This is an audio version of the Wikipedia Article:
00:02:46 1 Nature-inspired models of computation
00:03:33 1.1 Cellular automata
00:04:47 1.2 Neural computation
00:08:16 1.3 Evolutionary computation
00:11:48 1.4 Swarm intelligence
00:14:08 1.5 Artificial immune systems
00:15:34 1.6 Membrane computing
00:17:36 1.7 Amorphous computing
00:18:51 2 Synthesizing nature by means of computing
00:19:03 2.1 Artificial life
00:21:31 3 Nature-inspired novel hardware
00:22:07 3.1 Molecular computing
00:25:40 3.2 Quantum computing
00:27:57 4 Nature as information processing
00:28:29 4.1 Systems biology
00:33:43 4.2 Synthetic biology
00:36:13 4.3 Cellular computing
00:38:30 5 See also
Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago.
Learning by listening is a great way to:
- increases imagination and understanding
- improves your listening skills
- improves your own spoken accent
- learn while on the move
- reduce eye strain
Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone.
Listen on Google Assistant through Extra Audio:
Other Wikipedia audio articles at:
Upload your own Wikipedia articles through:
Speaking Rate: 0.7677558205663949
Voice name: en-US-Wavenet-B
"I cannot teach anybody anything, I can only make them think."
Natural computing, also called natural computation, is a terminology introduced to encompass three classes of methods: 1) those that take inspiration from nature for the development of novel problem-solving techniques; 2) those that are based on the use of computers to synthesize natural phenomena; and 3) those that employ natural materials (e.g., molecules) to compute. The main fields of research that compose these three branches are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, fractal geometry, artificial life, DNA computing, and quantum computing, among others.
Computational paradigms studied by natural computing are abstracted from natural phenomena as diverse as self-replication, the functioning of the brain, Darwinian evolution, group behavior, the immune system, the defining properties of life forms, cell membranes, and morphogenesis.
Besides traditional electronic hardware, these computational paradigms can be implemented on alternative physical media such as biomolecules (DNA, RNA), or trapped-ion quantum computing devices.
Dually, one can view processes occurring in nature as information processing. Such processes include self-assembly,
developmental processes, gene regulation networks, protein–protein interaction networks, biological transport (active transport, passive transport) networks, and gene assembly in unicellular organisms. Efforts to
understand biological systems also include engineering of semi-synthetic organisms, and understanding the universe itself from the point of view of information processing. Indeed, the idea was even advanced that information is more fundamental than matter or energy.
The Zuse-Fredkin thesis, dating back to the 1960s, states that the entire universe is a huge cellular automaton which continuously updates its rules.
Recently it has been suggested that the whole universe is a quantum computer that computes its own behaviour.