DeepSeek unveiled its first set of models — DeepSeek Coder, DeepSeek LLM, and DeepSeek Chat — in November 2023. But it wasn’t until last spring, when the startup released its next-gen ...

DeepSeek sent Wall Street into a frenzy on Monday, sending shares of Nvidia (NVDA) cratering more than 17% and raising questions about whether Big Tech firms like Microsoft (MSFT) and Meta (META ...

Internal testing by DeepSeek shows Janus Pro 7B scoring 80% on GenEval and 84.2 on DPG-Bench, outperforming models like DALL-E 3 and Stable Diffusion. However, independent testing will determine ...

DeepSeek, the Chinese AI startup known for its DeepSeek-R1 LLM model, has publicly exposed two databases containing sensitive user and operational information. The unsecured ClickHouse instances ...

DeepSeek released a surprisingly effective and inexpensive Large Language Model, or LLM, on Monday, shocking U.S. markets and causing the stock of the top U.S. chip manufacturer, Nvidia ...

“If DeepSeek can create an LLM in two years, why can't India do it? DeepSeek, in a matter of days, has completely upended how everyone sees artificial intelligence in terms of investment and as ...

The latest version of DeepSeek, an AI model from a Chinese start-up of the same name, appeared to equal OpenAI’s most advanced program, o1. On Monday, DeepSeek overtook ChatGPT as the No. 1 free ...

It’s hard to agree on anything when it comes to AI. But one thing we can all agree on is that the mass hysteria that DeepSeek’s arrival unleashed on the current cabal of AI Overlords dropped a ...

Canada’s best-capitalized large-language model (LLM) developer, Cohere, thinks the media firestorm surrounding the launch of the latest chatbot app from Chinese artificial intelligence (AI) company ...

News related to DeepSeek’s arrival in the AI space is emerging nonstop. However, some of it might not get you too excited. Cybersecurity experts have already warned about the potential ...

Chinese startup DeepSeek claims to have developed its high-performing AI tool using a fraction of the computing power that U.S. tech companies have needed to train an AI large language model (LLM).