What makes humans intelligent

When people acquire a new skill, for instance juggling, transient and selective structural changes are observed in brain areas that are associated with the processing and storage of complex visual motion Draganski et al. Similarly, sex differences and age differences are important factors that influence brain structure and can affect which cortical areas associate with intelligence. Substantial sex differences were reported in the pattern of correlations between intelligence and regional gray and white matter volumes Haier et al.

Haier et al. Similar results were obtained by Ryman et al. However, in females the results indicated associations with intelligence in white matter efficiency and total gray matter volume Ryman et al.

Yet different conclusions were drawn by Narr et al. Finally, in a recent study where surface-based morphometry SBM was applied instead of VBM, substantial group differences in brain structure were found between sexes but cognitive performance was unrelated to brain structural variation within and between sexes Escorial et al.

What the studies do agree on is that substantial sex differences exist in brain structure, but that these differences not always underlie variation in cognitive performance.

In addition to sex differences, gray matter volume shows dramatic changes during lifetime that are part of normal development Gogtay et al. The initial increase at earlier ages is followed by sustained thinning around puberty. This developmental change is thought to be a result of overproduction of synapses in early childhood and increased synaptic pruning in adolescence and young adulthood Bourgeois et al. Furthermore, different areas have their own timeline of maturation: higher-order association cortices mature only after lower-order somatosensory and visual cortices Gogtay et al.

Correlations with intelligence follow a similar developmental curve. The strongest correlations between gray matter volume and intelligence have been found for children around the age of 10 years Shaw et al. However, at age 12, around the start of cortical thinning, a negative relationship emerges Brouwer et al. Moreover, it seems that the whole pattern of cortical maturation unfolds differently in more intelligent children.

Children with higher IQ demonstrate a particularly plastic cortex, with an initial accelerated and prolonged phase of cortical increase and equally vigorous cortical thinning by early adolescence Shaw et al. In addition to associations of cortical structure with intelligence, imaging studies have revealed correlations of functional activation of cortical areas with intelligence. Crystallized intelligence is based on prior knowledge and experience and reflects verbal cognition, while fluid intelligence requires adaptive reasoning in novel situations Carroll, ; Engle et al.

Multiple studies imply that fluid intelligence relies on more efficient function of distributed cortical areas Duncan et al. In particular, lateral frontal cortex, with its well-established role in reasoning, attention and working memory, seems to support fluid intelligence, but also the parietal lobe is implicated. Cognitive performance showed significant negative correlations with cortical metabolic rates, suggesting more efficient neural circuits Haier et al. In later studies, fluid intelligence was strongly linked to both function and structure of frontal lobe regions Choi et al.

When participants perform verbal and nonverbal versions of a challenging working-memory task, while their brain activity is measured using functional magnetic resonance imaging fMRI , individuals with higher fluid intelligence are more accurate and have greater event-related neural activity in lateral prefrontal and parietal regions Gray et al.

Also in a PET-scan study, participants showed a selective recruitment of lateral frontal cortex during more complicated cognitive tasks compared to easier tasks Duncan et al. In a more recent report, the measurements of gray matter volume of two frontal areas—orbito-frontal OFC and rostral anterior cingulate cortices rACC —were complemented by white matter connectivity between these regions.

Thus, especially in prefrontal cortex, structure, function and connectivity all relate to general intelligence, specifically to reasoning ability and working memory Ohtani et al. Crystallized intelligence that largely relies on verbal ability, on the other hand, depends more on the cortical structure and cortical thickness in lateral areas of temporal lobes and temporal pole Choi et al. While parietal areas Brodman area 40 show overlap in their involvement in crystallized and other types of intelligence, temporal Brodman area 38 is exclusively involved in crystallized intelligence.

These findings harmonize well with the function of the temporal lobe—it is thought to be responsible for integrating diverse semantic information from distinct brain regions.

Studies of patients with semantic dementia support the role of temporal lobe in semantic working memory as well as memory storage Gainotti, It is likely that further subdividing fluid and crystallized intelligence, for instance in verbal comprehension, working memory, processing speed, and perceptual organization, may result in a more defined map of cortical regions on left and right hemisphere that relate to these subdomains of intelligence Jung and Haier, Not only gray matter, but also white matter volumes show an association with intelligence that can be explained by common genetic origin Posthuma et al.

