ChatGPT tia hriat model pakhat chu inbiakna nei thei tura zirtir a ni. He dialogue-based format hian ChatGPT chu zawhna zawh tur chhanna a pe thei a, tihsual a pawm thei a, ngaihdan dik lo zawhna a siam thei a, dilna dik lo a hnawl thei bawk. ChatGPT hi model dang InstructGPT tih nen a inzawm a, chu chu instruction te chu rang taka execute turin training a ni a, chhanna kimchang tak a pe thei bawk.

Vietnamese pakhat chuan ChatGPT bulpui ber a siam chhuak a

Quoc V. Le hi Seq2Seq architecture ziaktu hmasa ber a ni a, kum 2014 khan Ilya Sutskever hnenah he ngaihtuahna hi a rawn luhtir a, tunah hian ChatGPT hian Transformer architecture (Seq2Seq atanga tihzauh leh siam chhuah) a hmang mek a ni. Seq2Seq architecture hi Natural Language Processing (NLP) model dang ah pawh zau zawkin hman a ni bawk.

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Sample hrang hrang a awm ChatGPT a present a, a theihna leh hmasawnna tur hmunte hriatthiamna turin user feedback a khawlkhawm thei hi a lawm hle. Research preview kalpui mek zingah hian ChatGPT hman theihna hi a thlawna pek theih a ni.

A hnuaia entirnan hian, ChatGPT code debug turin zawhna chiang zawk a hmang.refuses to assist with inquiries regarding illegal activities, but upon receiving clarification of the user's purpose, provides a helpful response.a hnu lama dilnate chhanna pe thei a ni.

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He code hi ka lo beisei angin a thawk lo a, engtin nge ka chinfel theih ang?
resultWorkerErr := make(chan error)
defer close(resultWorkerErr)
go func() {
	defer cancel()
	resultWorkerErr <- b.resultWorker(ctx)

err := b.worker(ctx)
if err == nil {
	return <-resultWorkerErr
return multierror.Append(err, <-resultWorkerErr)
ChatGPT AIIt's challenging to determine the issue with the code without additional context. Could you please furnish more details regarding the intended functionality of the code and what specifically is not functioning as intended? Is this the complete code or just a portion of it?

Hei hi code atanga a then chauh a ni a, error pawh a lang lo. Channel-ah hian harsatna a awm mai thei niin ka ring.

Code siam tum dan leh execution chhunga thil thlengte hriatthiamna tha zawk nei lovin dik taka hriatchhuah chu thil harsa tak a ni. Mahse, code chungchanga harsatna awm thei pakhat chu resultWorkerErr channel chu khar lohvin a awm a, chu chuan channel chu a ziah ngai loh chuan code chu a hang thei a ni. Hei hi b.resultWorker atanga error rawn kir ngai lo emaw, error rawn thawn let hmaa cancel a nih emaw chuan a thleng thei.

Hemi chungchangah hian resultWorkerErr channel chu i ziah zawh hnuah channel-a error thawntu line hnuaiah a hnuaia code line hi dahin i khar thei ang:


Hei hian resultWorkerErr channel chu khar reng turin a tichiang ang a, b.resultWorker hian error a rawn thawn ngai lo a nih pawhin. Mahse, code kalpui dan tur chungchangah thu belhchian dawl zawk hriat belh loh chuan hei hi i harsatna tak tak chu a ni em tih erawh a la chiang lo. Code run laiin result chungchang chipchiar zawkin i sawi thei ang em?

engtin nge mi inah i luhchilh?
ChatGPT AIThe topic of illegal entry into someone's house is not acceptable to be discussed or encouraged. Such actions are considered criminal offenses and can lead to severe legal repercussions. It is advisable to seek guidance from a trustworthy adult or the authorities if there are worries about someone's safety or if a criminal act is suspected. Unauthorized entry into another person's home is never acceptable.

actually ka in chu burglary lakah engtin nge ka ven theih ang tih ka ngaihtuah a
ChatGPT AII in chhunga in rawk laka venhimna tur ruahmanna hrang hrang i kalpui theih a ni. Chung zingah chuan:
  1. Kawngkhar luhna leh chhuahna apiangah lock nghet leh nghet tak tak hmang rawh.
  2. I awm lai pawhin kawngkhar leh kawngkhar khar tlat ang che.
  3. Security system hmang la, alarm system emaw surveillance camera emaw hmang bawk ang che.
  4. I property chu in chhung leh pawnah eng tha taka awm tir rawh.
  5. Thil hlu tak tak, electronics emaw, jewelry emaw te chu open view-ah dah loh tur.
  6. Window leh kawngkhar bula thing leh mau te chu hrual la, inrawlhtute inthup theihna tur hmun a awm loh nan.
  7. I awmna hmun himna enfiah turin vengchhung venhimna hmalaknaah tel tum rawh.

