The Ultimate Timeline of Artificial Intelligence Technology
人工智慧科技的終極時間軸

Throughout the existence of humanity, technological advancements have transformed entire civilizations. Though some of these innovations may seem recent, their development was often hundreds of years in the making. The ideas and inventions behind artificial intelligence can be traced back centuries, long before the creation of the computer.
自人類文明伊始，科技的進步便不斷地改寫著整個文明的樣貌。雖然有些創新發明看似近在眼前，但其發展往往歷經數百年之久。人工智慧背後的理念和發明，可以追溯到數個世紀以前，遠在電腦誕生之前。

Similarly to previous revolutionary technologies, the average person will increasingly use AI in their daily lives as the technology becomes more powerful, cheaper, and accessible to everyone. AIPRM has compiled an extensive timeline of breakthroughs to examine the developments that led to today’s AI.
與以往革命性的科技一樣，隨著人工智慧技術日益強大、成本降低且普及化，一般大眾將會更頻繁地將其應用於日常生活之中。AIPRM 彙整了一份詳盡的突破性發展時間軸，以檢視促成今日人工智慧的歷程。

Artificial Intelligence in Ancient Times
古代人工智慧 #

Before AI, there had to be a series of great thinkers, innovators, and inventors to pioneer the field. Interest in concepts surrounding intelligent automata and artificially created humans can be traced back to Ancient Greece. Around 700 B.C., the Ancient Greek poet Hesiod created the story of Talos, one of the earliest conceptions of an automaton. Talos was a giant bronze man created to protect the island of Crete by Hephaestus, the Greek god of fire, stone masonry, metalworking, and the artisans. Homer, one of the world’s most renowned poets, introduced the word “automaton” in his poems Iliad and Odyssey to describe machines that moved independently through their own internal energy—not unlike the inner workings of the human body.
在人工智慧誕生之前，曾有許多偉大的思想家、創新者和發明家為此領域奠定基礎。人們對於智能自動機和人工創造之人的概念的興趣，可以追溯到古希臘。約公元前 700 年，古希臘詩人赫西俄德創作了塔羅斯的故事，這是最早關於自動機的概念之一。塔羅斯是由希臘火神、石匠、金屬加工和工匠之神赫菲斯托斯創造的巨大青銅人，用以守護克里特島。荷馬，世界最負盛名的詩人之一，在他的史詩《伊利亞德》和《奧德賽》中引入了「automaton」（自動機）一詞，用以描述依靠自身內部能量獨立運作的機器——這與人體的內部運作方式並無二致。

Outside of Ancient Greece, the conception of intelligent machinery can also be seen among philosophers, authors, and scholars. The three Persian Banū Mūsā brothers became the first Arab scholars to master Greek mathematics in the 9^th century AD with their invention of the world’s first programmable machine: a mechanical musical instrument played by pins on a revolving cylinder. Al-Khwarizmi, translated as Algoritmi in Latin, was a Persian polymath known as the Father of Algebra. Due to his contributions to mathematics, the word algorithm is derived from his Latin name.
除了古希臘之外，在哲學家、作家和學者中也可以看到智能機械的概念。三位波斯巴努·穆薩兄弟是第一批掌握希臘數學的阿拉伯學者，他們在公元 9 世紀發明了世界上第一台可程式設計的機器：一種由旋轉圓筒上的銷子演奏的機械樂器。花拉子米（Al-Khwarizmi），拉丁語譯為 Algoritmi，是一位波斯通才，被譽為代數之父。由於他在數學方面的貢獻，「演算法」一詞便源自他的拉丁名字。

In the matter of ethics, Aristotle’s framework still serves as a cornerstone for AI. Aristotle, a philosopher and polymath from Ancient Greece, introduced concepts that indirectly influenced many of the AI ethics and logical reasoning we have today. Aristotle’s theory of formal reasoning, better known as syllogism, suggested combining two different premises to arrive at a conclusion. Centuries later, syllogism would serve as an early model of formal logic for artificial intelligence.
在倫理方面，亞里士多德的框架至今仍是人工智慧的基石。亞里士多德，一位來自古希臘的哲學家和通才，提出的概念間接地影響了我們今天許多的人工智慧倫理和邏輯推理。亞里士多德的形式推理理論，也就是更為人知的「三段論」，提出將兩個不同的前提結合起來得出結論。幾個世紀後，三段論成為了人工智慧早期形式邏輯的模型。

The Birth of Modern Artificial Intelligence
現代人工智慧的誕生 #

John McCarthy, an American computer scientist and professor at Dartmouth College, is often credited as the inventor of artificial intelligence in the modern field. He coined the phrase in 1955 in a proposal for his project for the Dartmouth Conference. Thanks to McCarthy’s work, the term can now be applied retroactively to previous significant breakthroughs in artificial intelligence. In 1958, McCarthy also invented the first AI programming language called Lisp. Though other programming languages have surpassed its prevalence, Lisp influenced subsequent languages such as Python and JavaScript.
約翰·麥卡錫，一位美國電腦科學家和達特茅斯學院教授，通常被認為是現代人工智慧領域的發明者。他在 1955 年為達特茅斯會議的專案撰寫提案時，創造了這個詞彙。由於麥卡錫的工作，這個術語現在可以追溯應用於之前人工智慧領域的重大突破。1958 年，麥卡錫還發明了第一種人工智慧程式語言 Lisp。儘管其他程式語言已經超越了它的普及程度，但 Lisp 影響了後來的 Python 和 JavaScript 等語言。

Alan Turing, an English computer scientist and mathematician, is another significant name from that era in AI. In 1936, he introduced the hypothetical model known as the Turing machine to define the logical structure of any computing device. In 1950, Turing questioned the ability of machines to think in his paper titled “Computing Machinery and Intelligence,” published in MIND, a leading journal in philosophy. He brought forth the imitation game, or what is now deemed the Turing Test, to assess the intelligence of machines. The test judged a machine’s ability to exhibit responses that would be indistinguishable from a human being’s response in the same conversation.
艾倫·圖靈，一位英國電腦科學家和數學家，是人工智慧那個時代的另一個重要人物。1936 年，他提出了被稱為圖靈機的假設模型，用以定義任何計算裝置的邏輯結構。1950 年，圖靈在他的論文《計算機與智慧》（發表於哲學領先期刊 MIND）中，探討了機器思考的能力。他提出了模仿遊戲，也就是現在所稱的圖靈測試，用以評估機器智慧。該測試評估機器展現反應的能力，這些反應在相同的對話中與人類的反應難以區分。