White matter consists of myelinated axons transferring information from one brain region to another and integrity of the white matter tracts is essential for normal cognitive function. For example, Yu et al. IQ scores significantly correlated with the integrity of multiple white matter tracts in both healthy controls and mental retardation patients Yu et al. This correlation was especially prominent in right uncinate fasciculus that connects parts of temporal lobe with the frontal lobe areas Yu et al.

These results support previous findings on the association of particularly temporal and frontal lobe gray matter volume and intelligence Hulshoff Pol et al.

Longitudinal studies that track changes in white matter across development and during aging also show that changes in white matter are accompanied by changes in intelligence. During brain maturation in children, white matter structure shows associations with intelligence. In another study, where white matter was studied in typically-developing children vs.

Also at later stages in life, changes in white matter microstructure are coupled with changes in intelligence Ritchie et al. Substantial correlations of 12 major white matter tracts with general intelligence were found in older individuals Penke et al. Subsequent analysis showed that lower white matter tract integrity exerts a substantial negative effect on general intelligence through reduced information-processing speed Penke et al.

Thus, structurally intact axonal fibers across the brain provide the neuroanatomical infrastructure for fast information processing within widespread brain networks, supporting general intelligence Penke et al. Thus, both functional and structural neuroimaging studies show that general intelligence cannot be attributed to one specific region.

Rather, intelligence is supported by a distributed network of brain regions in many, if not all, higher-order association cortices, also known as parietal-frontal network Jung and Haier, ; Figure 1. This network includes a large number of regions—the dorsolateral prefrontal cortex, the parietal lobe, and the anterior cingulate, multiple regions within the temporal and occipital lobes and, finally, major white matter tracts.

Some limited division of function can be observed, implicating frontal and parietal areas in fluid intelligence, temporal lobes in crystallized intelligence and white matter integrity in processing speed. Although brain imaging studies have identified anatomical and functional correlates of human intelligence, the actual correlation coefficients have consistently been modest, around 0.

There are most likely various reasons for this, but an important conclusion is that human intelligence can only partly be explained by brain structure and functional activation of cortical areas observed in MRI. There are other factors contributing to intelligence that have to be considered. To put it in an evolutionary perspective, the human brain has outstanding cognitive capabilities compared to other species, that include many specific human abilities—abstract thinking, language and creativity.

However, human brain anatomy is not that distinct from other mammalian species and it cannot satisfactorily account for a marked evolutionary jump in intelligence. Both in its size and neuronal count, the human brain does not evolutionary stand out: elephants and whales have larger brains Manger et al. Especially the brains of our closest neighbors on the evolutionary scale, non-human primates, show remarkable resemblance. In fact, the human brain is anatomically in every way a linearly scaled-up primate brain Herculano-Houzel, , and appears to have little exceptional or extraordinary features to which outstanding cognitive abilities can be attributed.

Thus, answers to the origins of human intelligence and its variation between individuals most probably do not lie only in the gross anatomy of the brain, but rather should be sought at the level of its building blocks and computational units—neurons, synapses and their genetic make-up. Given that intelligence is one of the most heritable traits, it follows that also its neurobiological correlates should be under strong genetic influence.

Indeed, both cortical gray and white matter show a gradient of similarity in subjects with increasing genetic affinity Thompson et al. This structural brain similarity is especially strong in frontal and lateral temporal regions, which show most significant heritability Thompson et al.

Hence, overall brain volume links to intelligence and to a large extent shares a common genetic origin. How and when during the development is genetic influence exerted by individual genes and what are the genes that determine human intelligence?

Over the last decade, genome-wide association studies GWAS evolved into a powerful tool for investigating the genes underlying variation in many human traits and diseases Bush and Moore, GWAS studies test for associations between phenotypes and genetic variants—single-nucleotide polymorphisms SNPs —in large groups of unrelated individuals. Although the large majority of SNPs have a minimal impact on biological pathways, some SNPs can also have functional consequences, causing amino acid changes and thus lead to the identification of genetic underpinnings of a disease or a trait Bush and Moore, After the first wave of GWAS of intelligence studies yielded mostly non-replicable results Butcher et al.

Using educational attainment as proxy phenotype of intelligence boosted both the sample size and the number of found associated genes. Educational attainment is the number of years spent in full-time education. Both phenotypically Deary et al. Even larger samples sizes were obtained by combining the GWAS for cognitive ability with educational attainment Lam et al.

What are the genes of intelligence identified by these studies? The latest and largest genetic association study of intelligence to date identified genomic loci and implicated 1, genes, adding novel loci and novel genes to previously associated with cognitive ability Savage et al.

