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According to the latest prediction from Gartner, by 2028, 80% of generative AI business applications will be developed on existing data management platforms. This shift is expected to reduce development complexity and cut delivery time in half. Currently, the development of generative AI business applications mainly relies on combining large language models (LLMs) with corporate internal data, as well as evolving technologies such as vector search, metadata management, prompt design, and embedding techniques. However, without a unified management approach, companies may...

As the challenges and pressures faced by the banking industry in digital transformation intensify, more and more banks are beginning to integrate large model technology into their core businesses, rather than simply relying on chatbot applications. The latest financial reports show that some major domestic banks have made significant progress in technology investment and large model applications, but also reveal a trend of differentiated investment. According to an analysis of ten major banks by Titanium Media App, including the six major state-owned banks and several joint-stock banks, six of them have seen a reduction in technology investment. For example,

In today's rapidly developing AI landscape, developers often need to download massive model files. Traditional methods of downloading individual files one by one are time-consuming and cumbersome, and organizing the resulting files can be a headache. To address this, Xunlei recently released an updated plugin with significant upgrades for large model downloads, offering a seamless experience with automatic loading of complete files, intelligent archiving, and one-click download. The upgraded one-click download feature is designed to dramatically improve download efficiency.

Ever felt frustrated by a seemingly clueless AI, wishing you could make it think before acting? Now, Anthropic has given AI a major brain upgrade! They've equipped their star model, Claude, with a groundbreaking 'think tool,' enabling it to handle complex tasks not by blindly rushing in, but by pausing to carefully consider its decisions, much like a human. This isn't just about slowing things down; it's about...

Nvidia today announced that its premier global AI conference, GTC 2025, will be held in San Jose, California from March 17th to 21st. The event is expected to draw 25,000 in-person attendees and 300,000 online viewers, showcasing the latest breakthroughs in AI and accelerated computing. A highly anticipated keynote address from Nvidia CEO Jensen Huang will highlight the conference.

Recently, reports have emerged indicating that Google has entered into close cooperation with the Israel Defense Forces (IDF) following the outbreak of conflict with Hamas. This information comes from internal company documents obtained by The Washington Post, which reveal that employees from Google Cloud responded directly to requests from the Israeli military for AI tools in the weeks following the conflict. It is understood that after Hamas launched an attack on Israel on October 7th, Google Cloud employees established contact with the IDF and emphasized the urgent need for responses in internal discussions.

In recent years, the programming capabilities of Artificial Intelligence (AI) have been continuously evolving, but they have not yet reached perfection. Recently, Max Woolf, a senior data scientist at BuzzFeed, discovered through experiments that if continuous prompts for 'writing better code' are provided to large language models (LLMs), AI can indeed generate higher quality code. This finding has garnered widespread attention, with renowned AI scientists emphasizing the importance of iteration and prompt design. In Woolf's experiment,

Yuanshi Intelligence Co., Ltd. in Shenzhen recently announced that it has completed tens of millions of RMB in angel round financing on December 25, 2024, with Tianji Capital as the investor. This financing will accelerate Yuanshi Intelligence's efforts in ecological development, strengthening technological capabilities, and launching AI applications targeting end consumers. Founded in June 2023, Yuanshi Intelligence is a high-tech enterprise focusing on the research and development of large model architectures and AI applications. With its innovative technology and clear development strategy, the company has continuously attracted the favor of the capital markets. Prior to this financing, Yuanshi Intelligence had

The future development of artificial intelligence (AI) is gradually freeing itself from dependence on human data, labels, and preferences. A new AI self-learning model known as 'Socratic Learning' is being proposed, which is expected to drive AI towards genuine self-evolution. The core of this learning model is that AI improves its capabilities by interacting and questioning itself within a closed system, without external intervention from the real world. What is 'Socratic Learning'? Don't be fooled by the name; it essentially means AI plays with itself, continuously enhancing itself through dialogue and questioning.

The rapid development of deep learning relies on the scale of datasets, models, and computational power. In the fields of natural language processing and computer vision, researchers have already discovered a power-law relationship between model performance and data scale. However, in the field of robotics, especially in robot manipulation, such scalable patterns have yet to be established. A research team from Tsinghua University recently published a paper exploring data scaling laws in robot imitation learning and proposed an efficient data collection strategy that collected sufficient data in just one afternoon, enabling...

Large Language Models (LLMs) like the GPT series exhibit astonishing abilities in language understanding, reasoning, and planning, achieving human-level performance in various challenging tasks due to their vast datasets. Most research focuses on enhancing these models further by training them on larger datasets, aiming to develop more powerful foundational models. However, while training stronger foundational models is crucial, researchers believe that empowering models with the capability to continue evolving during the reasoning phase, known as AI self-evolution, is essential for the development of AI.

Recently, Google DeepMind announced its latest AI system - AlphaChip. This system is dedicated to accelerating and optimizing the development of computer chips, and the chip layouts designed by AlphaChip have already been implemented in Google's AI accelerators. AlphaChip operates similarly to what we have previously heard about AlphaGo and AlphaZero, utilizing reinforcement learning techniques to quickly generate optimized chip layouts. According to Google DeepMi

Recently, a research team from ETH Zurich has made a shocking breakthrough by successfully cracking Google's reCAPTCHA v2 system with a success rate of 100%! This research has sparked widespread discussions about the future of image verification. The team utilized an advanced image recognition algorithm called YOLO, which, by segmenting and classifying images, enables their system to automatically solve all three types of challenges in reCAPTCHA v2.

The technology company 'Accelerated Evolution', dedicated to humanoid robot research and development, has completed hundreds of millions in pre-A funding, with investors including Bianshi Times, Minyin International, Zhongguancun Science City, and iCANX Fund, along with follow-up investment from Inno Angel. The funds will primarily be used for the development of a general ontology and enhancement of software development capabilities. CEO Cheng Hao pointed out that the AI-driven humanoid robot boom, especially the demand for vehicles of Artificial General Intelligence (AGI), is driving the transition of humanoid robots from specialization to generalization. The company's phase one commercial positioning is to provide developers with general biped robots.

In the recently concluded International Mathematical Olympiad, Google's DeepMind AI systems, AlphaProof and AlphaGeometry2, showcased remarkable problem-solving abilities, finishing just one point shy of the championship while surpassing human competitors in speed and accuracy. The AI achieved perfect scores on four problems and solved one in an astonishing 19 seconds, adhering to mathematical competition standards with rigorous clarity. This com....