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DeepSeek 모델은 처음 2023년 하반기에 출시된 후에 빠르게 AI 커뮤니티의 많은 관심을 받으면서 유명세를 탄 편이라고 할 수 있는데요. AI 커뮤니티의 관심은 - 어찌보면 당연하게도 - Llama나 Mistral 같은 모델에 집중될 수 밖에 없지만, DeepSeek이라는 스타트업 자체, 이 회사의 연구 방향과 출시하는 모델의 흐름은 한 번 살펴볼 만한 중요한 대상이라고 생각합니다. 중국 AI 스타트업 DeepSeek이 GPT-4를 넘어서는 오픈소스 AI 모델을 개발해 많은 관심을 받고 있습니다. ‘DeepSeek’은 오늘 이야기할 생성형 AI 모델 패밀리의 이름이자 이 모델을 만들고 있는 스타트업의 이름이기도 합니다. 역시 중국의 스타트업인 이 DeepSeek의 기술 혁신은 실리콘 밸리에서도 주목을 받고 있습니다. 이 소형 모델은 GPT-4의 수학적 추론 능력에 근접하는 성능을 보여줬을 뿐 아니라 또 다른, 우리에게도 널리 알려진 중국의 모델, Qwen-72B보다도 뛰어난 성능을 보여주었습니다. Moonshot AI 같은 중국의 생성형 AI 유니콘을 이전에 튜링 포스트 코리아에서도 소개한 적이 있는데요. 시장의 규모, 경제적/산업적 환경, 정치적 안정성 측면에서 우리나라와는 많은 차이가 있기는 하지만, 과연 우리나라의 생성형 AI 생태계가 어떤 도전을 해야 할지에 대한 하나의 시금석이 될 수도 있다고 생각합니다.

특히 DeepSeek-V2는 더 적은 메모리를 사용하면서도 더 빠르게 정보를 처리하는 또 하나의 혁신적 기법, MLA (Multi-Head Latent Attention)을 도입했습니다. DeepSeek-V2 introduces Multi-Head Latent Attention (MLA), a modified attention mechanism that compresses the KV cache right into a much smaller type. DeepSeek-V2 is a state-of-the-art language model that makes use of a Transformer architecture mixed with an revolutionary MoE system and a specialised attention mechanism referred to as Multi-Head Latent Attention (MLA). Remember, these are recommendations, and the precise performance will rely upon a number of factors, together with the specific task, model implementation, and other system processes. Although particular technological instructions have constantly advanced, the mix of fashions, data, and computational energy remains fixed. Shared professional isolation: Shared experts are specific specialists that are all the time activated, regardless of what the router decides. OpenAI and ByteDance are even exploring potential analysis collaborations with the startup. At the time, the bank additionally highlighted that the magnitude of each potential knowledge middle capacity it walked away from and the choice to tug back on land acquisition (which helps core long-time period capacity development) indicates the loss of a major demand sign that Microsoft was initially responding to and that it believed the shift in Microsoft's appetite for capability is tied to OpenAI, which recent press stories appear to affirm.

As a result, Nvidia's inventory skilled a big decline on Monday, as anxious traders worried that demand for Nvidia's most superior chips-which also have the best revenue margins-would drop if firms realized they may develop excessive-efficiency AI models with cheaper, less superior chips. MSFT thinks AI provide demand must be extra inline by the top of their present FYI provide will grow extra consistent with demand going ahead quite than being in brief provide. Through RL, it naturally learned to allocate extra "thinking time" to harder issues. It additionally scored 84.1% on the GSM8K arithmetic dataset without wonderful-tuning, exhibiting exceptional prowess in fixing mathematical problems. Mathematical reasoning is a significant problem for language fashions due to the complex and structured nature of mathematics. Handling long contexts: DeepSeek-Coder-V2 extends the context size from 16,000 to 128,000 tokens, permitting it to work with much bigger and extra advanced initiatives. DeepSeek-V2: How does it work? We now have explored DeepSeek’s strategy to the development of superior models. In this wave, our place to begin is not to reap the benefits of the opportunity to make a quick revenue, however quite to reach the technical frontier and drive the event of your entire ecosystem … Combination of those improvements helps Deepseek Online chat-V2 achieve special features that make it much more competitive amongst different open models than earlier variations.

It handled duties like inventive writing and summarization, generating clear, properly-structured responses even for lengthy inputs. Managing extremely long textual content inputs as much as 128,000 tokens. 1,170 B of code tokens were taken from GitHub and CommonCrawl. The efficiency of DeepSeek-Coder-V2 on math and code benchmarks. Powered by the groundbreaking DeepSeek Ai Chat-V3 mannequin with over 600B parameters, this state-of-the-art AI leads international standards and matches top-tier international models throughout multiple benchmarks. This leads to better alignment with human preferences in coding tasks. The preferred, DeepSeek-Coder-V2, remains at the highest in coding tasks and may be run with Ollama, making it notably enticing for indie developers and coders. That call was definitely fruitful, and now the open-supply family of models, including DeepSeek Coder, DeepSeek LLM, DeepSeekMoE, DeepSeek-Coder-V1.5, DeepSeekMath, DeepSeek-VL, DeepSeek-V2, DeepSeek-Coder-V2, and DeepSeek-Prover-V1.5, might be utilized for many functions and is democratizing the utilization of generative models. DeepSeek-Coder-V2, costing 20-50x times lower than different models, represents a major improve over the unique Free Deepseek Online chat-Coder, with extra intensive coaching knowledge, larger and extra environment friendly models, enhanced context dealing with, and superior strategies like Fill-In-The-Middle and Reinforcement Learning. Testing DeepSeek-Coder-V2 on numerous benchmarks reveals that DeepSeek-Coder-V2 outperforms most fashions, together with Chinese competitors.