These findings show that intelligence is a highly polygenic trait where many different genes would exert extremely small, if any, influence, most probably at different stages of development. Indeed, the reported effect sizes for each allele are extremely small generally less than 0.

For example, the strongest effect of identified alleles on educational attainment explains only 0. However, small genetic effects at critical stages of development may have large consequences on brain function and development and together with it on cognitive ability.

Thus, it is important to know what these identified genes are, but also when and where they are expressed in the nervous tissue. Non-coding regions comprise most of the human genome and harbor a significant fraction of risk alleles for neuropsychiatric disease and behavioral traits. A very similar picture emerges for GWAS of intelligence studies. SNPs significantly associated with intelligence are mostly located in intronic Similar distributions were also found in earlier association studies Sniekers et al.

However, it is exactly these non-coding, gene regulatory regions that make the genome responsive to changes in synaptic activity and constitute a major force behind the evolution of human cognitive ability Hardingham et al. While the function of most intergenic regions in human DNA remain poorly defined, new insights emerge from studies combining high-resolution mapping of non-coding elements, chromatin accessibility and gene expression profiles.

These studies link the regulatory elements to their target genes. Thus, neurogenesis and cortical expansion in humans is thought to be controlled by specific genetic regulatory elements—human-gained enhancers HGEs , that show increased activity in the human lineage de la Torre-Ubieta et al.

Moreover, genetic variants associated with educational attainment were shown to be enriched within the regulatory elements involved in cortical neurogenesis de la Torre-Ubieta et al. Figure 2. Most of the associated genetic variants of intelligence lie in non-coding DNA regions—only 1.

Gene-set analyses implicate pathways related to neurogenesis, neuron differentiation and synaptic structure. The figure is based on the results from the most recent and largest genome-wide association studies GWAS of intelligence by Savage et al.

Thus, genetic effects on cognitive ability most probably do not operate independently of environmental factors, but rather reveal themselves through signal-regulated transcription driven by experience. This interplay between the epigenetic effects through regulatory elements and genetic make-up would also explain the increasing heritability of intelligence with age Bergen et al. The same regulatory genes require proper gene-environment interactions to reveal their role in cognitive ability.

In other words, during development, the same set of genes acquires an increasing impact on intelligence as early levels of cognitive ability become reinforced through the selection of environments and education consistent with those ability levels Briley and Tucker-Drob, ; Plomin and von Stumm, Many GWAS results identify genes and biological pathways that are primarily active during distinct stages of prenatal brain development Bergen et al.

A number of these genes were previously implicated in intellectual disability or developmental delay Coleman et al. Specifically, some genes with known mutations of large effect in mental disease show smaller regulatory effects on cognition, indicating naturally occurring dose-response curves regarding gene function Trampush et al.

Combining the SNP-data with transcriptome data showed that the candidate genes exhibit above-baseline expression in the brain throughout life, but show particularly higher expression levels in the brain during prenatal development Okbay et al.

When genes were grouped into functional clusters, many such clusters associated with educational attainment are primarily involved in different stages of neural development: the proliferation of neural progenitor cells and their specialization, the migration of new neurons to the different layers of the cortex, the projection of axons from neurons to their signaling target and dendritic sprouting Okbay et al.

Also for intelligence, gene-set analysis identifies neurogenesis, neuronal differentiation and regulation of nervous system development as major functions of the identified SNPs Savage et al. Finally, the largest and most significantly enriched cluster of genes associated with educational attainment contains genes with transcription cofactor activity Okbay et al.

Many of the identified genes that play a role in neurodevelopment might contribute to synaptic function and plasticity. Brain function relies on highly dynamic, activity-dependent processes that switch on and off genes. These can lead to profound structural and functional changes and involve formation of new and elimination of unused synapses, changes in cytoskeleton, receptor mobility and energy metabolism. Cognitive ability may depend on how efficient neurons can regulate these processes.

Interactions of cells with their direct environment is a fundamental function in both neurodevelopment and synaptic function. Many of the top protein-coding genes associated with cognitive ability are membrane-anchored proteins responsible for cell-to-cell and cell-to-matrix communication. For example, the ITIH3 gene that codes for a protein that stabilizes the extracellular matrix. Another example is LAMB2 gene that codes for laminin, an extracellular matrix glycoprotein a major constituent of basement membranes.

