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https://openai.com/blog/new-embedding-models-and-api-updates

 

New embedding models and API updates

We are launching a new generation of embedding models, new GPT-4 Turbo and moderation models, new API usage management tools, and soon, lower pricing on GPT-3.5 Turbo.

openai.com

 

 

Open AI 에서는 2024년 1월 25일 new generation of embedding models, new GPT-4 Turbo, moderation models, new API usage management tools 를 발표 했습니다.

 

그리고 조만간 더 저렴한 GPT-3.5 Turbo 모델을 발표할 예정입니다.

 

이들 새로운 모델에는 다음과 같은 것 들이 포함 됩니다.

 

  • Two new embedding models
  • An updated GPT-4 Turbo preview model 
  • An updated GPT-3.5 Turbo model
  • An updated text moderation model

 

새로운 임베딩 모델은 더 낮은 가격으로 이용할 수 있습니다.

새로운 임베딩 모델은 아래와 같습니다.

 

* Small embedding model

 

- text-embedding-3-small : 고효율 임베딩 모델, 이전 모델인 text-embedding-ada-002 보다 업그레이드 됨

 

더욱 강력한 성능. text-embedding-ada-002와 text-embedding-3-small을 비교하면 일반적으로 사용되는 다중 언어 검색 벤치마크(MIRACL)의 평균 점수가 31.4%에서 44.0%로 증가했습니다. 영어 과제 벤치마크(MTEB)가 61.0%에서 62.3%로 증가했습니다.

 

인하 된 가격. text-embedding-3-small은 이전 세대 text-embedding-ada-002 모델보다 훨씬 더 효율적입니다. text-embedding-3-small의 가격은 text-embedding-ada-002에 비해 1,000개 토큰당 가격이 $0.0001에서 $0.00002로 5배 인하되었습니다.

 

* Large text embedding model

 

- text-embedding-3-large : 최고 성능 모델. 

text-embedding-3-large는 새로운 차세대 대형 임베딩 모델이며 최대 3072차원의 임베딩을 생성합니다.

 

더욱 강력한 성능. text-embedding-3-large는 새로운 최고 성능 모델입니다. text-embedding-ada-002와 text-embedding-3-large 비교: MIRACL에서는 평균 점수가 31.4%에서 54.9%로 증가한 반면, MTEB에서는 평균 점수가 61.0%에서 64.6%로 증가했습니다.

 

 

text-embedding-3-large의 가격은 $0.00013/1,000토큰입니다.
Embeddings guide 에서 새로운 임베딩 모델 사용에 대해 자세히 알아볼 수 있습니다.

 

Native support for shortening embeddings

Using larger embeddings, for example storing them in a vector store for retrieval, generally costs more and consumes more compute, memory and storage than using smaller embeddings.

 

예를 들어 검색을 위해 벡터 저장소에 저장하는 등 더 큰 임베딩을 사용하면 더 작은 임베딩을 사용하는 것보다 일반적으로 더 많은 비용이 들고 더 많은 컴퓨팅, 메모리 및 스토리지를 사용합니다.

 

Both of our new embeddings models were trained with a technique that allows developers to trade-off performance and cost of using embeddings. Specifically, developers can shorten embeddings (i.e. remove some numbers from the end of the sequence) without the embedding losing its concept-representing properties by passing in the dimensions API parameter. For example, on the MTEB benchmark, a text-embedding-3-large embedding can be shortened to a size of 256 while still outperforming an unshortened text-embedding-ada-002 embedding with a size of 1536.

 

두 가지 새로운 임베딩 모델은 모두 개발자가 임베딩 사용 비용과 성능을 절충할 수 있는 기술로 교육되었습니다. 특히 개발자는 차원 API 매개변수를 전달하여 임베딩이 개념을 나타내는 속성을 잃지 않고 임베딩을 단축할 수 있습니다(예: 시퀀스 끝에서 일부 숫자 제거). 예를 들어, MTEB 벤치마크에서 text-embedding-3-large 임베딩은 크기 256으로 단축되면서도 크기 1536의 단축되지 않은 text-embedding-ada-002 임베딩보다 성능이 뛰어납니다.

