DeepSeek also says that it developed the chatbot for only $5.6 million, which if true is far less than the hundreds of millions of dollars spent by U.S. companies in the sector.

What DeepSeek showed, she said, is that there are different paths. The company says it used a little more than 2,000 Nvidia H800 GPUs to train the bot, and it did so in a matter of weeks for $5.6 ...

The bill would ban DeepSeek from federal devices as well as any future product developed by High-Flyer, the artificial intelligent tool's hedge fund backers. This comes after the U.S. House of ...

The final round of AI Madness was between DeepSeek and Gemini 2.0. I think it’s safe to say that most of us didn’t expect DeepSeek to win in nearly every category.

DeepSeek's app is powered by the DeepSeek-V3 model. The startup describes its app as using “state-of-the-art" AI that “leads global standards and matches top-tier international models.” ...

The quality and cost efficiency of DeepSeek's models have flipped this narrative on its head. The two models that have been showered with praise by Silicon Valley executives and U.S. tech company ...

When DeepSeek introduced its DeepSeek-V3 model the day after Christmas, it matched the abilities of the best chatbots from U.S. companies like OpenAI and Google. That alone would have been impressive.

DeepSeek has profited from open research and open-source. For example, PyTorch and Llama from Meta. They came up with new ideas and built on top of other people’s work.

DeepSeek R1 named actual models (GPT-4o, Gemini 1.5 Pro, AlphaFold 3, etc.) and technologies, making it clear that the response is based on real, recent developments rather than general trends.