SherbyNet - /page/wikibook/entry.mu

Micron Document

<!DOCTYPE html>

<title>On Intelligence</title>

</head>

<span id="openzim-page-title" class="mw-page-title-main"><i>On Intelligence</i></span>

</h1>

</header>

/* start https://en.wikipedia.org/ */

.mw-parser-output .ambox{border:1px solid #a2a9b1;border-left:10px solid #36c;background-color:#fbfbfb;box-sizing:border-box}.mw-parser-output .ambox+link+.ambox,.mw-parser-output .ambox+link+style+.ambox,.mw-parser-output .ambox+link+link+.ambox,.mw-parser-output .ambox+.mw-empty-elt+link+.ambox,.mw-parser-output .ambox+.mw-empty-elt+link+style+.ambox,.mw-parser-output .ambox+.mw-empty-elt+link+link+.ambox{margin-top:-1px}html body.mediawiki .mw-parser-output .ambox.mbox-small-left{margin:4px 1em 4px 0;overflow:hidden;width:238px;border-collapse:collapse;font-size:88%;line-height:1.25em}.mw-parser-output .ambox-speedy{border-left:10px solid #b32424;background-color:#fee7e6}.mw-parser-output .ambox-delete{border-left:10px solid #b32424}.mw-parser-output .ambox-content{border-left:10px solid #f28500}.mw-parser-output .ambox-style{border-left:10px solid #fc3}.mw-parser-output .ambox-move{border-left:10px solid #9932cc}.mw-parser-output .ambox-protection{border-left:10px solid #a2a9b1}.mw-parser-output .ambox .mbox-text{border:none;padding:0.25em 0.5em;width:100%}.mw-parser-output .ambox .mbox-image{border:none;padding:2px 0 2px 0.5em;text-align:center}.mw-parser-output .ambox .mbox-imageright{border:none;padding:2px 0.5em 2px 0;text-align:center}.mw-parser-output .ambox .mbox-empty-cell{border:none;padding:0;width:1px}.mw-parser-output .ambox .mbox-image-div{width:52px}@media(min-width:720px){.mw-parser-output .ambox{margin:0 10%}}@media print{body.ns-0 .mw-parser-output .ambox{display:none!important}}

/* end https://en.wikipedia.org/ */

</style><style data-mw-deduplicate="TemplateStyles:r1248332772">

/* start https://en.wikipedia.org/ */

.mw-parser-output .multiple-issues-text{width:95%;margin:0.2em 0}.mw-parser-output .multiple-issues-text>.mw-collapsible-content{margin-top:0.3em}.mw-parser-output .compact-ambox .ambox{border:none;border-collapse:collapse;background-color:transparent;margin:0 0 0 1.6em!important;padding:0!important;width:auto;display:block}body.mediawiki .mw-parser-output .compact-ambox .ambox.mbox-small-left{font-size:100%;width:auto;margin:0}.mw-parser-output .compact-ambox .ambox .mbox-text{padding:0!important;margin:0!important}.mw-parser-output .compact-ambox .ambox .mbox-text-span{display:list-item;line-height:1.5em;list-style-type:disc}body.skin-minerva .mw-parser-output .multiple-issues-text>.mw-collapsible-toggle,.mw-parser-output .compact-ambox .ambox .mbox-image,.mw-parser-output .compact-ambox .ambox .mbox-imageright,.mw-parser-output .compact-ambox .ambox .mbox-empty-cell,.mw-parser-output .compact-ambox .hide-when-compact{display:none}