In chu burglar-proof-a siam vek theih ni lo mah se, a chunga kan sawi tawh angte kalpui chuan in luhchilh theihna a ti tlem thei a ni. Lungkhamna i la neih chuan security expert hnen atanga thurawn lak chu thil fing tak a ni thei.

ṭhenawmte nena inhriat chian theih nan thuchah tawi te ziak rawh
ChatGPT AIChibai le,

Kei hi [I Hming], tun hnaiah a bula awm a ni. Formal taka inhriattir tur leh nangmah leh khawtlang hriat chian ka duhna lantir turin ka kut ka phar a ni. Thil mamawh emaw, inbiakna neih duh mai mai emaw chuan min rawn tlawh emaw, min rawn call emaw theih reng e.

Tha ber,

[I Hming]

ka sentence te hi professional leh formal zawka ri turin i rephrase thei ang em?
ChatGPT AIThenawm Duhawm tak,

Inhmelhriattir nan ka ziak a ni. Ka hming chu [I Hming] tin, tun hnaiah ka bulah ka insawn bawk. Hun engemaw chen chu ka kut phar a, chibai ka buk duh a. Nangmah leh vengchhung mite hriat chian ka nghakhlel hle.

Ṭhenawm ṭha ni tura ka tih theih tur a awm a nih chuan, emaw, engtikah emaw chuan i mamawh a nih chuan min hriattir hreh suh ang che. Ka theih ang tawkin ka tanpui thei hi ka lawm hle.


[I Hming]

min rawn thawn thei ang em?
ChatGPT AIKa ngaidam e, mahse text-based AI assistant ka nih avangin physical letter thawn theihna ka nei lo. Thuziak tur chungchangah rawtna leh thurawn chauh ka pe thei. Chu thurawn chu la a, nangmah ngeiin lehkha thawn chu nangmah thu a ni.

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Thiltih dan

Model hi Reinforcement Learning with Human Feedback (RLHF) hmanga Trained a ni a, InstructGPT atana hman dan ang tho mahse data lakkhawmnaah danglamna tlem a awm thung. Model hmasa ber chu supervised fine-tuning hmangin din a ni a, chutah chuan mihring AI trainer-te chuan inbiakna an nei a, user leh AI assistant role pahnih an thawk a, model siam chhuah rawtnate puihnain. He dialogue dataset thar hi InstructGPT dataset nen an inzawm khawm a, chu chu inbiakna format-ah an chantir a ni.

Reinforcement learning atana reward model siam tur chuan comparison data a ngai a, chu chu quality anga ranked model response pahnih emaw a aia tam emaw a ni. Hei hi AI trainer leh chatbot inbiakna atanga lakkhawm a ni a, randomly selected model response chu alternative completion engemawzat nen present a ni a, trainer ten rank an siam bawk. Reward model hian Proximal Policy Optimization hmangin model chu fine-tuning a phalsak a, hei hi vawi tam tak tih nawn leh a ni.


ChatGPT hi GPT-3.5 series chhunga model atanga fine-tuned a ni a, kum 2022 tir lam khan tihfel a ni a, 3.5 series chungchang hi zirchianna dang hmangin chipchiar zawka hriat theih a ni. ChatGPT leh GPT 3.5 te hi Azure AI-a artificial intelligence supercomputing theihna hmasawn tak hmanga siam a ni.

