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class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Hashing"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.1</span> <span>Hashing</span> </div> </a> <ul id="toc-Hashing-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-LLVM_standard_sorting_library" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#LLVM_standard_sorting_library"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.2</span> <span>LLVM standard sorting library</span> </div> </a> <ul id="toc-LLVM_standard_sorting_library-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Improved_deserialization_in_protobuf" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Improved_deserialization_in_protobuf"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.3</span> <span>Improved deserialization in protobuf</span> </div> </a> <ul id="toc-Improved_deserialization_in_protobuf-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Comparison_with_logical_AI_approach" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Comparison_with_logical_AI_approach"> <div class="vector-toc-text"> <span class="vector-toc-numb">4.4</span> <span>Comparison with logical AI approach</span> </div> </a> <ul id="toc-Comparison_with_logical_AI_approach-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-References" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#References"> <div class="vector-toc-text"> <span class="vector-toc-numb">5</span> <span>References</span> </div> </a> <ul id="toc-References-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-External_links" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#External_links"> <div class="vector-toc-text"> <span class="vector-toc-numb">6</span> 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<div class="vector-body-before-content"> <div class="mw-indicators"> </div> <div id="siteSub" class="noprint">From Wikipedia, the free encyclopedia</div> </div> <div id="contentSub"><div id="mw-content-subtitle"></div></div> <div id="mw-content-text" class="mw-body-content"><div class="mw-content-ltr mw-parser-output" lang="en" dir="ltr"><div class="shortdescription nomobile noexcerpt noprint searchaux" style="display:none">AI model that developer a super-human sorting algorithm</div> <style data-mw-deduplicate="TemplateStyles:r1257001546">.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 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.sidebar-title-with-pretitle a{color:var(--color-progressive)!important}}@media print{body.ns-0 .mw-parser-output .sidebar{display:none!important}}</style><table class="sidebar sidebar-collapse nomobile nowraplinks hlist"><tbody><tr><td class="sidebar-pretitle">Part of a series on</td></tr><tr><th class="sidebar-title-with-pretitle"><a href="/wiki/Artificial_intelligence" title="Artificial intelligence">Artificial intelligence (AI)</a></th></tr><tr><td class="sidebar-image"><figure class="mw-halign-center" typeof="mw:File"><a href="/wiki/File:Dall-e_3_(jan_%2724)_artificial_intelligence_icon.png" class="mw-file-description"><img src="//upload.wikimedia.org/wikipedia/commons/thumb/6/64/Dall-e_3_%28jan_%2724%29_artificial_intelligence_icon.png/100px-Dall-e_3_%28jan_%2724%29_artificial_intelligence_icon.png" decoding="async" width="100" height="100" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/6/64/Dall-e_3_%28jan_%2724%29_artificial_intelligence_icon.png/150px-Dall-e_3_%28jan_%2724%29_artificial_intelligence_icon.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/6/64/Dall-e_3_%28jan_%2724%29_artificial_intelligence_icon.png/200px-Dall-e_3_%28jan_%2724%29_artificial_intelligence_icon.png 2x" data-file-width="820" data-file-height="820" /></a><figcaption></figcaption></figure></td></tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed"><div class="sidebar-list-title" style="text-align:center;color: var(--color-base)"><a href="/wiki/Artificial_intelligence#Goals" title="Artificial intelligence">Major goals</a></div><div class="sidebar-list-content mw-collapsible-content"> <ul><li><a href="/wiki/Artificial_general_intelligence" title="Artificial general intelligence">Artificial general intelligence</a></li> <li><a href="/wiki/Intelligent_agent" title="Intelligent agent">Intelligent agent</a></li> <li><a href="/wiki/Recursive_self-improvement" title="Recursive