Robot With AI Brain Learns To Evolve Synthetic Protocells

Scientists have tried to research and explain the origin of life for many years -in fact, since time in memorial. All along it has been about theories but in this era of artificial intelligence, hopes are that practical explanations are the way to go. Thanks to the AI brain, because at least we can now understand evolution much better.

Ideally, if it is about the availability of data to facilitate analysis there is plenty of that in all fields of studies. So far, researchers are able to analyze the space as well as living cells with utter clarity using machine learning. And in this article, we are going to take a closer look into a newly developed AI brain system. The robot is basically designed for a chemistry lab and it can practically evolve synthetic photocells.

A Quick Glance At The Basics of Chemistry

Source: OGF

Just to remind us some chemistry -oil floats on water, reason: water is heavier than oil. Well, I believe that was the cut line for most of us in reading about oil in water. But you know what, there is more to the equation and this is a vast topic that scientist have used to discover very interesting principles that pre-exist in life -and now a robot with AI brain has also begun its explorations.

Where AI Meets Oil in Water

Oil-in-water droplets provide a recipe for protocell models. Why? Because, the drops exhibit complex cell-like behaviors -a drop of oil on water behaves really strange. It can divide and move around the surface exactly like a living cell. However, to be able to work out specific droplet properties that include but not limited to density, surface tension, and viscosity -which fuel the varying behaviors -droplet designs must be varied.  Well, it is also worth admitting that permutations are vast and depend on the droplet ingredients. That is exactly where the robot with the AI brain comes in.

How an AI brain is Able to Evolve Synthetic Protocells

Source: timesofisrael

Lee Cronin, a researcher at the University of Glasgow in the UK has created a robot with a special AI brain. The system is able to practically make varying oil-in-water droplets, analyze their behavior, compile the data and using evolutionary algorithms together with machine learning –it selects and predicts behaviors. It also evolves better and improves the preceding generations of droplets.

Ideally, the major focus in these droplet formulations is seeing how long it may take to create droplets that can be complex enough to resemble existing living cells. Along the way, Cronin and his team hope to invent a chemical memory that can carry genetic codes, which maybe can be programmed to become life-like. “With such a possibility, we will be able to tell how pre-living systems came into being so complex, as well as decode life’s mysteries,” explains Cronin.

The Setup Into Details

Source: N.A. of science

The somewhat complex setup uses robotic intelligence. It dispenses six varying aqueous surfactant solutions. First, the process begins with creating unique droplets with dye and varying quantities of oil then adding the surfactant solution. A powerful camera then records the behaviors of the specimens while an image recognition software analyzes, identifies, quantifies and classifies their detailed movements, vibrations, and properties.

The researchers were able to test 400 random mixtures by varying the oil and aqueous components in less than two days, and they ended up with amazing results. First, they concluded that the droplets were able to “feel” one another” and they swarm to specific directions.

With the unique behaviors, the team then tested the robot’s ability to evolve higher-grade droplets by feeding data back into the system using genetic algorithm 30 times. The number of rounds in this case ideally represents 30 generations –where they link the AI brain to prediction capabilities.

The Summary of The Findings

After a careful analysis, the end result showed that the new droplets became 14 times faster in everything, vibrating, movement, and dividing. They also displayed surprising motional patterns, which Holger Stark commented on that by saying, “this is most likely applicable to several other chemical and physical systems that already pre-exist.”

As in what we are seeing here is that there is more to explore using an AI brain when it comes to physical and chemical behaviors of matter as well as systems. In conclusion, this is definitely the era where we are going to experience the full potential of artificial intelligence.