In addition, in an extremely high IQ cohort, the gene most significantly enriched for association is ADAM12, a membrane-anchored protein involved in cell—cell and cell—matrix interactions Zabaneh et al. Some candidate genes are involved in the regulation of different signaling pathways through surface receptors.

These signaling pathways play an essential role in embryogenesis, cell proliferation, migration, but also synaptic communication throughout development. Remarkably, recent large-scale cellular-resolution gene profiling has identified species-specific differences exactly in the same functional categories of genes involved in intercellular communication Zeng et al. These results may highlight the importance of cell-to-environment interactions not only for human intelligence but also for human evolution in general.

Some findings of GWAS of intelligence point directly at genes with known functions in synaptic communication, plasticity and neuronal excitability. Some identified genes are primarily involved in presynaptic organization and vesicle release. Furthermore, at least two other identified genes are also involved in vesicle trafficking: GBF1 mediates vesicular trafficking in Golgi apparatus and ARHGAP27 plays a role in clathrin-mediated endocytosis.

Finally, BSN gene codes for a scaffolding protein involved in organizing the presynaptic cytoskeleton. This gene encodes a CREB—a nuclear protein that modulates the transcription of genes. It is an important component of intracellular signaling events and has widespread biological functions.

However, in neurons its most documented and well-studied roles is the regulation of synaptic plasticity, learning and memory formation Silva et al. Tapping into databases of drug targets and their gene annotations can shed new light on the associations of drug gene-sets with a phenotype Gaspar and Breen, Such a drug pathway analysis combined with GWAS results of intelligence revealed that the gene targets of two drugs involved in synaptic regulation and neuron excitability were significantly enriched: a T-type calcium channel blocker and a potassium channel inhibitor Lam et al.

In a related analysis of drug classes, significant enrichment was also observed for voltage-gated calcium channel subunits Lam et al. In another study, genes involved in regulation of voltage-gated calcium channel complex were also significantly linked to educational attainment in a previous study Okbay et al. Both ion channel types play a critical role in synaptic communication and action potential firing.

T-type calcium channels are involved in action potential initiation and switching between distinct modes of firing Cain and Snutch, Potassium channels are crucial for rapid repolarization during AP generation and maintenance of a resting membrane potential Hodgkin and Huxley, Most of this energy demand goes to generation postsynaptic potentials Attwell and Laughlin, ; Magistretti and Allaman, Notably, the emergence of higher cognitive functions in humans during evolution is also associated with the increased expression of energy metabolism genes Magistretti and Allaman, Genes involved in energy supply and metabolism could thus have an impact on maintenance of high-frequency firing during cognitive tasks.

Mitochondria are central for various cellular processes that include energy metabolism, intracellular calcium signaling, and generation of reactive oxygen species. Another remarkable cluster of protein-coding genes implicated in intelligence are genes coding for microtubule-associated proteins.

Microtubules are an essential part of the cytoskeleton and are involved in maintaining cell structure throughout development. The MAPT gene coding for microtubule-associated protein was linked to intelligence by several studies Sniekers et al. Furthermore, genetic influences are attributed to miniscule effects by a large number of genes. Ninety-five percent of these genetic variants are located in intronic and intergenic regions and might have a gene regulatory function.

Only a very small proportion of associated SNPs 1. The majority of associated genes are implicated in early, most probably prenatal development, with some genes essential for synaptic function and plasticity throughout lifespan. GWAS tests possible associations between genes and phenotype. However, the availability of cell-type and tissue-specific transcriptome data from post-mortem human brains Ardlie et al.

Linking hits of GWAS data to cell-type and tissue-specific transcriptomic profiles GTEx may indicate in which brain region and even which cell types intelligence genes are potentially expressed. This approach has obvious caveats, since genes associated with intelligence do not have to be expressed at the same developmental time, and since brain loci involved in intelligence are widely distributed, not all genes need to be expressed in the same brain area or cell type.

Nevertheless, using this approach, it was found that genes associated with educational attainment and intelligence preferentially express together in nervous tissue Okbay et al. Specifically, hippocampal, midbrain and generally cortical and frontal cortical regions show the highest enrichment of expression of these genes Savage et al. With the exception of midbrain, these are brain regions previously implicated in intelligence by brain imaging studies.

Cell-type specific expression profiles of genes of intelligence highlight the role of neuronal cell types. Although glia cells are the most abundant cell type in the human brain Vasile et al. Further in-depth analysis of neuronal types revealed significant enrichment of associated genes within pyramidal neurons in hippocampal area CA1 and cortical somatosensory regions. In addition, significant associations were found in the principal cell type in striatum—the medium spiny neurons Savage et al.