self-improvement">Recursive self-improvement</a></li> <li><a href="/wiki/Automated_planning_and_scheduling" title="Automated planning and scheduling">Planning</a></li> <li><a href="/wiki/Computer_vision" title="Computer vision">Computer vision</a></li> <li><a href="/wiki/General_game_playing" title="General game playing">General game playing</a></li> <li><a href="/wiki/Knowledge_representation_and_reasoning" title="Knowledge representation and reasoning">Knowledge reasoning</a></li> <li><a href="/wiki/Natural_language_processing" title="Natural language processing">Natural language processing</a></li> <li><a href="/wiki/Robotics" title="Robotics">Robotics</a></li> <li><a href="/wiki/AI_safety" title="AI safety">AI safety</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed"><div class="sidebar-list-title" style="text-align:center;color: var(--color-base)">Approaches</div><div class="sidebar-list-content mw-collapsible-content"> <ul><li><a href="/wiki/Machine_learning" title="Machine learning">Machine learning</a></li> <li><a href="/wiki/Symbolic_artificial_intelligence" title="Symbolic artificial intelligence">Symbolic</a></li> <li><a href="/wiki/Deep_learning" title="Deep learning">Deep learning</a></li> <li><a href="/wiki/Bayesian_network" title="Bayesian network">Bayesian networks</a></li> <li><a href="/wiki/Evolutionary_algorithm" title="Evolutionary algorithm">Evolutionary algorithms</a></li> <li><a href="/wiki/Hybrid_intelligent_system" title="Hybrid intelligent system">Hybrid intelligent systems</a></li> <li><a href="/wiki/Artificial_intelligence_systems_integration" title="Artificial intelligence systems integration">Systems integration</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed"><div class="sidebar-list-title" style="text-align:center;color: var(--color-base)"><a href="/wiki/Applications_of_artificial_intelligence" title="Applications of artificial intelligence">Applications</a></div><div class="sidebar-list-content mw-collapsible-content"> <ul><li><a href="/wiki/Machine_learning_in_bioinformatics" title="Machine learning in bioinformatics">Bioinformatics</a></li> <li><a href="/wiki/Deepfake" title="Deepfake">Deepfake</a></li> <li><a href="/wiki/Machine_learning_in_earth_sciences" title="Machine learning in earth sciences">Earth sciences</a></li> <li><a href="/wiki/Applications_of_artificial_intelligence#Finance" title="Applications of artificial intelligence"> Finance </a></li> <li><a href="/wiki/Generative_artificial_intelligence" title="Generative artificial intelligence">Generative AI</a> <ul><li><a href="/wiki/Artificial_intelligence_art" title="Artificial intelligence art">Art</a></li> <li><a href="/wiki/Generative_audio" title="Generative audio">Audio</a></li> <li><a href="/wiki/Music_and_artificial_intelligence" title="Music and artificial intelligence">Music</a></li></ul></li> <li><a href="/wiki/Artificial_intelligence_in_government" title="Artificial intelligence in government">Government</a></li> <li><a href="/wiki/Artificial_intelligence_in_healthcare" title="Artificial intelligence in healthcare">Healthcare</a> <ul><li><a href="/wiki/Artificial_intelligence_in_mental_health" title="Artificial intelligence in mental health">Mental health</a></li></ul></li> <li><a href="/wiki/Artificial_intelligence_in_industry" title="Artificial intelligence in industry">Industry</a></li> <li><a href="/wiki/Machine_translation" title="Machine translation">Translation</a></li> <li><a href="/wiki/Artificial_intelligence_arms_race" title="Artificial intelligence arms race"> Military </a></li> <li><a href="/wiki/Machine_learning_in_physics" title="Machine learning in physics">Physics</a></li> <li><a href="/wiki/List_of_artificial_intelligence_projects" title="List of artificial intelligence projects">Projects</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed"><div class="sidebar-list-title" style="text-align:center;color: var(--color-base)"><a href="/wiki/Philosophy_of_artificial_intelligence" title="Philosophy of artificial intelligence">Philosophy</a></div><div class="sidebar-list-content mw-collapsible-content"> <ul><li><a href="/wiki/Artificial_consciousness" title="Artificial consciousness">Artificial consciousness</a></li> <li><a href="/wiki/Chinese_room" title="Chinese room">Chinese room</a></li> <li><a