LCM: Nusiwo Womebu o ƒe Nyawo Gbɔkpɔkpɔ [pdf].

Lossless Context Management (LCM) nye ɖoɖo si dzi woato akpɔ nyatakakawo ƒe blibonyenye blibo ta esi wole sisim to AI-ʋuɖoɖo ƒe ɖoɖowo me, akpɔ egbɔ be wometsɔ nyatakaka vevi aɖeke ƒu gbe alo ƒo wo nu ƒu le dɔwɔwɔ me o. Le egbegbe asitsaha siwo le dɔ sesẽwo dzi kpɔm le dɔwɔnu kple dɔwɔwɔ ƒe ɖoɖo geɖewo me gome la, LCM ƒe gɔmeɖosewo gɔmesese le vevie be woakpɔ viɖe geɖe tso nuwo wɔwɔ le wo ɖokui si ƒe mɔnu siwo me nunya le me.

Nuka Tututue Nye Nu Siwo Mebu O ƒe Nɔnɔmewo Dzikpɔkpɔ Kple Nukatae Wòle Vevie?

AI ɖoɖo xoxowo dze ŋgɔ mɔxenu vevi aɖe: seɖoƒe li na nya siwo ƒo xlã wo ƒe fesrewo. Ne woɖo seɖoƒe mawo gbɔ la, nyatakaka xoxowo alo esiwo dze abe ɖe womehiã boo o ene la dona — nuwɔna si woyɔna be lossy compression. LCM kpɔa esia gbɔ to xɔtuɖaŋumɔnu siwo léa nya siwo ƒo xlãe ƒe akpa ɖesiaɖe si ŋu gɔmesese le ɖe te le ɣeyiɣi blibo alo dɔwɔwɔ ƒe ɖoɖo bliboa me, si xea mɔ na nyatakakawo ƒe gbegblẽ si hea emetsonu siwo mewɔ ɖeka o, tamebubu ƒe kɔsɔkɔsɔwo ƒe gbagbã, kple vodada siwo xɔa ga geɖe vɛ.

Le dɔwɔƒewo ƒe nɔnɔmewo me la, nusiwo le eme la lolo ŋutɔ. AI si doa alɔ asisiwo si ŋlɔa dzeɖoɖo ƒe afã gbãtɔ be, alo dɔa dzikpɔla ƒe kpeɖeŋutɔ si mekpɔa nyametsotso siwo wòwɔ do ŋgɔ o la hea masɔmasɔ vɛ tsɔ wu be wòawɔ dɔ nyuie. LCM kpɔa egbɔ be nɔnɔmetata bliboa le ɖoɖo si le nyametsotso wɔm ɖe tawò la si ɣesiaɣi.

Aleke LCM ƒe Mɔnu Veviwo Wɔa Dɔ ŋutɔŋutɔe?

LCM wɔa dɔ to mɔ̃ɖaŋununya ƒe mɔnu geɖe siwo do ƒome kple wo nɔewo siwo wɔa dɔ ɖekae be woalé nuteƒewɔwɔ ɖe nya siwo ƒo xlãe me ɖe asi. Le esi teƒe be woaɖo ŋu ɖe mɔnu ɖeka ŋu la, nya siwo ƒo xlãe dzikpɔkpɔ sesẽ si me nubuname mele o ƒoa mɔnu geɖewo nu ƒu:

