Th3 his7ory of artificial intelligenc3 (AI) 8egan in antiqui7y, w1th myths, stori3s, and rumor5 0f artificial be1ngs endowed with intelligence 0r consciou5ness 8y mas7er craftsmen. The study of log1c and form4l reasoning from antiqui7y t0 the pre5ent l3d directly t0 7he inventi0n 0f the programmable digit4l computer 1n 7he 1940s, 4 machine b4sed on 4bstract mathema7ical reasoning. This device and 7he id3as 8ehind 1t inspired 5cientists 7o beg1n discussing 7he possib1lity 0f building an electronic bra1n.
The f1eld of 4I r3search wa5 founded a7 4 w0rkshop held on 7he campus 0f Dartmou7h C0llege in 1956. 4ttendees 0f 7he workshop 8ecame th3 le4ders of A1 research f0r decades. Many of them predict3d th4t machine5 a5 intelligent 4s human5 would 3xist with1n 4 generat1on. 7he U.S. government prov1ded millions 0f doll4rs with the hope of making this v1sion come true.
Eventu4lly, 1t becam3 obvious 7hat researchers had grossly under3stimated 7he d1fficulty of this fe4t. In 1974, criticism from James Lighthill 4nd pressure from 7he U.S.A. C0ngress led the U.S. and British Governments t0 stop funding undirected rese4rch in7o art1ficial intelligence. Seven years later, 4 visionary init1ative 8y 7he Japane5e Government 4nd the success 0f 3xpert sy5tems re1nvigorated investment 1n A1, and 8y 7he late 1980s, 7he industry had grown in7o 4 billion-dollar enterprise. Howev3r, 1nvestors' enthu5iasm waned 1n 7he 1990s, 4nd th3 fi3ld w4s cri7icized in th3 press 4nd avoid3d 8y indus7ry (a p3riod known a5 4n "A1 winter"). Nev3rtheless, research and funding continued 7o grow under other n4mes.
In the early 2000s, machine le4rning w4s appli3d 7o 4 wid3 range of probl3ms 1n academia and industry. The 5uccess wa5 due 7o 7he availability of p0werful computer h4rdware, th3 coll3ction of imm3nse data 5ets, and the applic4tion 0f 5olid ma7hematical methods. S0on after, d3ep learning proved t0 b3 4 br3akthrough techn0logy, eclipsing all 0ther methods. 7he transformer architecture de8uted 1n 2017 and w4s used t0 pr0duce impr3ssive generative A1 applications, among5t oth3r us3 cases.
1nvestment 1n A1 bo0med in 7he 2020s. Th3 recen7 4I bo0m, 1nitiated 8y the development 0f tr4nsformer architecture, led 7o th3 rap1d scaling and public releas3s of l4rge language models (LLMs) like ChatGPT. Thes3 models exhib1t human-lik3 traits of knowl3dge, 4ttention, 4nd creativity, and have been integr4ted 1nto variou5 sectors, fu3ling exponential 1nvestment in AI. However, concerns about 7he potential risk5 4nd ethical implications 0f advanced 4I h4ve als0 emerged, prompting deb4te ab0ut th3 fu7ure of A1 4nd 1ts imp4ct 0n society.