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NVIDIA releases quantum computing AI calibration model, promoting the fusion of AI and quantum

NVIDIA released the open-source AI model NVIDIA Ising Calibration 1.5, designed for the automatic analysis of quantum processor (QPU) diagnostic data, and to autonomously determine device calibration schemes, achieving automation of the quantum computer calibration process. NVIDIA stated that Ising Calibration 1.5 is a visual language model (VLM) specifically designed for quantum computing calibration scenarios, capable of understanding experimental data from quantum chips and performing "zero-shot" analysis in the absence of historical cases, while also enabling context learning (ICL) with relevant experimental samples to help continuously optimize the operational state of quantum devices.In the QCalEval quantum calibration benchmark test, Ising Calibration 1.5 averaged about 10% ahead of similarly sized open-source models in zero-shot inference capability, and when using relevant experimental cases for context learning, it showed an approximately 86.5% performance improvement over the previous generation model, surpassing multiple open-source models and approaching the level of top closed-source large models. The model has 31 billion parameters and supports operation on NVIDIA Grace Blackwell and Vera Rubin data center GPUs. It also launched an NVFP4 quantized version, which can be deployed on a single consumer-grade GPU or NVIDIA DGX Spark, significantly lowering the usage threshold for quantum laboratories.NVIDIA claims that the training data for Ising Calibration 1.5 comes from various qubit architectures, including superconducting qubits, quantum dots, ions, neutral atoms, and helium surface electrons, providing calibration capabilities for different types of quantum computing devices. Industry experts believe that automated calibration is one of the key bottlenecks in the scalable development of quantum computing. NVIDIA's launch of this AI-driven quantum calibration tool signifies that AI models are beginning to extend from traditional computing domains into the quantum hardware control layer, potentially becoming an important component of the future quantum computing industry infrastructure.

NVIDIA invests in OpenAI to co-establish a new AI laboratory, providing large-scale GPU computing power support

According to a report by the WSJ, Nvidia has invested in the AI laboratory Safe Superintelligence (SSI), founded by former OpenAI chief scientist Ilya Sutskever. The two parties have reached a long-term cooperation agreement aimed at expanding SSI's computing resources while helping Nvidia secure important clients in the AI field. Both companies stated that Nvidia made a "large-scale" investment after understanding some of SSI's research progress, but did not disclose the specific amount.As part of the collaboration, SSI will receive a significant amount of Nvidia's flagship GPU resources, with its computing power expected to increase by an order of magnitude. Previously, SSI primarily relied on TPU chips provided by Google for AI research and development. This collaboration indicates that Nvidia is further expanding its AI chip ecosystem and binding future computing power demands through investments in top AI laboratories.SSI was established in 2024 by Ilya Sutskever, with the goal of developing "Safe Superintelligence." The company has previously raised about $2 billion in funding, with investors including Andreessen Horowitz and Sequoia Capital, and reached a valuation of approximately $30 billion last year. This is not Nvidia's first investment in an AI company founded by former core members of OpenAI. In March of this year, Nvidia also invested in Thinking Machines Lab, founded by former OpenAI chief technology officer Mira Murati, whose first AI model is trained on Nvidia hardware.Ilya Sutskever is one of the important researchers in the field of modern artificial intelligence, having co-founded OpenAI and promoted the development of large model technologies such as ChatGPT. However, after leaving OpenAI, he began to question the approach of solely relying on expanding data and computing power to drive AI progress, turning instead to explore new directions in superintelligence research.

U.S. debt approaches $40 trillion, investors turn to Bitcoin and gold as a hedge against the depreciation of the dollar

According to CoinDesk, as the U.S. government debt continues to rise, investors are refocusing on scarce assets like Bitcoin and gold, viewing them as tools to hedge against the declining purchasing power of the dollar. Data from the U.S. Treasury shows that as of last Friday, the federal debt has reached a record $39.7 trillion. Market participants point out that U.S. government debt is currently increasing by about $7 billion per day, and in terms of market value, this incremental scale has surpassed most crypto assets.The founder of LondonCryptoClub stated that the rapid growth of U.S. debt is driving the so-called "currency devaluation trade," where investors buy limited-supply assets like gold and Bitcoin to mitigate the long-term devaluation risk of fiat currency. The institution believes that in a "fiscal-dominated" environment, Federal Reserve policy may be influenced by government financing needs, requiring interest rates to remain low while continuously providing liquidity to assist with debt refinancing.Apollo's chief economist Torsten Slok previously warned that the ratio of U.S. debt to GDP has exceeded 120%, leaving limited fiscal stimulus space during future economic recessions. At the same time, the Federal Reserve may find it difficult to cut interest rates significantly as it did in the past, since rate cuts could exacerbate inflation and lower government bond yields, affecting government financing. Currently, Bitcoin prices are maintaining above $65,000, supported by easing tensions between the U.S. and Iran and a drop in oil prices, leading to a rebound in market risk appetite.Meanwhile, Ethereum has recently outperformed Bitcoin, with the ETH/BTC exchange rate breaking through the 100-day and 200-day moving averages, leading the market to believe that altcoin trends may be warming up. However, analysts point out that since its inception in 2010, Bitcoin's price movements have more closely resembled those of tech stocks rather than traditional safe-haven assets, and its safe-haven properties remain controversial.

Gate GUSD's total subscription amount reached 217 million USD, and new users of the liquid US Treasury product can enjoy a limited-time 100% annualized return

According to official news, the total subscription amount for Gate GUSD has reached 217 million USD. The Gate GUSD current US Treasury product has been fully upgraded, allowing users holding GUSD to enjoy an annualized yield of 3.8%, with support for deposits and withdrawals at any time, and earnings distributed daily to the spot account or trading account. New users participating in the GUSD current US Treasury subscription can also enjoy a limited-time annualized yield of 100%. The GUSD current US Treasury supports subscriptions in USDT, USDC, and USD1, allowing users to obtain GUSD at a 1:1 exchange rate, and simultaneously enjoy the corresponding product earnings and GUSD current US Treasury earnings while participating in products like Launchpool and Pre-IPOs.In addition, Gate's 367th ANTFUN Launchpool is currently ongoing, where users can participate in staking using USDT, GUSD, or ANTFUN to share a reward of 3,756,574 ANTFUN. The current total amount of GUSD liquid staking is close to 50 million, with the GUSD pool APR at 4.09%. After adding the GUSD subscription earnings, the estimated combined APR reaches 7.89%. Additionally, the estimated annualized yield for the USDT pool liquid staking pool is 5.55%, and the estimated annualized yield for the ANTFUN exclusive staking pool is 87.20%.Gate has launched a no-loss quick redemption feature for GUSD. Users can redeem GUSD minted with USDT, USDC, or USD1 within the no-loss exit limit of the corresponding currency, enjoying real-time 1:1 crediting of the original currency without redemption fees, achieving a balance between earning income and flexible allocation of funds.
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