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Brokerage morning meeting highlights: DeepSeek reopens its source code, focusing on changes in AI applications.
At today's Brokerage morning meeting, HTSC proposed that DeepSeek be open-sourced again and focus on changes in AI applications; China International Capital Corporation believes that AI+finance is expected to reach a scaling inflection point; China Securities Co.,Ltd. stated that the performance resonance of lithium battery demand is signaling the beginning of a new cycle.
Trump's pressure was effective, OPEC+ unexpectedly decided to start increasing oil supply, leading to a sharp decline in oil prices.
OPEC+, led by Saudi Arabia and Russia, will increase daily production by 0.138 million barrels in April. This is the first step in a gradual increase plan spanning several months, aimed at gradually restoring Crude Oil Product output. OPEC+ issued a statement confirming the decision to start increasing oil supply, and OPEC+ may decide to suspend or reverse this decision based on market conditions.
The divergence in the technology stock sector is increasing, pay attention to the rotation opportunities in low-level directions such as Solid State Battery and CSI Consumer 360 index.
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As high as 545%! DeepSeek has released its cost-profit margin for the first time. What is the impact on computing power?
According to DeepSeek's calculations, the theoretical daily profit of the V3/R1 inference system can reach 3.46 million yuan. The founder of Silicon-based Flow, Yuan Jinhui, commented that the V3/R1 architecture is significantly different from other mainstream models. Brokerage opinions suggest that in the medium to short term, technology giants will continue to make ongoing and large-scale investments in the field of AI computing power, which will remain a highly certain event.
US Morning News Call | Stock Futures Advance with Nvidia Earnings on the Horizon, Amid Hopes for AI Rally
China United Network Communications: Optimized and upgraded the DeepSeek series models, saving an average of 30% in inference computational load.
① China United Network Communications announced an "adaptive slow thinking" optimization upgrade for the DeepSeek series models, saving an average of approximately 30% in inference computation, and it has been open-sourced, making it a first in the industry; ② The specific modifications include difficulty-adaptive fine-tuning, secondary distillation, and difficulty-adaptive reinforcement learning to reduce redundant outputs and resource consumption.
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