/* end https://en.wikipedia.org/ */

</style>

/* start https://en.wikipedia.org/ */

.mw-parser-output .infobox-subbox{padding:0;border:none;margin:-3px;width:auto;min-width:100%;font-size:100%;clear:none;float:none;background-color:transparent}.mw-parser-output .infobox-3cols-child{margin:auto}.mw-parser-output .infobox .navbar{font-size:100%}@media screen{html.skin-theme-clientpref-night .mw-parser-output .infobox-full-data:not(.notheme)>div:not(.notheme)[style]{background:#1f1f23!important;color:#f8f9fa}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .infobox-full-data:not(.notheme)>div:not(.notheme)[style]{background:#1f1f23!important;color:#f8f9fa}}@media(min-width:640px){body.skin--responsive .mw-parser-output .infobox-table{display:table!important}body.skin--responsive .mw-parser-output .infobox-table>caption{display:table-caption!important}body.skin--responsive .mw-parser-output .infobox-table>tbody{display:table-row-group}body.skin--responsive .mw-parser-output .infobox-table th,body.skin--responsive .mw-parser-output .infobox-table td{padding-left:inherit;padding-right:inherit}}

/* end https://en.wikipedia.org/ */

</style><style data-mw-deduplicate="TemplateStyles:r1287740527">

/* start https://en.wikipedia.org/ */

.mw-parser-output .ib-book .infobox-title{font-style:italic;padding-bottom:0.2em}.mw-parser-output .ib-book .Z3988{display:none}.mw-parser-output .ib-book .infobox-below{border-top:#aaa 1px solid}

/* end https://en.wikipedia.org/ */

</style><table class="infobox ib-book vcard"><caption class="infobox-title">On Intelligence: How a New Understanding of the Brain will Lead to the Creation of Truly Intelligent Machines </caption><tbody><tr><td colspan="2" class="infobox-image"><div class="infobox-caption">Front cover</div></td></tr><tr><th scope="row" class="infobox-label">Author</th><td class="infobox-data"><a href="Jeff_Hawkins" title="Jeff Hawkins">Jeff Hawkins</a> & <a href="Sandra_Blakeslee" title="Sandra Blakeslee">Sandra Blakeslee</a></td></tr><tr><th scope="row" class="infobox-label">Language</th><td class="infobox-data">English</td></tr><tr><th scope="row" class="infobox-label">Subject</th><td class="infobox-data"><a href="Psychology" title="Psychology">Psychology</a></td></tr><tr><th scope="row" class="infobox-label">Publisher</th><td class="infobox-data"><a href="Times_Books" title="Times Books">Times Books</a></td></tr><tr><th scope="row" class="infobox-label"><div style="display: inline-block; line-height: 1.2em; padding: .1em 0;">Publication date</div></th><td class="infobox-data">2004</td></tr><tr><th scope="row" class="infobox-label">Publication place</th><td class="infobox-data">United States</td></tr><tr><th scope="row" class="infobox-label">Media type</th><td class="infobox-data"><a href="Paperback" title="Paperback">Paperback</a></td></tr><tr><th scope="row" class="infobox-label">Pages</th><td class="infobox-data">272</td></tr><tr><th scope="row" class="infobox-label"><a href="ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a></th><td class="infobox-data"><style data-mw-deduplicate="TemplateStyles:r1238218222">

/* start https://en.wikipedia.org/ */

.mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("./mw/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("./mw/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("./mw/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("./mw/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output .cs1-format{font-size:95%}html.skin-theme-clientpref-night .mw-parser-output .cs1-maint{color:#18911f}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .cs1-maint{color:#18911f}}

/* end https://en.wikipedia.org/ */

</style><bdi>0-8050-7456-2</bdi></td></tr><tr><th scope="row" class="infobox-label"><a href="OCLC_(identifier)" class="mw-redirect" title="OCLC (identifier)"><abbr title="Online Computer Library Center number">OCLC</abbr></a></th><td class="infobox-data"><a rel="nofollow" class="external text" href="https://www.worldcat.org/oclc/55510125">55510125</a></td></tr><tr><th scope="row" class="infobox-label"><div style="display: inline-block; line-height: 1.2em; padding: .1em 0;"><a href="Dewey_Decimal_Classification" title="Dewey Decimal Classification">Dewey Decimal</a></div></th><td class="infobox-data">612.8/2 22</td></tr><tr><th scope="row" class="infobox-label"><a href="LCC_(identifier)" class="mw-redirect" title="LCC (identifier)"><abbr title="Library of Congress Classification">LC Class</abbr></a></th><td class="infobox-data">QP376 .H294 2004</td></tr></tbody></table>