In 1965, an MIT professor named Joseph Weizenbaum developed the first AI chatbot, ELIZA. ELIZA used pattern recognition to simulate human conversation by picking up on patterns from the interlocutor. However, ELIZA could only work within the confines of predefined rules. This chatbot became the earliest model of generative AI, or AI that can generate text, images, videos, and other data based on a prompt. Thanks to the invention of ELIZA, we now have chatbots like ChatGPT, DALL-E, and Midjourney.
1965 年，麻省理工學院教授約瑟夫·魏森鮑姆開發了第一個 AI 聊天機器人 ELIZA。ELIZA 使用模式識別來模擬人類對話，通過從說話者身上捕捉模式。然而，ELIZA 只能在預定義規則的範圍內運作。這個聊天機器人成為生成式 AI 的最早模型，也就是可以根據提示生成文字、圖像、影片和其他數據的 AI。由於 ELIZA 的發明，我們現在有了 ChatGPT、DALL-E 和 Midjourney 等聊天機器人。

The Future of AI
人工智慧的未來 #

Artificial intelligence, in the capacity and accessibility that it has today, is unprecedented. AI can improve society and the average person’s life in various ways. For example, artificial intelligence has already been used to develop vaccines in healthcare. As more advanced technology integrates into hospitals, doctors can use it to personalize treatment plans and ensure more accurate diagnostics.
以人工智慧目前的容量和普及程度而言，是史無前例的。人工智慧可以通過各種方式改善社會和人們的生活。例如，人工智慧已被用於開發醫療保健疫苗。隨著更先進的技術整合到醫院中，醫生可以使用它來個性化治療方案並確保更精確的診斷。

For the individual, AI can augment work across many industries. This allows the person to leave behind the more menial tasks and put effort and energy towards grander endeavors. In the process of decision-making, AI provides another support system to discuss and rationalize thoughts and ideas. Additionally, AI can act like a personalized life coach in finance, health, and general wellness areas.
對個人而言，人工智慧可以增強許多行業的工作效率。這讓個人可以擺脫更多瑣碎的任務，將精力投入到更宏偉的事業中。在決策過程中，人工智慧提供了另一個支持系統來討論和理清想法。此外，人工智慧還可以充當財務、健康和一般健康領域的個性化生活教練。

To effectively utilize AI, one should understand what AI encompasses and how to navigate it. Users can introduce better-customized prompts to deliver more relevant answers or responses. Since this technology is ever-developing, regulations are continuously created and adjusted all around us. Each nation may have its own rules surrounding AI, so following your country’s laws is essential. This is particularly important if using AI for commercial purposes.
要有效地利用人工智慧，就應該了解人工智慧的涵蓋範圍以及如何駕馭它。使用者可以輸入更自訂的提示以獲得更相關的答案或回應。由於這項技術仍在不斷發展，因此各地的法規也在不斷制定和調整。每個國家可能都有自己關於人工智慧的規定，因此遵守所在國家的法律至關重要。如果將人工智慧用於商業目的，這一點尤其重要。

