Afternoon Bitcoin and Ethereum operation suggestions and direction sharing Good morning everyone! The weather is getting colder, so make sure to add more clothing. Looking back at the early morning Big Bit market, it reached a high point of 117875 before facing pressure, then gradually declined to a low point of 116489 in the morning. The short-term trend in the early morning was consistent with our midnight strategy, and when it reached our entry point, we decisively entered the market to short. The Big Bit captured over 900 points of space, while Ether captured 39 points of space. All strategies were provided in advance, and there was confidence without any hesitation. For trend discussions, you can refer to what Lao Zhao has said. From the current market perspective, Bitcoin is currently in a consolidation phase, with prices fluctuating narrowly around the Bollinger Band's middle track at 117300. The Bollinger Bands are generally flat, and the short-term market lacks a clear direction. The resistance is at the Bollinger Band's upper line of 117800, where the price has fallen back after several tests, indicating heavy selling pressure above. As for the support level, the lower line of the Bollinger Band around 116800 can serve as short-term support. If it breaks below this lower line, further pullback risks should be watched. During the afternoon, it is recommended to focus on high selling and low buying in the short-term range trading. You can go long above 116800 for Bitcoin, pay attention to 117800. Buy around 4580 to 4550 for two coins, focus on 4640. #BTC##ETH#

Gate News bot message, a trader identified as 0x2226 has established substantial leveraged positions in the cryptocurrency market. The trader opened a 40x leveraged long position with 700 BTC, valued at $82 million. Additionally, they hold a 20x leveraged long position with 120,000 SOL, worth $29.6.

NVIDIA invests $680 million in a UK AI company. What is the secret behind the transformation of the encryption mining farm into an AI supercomputing center? Chip giant NVIDIA recently announced an investment of $683 million in UK AI infrastructure company Nscale. What is noteworthy is that Nscale was formerly a cryptocurrency mining company - Arkon Energy. Now, it is transforming from a Bitcoin Mining Farm into an AI cloud computing service provider, attempting to convert its former status as a "power consumption heavyweight" into a "smart computing engine." This investment is not an isolated action, but part of the UK government's £11 billion AI infrastructure strategy. Nvidia CEO Jensen Huang publicly stated that this move will significantly promote the development of the UK's AI ecosystem. However, what is more worth contemplating is the industrial logic behind it: the cheap electricity, cooling technology, and large-scale data center operation experience relied upon by encryption mining are precisely in high alignment with the high-intensity computing power support required for current AI large model training. This wave of transformation is not accidental. With Ethereum completing its transition to PoS, many Mining Farms are facing survival pressure; on the other hand, since the outbreak of ChatGPT, the demand for GPU computing power in the AI field has grown exponentially. The two found a common language in the dimensions of energy and hardware—those facilities and management experiences originally used for mining have become a springboard to enter the AI cloud service market. International technology giants are also betting on this trend. OpenAI has partnered with Nscale to advance the "Stargate UK" project, while Microsoft has reserved $6.2 billion in computing resources from its Norwegian operations. Companies like Google are also actively positioning themselves. This is not only a commercial investment but also a global competition concerning the capabilities of "sovereign AI." However, the road to transformation is not a smooth one. Transitioning from encryption mining to AI services is not just a simple hardware replacement; it also involves restructuring the technical architecture, transforming the talent team, and adjusting the business model. The success of this transformation still needs to be tested over time. However, it is certain that in today's increasingly fierce AI competition, the once electricity-sensitive Mining Farm is quietly transforming into a key player in the new generation of computing power infrastructure.