<p><i><b>On Intelligence: How a New Understanding of the Brain will Lead to the Creation of Truly Intelligent Machines</b></i> is a 2004 book<sup id="cite_ref-hawkins_1-0" class="reference"><a href="#cite_note-hawkins-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> by <a href="Jeff_Hawkins" title="Jeff Hawkins">Jeff Hawkins</a> and <a href="Sandra_Blakeslee" title="Sandra Blakeslee">Sandra Blakeslee</a>. The book explains Hawkins' <a href="Memory-prediction_framework" title="Memory-prediction framework">memory-prediction framework</a> theory of the <a href="Brain" title="Brain">brain</a> and describes some of its consequences.

</p>

<div class="mw-heading mw-heading2"><h2 id="The_theory">The theory</h2></div>

/* start https://en.wikipedia.org/ */

.mw-parser-output .hatnote{font-style:italic}.mw-parser-output div.hatnote{padding-left:1.6em;margin-bottom:0.5em}.mw-parser-output .hatnote i{font-style:normal}.mw-parser-output .hatnote+link+.hatnote{margin-top:-0.5em}@media print{body.ns-0 .mw-parser-output .hatnote{display:none!important}}

/* end https://en.wikipedia.org/ */

</style><div role="note" class="hatnote navigation-not-searchable">Main article: <a href="Memory-prediction_framework" title="Memory-prediction framework">Memory-prediction framework</a></div>

<p>Hawkins' basic idea is that the brain is a mechanism to predict the future, specifically, hierarchical regions of the brain predict their future input sequences. Perhaps not always far in the future, but far enough to be of real use to an organism. As such, the brain is a <a href="Feed_forward_(control)" title="Feed forward (control)">feed forward</a> <a href="Hierarchical_state_machine" class="mw-redirect" title="Hierarchical state machine">hierarchical state machine</a> with special properties that enable it to <a href="Learning" title="Learning">learn</a>.<sup id="cite_ref-hawkins_1-1" class="reference"><a href="#cite_note-hawkins-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup><sup class="reference nowrap"><span title="Page / location: 208–210, 222">: 208–210, 222 </span></sup>

</p><p>The <a href="State_machine" class="mw-redirect" title="State machine">state machine</a> actually controls the behavior of the organism. Since it is a <a href="Feed_forward_(control)" title="Feed forward (control)">feed forward</a> state machine, the machine responds to future events predicted from past data.

</p><p>The hierarchy is capable of memorizing frequently observed sequences (<a href="Cognitive_modules" class="mw-redirect" title="Cognitive modules">Cognitive modules</a>) of patterns and developing invariant representations. Higher levels of the cortical hierarchy predict the future on a longer time scale, or over a wider range of sensory input. Lower levels interpret or control limited domains of experience, or sensory or effector systems. Connections from the higher level states predispose some selected transitions in the lower-level state machines.

</p><p><a href="Hebbian_learning" class="mw-redirect" title="Hebbian learning">Hebbian learning</a> is part of the framework, in which the event of learning physically alters neurons and connections, as learning takes place.<sup id="cite_ref-hawkins_1-2" class="reference"><a href="#cite_note-hawkins-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup><sup class="reference nowrap"><span title="Page / location: 48, 164">: 48, 164 </span></sup>

</p><p><a href="Vernon_Mountcastle" class="mw-redirect" title="Vernon Mountcastle">Vernon Mountcastle</a>'s formulation of a <a href="Cortical_column" title="Cortical column">cortical column</a> is a basic element in the framework. Hawkins places particular emphasis on the role of the interconnections from peer columns, and the activation of columns as a whole. He strongly implies that a column is the cortex's physical representation of a state in a state machine.<sup id="cite_ref-hawkins_1-3" class="reference"><a href="#cite_note-hawkins-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup><sup class="reference nowrap"><span title="Page / location: 50, 51, 55">: 50, 51, 55 </span></sup>

</p><p>As an engineer, any specific failure to find a natural occurrence of some process in his framework does not signal a fault in the memory-prediction framework <i>per se</i>, but merely signals that the natural process has performed Hawkins' functional decomposition in a different, unexpected way, as Hawkins' motivation is to create intelligent <a href="Machine" title="Machine">machines</a>. For example, for the purposes of his framework, the nerve impulses can be taken to form a temporal sequence (but phase encoding could be a possible implementation of such a sequence; these details are immaterial for the framework).