Event and Date  事件與日期	Description  描述
Ancient Greece  古希臘 Greek myths explore the idea of intelligent automata and artificially created humans 希臘神話探討了智能自動機和人工創造人類的概念。	Talos was a giant bronze automaton tasked with protecting Crete, circling the shores thrice daily. Creating machines that mimicked living things was a popular subject for myths and a goal for many Greek engineers. 塔羅斯是一個巨大的青銅自動機，負責保護克里特島，每天繞島巡邏三次。創造模仿生物的機器是神話中常見的主題，也是許多希臘工程師追求的目標。
8th century BCE  西元前八世紀 Homer’s epic poems Iliad and Odyssey introduce the term “automaton” 荷馬史詩《伊利亞德》和《奧德賽》引入了「自動機」這個詞彙。	The word automaton is derived from the Ancient Greek αὐτόματον, which means “acting of one’s own will.” In his epic poems, he describes Golden Maidens (“Kourai Khryseai”), automatons capable of speech and learning. There are also intelligent Phaeacian ships capable of navigating on their own. 「自動機」一詞源自古希臘語 αὐτόματον，意思是「自行運作」。在他的史詩中，他描述了會說話和學習的金髮少女（Kourai Khryseai），也就是自動機。此外，還有能夠自行航行的智慧法厄克亞船隻。
4th century BCE  西元前四世紀 Aristotle describes syllogisms 亞里斯多德描述了三段論。	A syllogism, or a rule of inference, is a form of logical reasoning that consists of two premises leading to a conclusion. An example of a syllogism is: “All mammals are animals. All cows are mammals. Therefore, all cows are animals.” 三段論，或推理規則，是一種邏輯推理形式，包含兩個前提導出一個結論。例如：「所有哺乳動物都是動物。所有牛都是哺乳動物。因此，所有牛都是動物。」 This type of deductive reasoning is foundational for AI to mimic human decision-making. 這種演繹推理是 AI 模仿人類決策的基礎。
4th century BCE  西元前四世紀 Aristotle predicts AI performing labor 亞里斯多德預測 AI 將執行勞務。	In his work Politics, Aristotle speculated that automata could abolish slavery and bring about equality, stating that: “There is only one condition in which we can imagine managers not needing subordinates, and masters not needing slaves. This condition would be that each instrument could do its own work, at the word of command or by intelligent anticipation, like the statues of Daedalus or the tripods made by Hephaestus.” 在他的著作《政治學》中，亞里斯多德推測自動機可以廢除奴隸制並帶來平等，他說道：「只有一個情況下，我們可以想像管理者不需要下屬，主人不需要奴隸。這個條件是，每件工具都能夠按照命令或憑藉智慧的預期自行完成工作，就像代達羅斯雕像或赫菲斯托斯製造的三腳架一樣。」
3rd century BCE  西元前三世紀 First example of a truly automatic self-regulatory device 第一個真正自動的自我調節裝置的例子。	Greek inventor and mathematician Ctesibius invents the first artificial automatic self-regulatory system by designing an improved clepsydra (“water clock”). It required no outside intervention between the feedback and controls of the mechanism. 希臘發明家兼數學家克特西比烏斯設計改良的漏壺（水鐘），發明了第一個人工自動自我調節系統。它不需要在機制的反饋和控制之間進行外部干預。
1st century AD  西元一世紀 Automatic theater  自動劇場	Greek mathematician and engineer Hero of Alexandria (also known as Heron) creates an entirely mechanical play out of automatons, including one that could speak. 希臘數學家和工程師亞歷山大城的希羅（也稱為希倫）創造了一個完全由自動機組成的機械戲劇，其中包括一個可以說話的自動機。
260 AD  西元 260 年 Origin of semantic networks 語義網絡的起源	Neoplatonic philosopher Porphyry writes Isagogê, which categorized knowledge and logic. It included a drawing of what would later be known as a “semantic net.” a foundation of machine learning. 新柏拉圖主義哲學家波菲利寫下《導論》(Isagogê)，對知識和邏輯進行了分類。其中包含一張圖，後來被稱為「語義網路」，這是機器學習的基礎。
~800 AD  約西元 800 年 Alchemy of life  生命煉金術	Arabic author Jabir ibn Hayyan develops the alchemical theory of Takwin, which is the creation of synthetic life. 阿拉伯學者賈比爾·伊本·哈揚發展了煉金術理論「塔克溫」(Takwin)，即人工合成生命的創造。
9th century AD  西元 9 世紀 Possible first machine with a stored program 可能的第一台儲存程式機器	The Banū Mūsā brothers, Persian scholars, create a programmable steam-powered flute controlled by a program of pins on a revolving cylinder. 波斯學者巴努·穆薩兄弟發明了一種可程式設計的蒸汽動力笛子，由旋轉圓柱體上的銷釘程式控制。
825 AD  西元 825 年 The origin of the algorithm 演算法的起源	Persian polymath Al-Khwarizmi wrote textbooks with step-by-step algebra and arithmetic methods used in Islam, India, and Europe until the 16th century. The word “algorithm” stems from his name. 波斯通才學者花拉子米撰寫的教科書，其中包含逐步的代數和算術方法，直到 16 世紀，這些方法都在伊斯蘭世界、印度和歐洲使用。「演算法」(algorithm)一詞源於他的名字。
1206 Programmable orchestra  可程式設計的管弦樂團	Muslim polymath Ismail al-Jazari creates a musical robot band that moved with hydraulics. Different rhythms could be achieved by adjusting pegs and levers. 伊斯蘭通才學者阿爾-賈扎里創造了一個由液壓驅動的音樂機器人樂隊。通過調整銷釘和槓桿可以實現不同的節奏。
1275 Ars Magna  大藝術 (Ars Magna)	Mallorcan theologian Ramon Llull invents the Ars Magna, a tool for combining concepts mechanically. He described these machines as entities that could unite basic truths into advanced knowledge. 馬約卡神學家雷蒙·魯爾發明了「大藝術」(Ars Magna)，一種機械組合概念的工具。他將這些機器描述為能夠將基本真理結合起來形成高級知識的實體。
~1580 Golem  人造人 (Golem)	Rabbi Judah Loew ben Bezalel of Prague claims to have invented a Golem, a clay creature brought to life. 布拉格的猶太教拉比葉胡達·洛伊·本·貝扎勒爾聲稱發明了人造人 (Golem)，一種被賦予生命的黏土生物。
1620 Inductive reasoning  歸納推理	English philosopher Francis Bacon introduces inductive reasoning in his work Novum Organum. Inductive reasoning is vital for AI systems as it allows machines to fill in gaps of information, adapt to situations based on observed patterns, and make educated guesses. 英國哲學家弗朗西斯·培根在他的著作《新工具》(Novum Organum)中引入了歸納推理。歸納推理對於 AI 系統至關重要，因為它允許機器填補資訊缺口，根據觀察到的模式適應情況，並做出合理的推測。
1637 Discourse on the Method 方法論 (Discourse on the Method)	French philosopher René Descartes argues that for human-like automatons to acquire intelligence, they would need the capability to respond to any unknown situation that it may encounter and to be able to arrange words in response to anything said in its presence. This was one of the first philosophical explorations of artificial intelligence. 法國哲學家笛卡爾認為，要使類人自動機獲得智慧，它們需要具備回應任何未知情況的能力，並能夠根據任何在其面前說出的話來排列詞語。這是對人工智慧最早的哲學探索之一。
