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Microsoft has released the public preview of Deep Research, a new service called Azure AI Foundry. This service functions as a research assistant similar to OpenAI agents. It can automatically break down complex tasks, perform multi-turn information retrieval and verification using Bing search and GPT models, and generate audit-able research reports. The service is applicable to fields such as academia, finance, and healthcare, and supports API integration, significantly improving research efficiency. Applications are now open, and developers can integrate its automation capabilities into their own applications.

AI infrastructure company CoreWeave plans to acquire data center operator Core Scientific for $9 billion in stock, with the transaction expected to be completed by Q4 2025. The acquisition will help CoreWeave reduce operational costs, decrease external dependencies, and enhance its AI computing capabilities. Core Scientific currently has 1.3 gigawatts of power capacity and 1 gigawatt of expansion potential, which will support CoreWeave's growing AI computing demand. Previously, OpenAI had invested in Core

In the media Q&A session after today's Honor Magic V5 and AI Terminal Ecosystem Launch, Honor CEO Li Jian, CFO Peng Qiuen, and Product Line President Fang Fei had in-depth discussions with the media. During the event, Honor officially announced support for the MCP and A2A protocols, and revealed that it will collaborate deeply with partners such as Alibaba, BYD, and Midea in the fields of intelligent service ecosystem, smart vehicle networking, and smart home. Honor CEO Li Jian emphasized in the conversation that 'openness' is the core philosophy of Honor. He pointed out...

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...

According to the latest report from Bloomberg, global renowned music companies including Universal Music Group, Warner Music Group and Sony Music Entertainment are in talks with two artificial intelligence startups, Udio and Suno, regarding copyright licensing. The aim of this negotiation is to establish a framework to ensure that AI companies can reasonably compensate artists for the use of their works. These two companies, Udio and Suno, focus on helping emerging music artists create songs; by simply providing prompts describing sounds or song themes, they can generate audio recordings.

China National Petroleum Corporation has officially released its latest Kunlun large model, with a parameter count as high as 300 billion. This milestone advancement marks an important step forward for China National Petroleum Corporation in the field of AI. The development of this large model was jointly created by four major giants: China National Petroleum Corporation, China Mobile, Huawei, and iFlytek. It is expected to complete formal filing by August 2024 and become the first approved large model in the energy and chemical industry. It is worth noting that the launch of the Kunlun large model was not accidental. As early as August 28 last year, China National Petroleum Corporation had launched a 33 billion parameter model.

Recently, several leading technology companies in the industry announced their joint investment to build a super-large artificial intelligence (AI) computing center called "Stargate UAE". This project is led by G42 Company of the UAE and jointly developed with international giants such as OpenAI, Oracle, NVIDIA, SoftBank, and Cisco, aiming to promote AI technology innovation and application in the Middle East region and even globally.

According to foreign media reports, Perplexity AI is in advanced negotiations for a funding round of up to $500 million, which is expected to push the company's valuation up to $14 billion. The round is being led by renowned venture capital firm Accel, marking the rapid rise of Perplexity in the AI search sector and its aim to challenge Google and Microsoft-backed OpenAI's dominance in search. AIbase observed that this news has sparked extensive discussions within the tech community, with investors showing extremely high enthusiasm for AI's potential to reshape the search market. Valuation surged

At the recently concluded 18th China Electronic Information Annual Conference, the China Electronics Society announced the winners of the 2024 Science and Technology Awards. Among them, the project "Key Technologies and Applications of Secure and Trusted Dynamic Behavior in the Internet with High-Efficiency Collaboration," jointly developed by Tsinghua University, Beijing Zhongguancun Laboratory, and Ant Group, won the first prize for scientific and technological progress. This achievement not only demonstrates the enormous potential of cutting-edge technology in the field of secure and trustworthy computing, but also provides an effective solution to address the increasingly complex network environment. With the proliferation of the internet, malicious traffic attacks and covert...

On March 27th, Alibaba launched its first multimodal large model, Qwen2.5-Omni-7B. This model boasts powerful capabilities, handling various input modalities such as text, images, audio, and video, and generating text and natural speech outputs in real-time. This innovative technological breakthrough marks another significant advancement for Alibaba in the field of artificial intelligence. In the authoritative OmniBench multimodal fusion task benchmark, Qwen2.5-Omni achieved...

A powerful newcomer has emerged in the fintech arena. The Fin-R1 model, jointly developed by Professor Liwen Zhang's team (SUFE-AIFLM-Lab) at the School of Statistics and Data Science, Shanghai University of Finance and Economics, and Caiyue Xingchen, has been officially open-sourced, attracting significant attention due to its impressive performance. This financial specialized large language model, based on Qwen2.5-7B and trained with reinforcement learning, achieves leading performance across multiple financial benchmark tests. Remarkably, Fin-R1 surpasses most models of comparable size, and even many significantly larger models, despite having only 7B parameters.