</p>

<div class="mw-heading mw-heading2"><h2 id="Predictions_of_the_theory_of_the_memory-prediction_framework">Predictions of the theory of the memory-prediction framework</h2></div>

<p>His <a href="Prediction" title="Prediction">predictions</a> use the <a href="Visual_system" title="Visual system">visual system</a> as a prototype for some example predictions, such as Predictions 2, 8, 10, and 11. Other predictions cite the <a href="Auditory_system" title="Auditory system">auditory system</a> ( Predictions 1, 3, 4, and 7).

</p>

<ul><li>An Appendix of 11 Testable Predictions, beginning on page 237:</li></ul>

<div class="mw-heading mw-heading3"><h3 id="Enhanced_neural_activity_in_anticipation_of_a_sensory_event">Enhanced neural activity in anticipation of a sensory event</h3></div>

<p>1. In all areas of <a href="Cerebral_cortex" title="Cerebral cortex">cortex</a>, Hawkins (2004) predicts "we should find <i>anticipatory cells</i>", cells that fire in anticipation of a sensory <a href="Phenomenon" title="Phenomenon">event</a>.

</p>

<dl><dd>Note: As of 2005 <a href="Mirror_neuron" title="Mirror neuron">mirror neurons</a> have been observed to fire <i>before</i> an anticipated event.<sup id="cite_ref-2" class="reference"><a href="#cite_note-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup></dd></dl>

<div class="mw-heading mw-heading3"><h3 id="Spatially_specific_prediction">Spatially specific prediction</h3></div>

<p>2. In primary sensory <a href="Cerebral_cortex" title="Cerebral cortex">cortex</a>, Hawkins predicts, for example, "we should find anticipatory cells in or near <a href="Visual_cortex#Primary_visual_cortex_(V1)" title="Visual cortex">V1</a>, at a precise location in the visual field (the scene)". It has been experimentally determined, for example, after mapping the angular position of some objects in the visual field, there will be a one-to-one correspondence of cells in the scene to the angular positions of those objects. Hawkins predicts that when the features of a visual scene are known in a memory, anticipatory cells should fire <i>before</i> the actual objects are seen in the scene.

</p>

<div class="mw-heading mw-heading3"><h3 id="Prediction_should_stop_propagating_in_the_cortical_column_at_layers_2_and_3">Prediction should stop propagating in the cortical column at layers 2 and 3</h3></div>

<p>3. In layers 2 and 3, predictive activity (neural firing) should stop propagating at specific cells, corresponding to a specific prediction. Hawkins does not rule out anticipatory cells in layers 4 and 5.

</p>

<div class="mw-heading mw-heading3"><h3 id=""Name_cells"_at_layers_2_and_3_should_preferentially_connect_to_layer_6_cells_of_cortex">"Name cells" at layers 2 and 3 should preferentially connect to layer 6 cells of cortex</h3></div>

<p>4. Learned sequences of firings comprise a representation of <i>temporally constant invariants</i>. Hawkins calls the cells which fire in this sequence "name cells". Hawkins suggests that these <i>name cells</i> are in layer 2, physically adjacent to layer 1. Hawkins does not rule out the existence of layer 3 cells with dendrites in layer 1, which might perform as <i>name cells</i>.