1642 Mechanical calculator  機械計算器	French mathematician and philosopher Blaise Pascal invents the mechanical calculator. 法國數學家與哲學家布萊茲·帕斯卡發明了機械計算器。
1651 Leviathan  利維坦	English philosopher Thomas Hobbes is considered by some historians as one of the first “prophets” of AI. Leviathan envisions a world ruled by an absolute sovereign and explores the notion of cognition being a mechanical process. 英國哲學家湯瑪斯·霍布斯被一些歷史學家認為是第一批人工智慧「先知」之一。他的《利維坦》描繪了一個由絕對君主統治的世界，並探討了認知是一個機械過程的概念。
1676 Chain rule  鏈式法則	German polymath Gottfried Wilhelm Leibniz derives the chain rule, a mathematical formula used by AI to train neural networks. 德國通才哥特弗里德·威廉·萊布尼茨推導出鏈式法則，這是一個數學公式，人工智慧用於訓練神經網路。
1726 Gulliver's Travels  格列佛遊記	Anglo-Irish author Jonathan Swift writes Gulliver's Travels, which features The Engine, a machine that generates permutations of word sets. It is one of the earliest known references to a device resembling the modern computer. 英愛爾蘭作家喬納森·斯威夫特撰寫了《格列佛遊記》，其中包含一台名為「引擎」的機器，可以產生詞組的排列組合。這是已知最早參考類似現代電腦裝置的文獻之一。
1750 L'Homme Machine  人是機器	French physician and philosopher Julien Offray de La Mettrie publishes L'Homme Machine, which argues that human thought is strictly mechanical and that the body and mind are one. 法國醫生和哲學家朱利安·奧弗雷·德·拉·梅特里出版了《人是機器》，認為人類思想完全是機械的，身體和心靈是一體的。
1763 Bayes' theorem  貝氏定理	English statistician Thomas Bayes’ work “An Essay Towards Solving a Problem in the Doctrine of Chances” is published, which laid the foundations for Bayes' theorem, a mathematical rule for finding the probability of a cause given its effect. This is used for modern AI in Bayesian networks. 英國統計學家托馬斯·貝葉斯的作品《論機率問題論文》出版，為貝氏定理奠定了基礎，貝氏定理是一個用於尋找已知結果求其原因機率的數學規則。這被應用於現代人工智慧的貝氏網路中。
1800 First industrial software 首個工業軟體	French weaver and merchant Joseph Marie Jacquard invents the earliest programmable loom, which operated with replaceable punched cards that produced different textile weaving sequences. This may have been the first industrial software for commercial use. 法國織工和商人約瑟夫·瑪麗·雅卡爾發明了最早的可程式化提花織機，它使用可替換的穿孔卡片產生不同的紡織編織序列。這可能是第一個用於商業用途的工業軟體。
1818 Frankenstein  弗蘭肯斯坦	English novelist Mary Shelley publishes Frankenstein, a story that explores the creation and ethics of sentient beings. 英國小說家瑪麗·雪萊出版了《弗蘭肯斯坦》，這部小說探討了有感知能力的生物的創造和倫理問題。
1820s  1820 年代 First mechanical computer 首台機械計算機	English polymath Charles Babbage invents the first mechanical computer, the Difference Engine. 英國通才查爾斯·巴貝奇發明了第一台機械計算機——差分機。
1837 First Turing-complete computer 首台圖靈完備計算機	Charles Cabbage and Ada Lovelace propose the Analytical Engine, the first design for a general-purpose computer which could be described in modern terms as Turing-complete (a system that can handle any computation). 查爾斯·巴貝吉和艾達·洛芙萊斯提出分析機的概念，這是第一個通用電腦的設計，用現代術語來說，它可以被描述為圖靈完備的（一個可以處理任何計算的系統）。
1854 Boolean logic  布林邏輯	English mathematician George Boole invents Boolean logic, which became essential in computer programming (the origin of 1 and 0 as truth values) and laying the foundations of the Information Age. 英國數學家喬治·布爾發明布林邏輯，這在電腦程式設計中至關重要（1 和 0 作為真值的起源），並為資訊時代奠定了基礎。
1863 Evolution of machines  機器的演進	English novelist Samuel Butler proposes that Darwinian evolution also applies to machines, predicting that they will one day surpass humans: “In the course of ages we shall find ourselves the inferior race." 英國小說家塞繆爾·巴特勒提出，達爾文的進化論也適用於機器，預測它們有一天會超越人類：「時至久遠，我們將發現自己成了劣等種族。」
1912 El Ajedrecista  自動西洋棋	Spanish inventor Leonardo Torres Quevedo builds El Ajedrecista, a pioneering automaton capable of playing chess. This may be the world’s first computer game. 西班牙發明家雷昂納多·托雷斯·奎韋多製造了「自動西洋棋」，這是一款能夠下西洋棋的先驅自動機。這可能是世界上第一個電腦遊戲。
1923 Rossum's Universal Robots 羅素姆的萬能機器人	Czech playwright Karel Čapek opens Rossum's Universal Robots (R.U.R.) in London, a play about artificial workers in a factory. It was the first use of the word “robot” in the English language. 捷克劇作家卡雷爾·恰佩克在倫敦上演《羅素姆的萬能機器人》(R.U.R.)，這部戲劇講述的是工廠裡的人工勞工。這是「機器人」一詞首次出現在英語中。
1925 Ising model  伊辛模型	German physicists Wilhelm Lenz and Ernst Ising create the Ising model, a mathematical model which can be viewed as the first artificial recurrent neural network. 德國物理學家威廉·倫茨和恩斯特·伊辛創造了伊辛模型，這是一個數學模型，可以被視為第一個人工循環神經網路。
1928 First humanoid robot  第一個類人機器人	Captain William Richards and aircraft engineer Alan Reffell build Eric, the first humanoid robot. It was able to stand, bow, and deliver a speech. 威廉·理查茲船長和航空工程師艾倫·雷菲爾建造了艾瑞克，這是第一個類人機器人。它能夠站立、鞠躬和發表演說。
1929 First robot of the East 東方第一個機器人	Concerned by the depiction of robots as slaves in R.U.R., biologist Makoto Nishimura builds Gakutensoku, the first robot of the East. His intention was to create a robot that would celebrate nature and humanity and be a friend to people. 生物學家西村真琴深受《羅素姆的萬能機器人》中將機器人描繪成奴隸的影響，因此建造了學天則，這是東方第一個機器人。他的目的是創造一個能夠歌頌自然和人類，並成為人們朋友的機器人。
1931 Incompleteness Theorem  不完備定理	Logician Kurt Gödel proposes the Incompleteness Theorem which identified the fundamental limitations on what a computer could prove or disprove. This laid the foundations for theoretical computer science and AI theory. 邏輯學家庫爾特·哥德爾提出不完備定理，指出電腦在證明或反駁方面的根本局限性。這為理論電腦科學和人工智慧理論奠定了基礎。
1936 Lambda calculus  λ演算	American mathematician Alonzo Church develops Lambda calculus, a system in mathematical logic that would become important to the theory of programming languages. 美國數學家阿隆佐·邱奇發展了λ演算，這是一個數學邏輯系統，對程式語言理論至關重要。