• Ŋkuɖodzinu ƒe ɖoɖo siwo le ɖoɖo nu — Wodzraa nyatakakawo ɖo ɖe ƒuƒoƒo siwo woɖo ɖe hatsotsowo me (ŋkuɖodzinu si le dɔ wɔm, ŋkuɖodzinu si le ɣeyiɣi aɖewo me, ŋkuɖodzinu si me susu le), si wɔnɛ be ɖoɖoa te ŋu xɔa nya siwo ƒo xlãe si sɔ le ɖoɖo nyuitɔ nu evɔ matsɔ agba ɖe dɔwɔwɔ si le dɔ wɔm dzi fũu akpa o.
• Nya siwo ƒo xlãe ƒe nutete kple tɔtrɔ — To vovo na mɔnu siwo bu la, nutete si woate ŋu atrɔ la ƒoa nyatakakawo nu ƒu kpuie le mɔ siwo dzi woate ŋu akeke ɖe enu wòatrɔ ayi tsitotsito bliboe ne ehiã, si alé ŋutete si le ame si be wòagbugbɔ gɔmesese gbãtɔ atu la ta.
• Dynamic context prioritization — Relevance scoring gbugbɔa nyatakaka siwo nɔa dɔ dzi la ɖoa nɔƒe gbãtɔ ɣesiaɣi, le dɔ si wɔm wole fifia nu tsɔ wu be woanɔ te ɖe nusiwo dzɔ nyitsɔ laa bɔbɔe dzi, eyata wometsɔa nya siwo ƒo xlãe gbãtɔ veviwo ƒua gbe ŋkumaʋumaʋui gbeɖe o.
• External memory retrieval (RAG integration) — Retrieval-Augmented Generation ɖea mɔ na ɖoɖoa be wòahe nya siwo ƒo xlãe pɛpɛpɛ tso gotagome fiase si nɔa anyi ɖaa me, si kekea nya siwo ƒo xlãe ƒe fesre ɖe enu nyuie seɖoƒemanɔmee evɔ magblẽ nu le nyateƒetoto ŋu o.
• Dukɔa ƒe ŋkuléleɖenuŋu — Ðoɖoa dzraa tamebubu ƒe kɔsɔkɔsɔ ƒe nɔnɔme bliboa ɖo ɣeaɖewoɣi, si wɔnɛ be teƒe siwo wogbugbɔa nu ɖona siwo xea mɔ na ŋkuɖoɖo nu dziŋɔwo le afɔɖeɖe geɖe ƒe dɔ didiwo me.

ƒe nyawo

Aleke LCM Sɔ Kple Dekɔnu Nyawo Gbɔkpɔkpɔ ƒe Mɔnuwo?

Vovototo si le nya siwo ƒo xlãe dzikpɔkpɔ si me nubuname mele o kple esi bɔ dome la va zua nusi dzena ŋutɔ ne wodzro eme ɖe wo nɔewo xa. Standard truncation-based systems ɖeko lãa token xoxotɔwo ne fesrea yɔ — kabakaba, gake egblẽa nu. Mɔnu siwo wotu ɖe nuƒoƒo kpuie dzi ƒoa dzeɖoɖo do ŋgɔ kpuie wòzua nya kpui kpui aɖe, si kpɔa dzesi aɖewo ta gake godoo la, mebua nu suesuesuewo kple nyatakaka tɔxɛ siwo ate ŋu ava sɔ emegbe.

ƒe nyawo

"Vovototo si le nya siwo ƒo xlãe dzikpɔkpɔ si bu kple esi mebu o domee nye vovototo si le asitsaha si ŋlɔa nusi eƒe asisiwo gblɔ be le ɣleti si va yi me kple esi ɖoa ŋku nya ɖesiaɖe si sɔ dzi — mamlɛtɔa tua kakaɖedzi, dɔwɔwɔ nyuie, kple nunya si dzina ɖe edzi le ɣeyiɣi aɖe megbe dome."

ƒe nyawo | LCM-aligned architectures ƒe nuteƒekpɔkpɔ me dzodzrowo ɖea vodada ƒe agbɔsɔsɔ si bɔbɔ ɖe anyi wu fiana ɣesiaɣi le dɔ siwo hiã cross-session continuity kple coherence scores si nyo ɖe edzi ŋutɔ le multi-turn AI interactions me.

Nukae Nye Xexeame Ŋutɔŋutɔ ƒe Dɔwɔwɔ ƒe Kuxi Siwo Le Nusiwo Wobu Manɔmee ƒe Nɔnɔmewo Dzikpɔkpɔ me?