href="/wiki/Friendly_artificial_intelligence" title="Friendly artificial intelligence">Friendly AI</a></li> <li><a href="/wiki/AI_control_problem" class="mw-redirect" title="AI control problem">Control problem</a>/<a href="/wiki/AI_takeover" title="AI takeover">Takeover</a></li> <li><a href="/wiki/Ethics_of_artificial_intelligence" title="Ethics of artificial intelligence">Ethics</a></li> <li><a href="/wiki/Existential_risk_from_artificial_general_intelligence" class="mw-redirect" title="Existential risk from artificial general intelligence">Existential risk</a></li> <li><a href="/wiki/Turing_test" title="Turing test">Turing test</a></li> <li><a href="/wiki/Uncanny_valley" title="Uncanny valley">Uncanny valley</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed"><div class="sidebar-list-title" style="text-align:center;color: var(--color-base)"><a href="/wiki/History_of_artificial_intelligence" title="History of artificial intelligence">History</a></div><div class="sidebar-list-content mw-collapsible-content"> <ul><li><a href="/wiki/Timeline_of_artificial_intelligence" title="Timeline of artificial intelligence">Timeline</a></li> <li><a href="/wiki/Progress_in_artificial_intelligence" title="Progress in artificial intelligence">Progress</a></li> <li><a href="/wiki/AI_winter" title="AI winter">AI winter</a></li> <li><a href="/wiki/AI_boom" title="AI boom">AI boom</a></li></ul></div></div></td> </tr><tr><td class="sidebar-content"> <div class="sidebar-list mw-collapsible mw-collapsed"><div class="sidebar-list-title" style="text-align:center;color: var(--color-base)">Glossary</div><div class="sidebar-list-content mw-collapsible-content"> <ul><li><a href="/wiki/Glossary_of_artificial_intelligence" title="Glossary of artificial intelligence">Glossary</a></li></ul></div></div></td> </tr><tr><td class="sidebar-navbar"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1129693374" /><style data-mw-deduplicate="TemplateStyles:r1239400231">.mw-parser-output .navbar{display:inline;font-size:88%;font-weight:normal}.mw-parser-output .navbar-collapse{float:left;text-align:left}.mw-parser-output .navbar-boxtext{word-spacing:0}.mw-parser-output .navbar ul{display:inline-block;white-space:nowrap;line-height:inherit}.mw-parser-output .navbar-brackets::before{margin-right:-0.125em;content:"[ "}.mw-parser-output .navbar-brackets::after{margin-left:-0.125em;content:" ]"}.mw-parser-output .navbar li{word-spacing:-0.125em}.mw-parser-output .navbar a>span,.mw-parser-output .navbar a>abbr{text-decoration:inherit}.mw-parser-output .navbar-mini abbr{font-variant:small-caps;border-bottom:none;text-decoration:none;cursor:inherit}.mw-parser-output .navbar-ct-full{font-size:114%;margin:0 7em}.mw-parser-output .navbar-ct-mini{font-size:114%;margin:0 4em}html.skin-theme-clientpref-night .mw-parser-output .navbar li a abbr{color:var(--color-base)!important}@media(prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .navbar li a abbr{color:var(--color-base)!important}}@media print{.mw-parser-output .navbar{display:none!important}}</style><div class="navbar plainlinks hlist navbar-mini"><ul><li class="nv-view"><a href="/wiki/Template:Artificial_intelligence" title="Template:Artificial intelligence"><abbr title="View this template">v</abbr></a></li><li class="nv-talk"><a href="/wiki/Template_talk:Artificial_intelligence" title="Template talk:Artificial intelligence"><abbr title="Discuss this template">t</abbr></a></li><li class="nv-edit"><a href="/wiki/Special:EditPage/Template:Artificial_intelligence" title="Special:EditPage/Template:Artificial intelligence"><abbr title="Edit this template">e</abbr></a></li></ul></div></td></tr></tbody></table> <p><b>AlphaDev</b> is an <a href="/wiki/Artificial_intelligence" title="Artificial intelligence">artificial intelligence</a> system developed by <a href="/wiki/Google_DeepMind" title="Google DeepMind">Google DeepMind</a> to discover enhanced computer science algorithms using <a href="/wiki/Reinforcement_learning" title="Reinforcement learning">reinforcement learning</a>. AlphaDev is based on <a href="/wiki/AlphaZero" title="AlphaZero">AlphaZero</a>, a system that mastered the games of <a href="/wiki/Chess" title="Chess">chess</a>, <a href="/wiki/Shogi" title="Shogi">shogi</a> and <a href="/wiki/Go_(game)" title="Go (game)">go</a> by self-play. AlphaDev applies the same approach to finding faster algorithms for fundamental tasks such as <a href="/wiki/Sorting" title="Sorting">sorting</a> and <a href="/wiki/Hash_function" title="Hash function">hashing</a>.