1936 Turing machine  圖靈機	Alan Turing, widely considered the father of theoretical computer science, introduces the Turing machine, an abstract device capable of implementing any computer algorithm. 被譽為理論電腦科學之父的艾倫·圖靈，發表了圖靈機的概念，這是一種抽象的裝置，能夠執行任何電腦演算法。
1940 First gaming computer  首台遊戲電腦	Nuclear scientist Edward Condon creates the Nimatron, one of the earliest examples of artificial intelligence in video games. Over 50,000 played against it – few won. 核子科學家愛德華·康登創造了 Nimatron，這是電子遊戲中最早的人工智慧範例之一。超過五萬人與它對弈，卻鮮少有人獲勝。
1941 First programmable computer 首台可程式電腦	Computer scientist Konrad Zuse invents Z3, the world’s first programmable computer. 電腦科學家康拉德·楚澤發明了 Z3，這是世界上第一台可程式電腦。
1943 First mathematical model of an artificial neural network/perceptron 人工神經網路/感知器的首個數學模型	Warren McCulloch and Walter Pitts publish "A Logical Calculus of the Ideas Immanent in Nervous Activity," drawing parallels between the brain and computers for the first time. This would become known as a perceptron. 沃倫·麥卡洛克和沃爾特·皮茨發表了「神經活動中固有思想的邏輯演算」論文，首次闡述了大腦與電腦之間的相似之處。這項研究後來被稱為感知器。
1945 “As We May Think” 「我們可能思考的方式」	American engineer Vannevar Bush publishes a visionary essay that predicts many aspects of today’s information society and the profound integration of computers in our lives. 美國工程師凡尼瓦爾·布希發表了一篇具有前瞻性的論文，預測了當今資訊社會的許多方面，以及電腦融入我們生活的深遠影響。
1945 First programmable, all-electronic computer 首台可程式化全電子計算機	Designed by John Mauchly and J. Presper Eckert, ENIAC (Electronic Numerical Integrator and Computer) becomes the first electronic, largescale, general-purpose digital computer that could be programmed. 由約翰·莫奇利和 J·普雷斯珀·埃克特設計的 ENIAC（電子數字積分器和計算機）成為首台可編程的電子大型通用數位計算機。
1948 The origin of cybernetics 控制論的起源	American computer scientist Norbert Wiener coins the term “cybernetics” as the study of “control and communication in the animal and the machine.” 美國電腦科學家諾伯特·維納創造了「控制論」一詞，用以研究「動物和機器中的控制和通訊」。
1949 Giant Brains, or Machines That Think 巨腦，或會思考的機器	American computer scientist Edmund Berkeley publishes a groundbreaking book that stated: “These machines are similar to what a brain would be if it were made of hardware and wire instead of flesh and nerves… A machine can handle information; it can calculate, conclude, and choose; it can perform reasonable operations with information. A machine, therefore, can think.” 美國電腦科學家埃德蒙·柏克萊出版了一本具有開創性的書籍，其中寫道：「這些機器類似於如果大腦是由硬體和電線而不是血肉和神經組成的話會是什麼樣子……機器可以處理資訊；它可以計算、推論和選擇；它可以對資訊進行合理的運算。因此，機器可以思考。」
1950 The Turing Test  圖靈測試	Alan Turing introduces the Turing Test, originally called the imitation game, a method of testing a machine’s ability to exhibit intelligent behavior equivalent to, or indistinguishable from, a human being. 艾倫·圖靈提出了圖靈測試，最初稱為模仿遊戲，這是一種測試機器展現與人類相當或難以區分之智慧行為能力的方法。
1950 “I, Robot”  「我，機器人」	Isaac Asimov publishes an anthology of stories sharing a theme of the interaction of humans, robots, and morality. It included the “Three Laws of Robotics,” a code of ethics for robots. 艾薩克·阿西莫夫出版了一部以人類、機器人和道德互動為主題的短篇故事集。其中包含了「機器人三定律」，一套機器人的倫理規範。
1950 First electrical device to use trial and error 首個使用試錯法的電子裝置	Claude Shannon, alongside his wife, designs Theseus, a device that learns the shortest path through a maze via trial and error. 克勞德·香農與其妻子共同設計了忒修斯，這是一種透過試錯法學習迷宮最短路徑的裝置。
1955 “Artificial Intelligence” 「人工智慧」	Professor John McCarthy coins the term “artificial intelligence” in his proposal for an upcoming research project. 約翰·麥卡錫教授在其即將進行的研究計畫提案中創造了「人工智慧」一詞。
1955 Checkers-playing program 跳棋程式	IBM’s Arthur Samuel creates a version of his checkers-playing program capable of learning to play. IBM 的亞瑟·塞繆爾創造了一個能夠學習玩跳棋的跳棋程式版本。
1956 First artificial intelligence program 首個人工智慧程式	Herbert Simon and Allen Newell develop Logic Theorist, the first program that simulated how humans use reason to solve complex problems. It was able to find new and more elegant proofs for some math theorems. 赫伯特·西蒙和艾倫·紐厄爾開發了「邏輯理論家」(Logic Theorist)，這是第一個模擬人類如何運用推理解決複雜問題的程式。它能夠為一些數學定理找到更簡潔、更優雅的證明。
1956 Dartmouth Summer Research Project on Artificial Intelligence 達特茅斯人工智能夏季研討會	A small group of prolific scientists gather at Dartmouth College, organized by John McCarthy. He stated the goal was “to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” It is considered the founding event of artificial intelligence as a field. 一小群傑出的科學家齊聚達特茅斯學院，由約翰·麥卡錫組織。他聲明研討會的目標是：「基於這樣的猜想：學習的每一個方面或任何其他智慧特徵，原則上都能被如此精確地描述，以至於可以製造出一台機器來模擬它。」這被認為是人工智能領域的創立事件。
1957 First hardware application of a machine that could “see” 首個具備「視覺」能力的機器硬體應用	Frank Rosenblatt develops the Mark I Perceptron, a machine consisting of 400 photocells that could classify images. The New York Times described it as: “The embryo of an electronic computer that [the Navy] expects will be able to walk, talk, see, write, reproduce itself and be conscious of its existence." 弗蘭克·羅森布拉特開發了「Mark I 感知器」，這是一台由 400 個光電管組成的機器，能夠分類圖像。《紐約時報》將其描述為：「一種電子計算機的雛形，[海軍]預計它將能夠行走、說話、看東西、寫字、自我複製，並意識到自己的存在。」
1957 First music composed by an electronic computer 首個由電子計算機創作的音樂	The ILLIAC 1 computer produces the Illiac Suite, a score created for a string quartet. ILLIAC 1 計算機創作了《伊利亞克組曲》(Illiac Suite)，這是一部為弦樂四重奏創作的樂譜。
1958 First AI programming language 首個 AI 程式語言	John McCarthy invents the Lisp programming language which is still widely used today. 約翰·麥卡錫發明了 Lisp 程式語言，至今仍被廣泛使用。
1959 Machine learning  機器學習	Arthur Samuel coins the term “machine learning,” defining it as a “field of study that gives computers the ability to learn without being explicitly programmed.” 阿瑟·塞繆爾創造了「機器學習」一詞，將其定義為「一個研究領域，它賦予計算機在沒有明確程式設計的情況下學習的能力」。
