The stock market burns with CPI.

The stock market burns with CPI.
The December consumer price index, which is said to have been the most important of the data released recently, provided investors with relief with a lower-than-expected decline in core prices.
In particular, housing costs, which have been perceived as the biggest headache so far, fell to their lowest level since January 2022, and real wages also fell, significantly easing inflationary pressures.


Interest rates and the dollar plunged on positive inflation data and turned downward, which was a huge boon for the market.
But if you look at it more soberly, there is not much change in the trend, because inflation is too high to change the Fed's stance and it is too high to be seen as a trend.
It is also concerning that the rise in energy prices is strengthening, especially as oil prices soared to $80 in January.
PMI price indicators, which are recognized as the fastest leading indicators of actual prices, and manufacturing price indicators of the regional Fed are soaring, so the possibility of inflation re-accelerating cannot be ruled out.
In fact, Morgan Stanley is suggesting the possibility of inflation rising again in January. The federal funds rate futures market has also seen little movement in bets on a rate cut in June.
The December CPI, in conclusion, offered investors some relief. Now the market is headed for corporate earnings.

There seems to be a lot of misunderstandings spreading in the US and Korea with unfounded content about DeepSeek...

A clear and concise article has been posted to correct this.

I think it would be good to refer to it.

In fact, DeepSeek didn't just drop from the sky all of a sudden, but the Generative AI community has been continuing to publish huge results in the last nine months (see graph)

1. Is DeepSeek a questionable company that has suddenly emerged?
-> Not true. DeepSeek has been continuously developing AI models since November 2023, and they were well known to AI researchers.

2. DeepSeek's Model Development Cost Can't Be $6M
-> False Claims. The training cost analysis published by DeepSeek is largely consistent with industry standards, and additional R&D costs are the same for all AI labs.

3. If DeepSeek made it too cheap, did American AI companies waste money?
-> Wrong. DeepSeek has maximized efficiency, but the scaling law that more computing resources increase AI performance is still in effect. American AI companies will still continue to invest in GPUs, and it does not directly affect NVIDIA's GPU market dominance.

4. DeepSeek is just a copy of the technology of American AI companies?
-> Not true. DeepSeek has achieved its own technological innovation, typically using more efficient memory compared to existing Transformer models such as Multi-lattent Attention, and increasing efficiency in the process of optimizing Reinforcement Learning (RL) and training multiple GPUs. On the other hand, DeepSeek shares its technology as an open source, while OpenAI and Anthropic operate the model in a closed manner. It should be praised.

5. DeepSeek trained the model using ChatGPT data
-> No basis. OpenAI claimed that DeepSeek took data from ChatGPT, but there is no concrete evidence. If DeepSeek directly generated and learned ChatGPT data, this is a violation of OpenAI's policy, but it doesn't matter if it used a public dataset. DeepSeek's success is not due to ChatGPT data, but to advances in its own techniques and learning techniques.

출처: https://www.tanishq.ai/blog/posts/deepseek-delusions.html