<sup id="cite_ref-nature_1-0" class="reference"><a href="#cite_note-nature-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-deepmind_2-0" class="reference"><a href="#cite_note-deepmind-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-understanding_3-0" class="reference"><a href="#cite_note-understanding-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> </p> <meta property="mw:PageProp/toc" /> <div class="mw-heading mw-heading2"><h2 id="Development">Development</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=1" title="Edit section: Development"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>On June 7, 2023, Google DeepMind published a paper in <a href="/wiki/Nature_(journal)" title="Nature (journal)">Nature</a> introducing AlphaDev, which discovered new algorithms that outperformed the state-of-the-art methods for small sort algorithms.<sup id="cite_ref-nature_1-1" class="reference"><a href="#cite_note-nature-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> For example, AlphaDev found a faster <a href="/wiki/Assembly_language" title="Assembly language">assembly language</a> sequence for sorting 5-element sequences.<sup id="cite_ref-4" class="reference"><a href="#cite_note-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> Upon analysing the algorithms in-depth, AlphaDev discovered two unique sequences of assembly instructions called the AlphaDev swap and copy moves that avoid a single assembly instruction each time they are applied.<sup id="cite_ref-nature_1-2" class="reference"><a href="#cite_note-nature-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-understanding_3-1" class="reference"><a href="#cite_note-understanding-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> For variable sort algorithms, AlphaDev discovered fundamentally different algorithm structures. For example, for VarSort4 (sort up to 4 elements) AlphaDev discovered an algorithm 29 assembly instructions shorter than the human benchmark.<sup id="cite_ref-nature_1-3" class="reference"><a href="#cite_note-nature-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> AlphaDev also improved on the speed of <a href="/wiki/Hashing_algorithm" class="mw-redirect" title="Hashing algorithm">hashing algorithms</a> by up to 30% in certain cases.<sup id="cite_ref-deepmind_2-1" class="reference"><a href="#cite_note-deepmind-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> </p><p>In January 2022, Google DeepMind submitted its new sorting algorithms to the organization that manages <a href="/wiki/C%2B%2B" title="C++">C++</a>, one of the most popular programming languages in the world, and after independent vetting, AlphaDev's algorithms were added to the library.<sup id="cite_ref-mit_5-0" class="reference"><a href="#cite_note-mit-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> This was the first change to the <a href="/wiki/C%2B%2B_Standard_Library" title="C++ Standard Library">C++ Standard Library</a> <a href="/wiki/Sorting_algorithm" title="Sorting algorithm">sorting algorithms</a> in more than a decade and the first update to involve an algorithm discovered using AI.<sup id="cite_ref-mit_5-1" class="reference"><a href="#cite_note-mit-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> In January 2023, DeepMind also added its hashing algorithm for inputs from 9 to 16 bytes to Abseil, an open-source collection of prewritten C++ algorithms that can be used by anyone coding with C++.<sup id="cite_ref-:0_6-0" class="reference"><a href="#cite_note-:0-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-mit_5-2" class="reference"><a href="#cite_note-mit-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> Google estimates that these two algorithms are used trillions of times every day.<sup id="cite_ref-7" class="reference"><a href="#cite_note-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Design">Design</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=2" title="Edit section: Design"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>AlphaDev is built on top of AlphaZero, the reinforcement-learning model that DeepMind trained to master games such as Go and chess.