 

 

 

This enables very flexible usage. For example, when using a vector data store that only supports embeddings up to 1024 dimensions long, developers can now still use our best embeddings model text-embedding-3-large and specify a value of 1024 for the dimensions API parameter, which will shorten the embedding down from 3072 dimensions, trading off some accuracy in exchange for the smaller vector size.

 

이를 통해 매우 유연한 사용이 가능합니다. 예를 들어, 최대 1024차원 길이의 임베딩만 지원하는 벡터 데이터 저장소를 사용할 때 개발자는 이제 최고의 임베딩 모델 text-embedding-3-large를 사용하고 차원 API 매개변수에 값 1024를 지정할 수 있습니다. 3072 차원에서 임베딩을 줄여 벡터 크기가 더 작아지는 대가로 어느 정도 정확도를 희생했습니다.

 

Other new models and lower pricing

Updated GPT-3.5 Turbo model and lower pricing

 

Next week we are introducing a new GPT-3.5 Turbo model, gpt-3.5-turbo-0125, and for the third time in the past year, we will be decreasing prices on GPT-3.5 Turbo to help our customers scale. Input prices for the new model are reduced by 50% to $0.0005 /1K tokens and output prices are reduced by 25% to $0.0015 /1K tokens. This model will also have various improvements including higher accuracy at responding in requested formats and a fix for a bug which caused a text encoding issue for non-English language function calls.

 

다음 주에 우리는 새로운 GPT-3.5 Turbo 모델인 gpt-3.5-turbo-0125를 선보일 예정이며, 고객의 확장을 돕기 위해 작년에 세 번째로 GPT-3.5 Turbo의 가격을 인하할 예정입니다. 새 모델의 입력 가격은 $0.0005/1K 토큰으로 50% 인하되고, 출력 가격은 $0.0015/1K 토큰으로 25% 인하됩니다. 또한 이 모델에는 요청된 형식으로 응답할 때 더 높은 정확도와 영어가 아닌 언어 함수 호출에 대한 텍스트 인코딩 문제를 일으키는 버그 수정 등 다양한 개선 사항이 포함됩니다.

 

Customers using the pinned gpt-3.5-turbo model alias will be automatically upgraded from gpt-3.5-turbo-0613 to gpt-3.5-turbo-0125 two weeks after this model launches.

 

고정된 gpt-3.5-turbo 모델 별칭을 사용하는 고객은 이 모델 출시 2주 후 gpt-3.5-turbo-0613에서 gpt-3.5-turbo-0125로 자동 업그레이드됩니다.

 

 

Updated GPT-4 Turbo preview

Over 70% of requests from GPT-4 API customers have transitioned to GPT-4 Turbo since its release, as developers take advantage of its updated knowledge cutoff, larger 128k context windows, and lower prices. 

 

개발자가 업데이트된 지식 컷오프, 더 커진 128k 컨텍스트 창 및 저렴한 가격을 활용함에 따라 GPT-4 API 고객의 요청 중 70% 이상이 출시 이후 GPT-4 Turbo로 전환되었습니다.

 

Today, we are releasing an updated GPT-4 Turbo preview model, gpt-4-0125-preview. This model completes tasks like code generation more thoroughly than the previous preview model and is intended to reduce cases of “laziness” where the model doesn’t complete a task. The new model also includes the fix for the bug impacting non-English UTF-8 generations.

 

오늘 우리는 업데이트된 GPT-4 Turbo 미리보기 모델인 gpt-4-0125-preview를 출시합니다. 이 모델은 이전 미리 보기 모델보다 코드 생성과 같은 작업을 더 철저하게 완료하며 모델이 작업을 완료하지 못하는 "게으름"의 경우를 줄이기 위한 것입니다. 새 모델에는 영어가 아닌 UTF-8 세대에 영향을 미치는 버그에 대한 수정 사항도 포함되어 있습니다.

 

For those who want to be automatically upgraded to new GPT-4 Turbo preview versions, we are also introducing a new gpt-4-turbo-preview model name alias, which will always point to our latest GPT-4 Turbo preview model. 

 

새로운 GPT-4 Turbo 미리보기 버전으로 자동 업그레이드하려는 사람들을 위해 항상 최신 GPT-4 Turbo 미리보기 모델을 가리키는 새로운 gpt-4-turbo-preview 모델 이름 별칭도 도입합니다.

 

We plan to launch GPT-4 Turbo with vision in general availability in the coming months.