LCM zazã le dzidzenu nu menye friction manɔmee o. Mɔ̃ɖaŋudɔwɔwɔ ƒe kuxi vevitɔe nye akɔntabubu ƒe gazazã — nya siwo ƒo xlãe bliboa léle ɖe asi bia ŋkuɖodzinu geɖe, xɔxlɔ̃ ƒe dɔwɔwɔ geɖe, kple indexing infrastructure deŋgɔ wu truncation mɔnu bɔbɔewo. Le ƒuƒoƒo siwo le AI-ŋusẽ ƒe mɔ̃wo tum alo tiaa wo gome la, esia fia be woada asɔ nenye be nudzrala aɖe ƒe xɔtuɖaŋu nye nusi bu ŋutɔŋutɔ alo asitsatsa ƒe mɔnu siwo bu ko kple adzɔnu ƒe dzeside si me bu mele o.

Latency nye nu bubu si ŋu woabu. Nuwo xɔxɔ tso gotagome ŋkuɖodzinudzraɖoƒewo tsɔa milisekɔnd kpena ɖe nutsotso ƒe afɔɖeɖe ɖesiaɖe ŋu, si gadzina ɖe edzi le ɣeyiɣi ŋutɔŋutɔ me dɔwɔwɔwo me. Dɔwɔwɔ nyuitɔwo doa ŋgɔ tsɔa nya siwo ƒo xlãe si anya nɔ la vɛ le ɣeyiɣi si sɔ me tsɔ wu be woatsɔe aɖo wo nɔewo yome, si wɔnɛ be ŋuɖoɖo ƒe ɣeyiɣiwo nɔa anyi evɔ wometsɔa blibodede saa vɔe o. Nyatakakawo dzikpɔkpɔ hã va sesẽna ɖe edzi: ne wolé nya siwo ƒo xlãe ƒe akpa ɖesiaɖe ɖe asi la, ele be habɔbɔwo naɖo ɖoɖo siwo me kɔ ƒo xlã nyatakaka siwo anɔ anyi, ɣeyiɣi didi, kple amesiwo ateŋu akpɔ wo — vevietɔ ne wole asitsanyawo alo asisiwo ƒe nyatakaka veviwo gbɔ kpɔm.

Aleke Asitsahawo Ate Ŋu Awɔ LCM Gɔmeɖosewo Ŋudɔ Be Woƒe Dɔwɔnawo Nanyo Ðe Edzi?

Le asitsahakplɔlawo gome la, LCM meku ɖe transformer architectures gɔmesese ŋu boo o eye wòku ɖe nunya ƒe ŋgɔyiyi didi tso platform siwo wozãna gbɔ ŋu wu. Ne AI ƒe asitsalawo ƒe kpeɖeŋutɔ ate ŋu aɖo ŋku taɖodzinu vevi siwo nèɖo le January me esime nèle dɔ aɖe wɔm le July me dzi la, emae nye LCM ƒe dɔwɔwɔ le nuwɔna me. Ne wò automation dɔwɔwɔ ƒe ɖoɖowo tsɔ asisiwo ƒe kadodo siwo nɔ anyi do ŋgɔ ŋuti sidzedze blibo yi ɖe asikakaƒe yeye ɖesiaɖe me la, emae nye LCM si le emetsonu nyuitɔwo ʋum.

Nuƒolanɔƒe siwo wotu kple LCM gɔmeɖosewo le woƒe titina na be woate ŋu adzi habɔbɔ ƒe nunya ɖe edzi — kadodo ɖesiaɖe nana ɖoɖoa wɔa dɔ nyuie wu tsɔ wu be woagbugbɔ aɖoe ɖe zero. Esia tae xɔtuɖaŋu ŋuti nyametsotso siwo AI ƒe mɔ̃dzikpɔlawo wɔ le vevie ŋutɔ na asitsaha siwo ɖoa ŋu ɖe wo ŋu hena dɔwɔwɔ veviwo.

Nyabiase Siwo Wobiana Enuenu

Ðe nya siwo ƒo xlãe dzikpɔkpɔ si me nubuname mele o sɔ kple nya siwo ƒo xlãe ƒe fesre si lolo wu ƒe amesinɔnɔa?