</p>

<div class="mw-heading mw-heading3"><h3 id=""Name_cells"_should_remain_ON_during_a_learned_sequence">"Name cells" should remain ON during a learned sequence</h3></div>

<p>5. By definition, a <i>temporally constant invariant</i> will be active during a learned sequence. Hawkins posits that these cells will remain active for the duration of the learned sequence, even if the remainder of the cortical column is shifting state. Since we do not know the encoding of the sequence, we do not yet know the definition of <i>ON</i> or <i>active</i>; Hawkins suggests that the ON pattern may be as simple as a simultaneous <a href="Logical_and" class="mw-redirect" title="Logical and">AND</a> (i.e., the name cells simultaneously "light up") across an array of name cells.

</p>

<dl><dd>See <a href="Neural_ensemble" class="mw-redirect" title="Neural ensemble">Neural ensemble#Encoding</a> for <i>grandmother neurons</i> which perform this type of function.</dd></dl>

<div class="mw-heading mw-heading3"><h3 id=""Exception_cells"_should_remain_OFF_during_a_learned_sequence">"Exception cells" should remain OFF during a learned sequence</h3></div>

<p>6. Hawkins' novel prediction is that certain cells are inhibited during a learned sequence. A class of cells in layers 2 and 3 should NOT fire during a learned sequence, the axons of these "exception cells" should fire <i>only if a local prediction is failing</i>. This prevents flooding the brain with the usual sensations, leaving only exceptions for post-processing.

</p>

<div class="mw-heading mw-heading3"><h3 id=""Exception_cells"_should_propagate_unanticipated_events">"Exception cells" should propagate unanticipated events</h3></div>

<p>7. If an unusual event occurs (the learned sequence fails), the "exception cells" should fire, propagating up the cortical hierarchy to the <a href="Hippocampus" title="Hippocampus">hippocampus</a>, the repository of new memories.

</p>

<div class="mw-heading mw-heading3"><h3 id=""Aha!_cells"_should_trigger_predictive_activity">"Aha! cells" should trigger predictive activity</h3></div>

<p>8. Hawkins predicts a cascade of predictions, when recognition occurs, propagating down the cortical column (with each <a href="Saccade" title="Saccade">saccade</a> of the <a href="Human_eye" title="Human eye">eye</a> over a learned scene, for example).

</p>

<div class="mw-heading mw-heading3"><h3 id="Pyramidal_cells_should_detect_coincidences_of_synaptic_activity_on_thin_dendrites">Pyramidal cells should detect coincidences of synaptic activity on thin dendrites</h3></div>

<p>9. <a href="Pyramidal_cell" title="Pyramidal cell">Pyramidal cells</a> should be capable of detecting coincident events on thin <a href="Dendrite" title="Dendrite">dendrites</a>, even for a <a href="Neuron" title="Neuron">neuron</a> with thousands of <a href="Synapse" title="Synapse">synapses</a>. Hawkins posits a temporal window (presuming time-encoded firing) which is necessary for his <a href="Theory" title="Theory">theory</a> to remain viable.

</p>

<div class="mw-heading mw-heading3"><h3 id="Learned_representations_move_down_the_cortical_hierarchy,_with_training">Learned representations move down the cortical hierarchy, with training</h3></div>

<p>10. Hawkins posits, for example, that if the <a href="Inferotemporal_cortex" class="mw-redirect" title="Inferotemporal cortex">inferotemporal</a> (IT) level has learned a sequence, that eventually cells in <a href="Visual_area_V4" class="mw-redirect" title="Visual area V4">V4</a> will also learn the sequence.

</p>

<div class="mw-heading mw-heading3"><h3 id=""Name_cells"_exist_in_all_regions_of_cortex">"Name cells" exist in all regions of cortex</h3></div>

<p>11. Hawkins predicts that "name cells" will be found in all regions of the cortex.

