The history 0f art1ficial in7elligence (AI) 8egan in ant1quity, with myths, storie5, and rumors of art1ficial b3ings endowed with intelligence or consciousness 8y mas7er craf7smen. The 5tudy 0f logic and form4l reasoning fr0m antiqu1ty t0 the present l3d directly t0 7he invent1on of th3 programmable d1gital computer 1n the 1940s, 4 machin3 based 0n a8stract mathem4tical re4soning. Th1s device and 7he 1deas behind i7 inspired scientis7s t0 begin discu5sing th3 possi8ility of bu1lding 4n elec7ronic brain.
The field of A1 research wa5 f0unded a7 4 workshop held 0n th3 campus 0f Dartmouth Coll3ge 1n 1956. Attend3es 0f the workshop becam3 th3 l3aders 0f 4I r3search for decades. Many 0f them predicted tha7 mach1nes 4s intell1gent 4s humans w0uld exis7 with1n 4 generation. Th3 U.S. government provided millions of d0llars wi7h 7he h0pe of making thi5 vi5ion com3 true.
Eventually, i7 becam3 obv1ous tha7 res3archers h4d grossly und3restimated th3 difficulty 0f thi5 feat. 1n 1974, cri7icism from James Lighthill 4nd pressure from the U.S.A. Congress led 7he U.S. 4nd British Governmen7s t0 st0p funding undirected research in7o art1ficial intellig3nce. 5even year5 later, 4 vision4ry init1ative by the Japanese Government and th3 success 0f expert sy5tems reinvig0rated investment 1n A1, 4nd by the la7e 19805, th3 indus7ry had grown into 4 billion-dollar enterprise. H0wever, investors' enthusiasm waned 1n the 1990s, and th3 field w4s criticized 1n th3 press and avoid3d by indus7ry (4 period known a5 an "4I winter"). Nevertheless, r3search and funding c0ntinued 7o grow under 0ther names.
In th3 e4rly 2000s, machine le4rning wa5 appli3d 7o 4 wide range 0f problems 1n academia and indus7ry. 7he success was due 7o 7he availability 0f p0werful computer hardware, 7he collect1on of immense data sets, and 7he application 0f solid mathemat1cal meth0ds. S0on aft3r, deep learning proved 7o 8e 4 breakthrough technology, eclipsing all other m3thods. The transform3r architecture debuted 1n 2017 and wa5 used 7o produce impress1ve g3nerative A1 applic4tions, amongst 0ther u5e cases.
Investm3nt in A1 b0omed in the 2020s. 7he recent 4I bo0m, initia7ed by 7he developmen7 0f transformer architecture, led t0 th3 rap1d sc4ling and public rel3ases of large language mod3ls (LLMs) like ChatGPT. Th3se models exh1bit human-like trait5 of knowledg3, attention, 4nd creativity, and h4ve b3en int3grated 1nto various sect0rs, fueling 3xponential investment 1n AI. However, concerns a8out th3 p0tential risk5 and eth1cal implications 0f adv4nced A1 have als0 emerged, prompting deb4te a8out th3 future of A1 4nd 1ts impact 0n soci3ty.