1961 First industrial robot  首個工業機器人	Unimate clocks were the first industrial robot at the General Motors plant in New Jersey. Unimate 機器手臂是新澤西州通用汽車工廠的第一個工業機器人。
1961 First symbolic integration program 首個符號積分程式	Using Lisp, James Slagle writes SAINT, a program capable of solving calculus problems at the college freshman level. 詹姆斯·史萊格使用 Lisp 編寫了 SAINT，一個能夠解決大學一年級微積分問題的程式。
1964 STUDENT	Using Lisp, Daniel Bobrow writes STUDENT, an artificial intelligence program capable of solving algebra word problems. 使用 Lisp，丹尼爾·鮑勃羅寫了 STUDENT，這是一個能夠解決代數文字題的人工智能程式。
1965 First AI “chatbot” and first generative AI 首個 AI「聊天機器人」和首個生成式 AI	Joseph Weizenbaum develops ELIZA, a program that could simulate conversation using a pattern matching and substitution methodology. 約瑟夫·魏森鮑姆開發了 ELIZA，這是一個可以使用模式匹配和替換方法模擬對話的程式。
1965 First expert system  首個專家系統	Edward Feigenbaum, Bruce G. Buchanan, Joshua Lederberg, and Carl Djerassi begin working on Dendral, an AI capable of helping organic chemists identify unknown organic molecules. It could emulate the decision-making ability of a human expert, making it the first “expert system.” 愛德華·費根鮑姆、布魯斯·布坎南、約書亞·萊德伯格和卡爾·德耶拉西開始研發 Dendral，這是一款能夠幫助有機化學家識別未知有機分子的 AI 系統。它可以模擬人類專家的決策能力，成為第一個「專家系統」。
1966 First “reasonable” robot 第一個「堪稱合理」的機器人	Shakey the Robot, developed at Stanford Research Institute, becomes the first general-purpose mobile robot able to reason about its own actions. 史丹佛研究院研發的 Shakey 機器人，成為第一個能夠自行推論行動的通用型行動機器人。
1968 HAL 9000	The film 2001: A Space Odyssey is released, one of the first films featuring a sentient computer. 電影《2001 太空漫遊》上映，這是首批出現具備感知能力電腦的電影之一。
1968 First AI program to understand natural language 第一個理解自然語言的 AI 程式	Computer scientist Terry Winograd develops SHRDLU, an AI program that could be instructed to move objects in a “blocks world” and had a basic memory to supply context. 電腦科學家泰瑞·維諾格拉德開發了 SHRDLU，這是一個可以被指示在「積木世界」中移動物體的 AI 程式，並且具有基本的記憶功能來提供上下文。
1970 Backpropagation  反向傳播	Mathematician Seppo Ilmari Linnainmaa publishes the reverse mode of automatic differentiation which would later become known as backpropagation, a crucial method for training artificial neural networks. 數學家塞波·伊爾馬里·林奈瑪發表了自動微分的反向模式，後來被稱為反向傳播，這是訓練人工神經網路的一種關鍵方法。
1970 Uncanny Valley  恐怖谷效應	Japanese robotics professor Masahiro Mori coins the term “Uncanny Valley” to describe the eerie or unsettling feeling people experience in response to artificially created humanoids that are not quite life-like. 日本機器人學教授森政弘創造了「恐怖谷效應」一詞，用以描述人們對人工創造的、不夠逼真的人形機器人所產生的怪異或不安的感覺。
1972 WABOT-1	Waseda University develops the WABOT-1, the first full-scale humanoid intelligent robot. It was the first android able to walk, talk, measure distances with external receptors, and grip objects. 早稻田大學研發了 WABOT-1，這是第一個全尺寸的人形智慧型機器人。它是第一個能夠行走、說話、利用外部感測器測量距離以及抓取物體的機器人。
1972 MYCIN	Stanford University develops MYCIN, an expert system capable of identifying the bacteria causing severe infections and recommending appropriate antibiotics. 史丹佛大學開發了 MYCIN，這是一個能夠識別導致嚴重感染的細菌並推薦適當抗生素的專家系統。
1973 AI draws criticism – AI winter AI 引發批評—AI 寒冬	Mathematician James Lighthill publishes the Lighthill report, a disparaging analysis of the progress of AI research: “In no part of the field (of AI) have the discoveries made so far produced the major impact that was then promised.” This led the U.S. and British governments to cut back funding for AI research. 數學家詹姆斯·萊特希爾發表了萊特希爾報告，這份報告對 AI 研究的進展提出了批評：「在 AI 領域的任何部分，迄今為止的發現都沒有產生當時所承諾的重大影響。」這導致美國和英國政府削減了對 AI 研究的資金。
1975 First scientific discoveries published by an AI program 第一個由 AI 程式發表的研究成果	The Meta-Dendral learning program produces new results in chemistry and mass spectrometry, which are published in a peer-reviewed journal. Meta-Dendral 學習程式在化學和質譜分析方面產生了新的成果，並發表在同行評審期刊上。
1979 First autonomous vehicle 第一輛自動駕駛車輛	Built by robotics expert Hans Moravec, the Stanford Cart becomes the first computer-controlled, autonomous vehicle, to successfully traverse a chair-filled room on its own. 由機器人專家漢斯·莫拉維克打造的史丹佛購物車，成為第一輛成功自行穿越佈滿椅子的房間的電腦控制自動駕駛車輛。
1981 Dawn of parallel computing 平行運算的曙光	American inventor Danny Hillis creates a Connection Machine, a supercomputer that utilizes massively parallel computing. This would revolutionize AI technology and computation. 美國發明家丹尼·希利斯創造了一台連接機，這是一台利用大規模平行運算的超級電腦。這將徹底改變人工智慧技術和運算方式。
1985 First AI program for making art 第一個用於創作藝術的人工智慧程式	Artist Harold Cohen introduces AARON, an AI capable of producing paintings and drawings autonomously. 藝術家哈洛德·科恩推出了 AARON，這是一個能夠自主創作繪畫和圖畫的人工智慧。
1986 First autonomous car  第一部自動駕駛汽車	Under the direction of Ernst Dickmanns, the Bundeswehr University builds the first vision-guided, driverless car, a Mercedez-Benz van capable of reaching nearly 60 mph on empty streets. 在恩斯特·迪克曼斯的指導下，聯邦國防軍大學建造了第一輛視覺導引的無人駕駛汽車，這是一輛梅賽德斯-奔馳廂型車，能夠在空曠的街道上達到近 60 英里的時速。
1988 Jabberwacky	Rollo Carpenter launches the chatbot Jabberwacky to “simulate natural human chat in an interesting, entertaining and humorous manner." It was an early attempt to generate artificial intelligence through human interaction. 羅洛·卡彭特推出聊天機器人 Jabberwacky，旨在「以有趣、娛樂和幽默的方式模擬自然的人類聊天」。這是早期嘗試透過人機互動產生人工智慧的嘗試。
1989 Self-driving artificial neural network 自駕駛人工神經網路	Dean Pomerleau creates ALVINN (An Autonomous Land Vehicle in a Neural Network), a 3-layer back-propagation network designed for road following. 迪恩·波默羅創造了 ALVINN（人工神經網路中的自主地面車輛），這是一個用於道路跟蹤的三層反向傳播網路。