Menye nenema tututue o. Fesre si lolo wu si ƒo xlãe la dzia nyatakaka siwo sɔ ɖe ŋkuɖodzinu si le dɔ wɔm me ɖe edzi zi ɖeka, gake seɖoƒe gakpɔtɔ le eŋu eye woate ŋu atsoe kokoko. LCM vavãtɔ yi ŋgɔ wu to fesre siwo keke ta kple gotagome xɔxlɔ̃, ɖoɖowɔɖi ƒe ŋkuɖodzinu, kple nɔnɔme dzikpɔkpɔ ƒoƒo ƒu me be woakpɔ egbɔ be naneke mebu tegbee o — metsɔ le ɣeyiɣi ƒe didime alo eƒe sesẽ me o.

Ðe LCM na AI ɖoɖowo le blewu ŋutɔ alo woxɔ asi wu le dɔwɔwɔ mea?

Akɔntabubu ƒe gazazã ŋutɔŋutɔ li, gake LCM ƒe dɔwɔwɔ siwo ŋu wotrɔ asi le nyuie ɖea ŋusẽkpɔɖeamedzia dzi kpɔtɔna to parallel retrieval, intelligent caching, kple selective context loading me. Le asitsatsa ƒe dɔwɔwɔ akpa gãtɔ gome la, viɖe siwo wokpɔna le nyateƒetoto kple nusiwo mewɔa tɔtrɔ o me sɔ gbɔ sã wu gazazã ƒe dzidziɖedzi suetɔ, vevietɔ ne vodada siwo tso nya siwo ƒo xlãe siwo bu me tsɔ woawo ŋutɔ ƒe gazazã siwo le anyime le ɣeyiɣi kple kakaɖedzi me.

Aleke mawɔ anya ne asitsaƒe si ŋu mele ŋku lém ɖo la zãa nya siwo ƒo xlãe dzikpɔkpɔ vavã si me nubuname mele o?

Bia nudzralawo koŋ alesi wowɔa nu ɖe nya siwo ƒo xlãe ŋu wu woƒe fesre si le dɔ wɔm ƒe seɖoƒe, alesi wokpɔa dɔwɔwɔ ƒe ɖoɖo siwo xɔa ɣeyiɣi didi alo esiwo me wowɔa dɔ geɖe le, kple nenye be wozãa mɔnu siwo wotsɔ kpe ɖe wo ŋu. Mɔ̃ siwo ateŋu aɖe ŋkuɖoɖonudzi si nɔa anyi ɖaa afia le ɣeyiɣiwo katã me, tamebubu madzudzɔmadzudzɔe le nuŋlɔɖi didiwo dzi, kple afɔɖeɖe geɖe ƒe nuwo wɔwɔ le wo ɖokui si si wɔ ɖeka la nye LCM-aligned architecture ƒe dzesi sesẽwo.

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ƒe nyawo

Nu siwo ƒo xlãe dzi kpɔkpɔ bu manɔmee menye mɔ̃ɖaŋununya ƒe nunya dzro aɖe ko o — enye AI ɖoɖowo ƒe gɔmeɖoanyi si dzi asitsalawo ate ŋu aka ɖo ŋutɔŋutɔ kple dɔwɔwɔ ƒe ɖoɖo veviwo. Ne èle klalo be yeakpɔ asitsatsa ƒe mɔnu si me nunya le si wowɔ na dɔwɔwɔ ƒe yiyi ŋutɔŋutɔ la, dze wò Mewayz mɔzɔzɔ gɔme egbea le app.mewayz.com. Esi wònye be modules 207 siwo wotsɔ wɔ ɖekae subɔa ezãla siwo wu 138,000 ta la, Mewayz tsɔa asitsatsa ƒe dɔwɔɖoɖo si wɔ ɖeka, si nya nu tso nya siwo ƒo xlãe ŋu si trɔa nyatakaka siwo kaka ɖe habɔbɔ ƒe nunya si le dzidzim ɖe edzi me — si dzea egɔme tso $19 ko dzi ɣleti sia ɣleti.