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libra

LIBRA is a private enterprise project that was initially posted on the X account of Argentine President Milei, who later deleted the related tweets. LIBRA claims to be committed to promoting the growth of the Argentine economy by funding small businesses and startups in Argentina.
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first_img DeepSeek open-source Ascend basic components, covering compilation, computation, and communication libraries

The artificial intelligence company DeepSeek has officially open-sourced infrastructure components for the Huawei Ascend computing platform, covering the TileLang high-level language compilation tool, computing libraries, and distributed communication libraries, corresponding to the previously open-sourced components for the NVIDIA platform. TileLang aims to provide a general-purpose, simpler programming language that can achieve the hardware performance limits, improving development efficiency and simplifying logic compared to CUDA, while its programming model can also leverage chip features.The TileLang route was first validated on the NVIDIA platform and has already supported the implementation of most operators in the training of the DeepSeek V4 series models. The open-sourced Ascend version encapsulates the underlying instructions of the Ascend C, providing a high-level programming approach without sacrificing hardware performance. Currently, every TileLang operator used in DeepSeek's training has a corresponding high-performance implementation on Ascend.The components open-sourced at the same time also include DeepGEMM, DeepEP, TileKernels, FlashMLA, and DeepSelect, which are used for general matrix operations, large-scale cross-device communication, conventional vector calculations and memory access, long-context sparse attention, and data filtering, respectively. DeepSeek claims that in multiple key tests, the related computing and communication performance has approached hardware limits; during the R&D process, the Huawei team provided support, and both parties collaborated to advance the 128-card supernode solution based on Ascend 950, with deep optimizations made for computing and communication.

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.

Bitget launches the AI strategy workflow GetAgent Playbook, supporting one-click access to the strategy library

Bitget officially launched the AI trading strategy workflow layer GetAgent Playbook, marking the first time the Agent Harness framework is available to users. Users can select, preview, configure, and launch AI trading strategies from the Agent Playbook strategy library without having to write prompts themselves, all running in an isolated sub-account with auditable operations and transparent processes. Currently, this feature is available to GetAgent Plus and Pro users.Bitget CEO Gracy Chen stated that AI trading is evolving from Q&A to workflows, with prompt configuration being the biggest source of complexity. The Playbook allows users to easily transform trading ideas into Agent runnable and adjustable strategies through a ready-to-use strategy library (Agent Playbook).As of now, Bitget's AI trading tools have attracted over 1 million users, with a cumulative trading volume exceeding $1.2 billion. The Agent Hub covers 9 major modules and 57 tools, supporting read-only mode, simulated trading environments, and Agent exclusive sub-accounts, completely isolating agent operational permissions from the main account, and integrating the entire business chain of spot trading, contracts, copy trading, and wealth management, while exclusively supporting trading of tokenized assets in the US stock market.
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