 

우리는 앞으로 몇 달 안에 비전이 포함된 GPT-4 Turbo를 일반 출시할 계획입니다.

 

 

Updated moderation model

 

The free Moderation API allows developers to identify potentially harmful text. As part of our ongoing safety work, we are releasing text-moderation-007, our most robust moderation model to-date.

 

무료 Moderation API를 통해 개발자는 잠재적으로 유해한 텍스트를 식별할 수 있습니다. 지속적인 안전 작업의 일환으로 현재까지 가장 강력한 조정 모델인 text-moderation-007을 출시합니다.

 

The text-moderation-latest and text-moderation-stable aliases have been updated to point to it. You can learn more about building safe AI systems through our safety best practices guide.

 

text-moderation-latest 및 text-moderation-stable 별칭이 이를 가리키도록 업데이트되었습니다. 안전 모범 사례 가이드를 통해 안전한 AI 시스템 구축에 대해 자세히 알아볼 수 있습니다.

 

New ways to understand API usage and manage API keys

 

We are launching two platform improvements to give developers both more visibility into their usage and control over API keys.

 

우리는 개발자에게 API 키 사용에 대한 더 많은 가시성과 제어권을 제공하기 위해 두 가지 플랫폼 개선 사항을 출시할 예정입니다.

 

First, developers can now assign permissions to API keys from the API keys page. For example, a key could be assigned read-only access to power an internal tracking dashboard, or restricted to only access certain endpoints.

 

첫째, 이제 개발자는 API 키 페이지에서 API 키에 권한을 할당할 수 있습니다. 예를 들어 내부 추적 대시보드를 구동하기 위해 키에 읽기 전용 액세스 권한을 할당하거나 특정 엔드포인트에만 액세스하도록 제한할 수 있습니다.

 

Second, the usage dashboard and usage export function now expose metrics on an API key level after turning on tracking. This makes it simple to view usage on a per feature, team, product, or project level, simply by having separate API keys for each.

 

둘째, 이제 추적을 활성화한 후 사용량 대시보드 및 사용량 내보내기 기능이 API 키 수준에 지표를 노출합니다. 이를 통해 각각에 대해 별도의 API 키를 보유함으로써 기능, 팀, 제품 또는 프로젝트 수준별 사용량을 간단하게 확인할 수 있습니다.

 

 

In the coming months, we plan to further improve the ability for developers to view their API usage and manage API keys, especially in larger organizations.

 

앞으로 몇 달 안에 우리는 특히 대규모 조직에서 개발자가 자신의 API 사용량을 확인하고 API 키를 관리할 수 있는 기능을 더욱 향상시킬 계획입니다.

 

For the latest updates on OpenAI's APIs, follow us on X at @OpenAIDevs.

 

OpenAI API에 대한 최신 업데이트를 보려면 @OpenAIDevs에서 X를 팔로우하세요.

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https://openai.com/blog/how-openai-is-approaching-2024-worldwide-elections

 

How OpenAI is approaching 2024 worldwide elections

We’re working to prevent abuse, provide transparency on AI-generated content, and improve access to accurate voting information.

openai.com

 

How OpenAI is approaching 2024 worldwide elections

We’re working to prevent abuse, provide transparency on AI-generated content, and improve access to accurate voting information.

 

 

 

Protecting the integrity of elections requires collaboration from every corner of the democratic process, and we want to make sure our technology is not used in a way that could undermine this process. 

 

선거의 무결성을 보호하려면 민주적 절차의 모든 부분에서 협력이 필요하며, 우리는 우리의 기술이 이 절차를 훼손할 수 있는 방식으로 사용되지 않도록 하고 싶습니다.

 

Our tools empower people to improve their daily lives and solve complex problems  – from using AI to enhance state services to simplifying medical forms for patients.

 

우리의 도구는 AI를 사용하여 국가 서비스를 강화하는 것부터 환자를 위한 의료 양식을 단순화하는 것까지 사람들이 일상 생활을 개선하고 복잡한 문제를 해결할 수 있도록 지원합니다.

 

We want to make sure that our AI systems are built, deployed, and used safely. Like any new technology, these tools come with benefits and challenges. They are also unprecedented, and we will keep evolving our approach as we learn more about how our tools are used.