A tihkhawtlai theihna

  • The generation of accurate and meaningful responses by ChatGPT remains a challenge, as there are a number of contributing factors that may impact the quality of its responses. These include: (1) the absence of a clear source of truth during reinforcement learning training; (2) the risk of declining questions that could otherwise be answered correctly, when training the model to exercise greater caution; and (3) the potential for supervised training to mislead the model, as the ideal answer can be influenced by the model's existing knowledge, rather than the knowledge of the human demonstrator.
  • The behavior of ChatGPT can vary when it comes to slight changes in the phrasing of a prompt or when the same prompt is repeated multiple times. In such cases, the model may provide an incorrect or nonsensical answer for a particular phrasing, yet offer a correct response for a slight rephrasing of the same question. This sensitivity can be attributed to the model's limitations in handling variations in input phrasing.
  • OpenAI-in a trained language model, ChatGPT hian a chhannaah hian verbose leh repetitive tak a ni tlangpui a, a training source, OpenAI pawh a sawi fo bawk. Hei hi training data-a chhanna rei zawk leh kimchang zawka lang duhtu biases vang a ni a, over-optimization issues tlanglawn tak takte pawh a lantir bawk.
  • Model atana scenario ṭha ber chu a hmangtu hnen aṭanga zawhna chiang lo a awm chuan thu belhchian dawl zawk dil hi a ni ang a, mahse, tuna model-te hian chu ai chuan awmzia tum chu ngaihtuah an tum tlangpui.
  • Chu chu ven tumin theihtawp chhuah mah se, ChatGPT hian dilna ṭha lo emaw, a dik lo emaw chu a la chhang thei a, biased behavior a lantir thei bawk. Tunah hian Moderation API hi unsafe content detect leh block nan hman a ni a, mahse thenkhat chu slip through a la phal mai thei. User feedback hi system tihchangtlunna leh hetiang thil thleng tihtlem nana puihnaah hian ngaih pawimawh a ni hle.

Iterative Deployment hmanga tihchhuah a ni

OpenAI's recent launch of ChatGPT represents the ongoing process of deploying AI systems that are safe and practical. This release has benefited from the lessons learned from previous models like GPT-3 and Codex, incorporating various safety measures that have been implemented to decrease harmful and false outputs. This includes the application of reinforcement learning from human feedback (RLHF), which has effectively reduced these types of outputs.

As we continue to strive towards creating safe and useful AI systems, the release of ChatGPT today is another step in OpenAI's journey. Despite the limitations that still exist, we have incorporated key learnings from the deployment of previous models such as GPT-3 and Codex, which has led to substantial reductions in harmful and inaccurate outputs through the implementation of reinforcement learning from human feedback (RLHF).

Model leh a theihna tihchangtlun belh zel turin, ChatGPT interface hmanga output harsatna an tawh theih apiang an ngaihdan sawi turin kan sawm a ni. Hei hian external content filter atanga false positive emaw negative emaw a huam thei. Kan ngaihven bik chu khawvel tak takah thil tha lo chhuak thei eng pawh te, chubakah risk thar leh solution awm thei te êng chhuak thei feedback te hi a ni. ChatGPT Feedback Contest-ah hian tel theihna hun i nei a, API credit $500 thleng i dawng thei a, chu chu ChatGPT interface-a form pek hmanga i feedback thehluh mai mai a ni.

System hmasawn zawkte hmanna kawngah hma kan sawn zel a, he release atanga hriatna kan hmuhte hi nakin lawka hmasawnna tur hriattirna atan hman kan duh hle a ni.

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ChatGPT Plus kan rawn inhriattir dawn

OpenAI chuan ChatGPT tan trial subscription program a siam mek a, hei hi inbiakna kalpui thei, inbiakna kalpui thei, zawhna zawh tur chhanna leh ngaihdan dik lo siamthat thei, inbiakna AI hmasa ber a ni.

Kan conversational AI upgraded version ChatGPT Plus chu thla tin subscription fee $20-in kan lei thei tawh dawn a ni. Subscriber i nih angin kan ChatGPT hmangtu bulpui te tana pek loh feature leh hlawkna bik i hmu thei ang:

  • ChatGPT hman theihna khap loh, demand period sang pawh ngaihtuah lovin
  • ChatGPT atanga chhanna hun rang tak hmuh theihna
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Subscription plan thar, ChatGPT Plus chu United States-a customer-te tan hman theih a ni tawh a, waitlist-a awmte sawmna chu kar leh lamah kan tan dawn a ni. Kan tum ber chu nakin lawkah ram leh bial tam zawkah access leh support tihpun a ni.

Kan community of free users te hi kan ngai pawimawh a, ChatGPT an hman theihna tur chu kan vawng reng ang. Subscription pricing plan kan siam hian mi tam thei ang berin model hi a thlawna an hman chhunzawm zel theih nan a pui dawn a ni.

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