Intelligence

Intelligence is associated with a property of mind.
From wiki:
Intelligence
From the first sentence:

Quote:

Intelligence (also called intellect) is an umbrella term used to describe a property of the mind that encompasses many related abilities, such as the capacities to reason, to plan, to solve problems, to think abstractly, to comprehend ideas, to use language, and to learn.

Artificial intelligence
From this article a few essential traits of intelligence are considered:
1) Deduction, reasoning, problem solving
2) Knowledge representation
3) Planning
4) Learning
5) Natural language processing
6) Motion and manipulation
7) Perception
8) Social intelligence
9) Creativity
10) General intelligence

However, there is no universally accepted definition of intelligence.
So let's take what we do know about intelligence (the 10 criteria above) and compare the systems and machinery within cells to any intelligent AI system.

1) Deduction, reasoning, problem solving
Cells:
Deduction: No
Reasoning: No
Problem solving: Yes. E.g. (from Nature;Vol 446;12 April 2007: Quantum path to photosynthesis)

Quote:

Elsewhere in this issue, Engel et al. (page 782) take a close look at how nature, in the form of the green sulphur bacterium Chlorobium tepidum, manages to transfer and trap light’s energy so effectively. The key might be a clever quantum computation built into the photosynthetic algorithm.

Quote:

The process is analogous to Grover’s algorithm in quantum computing, which has been proved to provide the fastest possible search of an unsorted information database.

And in the same issue: Evidence for wavelike energy transfer through quantum coherence in photosynthetic systems

Quote:

When viewed in this way, the system is essentially performing a single quantum computation, sensing many states simultaneously and selecting the correct answer, as indicated by the efficiency of the energy transfer.

Who knows what other kinds of quantum computing we will discover in organisms? Perhaps a clever quantum “trick” together with coulombic interactions in the bifurcated electron transfer of bc1-like complexes through the Q-cycle? Microtubles, centrioles etc.?

AI:
Deduction: No
Reasoning: No
Problem solving: Yes. (not quantum mechanically)

2) Knowledge representation
Cells:
Default reasoning and the qualification problem: No?
Unconscious knowledge: Perhaps? Stored in any or all of the cellular codes?
The breadth of common sense knowledge: No.
AI:
Default reasoning and the qualification problem: No
Unconscious knowledge: Yes. The software contains the stored information
The breadth of common sense knowledge: No


3) Planning
Cells: Possibly yes!
Predictive Behavior Within Microbial Genetic Networks

Quote:

We question whether homeostasis alone adequately explains microbial responses to environmental stimuli, and explore the capacity of intra-cellular networks for predictive behavior in a fashion similar to metazoan nervous systems. We show that in silico biochemical networks, evolving randomly under precisely defined complex habitats, capture the dynamical, multidimensional structure of diverse environments by forming internal models that allow prediction of environmental change. We provide evidence for such anticipatory behavior by revealing striking correlations of Escherichia coli transcriptional responses to temperature and oxygen perturbations—precisely mirroring the co-variation of these parameters upon transitions between the outside world and the mammalian gastrointestinal-tract. We further show that these internal correlations reflect a true associative learning paradigm, since they show rapid decoupling upon exposure to novel environments.

Emphasis mine.

Microarray transcriptional profiling was employed to determine whether gene expression correlates with the observed global cellular state and physiological responses. And indeed it does.
From the study it was determined that anticipatory transcriptional reprogramming occurs in response to aerobic and anaerobic environmental changes and these anticipatory transcriptional reprogramming events are as a result an “associative learning” paradigm. Is this an example of harnessing random variation and selection that allow for predictive transcriptional reprogramming in response to environmental change that gives the illusion of foresight? Creativity?

It should also be interesting to determine how big a part riboswitches play in this phenomenon.

AI:Yes if programmed to.

4) Learning
Cells: Yes, see "planning".
AI: Yes, certain artificial neural networks are capable of this.

5) Natural language processing
Cells: Yes and no. Yes because cells are able to communicate and process information from themselves and other cells (autocrine, paracrine, endocrine etc). No, cells do not consciously talk to exchange concepts and ideas.
AI: Yes and no. Yes because certain programs can interpret human language and systems of various platforms can communicate (Linux to Mac etc). No, AI does not consciously talk to exchange concepts and ideas.

6) Motion and manipulation
Cells: Yes, with the possibility that tubulin and other structural components of cells acting as quantum computers, motion and manipulation is directed, not stochastic, in even the simplest organisms.
Movement of organisms without a nervous system.
Also here:
Interesting site about cell intelligence and movement.
AI: Yes

7) Perception
Cells: Yes, cells communicate with the environment through surface receptors and relays information through signal transduction which in turn affects gene expression and protein activity which it turn results in predictive cell responses. Information from the environment is also processed via the multiples codes, e.g. histone code, ribosomal code and the standard genetic code.
AI: Yes

8) Social intelligence
Cells: Yes, even bacteria interact with other bacteria and can even mimic a multicellular organism through quorum sensing.
AI: Perhaps? AI neural networks?

9) Creativity
Cells: Perhaps? Harnessing random variation and selection to adapt?
AI: Perhaps? An example?

10) General intelligence
Cells: No (Only in humans so far)
AI: No


At present, even traditionally viewed simple cells outsmart our best efforts at AI.


I don't know where to put the following:
Cell's 'Quality Control' Mechanism Discovered
Is this an example of a non-passive selection system to remove mutated proteins from the population, even if the mutated proteins are functional? Perhaps a system that preserves a set of proteins? Unconscious knowledge (2)? Constrained creativity (9)?
This mechanism (system?) is not limited to eukaryotic cells. The ERdj5 enzyme operates in eukaryotes. The DnaJ enzyme is a homlogous chaperone protein in bacteria that carries out virtually the same function. Also known as heat shock 40 proteins (HSP40).
The DNAJ gene family.
DnaJ is also found in primitive eubacteria, indicating that the system was present VERY early on during evolution.
Eubacteria:

Quote:

Most eubacteria are gram positive, and they are generally less structurally complex than other bacteria.

Articles:
ERdj4 and ERdj5 Are Required for Endoplasmic Reticulum-associated Protein Degradation of Misfolded Surfactant Protein C
ERdj5 is required as a disulfide reductase for degradation of misfolded proteins in the ER.

Seems interesting nonetheless.