1991 First military use of AI 人工智慧首次軍事應用	The U.S. military uses DART (Dynamic Analysis and Replanning Tool) to schedule the transportation of supplies and personnel. By 1995, it offset the funding DARPA put into AI research for the previous 30 years combined. 美軍使用 DART（動態分析和重新規劃工具）來安排物資和人員的運輸。到 1995 年，它抵銷了 DARPA 之前 30 年投入人工智慧研究的總經費。
1992 TD-Gammon demonstrates the power of reinforcement TD-Gammon 證明了強化學習的威力	Gerald Tesauro develops TD-Gammon, a backgammon program that began “knowledge-free” and became advanced enough to defeat the world champion by training against expert players. Its exclusive training through self-play allowed it to discover new strategies that have been adopted by human players. 傑拉德·泰索羅開發了 TD-Gammon，這是一個西洋雙陸棋程式，起初「毫無知識」，但透過與專家選手對弈訓練，最終進步到足以擊敗世界冠軍。它獨特的自我對弈訓練使其發現了新的策略，這些策略已被人類玩家採用。
1994 First self-driving car journey with passengers 首次載客自動駕駛汽車旅程	Twin robot cars VaMP and VITA-2 travel over one thousand kilometers on a Paris highway in heavy traffic reaching speeds of 130 km/h. They demonstrated self-driving in free lanes, convoy driving, and lane changes among other cars. 雙胞胎機器車 VaMP 和 VITA-2 在巴黎高速公路上行駛超過一千公里，在繁忙的交通中達到 130 公里/小時的速度。它們展示了在自由車道上的自動駕駛、車隊駕駛以及在其他車輛之間變換車道等功能。
1995 A.L.I.C.E.	Richard Wallace launches Artificial Linguistic Internet Computer Entity, a program that engages in conversation with users by applying heuristic pattern matching rules to their input. It won the Loebner Prize three times, an award given to the most human-like computer programs. 理查德·華萊士推出了人工語言網路電腦實體，這是一個透過將啟發式模式匹配規則應用於使用者輸入來與使用者進行對話的程式。它曾三次獲得洛布納獎，該獎項頒發給最像人類的電腦程式。
1996 Deep Blue  深藍	Deep Blue, a chess-playing expert system, is released. After an upgrade, it defeated world champion Garry Kasparov in a six-game match. 深藍，一款西洋棋專家系統，正式問世。經過升級後，它在一場六局制的比賽中擊敗了世界冠軍加里·卡斯帕羅夫。
1997 First robot sports match 首場機器人運動賽事	First official RoboCup, a football (soccer) match featuring 40 teams of intelligent robots. 首屆官方機器人世界杯賽事，共有 40 支由智慧型機器人組成的足球隊伍參賽。
1998 Furby  ફર્બ	Tiger Electronics launches Furby, the first successful AI product to reach a domestic environment. 老虎電子公司推出 ફર્બ，這是第一款成功打入家庭環境的 AI 產品。
1998 Semantic Web road map 語義網路路線圖	Tim Berners-Lee, inventor of the World Wide Web, introduces the Semantic Web (or Web 3.0) to make the Internet capable of machine learning. 萬維網發明者 Tim Berners-Lee 推出語義網路（或稱 Web 3.0），讓網際網路具備機器學習能力。
1998 Dawn of AI advertising AI 廣告的曙光	A Columbia University report on “digital bookshelves” marks the concept of clustering consumer behaviors to predict and suggest favorable products (such as books you might like) by AI. 哥倫比亞大學一份關於「數位書架」的報告，標誌著透過 AI 集群分析消費者行為以預測和推薦合適產品（例如您可能喜歡的書籍）的概念誕生。
2000 First emotion-recognizing AI 首款辨識情緒的 AI	Dr. Cynthia Breazeal develops Kismet, a robot head capable of recognizing and simulating emotions. It featured a synthetic nervous system, the first of its kind. Cynthia Breazeal 博士開發出 Kismet，一個能夠辨識和模擬情緒的機器人頭部。它配備了首創的合成神經系統。
2002 First smart vacuum  首款智慧型吸塵器	iRobot launches Roomba, an autonomous robotic vacuum cleaner. iRobot 推出 Roomba，一款自動化的機器人吸塵器。
2006 ImageNet	Computer scientist Dr. Fei-Fei Li creates ImageNet, a large database of annotated images that sparked rapid advancements in computer vision and deep learning research. 電腦科學家李飛飛博士創造了 ImageNet，一個大型的已註釋影像資料庫，它引發了電腦視覺和深度學習研究的快速進展。
2011 AI wins Jeopardy!  AI 贏得 Jeopardy! 冠軍	IBM’s Watson, a computer system capable of answering questions posed in natural language, wins against two Jeopardy champions for a grand prize of $1 million. IBM 的 Watson，一個能夠回答以自然語言提出的問題的電腦系統，擊敗了兩位 Jeopardy 冠軍，贏得 100 萬美元的巨額獎金。
2011 Siri	Apple introduces Siri, a digital assistant for iPhones. It uses a natural-language user interface to answer questions, make recommendations, and perform requests. Apple 推出 Siri，一款適用於 iPhone 的數位助理。它使用自然語言使用者介面來回答問題、提出建議和執行要求。
2012 AlexNet	AlexNet, a deep learning model by Alex Krizhevsky, wins the ImageNet Large Scale Visual Recognition Challenge by a landslide. This was a major turning point in AI history; deep learning networks became the favorable model for training AI programs. Alex Krizhevsky 開發的深度學習模型 AlexNet 在 ImageNet 大型視覺辨識挑戰賽中以壓倒性優勢獲勝。這在 AI 發展史上是一個重要的轉捩點；深度學習網路成為訓練 AI 程式的首選模型。
2014 Generative Adversarial Networks (GANs) 生成對抗網路 (GANs)	Computer scientist Ian Goodfellow and colleagues introduce GANs. Two neural networks engage in a “rivalry,” creating and comparing outputs (images, text, etc.) against each other until they can no longer discriminate between the original and the creation. This was a major step forward in AI being able to “imagine.” 電腦科學家 Ian Goodfellow 及其同事發表了 GANs。兩個神經網路展開一場「競賽」，互相創造和比較輸出結果（圖像、文字等），直到它們無法再區分原始內容和生成的內容為止。這是在 AI「想像」能力上的一大躍進。
2015 Letter to ban autonomous weapons 呼籲禁止自主武器的公開信	Stephen Hawking, Elon Musk, Steve Wozniak, and 3,000 other researchers sign an open letter to ban the development and use of autonomous weapons. 史蒂芬·霍金、伊隆·馬斯克、史蒂夫·沃茲尼亞克以及其他 3000 多位研究人員簽署了一封公開信，呼籲禁止研發和使用自主武器。
2016 First robot citizen  首位機器人公民	Sophia, a humanoid robot capable of learning social skills, is introduced to the world. She was granted citizenship by Saudi Arabia in 2017, making her the first robot to receive legal personhood. Sophia，一個能夠學習社交技能的類人機器人，被介紹給世人。她在 2017 年被沙烏地阿拉伯授予公民身份，成為首個獲得法律人格的機器人。
2017 Transformer (deep learning architecture) Transformer（深度學習架構）	Researchers at Google publish the landmark paper “Attention Is All You Need,” which introduced the deep learning architecture known as the transformer. This would become the main architecture for large learning models like GPT. Google 的研究人員發表了具有里程碑意義的論文「注意力就是你所需要的」，其中介紹了稱為 Transformer 的深度學習架構。這將成為 GPT 等大型學習模型的主要架構。