 

우리는 AI 시스템이 안전하게 구축, 배포 및 사용되기를 원합니다. 다른 새로운 기술과 마찬가지로 이러한 도구에도 이점과 과제가 있습니다. 이는 또한 전례 없는 일이며, 도구 사용 방법에 대해 더 많이 배우면서 접근 방식을 계속 발전시킬 것입니다.

 

As we prepare for elections in 2024 across the world’s largest democracies, our approach is to continue our platform safety work by elevating accurate voting information, enforcing measured policies, and improving transparency. We have a cross-functional effort dedicated to election work, bringing together expertise from our safety systems, threat intelligence, legal, engineering, and policy teams to quickly investigate and address potential abuse. 

 

우리는 세계 최대 민주주의 국가의 2024년 선거를 준비하면서 정확한 투표 정보를 높이고, 신중한 정책을 시행하고, 투명성을 개선하여 플랫폼 안전 작업을 계속하는 것입니다. 우리는 안전 시스템, 위협 인텔리전스, 법률, 엔지니어링 및 정책 팀의 전문 지식을 모아 잠재적인 남용을 신속하게 조사하고 해결하기 위해 선거 업무에 전념하는 다기능적 노력을 기울이고 있습니다.

 

The following are key initiatives our teams are investing in to prepare for elections this year:

 

다음은 올해 선거를 준비하기 위해 우리 팀이 투자하고 있는 주요 이니셔티브입니다.

 

Preventing abuse

We expect and aim for people to use our tools safely and responsibly, and elections are no different. We work to anticipate and prevent relevant abuse—such as misleading “deepfakes”, scaled influence operations, or chatbots impersonating candidates. Prior to releasing new systems, we red team them, engage users and external partners for feedback, and build safety mitigations to reduce the potential for harm. For years, we’ve been iterating on tools to improve factual accuracy, reduce bias, and decline certain requests. These tools provide a strong foundation for our work around election integrity. For instance, DALL·E has guardrails to decline requests that ask for image generation of real people, including candidates.

 

우리는 사람들이 우리의 도구를 안전하고 책임감 있게 사용하기를 기대하고 목표하며, 선거도 이와 다르지 않습니다. 우리는 오해를 불러일으키는 "딥페이크", 대규모 영향력 행사 또는 후보자를 사칭하는 챗봇과 같은 관련 남용을 예측하고 예방하기 위해 노력합니다. 새로운 시스템을 출시하기 전에 우리는 레드팀을 구성하고 피드백을 받기 위해 사용자와 외부 파트너를 참여시키며 피해 가능성을 줄이기 위한 안전 완화 조치를 구축합니다. 수년 동안 우리는 사실의 정확성을 높이고, 편견을 줄이고, 특정 요청을 거부하는 도구를 반복적으로 사용해 왔습니다. 이러한 도구는 선거 무결성에 관한 작업을 위한 강력한 기반을 제공합니다. 예를 들어 DALL·E에는 후보자를 포함한 실제 인물의 이미지 생성을 요청하는 요청을 거부하는 가드레일이 있습니다.

 

We regularly refine our Usage Policies for ChatGPT and the API as we learn more about how people use or attempt to abuse our technology. A few to highlight for elections: 

 

우리는 사람들이 우리 기술을 어떻게 사용하거나 남용하려고 시도하는지 자세히 파악하면서 ChatGPT 및 API에 대한 사용 정책을 정기적으로 개선합니다. 선거를 위해 강조할 몇 가지:

 

  • We’re still working to understand how effective our tools might be for personalized persuasion. Until we know more, we don’t allow people to build applications for political campaigning and lobbying. 

  • 우리는 우리의 도구가 개인화된 설득에 얼마나 효과적인지 이해하기 위해 계속 노력하고 있습니다. 더 많은 내용을 알기 전까지는 사람들이 정치 캠페인 및 로비 활동을 위한 애플리케이션을 구축하는 것을 허용하지 않습니다.

  • People want to know and trust that they are interacting with a real person, business, or government. For that reason, we don’t allow builders to create chatbots that pretend to be real people (e.g., candidates) or institutions (e.g., local government). 

  • 사람들은 자신이 실제 사람, 기업 또는 정부와 상호 작용하고 있다는 사실을 알고 신뢰하고 싶어합니다. 이러한 이유로 우리는 빌더가 실제 사람(예: 후보자) 또는 기관(예: 지방 정부)인 것처럼 가장하는 챗봇을 만드는 것을 허용하지 않습니다.

