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Recently, a research team from the University of Hong Kong, The Chinese University of Hong Kong, and SenseTime has released a groundbreaking framework - GoT-R1. This new multimodal large model significantly enhances the semantic and spatial reasoning capabilities of AI in visual generation tasks by introducing reinforcement learning (RL), successfully generating high-fidelity and semantically consistent images from complex text prompts. This advancement marks another leap in image generation technology. Currently, although existing multimodal large models have made significant progress in generating images based on text prompts

Hoje, o Hello, o Grupo Ant e a BYD, por meio de seus investidores, registraram conjuntamente a empresa Shanghai Zao Fu Intelligent Technology Co., Ltd. em Xangai. Esta nova empresa

A deep dive into how Eureka AI addresses three major pain points in R&D - information overload, innovation bottlenecks, and evaluation difficulties - through core features such as a technical Q&A assistant and TRIZ theory innovation. It provides end-to-end AI support solutions from concept to implementation.

A comprehensive analysis of the core functions of Patsnap's Eureka AI Agent, including creative generation, feasibility validation, intellectual property protection, and material R&D acceleration capabilities, to understand how AI can increase R&D efficiency by 3-5 times.

This article provides a comprehensive review of the innovation acceleration features of Patsnap's Eureka AI Agent, covering core capabilities such as creative generation, patent search, and cross-domain analysis, revealing how AI is transforming enterprise R&D processes.

On the evening of June 11, XPeng Motor officially released its latest model - XPeng G7. This car is known as the world's first AI car with L3-level computing power. Its biggest highlight lies in the installation of XPeng’s self-developed Turing AI chip, which has a computational capability equivalent to three Orin-X chips, showcasing XPeng's technical advantages in the intelligent vehicle field. The XPeng G7 is equipped with a powerful 40-core processor that can run up to 30B simulation parameters and features two self-developed neural network processors.

According to a report by Bloomberg, in January this year, the low-cost and high-performance AI model launched by Chinese AI company DeepSeek caused a shock in the global technology community and brought significant urgency to China's tech giant Alibaba. To quickly catch up with this technological breakthrough, engineers at Alibaba canceled their vacation during the most important traditional Chinese festival — the Spring Festival — choosing to stay overnight in the company and fully commit themselves to AI R&D. Chairman of Alibaba, Joseph Tsai, vividly told this story of racing against time at the VivaTech Science and Technology Conference held in Paris on Wednesday.

The field of artificial intelligence continues to develop rapidly, and DeepSeek's latest update for its R1-0528 model has drawn significant attention from the developer community. According to AIbase, the upgraded DeepSeek R1-0528 now supports local tool calls on OpenRouter, a major improvement that enables developers to seamlessly integrate local tools into their AI workflows. Local tool calls enhance workflow efficiency. DeepSeek R1-0528 is an open-source inference model that rivals Ope

A new study led by Apple researchers has poured cold water on the current large reasoning models (LRMs) that are highly anticipated. The research found that when solving complex tasks, reasoning models designed to simulate thinking processes, such as Claude3.7Thinking and Deepseek-R1, not only failed to show advantages but also exhibited serious problems like insufficient reasoning and performance collapse. This study tested four classic logical puzzles: the Tower of Hanoi, Checkers, River Crossing, and Block World. These puzzles allow precise control over the tasks.

Google recently released its latest preview version of Gemini2.5Pro, a product known as the 'most intelligent' model, which was first announced in March and then updated in May. The preview version aims to give enterprises an opportunity to test new applications or replace earlier versions. According to Google's official blog, this new version performs better in responsiveness and creativity, while surpassing other models in coding and reasoning ability. At the I/O Developer Conference in May, Google revealed that Gemini2.

According to a deep analysis of Mary Meeker's latest AI trend report, the world's largest tech companies are investing in AI research and development and capital expenditure on an unprecedented scale and speed. The report points out that over the past two decades, capital expenditures in the technology industry have been continuously increasing, initially for storing and accessing data, then for distributing and scaling, and now mainly focusing on computing and intelligence. This AI trend report highlights that by 2023, AI has evolved from a research function into an important capital expenditure project. The six major U.S. companies...

Recently, Stanford University released a comprehensive evaluation of clinical medical AI models. DeepSeek R1 stood out as the champion among nine leading large models, achieving a 66% win rate and a macro average score of 0.75. The highlight of this evaluation is that it not only focuses on traditional medical license exam questions but also delves into the daily work scenarios of clinical doctors, providing more practical assessments. The evaluation team developed an integrated assessment framework called MedHELM, which includes 35 benchmarks covering 22 subtasks in medicine.

Recently, DeepSeek released an updated version of its latest R1 reasoning AI model, which demonstrated excellent performance in multiple math and coding benchmarks. However, DeepSeek did not disclose the source of the training data for its model, leading some AI researchers to question it and speculate that the model may have been partially trained based on Google's Gemini AI series. Melbourne developer Sam Paeach claimed that he found...

According to a new analysis, the power consumption of artificial intelligence is expected to reach nearly half of the total electricity consumption of global data centers by the end of 2025, meaning AI energy consumption will soon surpass bitcoin mining. The analysis was conducted by Alex de Vries-Gao, a Ph.D. student at the Environmental Institute of Vrije Universiteit Amsterdam. He has previously tracked the power consumption and environmental impact of cryptocurrencies and published related data on his website Digiconomist. Currently, AI has already accounted for a significant portion of data center energy usage.