</p>

<ul><li><a href="Hierarchical_temporal_memory" title="Hierarchical temporal memory">Hierarchical temporal memory</a>, a technology by Hawkins's startup Numenta Inc. to replicate the properties of the neocortex.</li>

<li><a href="Memory-prediction_framework" title="Memory-prediction framework">Memory-prediction framework</a></li></ul>

<div class="mw-heading mw-heading2"><h2 id="References">References</h2></div>

/* start https://en.wikipedia.org/ */

.mw-parser-output .reflist{margin-bottom:0.5em;list-style-type:decimal}@media screen{.mw-parser-output .reflist{font-size:90%}}.mw-parser-output .reflist .references{font-size:100%;margin-bottom:0;list-style-type:inherit}.mw-parser-output .reflist-columns-2{column-width:30em}.mw-parser-output .reflist-columns-3{column-width:25em}.mw-parser-output .reflist-columns{margin-top:0.3em}.mw-parser-output .reflist-columns ol{margin-top:0}.mw-parser-output .reflist-columns li{page-break-inside:avoid;break-inside:avoid-column}.mw-parser-output .reflist-upper-alpha{list-style-type:upper-alpha}.mw-parser-output .reflist-upper-roman{list-style-type:upper-roman}.mw-parser-output .reflist-lower-alpha{list-style-type:lower-alpha}.mw-parser-output .reflist-lower-greek{list-style-type:lower-greek}.mw-parser-output .reflist-lower-roman{list-style-type:lower-roman}

/* end https://en.wikipedia.org/ */

</style><div class="reflist">

<li id="cite_note-hawkins-1"><span class="mw-cite-backlink">^ <a href="#cite_ref-hawkins_1-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-hawkins_1-1"><sup><i><b>b</b></i></sup></a> <a href="#cite_ref-hawkins_1-2"><sup><i><b>c</b></i></sup></a> <a href="#cite_ref-hawkins_1-3"><sup><i><b>d</b></i></sup></a></span> <span class="reference-text"><cite id="CITEREFHawkins2004" class="citation book cs1">Hawkins, Jeff (2004). <span class="id-lock-registration" title="Free registration required"><a rel="nofollow" class="external text" href="https://archive.org/details/onintelligence0000hawk/page/272"><i>On Intelligence</i></a></span> (1st ed.). Times Books. pp. <a rel="nofollow" class="external text" href="https://archive.org/details/onintelligence0000hawk/page/272">272</a>. <a href="ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <bdi>978-0805074567</bdi>.</cite></span>

</li>

<cite id="CITEREFFogassiFerrariGesierichRozzi2005" class="citation journal cs1">Fogassi, Leonardo; Ferrari, Pier Francesco; Gesierich, Benno; Rozzi, Stefano; Chersi, Fabian; Rizzolatti, Giacomo (April 29, 2005). <a rel="nofollow" class="external text" href="https://web.archive.org/web/20170809160457/http://old.unipr.it/arpa///mirror/pubs/pdffiles/Fogassi-Ferrari2005.pdf">"Parietal lobe: from action organization to intention understanding"</a> <span class="cs1-format">(PDF)</span>. <i>Science</i>. <b>308</b> (5722): <span class="nowrap">662–</span>667. <a href="Bibcode_(identifier)" class="mw-redirect" title="Bibcode (identifier)">Bibcode</a>:<a rel="nofollow" class="external text" href="https://ui.adsabs.harvard.edu/abs/2005Sci...308..662F">2005Sci...308..662F</a>. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1126%2Fscience.1106138">10.1126/science.1106138</a>. <a href="PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/15860620">15860620</a>. <a href="S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:5720234">5720234</a>. Archived from <a rel="nofollow" class="external text" href="http://www.unipr.it/arpa/mirror/pubs/pdffiles/Fogassi-Ferrari2005.pdf">the original</a> <span class="cs1-format">(PDF)</span> on 2017-08-09<span class="reference-accessdate">. Retrieved <span class="nowrap">2006-11-18</span></span>.</cite></span>

</li>

</ol></div></div>

<div class="mw-heading mw-heading2"><h2 id="External_links">External links</h2></div>

<ul><li><span class="official-website"><span class="url"><a rel="nofollow" class="external text" href="http://www.onintelligence.com">Official website</a></span></span></li>