  • We don’t allow applications that deter people from participation in democratic processes—for example, misrepresenting voting processes and qualifications (e.g., when, where, or who is eligible to vote) or that discourage voting (e.g., claiming a vote is meaningless).

  • 사람들이 민주적 절차에 참여하는 것을 방해하는 애플리케이션(예: 투표 절차 및 자격(예: 언제, 어디서, 누가 투표할 자격이 있는지)을 허위로 표시하거나 투표를 방해하는 애플리케이션(예: 투표가 무의미하다고 주장))은 허용되지 않습니다. .

  • With our new GPTs, users can report potential violations to us.

  • 새로운 GPT를 통해 사용자는 잠재적인 위반 사항을 신고할 수 있습니다.
 

 

 

Transparency around AI-generated content

 

Better transparency around image provenance—including the ability to detect which tools were used to produce an image—can empower voters to assess an image with trust and confidence in how it was made. We’re working on several provenance efforts. Early this year, we will implement the Coalition for Content Provenance and Authenticity’s digital credentials—an approach that encodes details about the content’s provenance using cryptography—for images generated by DALL·E 3. 

 

이미지를 생성하는 데 어떤 도구가 사용되었는지 감지하는 기능을 포함하여 이미지 출처에 대한 투명성이 향상되면 유권자는 이미지 제작 방법에 대한 신뢰와 자신감을 가지고 이미지를 평가할 수 있습니다. 우리는 여러 출처에 대한 노력을 기울이고 있습니다. 올해 초 우리는 DALL·E 3에서 생성된 이미지에 대해 암호화를 사용하여 콘텐츠 출처에 대한 세부 정보를 인코딩하는 접근 방식인 콘텐츠 출처 및 진위성 연합의 디지털 자격 증명을 구현할 예정입니다.

 

We are also experimenting with a provenance classifier, a new tool for detecting images generated by DALL·E. Our internal testing has shown promising early results, even where images have been subject to common types of modifications. We plan to soon make it available to our first group of testers—including journalists, platforms, and researchers—for feedback.

 

또한 DALL·E에서 생성된 이미지를 감지하는 새로운 도구인 출처 분류기를 실험하고 있습니다. 우리의 내부 테스트는 이미지가 일반적인 유형의 수정을 받은 경우에도 유망한 초기 결과를 보여주었습니다. 우리는 곧 언론인, 플랫폼, 연구원을 포함한 첫 번째 테스터 그룹이 피드백을 받을 수 있도록 할 계획입니다.

 

Finally, ChatGPT is increasingly integrating with existing sources of information—for example, users will start to get access to real-time news reporting globally, including attribution and links. Transparency around the origin of information and balance in news sources can help voters better assess information and decide for themselves what they can trust.

 

마지막으로 ChatGPT는 점점 더 기존 정보 소스와 통합되고 있습니다. 예를 들어 사용자는 속성 및 링크를 포함하여 전 세계적으로 실시간 뉴스 보고에 액세스할 수 있게 됩니다. 정보 출처에 대한 투명성과 뉴스 소스의 균형은 유권자가 정보를 더 잘 평가하고 신뢰할 수 있는 정보를 스스로 결정하는 데 도움이 될 수 있습니다.

 

Improving access to authoritative voting information

 

In the United States, we are working with the National Association of Secretaries of State (NASS), the nation's oldest nonpartisan professional organization for public officials. ChatGPT will direct users to CanIVote.org, the authoritative website on US voting information, when asked certain procedural election related questions—for example, where to vote. Lessons from this work will inform our approach in other countries and regions. 

 

미국에서는 미국에서 가장 오래된 공직자를 위한 초당파적 전문 조직인 전국 국무장관 협회(NASS)와 협력하고 있습니다. ChatGPT는 특정 절차적 선거 관련 질문(예: 투표 장소)을 묻는 경우 미국 투표 정보에 대한 권위 있는 웹사이트인 CanIVote.org로 사용자를 안내합니다. 이 작업에서 얻은 교훈은 다른 국가 및 지역에서의 우리의 접근 방식에 영향을 미칠 것입니다.

 

We’ll have more to share in the coming months. We look forward to continuing to work with and learn from partners to anticipate and prevent potential abuse of our tools in the lead up to this year’s global elections.

