Topic #10: 오픈소스 LLM 씬의 라이징 스타! 'DeepSeek'을 알아보자 > 자유게시판

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1. Get a VPS plan and DeepSeek API key. It will also be downloaded via the Get DeepSeek App choice on the principle website. The pace at which the new Chinese AI app DeepSeek has shaken the technology business, the markets and the bullish sense of American superiority in the sector of synthetic intelligence (AI) has been nothing short of stunning. The DeepSeek chatbot app skyrocketed to the top of the iOS Free DeepSeek app charts in both the U.S. U.S. tech stocks additionally experienced a significant downturn on Monday as a consequence of investor issues over aggressive advancements in AI by DeepSeek. DeepSeek CEO Liang Wenfeng, additionally the founding father of High-Flyer - a Chinese quantitative fund and DeepSeek’s major backer - recently met with Chinese Premier Li Qiang, where he highlighted the challenges Chinese corporations face due to U.S. Regardless, DeepSeek’s sudden arrival is a "flex" by China and a "black eye for US tech," to use his personal phrases. Japan’s semiconductor sector is dealing with a downturn as shares of major chip firms fell sharply on Monday following the emergence of DeepSeek’s models.

Liang Wenfeng: Currently, plainly neither major firms nor startups can shortly set up a dominant technological benefit. Both main firms and startups have their opportunities. Many VCs have reservations about funding research; they want exits and wish to commercialize products rapidly. When generative first took off in 2022, many commentators and policymakers had an comprehensible response: we have to label AI-generated content material. Avoid dangerous, unethical, prejudiced, or damaging content. It’s unfortunate as a result of this situation has quite a few adverse consequences. The final reply isn’t terribly interesting; tl;dr it figures out that it’s a nonsense query. Chinese firm to figure out do how state-of-the-art work utilizing non-state-of-the-art chips. It is mostly believed that 10,000 NVIDIA A100 chips are the computational threshold for coaching LLMs independently. OpenAI and ByteDance are even exploring potential research collaborations with the startup. However, since these eventualities are finally fragmented and consist of small needs, they are extra suited to flexible startup organizations. In November, the Beijing-primarily based AI startup ShengShu Technology unveiled its picture-to-video tool referred to as Vidu-1.5, capable of generating a video from as few as three input images inside 30 seconds while establishing logical relationships amongst these objects in a scene. It is a recreation destined for the few.

However, LLMs heavily rely on computational energy, algorithms, and information, requiring an initial investment of $50 million and tens of tens of millions of dollars per coaching session, making it troublesome for corporations not worth billions to maintain. In truth, this company, hardly ever seen via the lens of AI, has long been a hidden AI giant: in 2019, High-Flyer Quant established an AI company, with its self-developed deep learning coaching platform "Firefly One" totaling almost 200 million yuan in funding, outfitted with 1,100 GPUs; two years later, "Firefly Two" elevated its funding to 1 billion yuan, geared up with about 10,000 NVIDIA A100 graphics cards. The public cloud business posted double-digit positive factors, whereas adjusted EBITA revenue skyrocketed 155% yr-on-year to RMB 2.337 billion (USD 327.2 million). Liang Wenfeng: Simply replicating can be completed primarily based on public papers or open-source code, requiring minimal coaching or simply superb-tuning, which is low price. Therefore, past the inevitable matters of money, expertise, and computational energy concerned in LLMs, we also mentioned with High-Flyer founder Liang about what sort of organizational structure can foster innovation and how lengthy human madness can final.

36Kr: What sort of curiosity? 36Kr: Regardless, a business company engaging in an infinitely investing analysis exploration seems somewhat crazy. 36Kr: But analysis means incurring greater costs. This fixed attention span, means we can implement a rolling buffer cache. 2. The AI Scientist can incorrectly implement its ideas or make unfair comparisons to baselines, leading to deceptive results. Detailed metrics have been extracted and can be found to make it potential to reproduce findings. Sadly, while AI is helpful for monitoring and alerts, it can’t design system architectures or make critical deployment decisions. While we now have seen makes an attempt to introduce new architectures resembling Mamba and extra lately xLSTM to only title a number of, it appears probably that the decoder-only transformer is here to remain - not less than for essentially the most half. But we have computational energy and an engineering workforce, which is half the battle. 36Kr: GPUs have develop into a highly sought-after resource amidst the surge of ChatGPT-driven entrepreneurship.. You had the foresight to reserve 10,000 GPUs as early as 2021. Why? General AI is perhaps considered one of the subsequent big challenges, so for us, it's a matter of how you can do it, not why. Many may think there's an undisclosed enterprise logic behind this, however in reality, it is primarily driven by curiosity.

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