In the past seven days, VISTA has risen by 850%. A trader bought 12802 VISTA at a price of 27.46 ETH 25 days ago, with an average price of $5.3. Seven days ago, all the held VISTA were sold at an average price of $6.2, and only 32.81 ETH were obtained, with a net profit of only 5.35 ETH. If these VISTA were still held, the value of these tokens would now exceed $926,000.

The Ethervista protocolToken VISTA Market Cap of the ETH ecosystem has reached 46 million US dollars, and the coin price has reached a historical high, with an increase of 28.8%. The platform has launched the Etherfun product, and the fees generated by the initial LP pool will be sent to the VISTA treasury, part of which will be used to purchase and destroy more VISTA Tokens to support the ecosystem.

The TokenVISTA launched by Ethervista, a one-click launch coin platform for the Ethereum ecosystem, has seen a surge of 69.9% and a market capitalization of $31.6 million. It has launched a new product, Etherfun, and a portion of its revenue will be used to purchase and destroy more VISTATokens to support the ecosystem's development.

The ETH platform Ethervista announced the upcoming launch of the VISTA application, which aims to empower users to create and view Tokens, helping creators go beyond basic memecoins and inspiring them to create. The platform has achieved a volume of 4 billion USD in just 8 days since its establishment, and the community has also added @vistaRover to the Allowlist.

BlockBeats news, on September 5th, according to The Data Nerd's monitoring, a certain Smart Money bought 15,700 VISTA at an average price of $0.96. Subsequently, it exchanged 5,600 VISTA for $117,000 (realizing a profit of approximately $102,000). Currently, it still holds 10,100 VISTA (approximately $311,000), making it one of the top 8 holders.

BlockBeats news, on September 3rd, according to Arkham Monitor, trader 0x430 participated in the issuance of Ethervista and spent $5000 to obtain over 5% of the VISTA supply. He diversified his holdings of VISTA assets into 7 different Wallets for sale, and two days later, he made a profit of $670,000 in ETH, which has already achieved over 130 times return.

BlockBeats news, on September 3rd, EtherVista project publicly explained the operation mechanism of its VISTA Token. The token is designed as a value compounding deflationary currency, with the core feature being a continuous automatic buyback and burn mechanism. The EtherVista system will continuously buy and burn VISTA Tokens, each operation raising the price floor of the token. According to official data, currently 2.17% of the total token supply has been permanently repurchased and burned.

According to Lookonchain monitoring, frenulum.eth earned 274 ETH ($696,700) through trading VISTA in 2 days, with a return rate of 134 times! frenulum.eth only spent 2.05 ETH ($5.1K) to buy 52,822 VISTA, and sold them at a price of 276.5 ETH ($701.8K).

BlockBeats news, on September 2nd, according to market data, VISTA reached 17.58 US dollars in the upward trend and then fell back, now trading at 12.37 US dollars, with a 24-hour increase of 1942%. The current market capitalization is temporarily reported at 12.84 million US dollars, and the 24-hour volume reaches 8.33 million US dollars. VISTA is the native Token of Ethervista. According to its official Twitter introduction, Ethervista aims to establish a new standard for decentralized trading platforms and has released the White Paper yesterday.

ByteDance has partnered with Zhejiang University to launch Vista-LLaMA, a multimodal large language model designed for video content understanding and capable of outputting high-quality video descriptions. Through innovative visual and verbal token processing, Vista-LLaMA solves the problem of "hallucinations" in video content. Vista-LLaMA excels in multiple open video Q&A benchmarks, especially in the NExT-QA and MSRVTT-QA tests. It achieved an accuracy rate of 60.7% in the zero-shot NExT-QA test and 60.5% in the MSRVTT-QA test, surpassing all current SOTA methods. These results demonstrate the efficiency and accuracy of Vista-LLaMA in video content understanding and description generation.