Pyramidal neurons are the most abundant neuronal types in neocortex and hippocampus, structures associated with higher executive functions, decision-making, problem-solving and memory. The results of the GWAS studies put forward the hypothesis that these neuron types play a role in supporting intelligence Coleman et al.

Is there evidence that particular properties of brain cells contribute to intelligence? However, the neuroscientific search for the biological basis of intelligence has so far focused almost exclusively on the macroscopic brain level and genetics of intelligence, leaving a large gap of knowledge at cellular level. We assume that our mind functions through the activity of 86 billion neurons Herculano-Houzel, and their connections, that form principal building blocks for coding, processing, and storage of information in the brain and ultimately give rise to cognition Salinas and Sejnowski, Given the astronomic number of neuronal connections Drachman, , even the slightest change in efficiency of information processing by neurons can translate into large differences in cognitive ability.

Indeed, one of the most robust and replicable associations in behavioral psychology is that of intelligence with mental processing speed, measured by reaction times by human test subjects Vernon, ; Barrett et al. However, very few studies attempted to answer the question whether the activity and structure of single human neurons support human intelligence and how faster mental processing can be brought about by properties of cells in our brain.

This knowledge gap is not surprising: the access to neurons in the living human brain is very limited and most of what is known about the function of neurons comes from laboratory animal research.

To gain access to affected deep brain structures, neurosurgeons resect overlaying non-pathological neocortex that can be transported to the lab for further investigation. In combination with cognitive testing prior to surgery, this approach offers great opportunity to study neuronal function in relation to human intelligence.

Such use of living human brain tissue from neurosurgery cannot be substituted by other techniques: post-mortem tissue is generally not suitable for physiological studies but see Kramvis et al. Genetic studies indicate that expression of genes associated with intelligence accumulates in cortical pyramidal neurons Savage et al. Comparisons of key cellular properties of pyramidal neurons across species may offer insights into functional significance of such differences for human cognition.

In fact, human tissue used in research always comes from higher-order association areas, typically temporal cortex, in order to spare primary sensory and language functions of the patient. These are exactly the areas implicated by brain imaging in human intelligence. Which properties of pyramidal neurons from temporal cortex stand out when compared across species? Moreover, these large dendrites also receive two times more synapses than rodent pyramidal neurons DeFelipe et al.

Apart from structural differences, human pyramidal neurons display a number of unique functional properties. In addition, adult human neurons can associate synaptic events in a much wider temporal window for plasticity Testa-Silva et al.

These differences across species may suggest evolutionary pressure on both dendritic structure and neuronal function in temporal lobe and emphasize specific adaptations of human pyramidal cells in cognitive functions these brain areas perform.

Recently, these differences in human pyramidal neuron function and structure were linked to the intelligence scores and anatomical structure of temporal lobes from the same subjects Goriounova et al. The results showed that high IQ scores associated with larger temporal cortical thickness in neurosurgery patients, as in healthy subjects Choi et al.

Furthermore, thicker temporal cortex linked to larger, more complex dendrites of human pyramidal neurons. Incorporating these realistic dendritic morphologies into computational model showed that larger model neurons were able to process synaptic inputs with higher temporal precision.

Improved information transfer by model neurons was due to faster action potentials in larger cells. Finally, as predicted by the model, experimental recordings of action potential spiking in human pyramidal neurons demonstrated that individuals with higher IQ scores were able to sustain fast action potentials during neuronal activity.

These findings provide the first evidence that human intelligence is associated with larger and more complex neurons and faster action potentials and more efficient synaptic information transfer Goriounova et al. Figure 3. A cellular basis of human intelligence.

Higher IQ scores associate with larger dendrites, faster action potentials during neuronal activity and more efficient information tracking in pyramidal neurons of temporal cortex.

The figure is based on the results from Goriounova et al. Pyramidal cells, especially in superficial layers of multimodal integration areas such as temporal or frontal cortex, are main integrators and accumulators of synaptic information.

Larger dendrites can physically contain more synaptic contacts and process more information. Indeed, dendrites of human pyramidal neuron receive twice as many synapses than those in rodents DeFelipe et al. The increasing information integration capacity of these brain areas is also reflected in a gradient in complexity of pyramidal cells across cortical areas—cells have increasingly larger dendrites in regions involved in higher-order cortical processing Elston et al.