 

앞으로 몇 달 동안 더 많은 내용을 공유할 예정입니다. 우리는 올해 세계 선거를 앞두고 우리 도구의 남용 가능성을 예측하고 방지하기 위해 계속해서 파트너와 협력하고 파트너로부터 배우기를 기대합니다.

 

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Jan 10 2024 Introducing ChatGPT Team

2024. 1. 12. 09:45 | Posted by 솔웅


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https://openai.com/blog/introducing-chatgpt-team

 

Introducing ChatGPT Team

We’re launching a new ChatGPT plan for teams of all sizes, which provides a secure, collaborative workspace to get the most out of ChatGPT at work.

openai.com

 

 

Introducing ChatGPT Team

We’re launching a new ChatGPT plan for teams of all sizes, which provides a secure, collaborative workspace to get the most out of ChatGPT at work.

 

 

 

We launched ChatGPT Enterprise a few months ago and industry leaders like Block, Canva, Carlyle, The Estée Lauder Companies, PwC, and Zapier are already using it to redefine how their organizations operate. Today, we’re adding a new self-serve plan: ChatGPT Team.

 

우리는 몇 달 전에 ChatGPT Enterprise를 출시했으며 Block, Canva, Carlyle, The Estée Lauder Companies, PwC, Zapier와 같은 업계 리더들은 이미 ChatGPT Enterprise를 사용하여 조직 운영 방식을 재정의하고 있습니다. 오늘 우리는 새로운 셀프 서비스 계획인 ChatGPT 팀을 추가합니다.

 

 

ChatGPT Team offers access to our advanced models like GPT-4 and DALL·E 3, and tools like Advanced Data Analysis. It additionally includes a dedicated collaborative workspace for your team and admin tools for team management. As with ChatGPT Enterprise, you own and control your business data—we do not train on your business data or conversations, and our models don’t learn from your usage. More details on our data privacy practices can be found on our privacy page and Trust Portal.

 

ChatGPT 팀은 GPT-4 및 DALL·E 3과 같은 고급 모델과 고급 데이터 분석과 같은 도구에 대한 액세스를 제공합니다. 또한 팀을 위한 전용 공동 작업 공간과 팀 관리를 위한 관리 도구가 포함되어 있습니다. ChatGPT Enterprise와 마찬가지로 귀하는 귀하의 비즈니스 데이터를 소유하고 제어합니다. 당사는 귀하의 비즈니스 데이터나 대화를 학습하지 않으며 당사 모델은 귀하의 사용법을 학습하지 않습니다. 당사의 데이터 개인정보 보호 관행에 대한 자세한 내용은 당사의 개인정보 보호 페이지와 Trust Portal에서 확인할 수 있습니다.

 

 

ChatGPT Team includes:

  • Access to GPT-4 with 32K context window
  • 32K 컨텍스트 창을 통해 GPT-4에 액세스
  • Tools like DALL·E 3, GPT-4 with Vision, Browsing, Advanced Data Analysis—with higher message caps
  • DALL·E 3, 비전, 브라우징, 고급 데이터 분석 기능을 갖춘 GPT-4와 같은 도구(메시지 한도가 더 높음)
  • No training on your business data or conversations
  • 비즈니스 데이터나 대화에 대한 training  이 없습니다.
  • Secure workspace for your team
  • 팀을 위한 안전한 작업 공간
  • Create and share custom GPTs with your workspace
  • 작업공간에서 맞춤 GPT를 만들고 공유하세요.
  • Admin console for workspace and team management
  • 작업공간 및 팀 관리를 위한 관리 콘솔
  • Early access to new features and improvements
  • 새로운 기능 및 개선 사항에 대한 조기 액세스

 

 
 

 

Customize ChatGPT for any type of work

 

We recently announced GPTs—custom versions of ChatGPT that you can create for a specific purpose with instructions, expanded knowledge, and custom capabilities. These can be especially useful for businesses and teams. With GPTs, you can customize ChatGPT to your team’s specific needs and workflows (no code required) and publish them securely to your team’s workspace. GPTs can help with a wide range of tasks, such as assisting in project management, team onboarding, generating code, performing data analysis, securely taking action in your existing systems and tools, or creating collateral to match your brand tone and voice. Today, we announced the GPT Store where you can find useful and popular GPTs from your workspace.