<sup id="cite_ref-mit_5-3" class="reference"><a href="#cite_note-mit-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> The company's breakthrough was to treat the problem of finding a faster algorithm as a game and then train its AI to win it.<sup id="cite_ref-deepmind_2-2" class="reference"><a href="#cite_note-deepmind-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> AlphaDev plays a single-player game where the objective is to iteratively build an algorithm in the assembly language that is both fast and correct.<sup id="cite_ref-nature_1-4" class="reference"><a href="#cite_note-nature-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> AlphaDev uses a neural network to guide its search for optimal moves, and learns from its own experience and synthetic demonstrations.<sup id="cite_ref-nature_1-5" class="reference"><a href="#cite_note-nature-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> </p><p>AlphaDev showcases the potential of AI to advance the foundations of computing and optimize code for different criteria. Google DeepMind hopes that AlphaDev will inspire further research on using AI to discover new algorithms and improve existing ones.<sup id="cite_ref-deepmind_2-3" class="reference"><a href="#cite_note-deepmind-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Algorithm">Algorithm</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=3" title="Edit section: Algorithm"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The primary learning algorithm in AlphaDev is an extension of <a href="/wiki/AlphaZero" title="AlphaZero">AlphaZero</a>. </p> <div class="mw-heading mw-heading3"><h3 id="Encoding_assembly_programming_into_a_game">Encoding assembly programming into a game</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=4" title="Edit section: Encoding assembly programming into a game"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>In order to use AlphaZero on assembly programming, the authors created a <a href="/wiki/Transformer_(machine_learning_model)" class="mw-redirect" title="Transformer (machine learning model)">Transformer</a>-based vector representation of <a href="/wiki/Assembly_language" title="Assembly language">assembly programs</a> designed to capture their underlying structure.<sup id="cite_ref-nature_1-6" class="reference"><a href="#cite_note-nature-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> This finite representation allows a neural network to play assembly programming like a game with finitely many possible moves (like Go), </p><p>The representation uses the following components: </p> <ul><li>A Transformer network, to encode assembly <a href="/wiki/Opcode" title="Opcode">opcodes</a> are converted to one-hot encodings and concatenated to form the raw input sequence.</li> <li>A <a href="/wiki/Multilayer_perceptron" title="Multilayer perceptron">multilayer perceptron</a> network, which encodes the "CPU state", that is, the states of each register and memory location for a given set of inputs,</li></ul> <div class="mw-heading mw-heading3"><h3 id="Playing_the_game">Playing the game</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=5" title="Edit section: Playing the game"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The game <i>state</i> is the assembly program generated up to a given point. </p><p>The game <i>move</i> is an extra instruction appended to the current assembly program. </p><p>The game's <i>reward</i> is a function of the assembly program's correctness and latency. To reduce cost, AlphaDev only computes actual measured latency on less than 0.002% of generated programs, as it does not evaluate latency during the search process. Instead, it uses two functions that <i>estimate</i> the correctness and latency by being trained via supervised learning using the real measured correctness and latency values. </p> <div class="mw-heading mw-heading2"><h2 id="Result">Result</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=6" title="Edit section: Result"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <div class="mw-heading mw-heading3"><h3 id="Hashing">Hashing</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=7" title="Edit section: Hashing"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>AlphaDev developed hashing algorithms for inputs from 9 to 16 bytes to Abseil, an open-source collection of prewritten C++ algorithms.<sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="LLVM_standard_sorting_library">LLVM standard sorting library</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=8" title="Edit section: LLVM standard sorting library"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>AlphaDev discovered new sorting algorithms, which led to up to 70% improvements in the LLVM libc++ sorting library for shorter sequences and about 1.7% improvements for sequences exceeding 250,000 elements. These improvements apply to the uint32, uint64 and float data types for ARMv8, Intel Skylake and AMD Zen 2 CPU architectures. AlphaDev's branchless conditional assembly and new swap move contributed to these performance improvements. The discovered algorithms were reverse-engineered from low-level assembly to C++, and have officially been included in the libc++ standard sorting library.<sup id="cite_ref-:0_6-1" class="reference"><a href="#cite_note-:0-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Improved_deserialization_in_protobuf">Improved deserialization in protobuf</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=9" title="Edit section: Improved deserialization in protobuf"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>AlphaDev learned an optimized VarInt deserialization function in <a href="/wiki/Protocol_Buffers" title="Protocol Buffers">protobuf</a>,<sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup> outperforming the human benchmark for single valued inputs by approximately three times in terms of speed. AlphaDev also discovered a new VarInt assignment move, combining two operations into a single instruction for latency savings. </p> <div class="mw-heading mw-heading3"><h3 id="Comparison_with_logical_AI_approach">Comparison with logical AI approach</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=10" title="Edit section: Comparison with logical AI approach"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The AlphaDev's performance was compared to stochastic superoptimization,<sup id="cite_ref-10" class="reference"><a href="#cite_note-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> a logical AI approach. The latter was run with at least the same amount of resources and wall-clock time as AlphaDev. The results showed that AlphaDev-S requires a prohibitive amount of time to optimize directly for latency, as latency needs to be computed after every mutation. As such, AlphaDev-S optimizes for a latency proxy, specifically algorithm length, and, then, at the end of training, all correct programs generated by AlphaDev-S are searched through. </p> <div class="mw-heading mw-heading2"><h2 id="References">References</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=11" title="Edit section: References"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1239543626">.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}</style><div class="reflist"> <div class="mw-references-wrap"><ol class="references"> <li id="cite_note-nature-1"><span class="mw-cite-backlink">^ <a href="#cite_ref-nature_1-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-nature_1-1"><sup><i><b>b</b></i></sup></a> <a href="#cite_ref-nature_1-2"><sup><i><b>c</b></i></sup></a> <a href="#cite_ref-nature_1-3"><sup><i><b>d</b></i></sup></a> <a href="#cite_ref-nature_1-4"><sup><i><b>e</b></i></sup></a> <a href="#cite_ref-nature_1-5"><sup><i><b>f</b></i></sup></a> <a href="#cite_ref-nature_1-6"><sup><i><b>g</b></i></sup></a></span> <span class="reference-text"><style data-mw-deduplicate="TemplateStyles:r1238218222">.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("//upload.wikimedia.org/wikipedia/commons/6/65/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("//upload.wikimedia.org/wikipedia/commons/d/d6/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/a/aa/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("//upload.wikimedia.org/wikipedia/commons/4/4c/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}}</style><cite id="CITEREFMankowitzMichiZhernovGelmi2023" class="citation journal cs1">Mankowitz, Daniel J.; 