UK has emerged as a world leader in AI and machine learning over the last few years thanks in large part to the work being done at universities like Cambridge, UCL, and Imperial. Scientific entrepreneurs like those in the DeepMind founding team often work on ideas behind the walls of academia before spinning out private companies that are desired by Silicon Valley tech giants.

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