Is Evolutionary Computation Actually a Functional Quantum Computer?

Quantum computing is amazing because instead of storing information in zeros and ones, data is stored data in quantum states (qubits), enabling quantum computers to manipulate enormous combinations of states at once. Do you want to find a cure for cancer? Do you want to prevent bad guys from hacking your banking system? Quantum computing. The quantum realm is the real manifestation of the paradoxical Schrödinger's cat. But all this quantum goodness cannot come without a price. 

The ability of quantum computing to see virtually all futures at once does not come without limitations: availability and cost. While we are on the verge of a great quantum computing revolution, its commercial benefits will not likely be available to the average corporation for another decade or so. And even when it does become available, the cost of developing quantum-based solutions and operating these systems will probably prohibitive it. 

So, where does this leave the everyday company? Today’s functional and affordable quantum-like capabilities can be found in Evolutionary Computing, today's functional quantum machine. Evolutionary computation solves problems by exploring all possible solutions simultaneously and retaining only the best outcomes, evolving rapidly to optimal results. 

Instead of seeing all the possibilities today all at once, as with quantum computing, evolutionary algorithms quickly analyze potential outcomes over time (epochs). Where it would take millions of evolutions for humans to solve a complex problem and a few for quantum computers, evolutionary computing is in that comfortable middle. It does so through organically creating the next generation of possibilities by combining the best of the current one. In doing so, evolutionary computing exponentially evolves to an optimal outcome.

Evolutionary computation can find optimal solutions in every market: 

• Healthcare - Help predict the onset of sepsis, which prevents deaths and reduce hospital deaths. 

• Insurance - Identify traffickers of substance use disorder patients (AKA addicts) through the recovery industry, saving lives and reducing costs

• Banking - Recommend how to sell existing services to current clients, which grows revenue without the risk of new product development.

• Manufacturing - Pricing recommendations for customized trucks that are built out of thousands of parts, maximizing profits.

• Entertainment - Drive better marketing performance by optimizing the impact of the theatrical trailer.

• Government – Reduce veteran suicides by predicting who will suffer from a post-traumatic stress disorder (PTSD) event and prescribe recovery actions.

Evolutionary algorithms represent the “computerization” of biological evolution that can scale on the back of our existing enterprises today. And it is capable of solving some of the hardest problems we face at a cost that is within the budgets of even the most cost-conscious business.

What is the cost and fuel of evolutionary computation? It needs a lot of data or it needs to grow it. It is most effective and useful when there are lots and lots of variables (elbits - pronounced L-bits) to consider. Very few problems are actually too big to solve for this biological machine. 

In one example, evolutionary computing predicted the best outcome is a space the size of 2^2^70. Now, before you go gabbing that calculator, if you printed this number in 10pt font, it would take you around 95 light-years to travel it. That is a big problem, bigger that most business issues facing you on any given day.

Evolutionary computation comes with many of the same advantages as it's quantum computing cousin. The most noteworthy is the ability to see beyond the limited vision of human beings. Both quantum and evolutionary computing can test all possible futures, but without the biases (assumptions) associated with the human condition. 

In another example, evolutionary computation tested optimal growing conditions for basal leaves, the goal is to produce the best taste in the shortest time and with the least resources. At the time study, agronomists believed that the basil plant needed around 6 hours of sleep (18 hours of light). Surprisingly, evolutionary computing discovered and suggested the optimal plant growth should occur with 24 hours of light and no darkness – proving that basal plants do not need to “sleep.” 

Evolutionary AI is the modern and current equivalent of a functional quantum computer. With it, every company can now solve the hardest of their previously intractable problems. Whether you are trying to predict the price of an insurance product based on your existing client base, evaluating breast cancer patients and drug protocols to map out the best treatment or identifying which veterans at greatest risk of suicide from post-traumatic stress disorders, evolution takes all variables under consideration and recommends the solutions that produce those exact results.

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