Welcome to the age of empirical computation

Agents of innovation

We’re entering an age in which humans will no longer be the sole agents of innovation.

Nothing is invented – only discovered

It’s Christmas, you’re 5 years old and the proud recipient of 18 shiny red LEGO bricks and an accompanying manual.

Solution space

Any problem has an infinite number of solutions which exist (albeit theoretically) irrespective of whether they’ve been manifested in the real world. If you can’t get on board with this, don’t read any further.

Type 1 search algorithms

Darwinian evolution is a purely empirical (Type 1) search algorithm in that it both generates and tests hypotheses in the real world. Every new genome that arises through mutation or recombination can be thought of as a new genetic hypothesis. Once formulated, a genetic hypothesis is compiled by cellular machinery and its impact on the corresponding organism’s fitness is measured as a function of reproductive success. As a process, Darwinian evolution has been operating continuously for the past 3.8 billion years and has been responsible for autonomously filling all biological niches with high performing genetic designs.

Type 2 search algorithms

Biological Type 2 search

Type 3 search algorithms

For a Type 3 search algorithm, hypotheses are generated virtually (e.g. in a brain or computationally) and then tested in the real world (i.e. empirically). We tend to call the virtual world ‘the world of bits’ and the real world ‘the world of atoms’.

Ethical & societal questions posed by the rise of ECEs

Empirical computation is a technology that’s set to deliver incredible benefits to humanity. At the same time, it also presents several important ethical and societal questions.

Get involved now

Interested in building an ECE that will fundamentally change the nature of scientific discovery?

Great news, LabGenius is hiring.

CEO & Founder at LabGenius (@labgeni_us), Forbes 30 Under 30, BBSRC Innovator of the Year, Synbio LEAP fellow, Dad

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