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title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=ACM+SIGARCH+Computer+Architecture+News&rft.atitle=Stochastic+superoptimization&rft.volume=41&rft.issue=1&rft.pages=%3Cspan+class%3D%22nowrap%22%3E305-%3C%2Fspan%3E316&rft.date=2013-03-16&rft_id=info%3Aarxiv%2F1211.0557&rft.issn=0163-5964&rft_id=info%3Adoi%2F10.1145%2F2490301.2451150&rft.aulast=Schkufza&rft.aufirst=Eric&rft.au=Sharma%2C+Rahul&rft.au=Aiken%2C+Alex&rft_id=https%3A%2F%2Fdoi.org%2F10.1145%252F2490301.2451150&rfr_id=info%3Asid%2Fen.wikipedia.org%3AAlphaDev" class="Z3988"></span></span> </li> </ol></div></div> <div class="mw-heading mw-heading2"><h2 id="External_links">External links</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=AlphaDev&action=edit&section=12" title="Edit section: External links"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a rel="nofollow" class="external text" href="https://codeconfessions.substack.com/p/exploring-deepminds-alphadev-breakthrough">Understanding DeepMind's AlphaDev Breakthrough in Optimizing Sorting Algorithms</a></li> <li><a rel="nofollow" class="external text" href="https://justine.lol/sorting/">Understanding DeepMind's Sorting Algorithm</a></li></ul> <div class="navbox-styles"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1129693374" /><style data-mw-deduplicate="TemplateStyles:r1236075235">.mw-parser-output .navbox{box-sizing:border-box;border:1px solid #a2a9b1;width:100%;clear:both;font-size:88%;text-align:center;padding:1px;margin:1em auto 0}.mw-parser-output .navbox .navbox{margin-top:0}.mw-parser-output .navbox+.navbox,.mw-parser-output .navbox+.navbox-styles+.navbox{margin-top:-1px}.mw-parser-output .navbox-inner,.mw-parser-output .navbox-subgroup{width:100%}.mw-parser-output .navbox-group,.mw-parser-output .navbox-title,.mw-parser-output .navbox-abovebelow{padding:0.25em 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rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1239400231" /><div class="navbar plainlinks hlist navbar-mini"><ul><li class="nv-view"><a href="/wiki/Template:Google_AI" title="Template:Google AI"><abbr title="View this template">v</abbr></a></li><li class="nv-talk"><a href="/wiki/Template_talk:Google_AI" title="Template talk:Google AI"><abbr title="Discuss this template">t</abbr></a></li><li class="nv-edit"><a href="/wiki/Special:EditPage/Template:Google_AI" title="Special:EditPage/Template:Google AI"><abbr title="Edit this template">e</abbr></a></li></ul></div><div id="Google_AI352" style="font-size:114%;margin:0 4em"><a href="/wiki/Google_AI" title="Google AI">Google AI</a></div></th></tr><tr><td class="navbox-abovebelow" colspan="2"><div> <ul><li><a href="/wiki/Google" title="Google">Google</a></li> <li><a href="/wiki/Google_Brain" title="Google Brain">Google Brain</a></li> <li><a href="/wiki/Google_DeepMind" title="Google DeepMind">Google DeepMind</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Computer programs</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%">AlphaGo</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%">Versions</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/AlphaGo" title="AlphaGo">AlphaGo</a> (2015)</li> <li><a href="/wiki/Master_(software)" title="Master (software)">Master</a> (2016)</li> <li><a href="/wiki/AlphaGo_Zero" title="AlphaGo Zero">AlphaGo Zero</a> (2017)</li> <li><a href="/wiki/AlphaZero" title="AlphaZero">AlphaZero</a> (2017)</li> <li><a href="/wiki/MuZero" title="MuZero">MuZero</a> (2019)</li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Competitions</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/AlphaGo_versus_Fan_Hui" title="AlphaGo versus Fan Hui">Fan Hui</a> (2015)</li> <li><a href="/wiki/AlphaGo_versus_Lee_Sedol" title="AlphaGo versus Lee Sedol">Lee Sedol</a> (2016)</li> <li><a href="/wiki/AlphaGo_versus_Ke_Jie" title="AlphaGo versus Ke Jie">Ke Jie</a> (2017)</li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">In popular culture</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><i><a href="/wiki/AlphaGo_(film)" title="AlphaGo (film)">AlphaGo</a></i> (2017)</li> <li><i><a href="/wiki/The_MANIAC" title="The MANIAC">The MANIAC</a></i> (2023)</li></ul> </div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Other</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/AlphaFold" title="AlphaFold">AlphaFold</a> (2018)</li> <li><a href="/wiki/AlphaStar_(software)" title="AlphaStar (software)">AlphaStar</a> (2019)</li> <li><a class="mw-selflink selflink">AlphaDev</a> (2023)</li> <li><a href="/wiki/AlphaGeometry" title="AlphaGeometry">AlphaGeometry</a> (2024)</li></ul> </div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Machine learning</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%">Neural networks</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Inception_(deep_learning_architecture)" title="Inception (deep learning architecture)">Inception</a> (2014)</li> <li><a href="/wiki/WaveNet" title="WaveNet">WaveNet</a> (2016)</li> <li><a href="/wiki/MobileNet" title="MobileNet">MobileNet</a> (2017)</li> <li><a href="/wiki/Transformer_(deep_learning_architecture)" title="Transformer (deep learning architecture)">Transformer</a> (2017)</li> <li><a href="/wiki/EfficientNet" title="EfficientNet">EfficientNet</a> (2019)</li> <li><a href="/wiki/Gato_(DeepMind)" title="Gato (DeepMind)">Gato</a> (2022)</li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Other</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Quantum_Artificial_Intelligence_Lab" title="Quantum Artificial Intelligence Lab">Quantum Artificial Intelligence Lab</a></li> <li><a href="/wiki/TensorFlow" title="TensorFlow">TensorFlow</a></li> <li><a href="/wiki/Tensor_Processing_Unit" title="Tensor Processing Unit">Tensor Processing Unit</a></li></ul> </div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Generative AI</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%">Chatbots</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Google_Assistant" title="Google Assistant">Assistant</a> (2016)</li> <li><a href="/wiki/Sparrow_(chatbot)" title="Sparrow (chatbot)">Sparrow</a> (2022)</li> <li><a href="/wiki/Gemini_(chatbot)" title="Gemini (chatbot)">Gemini</a> (2023)</li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Language models</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/BERT_(language_model)" title="BERT (language model)">BERT</a> (2018)</li> <li><a href="/wiki/XLNet" title="XLNet">XLNet</a> (2019)</li> <li><a href="/wiki/T5_(language_model)" title="T5 (language model)">T5</a> (2019)</li> <li><a href="/wiki/LaMDA" title="LaMDA">LaMDA</a> (2021)</li> <li><a href="/wiki/Chinchilla_(language_model)" title="Chinchilla (language model)">Chinchilla</a> (2022)</li> <li><a href="/wiki/PaLM" title="PaLM">PaLM</a> (2022)</li> <li><a href="/wiki/Gemini_(language_model)" title="Gemini (language model)">Gemini</a> (2023)</li> <li><a href="/wiki/VideoPoet" title="VideoPoet">VideoPoet</a> (2024)</li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Other</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/DreamBooth" title="DreamBooth">DreamBooth</a> (2022)</li> <li><a href="/wiki/NotebookLM" title="NotebookLM">NotebookLM</a> (2023)</li> <li><a href="/wiki/Google_Vids" title="Google Vids">Vids</a> (2024)</li></ul> </div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">See also</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li>"<a href="/wiki/Attention_Is_All_You_Need" title="Attention Is All You Need">Attention Is All You Need</a>"</li> <li><a href="/wiki/Future_of_Go_Summit" title="Future of Go Summit">Future of Go Summit</a></li> <li><a href="/wiki/Generative_pre-trained_transformer" title="Generative pre-trained transformer">Generative pre-trained transformer</a></li> <li><a href="/wiki/Google_Labs" title="Google Labs">Google Labs</a></li> <li><a href="/wiki/Google_Pixel" title="Google Pixel">Google Pixel</a></li> <li><a href="/wiki/Google_Workspace" title="Google Workspace">Google Workspace</a></li> <li><a href="/wiki/Robot_Constitution" title="Robot Constitution">Robot Constitution</a></li></ul> </div></td></tr><tr><td class="navbox-abovebelow" colspan="2"><div> <ul><li><span class="noviewer" typeof="mw:File"><span title="Category"><img alt="" src="//upload.wikimedia.org/wikipedia/en/thumb/9/96/Symbol_category_class.svg/16px-Symbol_category_class.svg.png" decoding="async" width="16" height="16" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/en/thumb/9/96/Symbol_category_class.svg/23px-Symbol_category_class.svg.png 1.5x, //upload.wikimedia.org/wikipedia/en/thumb/9/96/Symbol_category_class.svg/31px-Symbol_category_class.svg.png 2x" data-file-width="180" data-file-height="185" 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