Both in humans and other primates, cortico-cortical whole-brain connectivity positively correlates with the size of pyramidal cell dendrites Scholtens et al. Overall, larger dendritic length in human neurons compared to other species, and in particular elongation of their basal dendritic terminals Deitcher et al.

Recently, Eyal et al. The results show that particularly large number of basal dendrites in human pyramidal cells and elongation of their terminals compared to other species result in electrical decoupling of the basal terminals from each other. Similar observations were also recently made by dendritic recordings from human layer 5 pyramidal neurons Beaulieu-Laroche et al. In this way, human dendrites can function as multiple, semi-independent subunits and generate more dendritic NMDA- spikes independently and simultaneously, compared to rat temporal cortex Eyal et al.

The study, 'No pattern separation in the human hippocampus', argues that the lack of pattern separation in memory coding is a key difference compared to other species, which has profound implications that could explain cognitive abilities uniquely developed in humans, such as our power of generalization and of creative thought. Quiroga believes we should go beyond behavioural comparisons between humans and animals and seek for more mechanistic insights, asking what in our brain gives rise to human's unique and vast repertoire of cognitive functions.

Quiroga argues that brain size or number of neurons cannot solely explain the difference, since there is, for example, a comparable number and type of neurons in the chimp and the human brain, and both species have more or less the same anatomical structures. Therefore, our neurons, or at least some of them, must be doing something completely different, and one such difference is given by how they store our memories.

What makes human intelligence special? Machines can handle more data at a speedier rate as compared to humans. As of now, humans cannot beat the speed of computers.

Artificial Intelligence has not aced the ability to choose up on related social and excited codes. The most obvious impact of AI is the outcome of the automation of tasks across an expansive scope of businesses, changed from manual to digital.

Tasks or jobs that incorporate a level of reiteration or the utilization and translation of tremendous measures of information are currently conveyed and handled by a computer, some of the time not requiring the intercession of people. As artificial intelligence and machine learning execute the manual assignments that people used to perform, it opens up and breeds new businesses and open doors for the labour force.

Digital engineering is an illustration of an arising calling that came about because of the quick improvement of innovation, and it is as yet developing. Thus, while old manual assignments might be out, new openings and professions will be arising. At the point when used with a reason and not for the good of technology, artificial intelligence can open huge loads of chances for organizations and improve efficiency and cooperation inside the association.

Hence in return, it can bring about an expansion sought after for items and administrations and drive a monetary development model that conveys and improves the nature of living. In the time of AI, understanding the capacity of work past only supporting a way of life is significantly more significant.

It turns into an impression of the crucial human requirement for investment, co-creation, commitment, and a feeling of being required; and accordingly, should not be ignored. So, here and there, even the customary and dull assignments at work become significant and beneficial, and if it is taken out or has been robotized, it should be supplanted with something that gives a similar occasion to human articulation and disclosure.

With robots, AI, and robotization taking a portion of the ordinary and manual tasks out of our hands, experts have more opportunity to centre in reasoning, conveying imaginative and inventive arrangements, and activities that are past the compass of AI and are soundly in the space of human intelligence. Artificial Intelligence has come a long way from being a component of science fiction to reality and there is no doubt that artificial intelligence is shaping every industry and taking the world to the next level.

But, it is still not possible to exactly mimic the level of human intelligence. It is highly uncertain that we will generate machines that can think like humans anytime soon. It would take off on its own, and re-design itself at an ever-increasing rate. Therefore, in the rising discussion about artificial intelligence vs.

Be a part of our Instagram community. Definition of Artificial Intelligence and Human Intelligence Artificial Intelligence simply means technology that can make machines think like human beings and they can work the way we humans do. Must read: Role of AI in Animation Artificial intelligence is always around us whether we realize it or not like when we use Google Maps, autocorrect, smart speakers, face recognition, and many more. Related blog: 10 powerful examples of AI Human intelligence is the thing that shapes the development and appropriation of man-made consciousness and creative arrangements related to it.

Artificial Intelligence vs Human Intelligence The idea of making a machine that can think like human beings has arrived from the fiction world to the real world. Differences between Artificial Intelligence and Human Intelligence Following are the fundamental differences between artificial intelligence and human intelligence; If we can compare it nature wise then, human intelligence intends to revise to modern environments by using a mixture of distinct cognitive procedures, whereas artificial intelligence intends to create devices that can mock human behaviour and conduct human-like actions.

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