<li><cite id="CITEREFGeorgeHawkins2005" class="citation journal cs1">George, Dileep; Hawkins, Jeff (2005). "A Hierarchical Bayesian Model of Invariant Pattern Recognition in the Visual Cortex": <span class="nowrap">1812–</span>1817. <a href="CiteSeerX_(identifier)" class="mw-redirect" title="CiteSeerX (identifier)">CiteSeerX</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.132.6744">10.1.1.132.6744</a></span>.</cite> <span class="cs1-visible-error citation-comment"><code class="cs1-code">{{cite journal}}</code>: </span><span class="cs1-visible-error citation-comment">Cite journal requires <code class="cs1-code">|journal=</code> (help)</span></li>

<li><a rel="nofollow" class="external text" href="https://web.archive.org/web/20061013134333/http://www.phillylac.org/prediction/">Saulius Garalevicius' research page</a> - Research papers and programs presenting experimental results with Bayesian models of the Memory-Prediction Framework</li>

<li><a rel="nofollow" class="external text" href="https://sourceforge.net/projects/neocortex/">Project Neocortex</a> - An open source project for modeling Memory-Prediction Framework</li></ul>

<div class="mw-heading mw-heading3"><h3 id="Reviews">Reviews</h3></div>

<ul><li><cite id="CITEREFColwell2005" class="citation journal cs1">Colwell, Bob (January 2005). <a rel="nofollow" class="external text" href="https://web.archive.org/web/20050204164903/http://www.computer.org/computer/homepage/0105/random/index.htm">"Machine Intelligence Meets Neuroscience"</a>. <i>Computer</i>. <b>38</b> (1). <a href="IEEE" class="mw-redirect" title="IEEE">IEEE</a>: <span class="nowrap">12–</span>15. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1109%2FMC.2005.24">10.1109/MC.2005.24</a>. Archived from <span class="id-lock-subscription" title="Paid subscription required"><a rel="nofollow" class="external text" href="http://www.computer.org/computer/homepage/0105/random/index.htm">the original</a></span> on 2005-02-04.</cite>

<ul><li><cite id="CITEREFColwell2005" class="citation journal cs1">Colwell, B. (2005). "Machine Intelligence Meets Neuroscience". <i>Computer</i>. <b>38</b>: <span class="nowrap">12–</span>15. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1109%2FMC.2005.24">10.1109/MC.2005.24</a>.</cite></li></ul></li>

<li><cite id="CITEREFDill2004" class="citation web cs1">Dill, Franz (October 30, 2004). <a rel="nofollow" class="external text" href="https://web.archive.org/web/20120205200130/https://future.iftf.org/2004/10/jeff_hawkins_on.html">"Jeff Hawkins: On Intelligence"</a>. Archived from <a rel="nofollow" class="external text" href="http://future.iftf.org/2004/10/jeff_hawkins_on.html">the original</a> on 2012-02-05.</cite></li>

<li><cite id="CITEREFKling2004" class="citation web cs1">Kling, Arnold (22 November 2004). <a rel="nofollow" class="external text" href="https://web.archive.org/web/20120305062713/http://www.techcentralstation.com/article.aspx?id=112204B">"On Intelligence, People and Computers"</a>. <i>Tech Central Station</i>. Archived from <a rel="nofollow" class="external text" href="http://www.techcentralstation.com/article.aspx?id=112204B">the original</a> on 2012-03-05.</cite></li>

<li><a rel="nofollow" class="external text" href="http://www.goertzel.org/dynapsyc/2004/OnBiologicalAndDigitalIntelligence.htm">On Biological and Digital Intelligence</a> A review by <a href="Ben_Goertzel" title="Ben Goertzel">Ben Goertzel</a> (7 Oct 2004)</li></ul></div><div><div class="zim-footer">

This article is issued from <a class="external text" title="Last edited on 2025-05-26" href="https://en.wikipedia.org/wiki/?title=On_Intelligence&oldid=1292289056">Wikipedia</a>. The text is available under <a class="external text" href="https://creativecommons.org/licenses/by-sa/4.0/deed.en">Creative Commons Attribution-Share Alike 4.0</a> unless otherwise noted. Additional terms may apply for the media files.

</div>

</div></div>

</div>

</main>

</div>

</body></html>