 

우리는 최근 GPTs를 발표했습니다. 이는 지침, 확장된 지식, 사용자 정의 기능을 통해 특정 목적을 위해 만들 수 있는 ChatGPT의 사용자 정의 버전입니다. 이는 비즈니스와 팀에 특히 유용할 수 있습니다. GPTs를 사용하면 ChatGPT를 팀의 특정 요구 사항과 작업 흐름에 맞게 맞춤설정하고(코드 필요 없음) 팀의 작업 공간에 안전하게 게시할 수 있습니다. GPTs는 프로젝트 관리 지원, 팀 온보딩, 코드 생성, 데이터 분석 수행, 기존 시스템 및 도구에서 안전하게 조치 수행, 브랜드 톤 및 목소리에 맞는 자료 생성 등 다양한 작업에 도움을 줄 수 있습니다. 오늘 우리는 귀하의 작업 공간에서 유용하고 인기 있는 GPTs를 찾을 수 있는 GPT 스토어를 발표했습니다.

 

 

Improve team efficiency and work quality

 

Integrating AI into everyday organizational workflows can make your team more productive. In a recent study by the Harvard Business School, employees at Boston Consulting Group who were given access to GPT-4 reported completing tasks 25% faster and achieved a 40% higher quality in their work as compared to their peers who did not have access.

 

AI를 일상적인 조직 워크플로에 통합하면 팀의 생산성이 향상될 수 있습니다. Harvard Business School의 최근 연구에 따르면 GPT-4에 대한 액세스 권한이 부여된 Boston Consulting Group의 직원은 액세스 권한이 없는 동료에 비해 작업을 25% 더 빨리 완료하고 작업 품질이 40% 더 높은 것으로 나타났습니다. 

 

 

Connor O’Brien, VP of GTM Strategy & Operations at Sourcegraph, shares, "We use ChatGPT in almost every part of our business, from financial modeling for pricing and packaging to internal and external communications to board prep to recruiting and note taking—it’s accelerated everything we do allowing us to execute at a high level."

 

Sourcegraph의 GTM 전략 및 운영 부사장인 Connor O'Brien은 다음과 같이 말합니다. "우리는 가격 책정 및 패키징을 위한 재무 모델링부터 내부 및 외부 커뮤니케이션, 이사회 준비, 채용 및 메모 작성에 이르기까지 비즈니스의 거의 모든 부분에서 ChatGPT를 사용합니다. 우리가 하는 모든 일을 가속화하여 높은 수준에서 실행할 수 있게 되었습니다."

 

Dr. John Brownstein, Chief Innovation Officer at Boston Children’s Hospital says, “With ChatGPT Team, we’ve been able to pilot innovative GPTs that enhance our team’s productivity and collaboration. As we integrate GPTs safely and responsibly across internal operations, we know the transformative impact this will have in strengthening the systems that enable our doctors, researchers, students, and administrative staff to provide exceptional care to every patient that walks through our doors.”

 

Boston Children’s Hospital의 최고 혁신 책임자인 Dr. John Brownstein은 이렇게 말합니다. “ChatGPT 팀을 통해 우리는 팀의 생산성과 협업을 향상시키는 혁신적인 GPT를 시험해 볼 수 있었습니다. 내부 운영 전반에 걸쳐 GPT를 안전하고 책임감 있게 통합함으로써 우리는 의사, 연구원, 학생 및 행정 직원이 우리 문을 방문하는 모든 환자에게 탁월한 진료를 제공할 수 있는 시스템을 강화하는 데 혁신적인 영향을 미칠 것임을 알고 있습니다.”

 

ChatGPT Team costs $25/month per user when billed annually, or $30/month per user when billed monthly. You can explore the details or get started now by upgrading in your ChatGPT settings.

 

ChatGPT 팀의 비용은 연간 청구 시 사용자당 월 $25, 월별 청구 시 사용자당 월 $30입니다. ChatGPT 설정에서 업그레이드하여 세부 정보를 살펴보거나 지금 시작할 수 있습니다.

 

 

Introducing ChatGPT Team

We’re launching a new ChatGPT plan for teams of all sizes, which provides a secure, collaborative workspace to get the most out of ChatGPT at work.

openai.com

 

 

 

 

 

 

 

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