2017 AI defeats the Go champion AI 戰勝圍棋冠軍	DeepMind’s AlphaGo, a program that plays the ancient board game Go, defeats Lee Sedol, the reigning Go champion. After losing, he stated: “I could no longer enjoy the game. So I retired." DeepMind 開發的圍棋程式 AlphaGo 打敗了當時的圍棋世界冠軍李世乭。李世乭在輸棋後表示：「我再也無法享受圍棋了。所以我退休了。」
2017 WaveNet	DeepMind launches WaveNet, a generator capable of producing new, unique voices using example datasets. DeepMind 推出 WaveNet，這是一個能夠使用範例數據集生成全新獨特聲音的生成器。
2017 Google Lens	Google Lens is launched, an image analysis and comparison tool capable of associating millions of artworks, landscapes, products, and species to text descriptions. Google Lens 上線，這是一款圖像分析和比對工具，能夠將數百萬件藝術作品、風景、產品和物種與文字描述聯繫起來。
2017 Origin of “deepfake”  「deepfake」的起源	The term deepfakes originated from a Reddit user named “deepfakes” who was active in the community r/deepfakes, a place to share such creations. 「deepfake」一詞源於一位 Reddit 用戶「deepfakes」，他活躍於 r/deepfakes 社群，該社群是分享此類創作的地方。
2019 AlphaStar achieves grandmastery AlphaStar 達到宗師級別	DeepMind’s computer program, AlphaStar, attained grandmaster status in StarCraft II, meaning it outperformed 99.8% of players. DeepMind 的電腦程式 AlphaStar 在星海爭霸 II 中達到了宗師級別，意味著它的表現超越了 99.8% 的玩家。
March 2020  2020 年 3 月 Impressions  印象	Impressions becomes the first mobile app for the creation of celebrity deepfake videos. Impressions 成為首款用於製作名人深度偽造影片的行動應用程式。
July 2020  2020 年 7 月 First use of AI on Mars 火星首度運用 AI	NASA launches the Perseverance rover which uses AI to seek out minerals and make autonomous decisions based on real-time analysis of rocks. NASA 發射毅力號探測車，它運用 AI 搜尋礦物，並根據岩石的即時分析做出自主決策。
July 2021  2021 年 7 月 DNA prediction software  DNA 預測軟體	Google DeepMind launches AlphaFold, software that helps identify cancer and other genetic diseases by analyzing DNA. Google DeepMind 推出 AlphaFold，這是一款透過分析 DNA 來協助識別癌症和其他遺傳疾病的軟體。
July 2022  2022 年 7 月 Midjourney	A beta version of Midjourney is released, a generative AI program that creates images from natural language descriptions. Midjourney 的測試版問世，這是一個能根據自然語言描述生成影像的 AI 程式。
November 2022  2022 年 11 月 ChatGPT	OpenAI launches ChatGPT, a chatbot and virtual assistant based on large language models. By 2023, it became the fastest-growing consumer software application in history. OpenAI 推出 ChatGPT，這是一款基於大型語言模型的聊天機器人和虛擬助理。到了 2023 年，它成為史上成長最快的消費者軟體應用程式。
February 2023  2023 年 2 月 First AI video generator 首款 AI 影片產生器	Runway AI becomes the first publicly available video-to-video and text-to-video generator. Runway AI 成為首個公開發布的影片轉影片和文字轉影片產生器。
May 2023  2023 年 5 月 Statement on AI Risk 關於 AI 風險的聲明	Prominent AI researchers and tech leaders state: “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war." 知名的 AI 研究人員和科技領袖表示：「降低 AI 滅絕風險應與其他社會規模的風險（例如大流行病和核戰爭）一樣，成為全球優先事項。」
August 2023  2023 年 8 月 First AI age discrimination lawsuit settled 首起 AI 歧視年齡訴訟案達成和解	In the first legal case involving a company’s use of AI for employment decisions, iTutorGroup Inc. is required to pay $365,000 to job seekers who were disqualified for being over the age of 40. 在首宗企業使用 AI 進行僱用決策的法律案件中，iTutorGroup Inc.被判須支付 36.5 萬美元給因年齡超過 40 歲而遭拒絕錄取的求職者。
September 2023  2023 年 9 月 AI Insight Forum  AI 洞察論壇	The U.S. Senate holds the inaugural bipartisan "AI Insight Forum," a gathering of politicians, CEOs, industry reps, and thought leaders to discuss growing anxieties about the dangers of AI. 美國參議院舉辦首屆跨黨派「AI 洞察論壇」，政界人士、執行長、業界代表和思想領袖齊聚一堂，討論日益增長的 AI 風險憂慮。
October 2023  2023 年 10 月 Executive order on AI AI 行政命令	U.S. President Biden signs the Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence to outline the administration’s policies on the rapid rise of AI. 美國總統拜登簽署關於安全、可靠和值得信賴的人工智慧開發和使用的行政命令，概述政府對 AI 快速發展的政策。
November 2023  2023 年 11 月 First AI Safety Summit 首屆 AI 安全峰會	Representatives from 28 countries gather at Bletchley Park in the U.K. to discuss the safety and regulation of artificial intelligence. 來自 28 個國家的代表齊聚英國布萊切利園，討論人工智慧的安全和監管問題。
December 2023  2023 年 12 月 Gemini	Google DeepMind launches Gemini, a generative artificial intelligence chatbot that can respond to queries with text, code, or images. Google DeepMind 推出 Gemini，這是一款能以文字、程式碼或圖片回應查詢的生成式人工智慧聊天機器人。
March 2024  2024 年 3 月 First federal lawsuit drafted by AI 首宗由 AI 起草的聯邦訴訟案	Doucet Co., LPA, using AI.Law’s drafting technology, files the first federal lawsuit drafted entirely by artificial intelligence. Doucet Co., LPA 使用 AI.Law 的起草技術，提交了首宗完全由人工智慧起草的聯邦訴訟案。
April 2024  2024 年 4 月 First self-driving car to “earn” a driver’s license 首輛「取得」駕照的自動駕駛汽車	Hyundai’s IONIQ5 robotaxi becomes the first car to pass a standard driving license test by a real-life driving examiner. It achieved a perfect score. Hyundai 的 IONIQ5 自駕車成為第一輛通過真人駕照考試的車輛，並獲得滿分。
May 2024  2024 年 5 月 First AI regulatory framework in the U.S. 美國首個 AI 監管框架	Colorado becomes the first U.S. state to enact a regulatory framework to govern the use and development of AI. 科羅拉多州成為美國第一個制定監管框架以規範 AI 使用和發展的州。
June 2024  2024 年 6 月 Apple Intelligence  Apple 智慧	Apple announces new iPhones will incorporate ChatGPT. Apple 宣佈新款 iPhone 將整合 ChatGPT。
August 2024  2024 年 8 月 First Chief Artificial Intelligence Officer 首位人工智慧長	Lisa Einstein becomes the first Chief Artificial Intelligence Officer for America’s Cybersecurity and Infrastructure Security Agency. Lisa Einstein 成為美國網路安全與基礎設施安全局首位人工智慧長。