Recently, according to Bloomberg, Apple is developing a new voice assistant, Siri, which will utilize advanced large language models (LLMs) technology to achieve a more natural conversational experience. This move aims to close the gap with competitors, as products like Google's Gemini Live have demonstrated higher naturalness in conversational capabilities in recent years. According to sources, the new Siri assistant will completely replace the current Siri interface used by customers, with a planned release in 2026.

With the rapid development of artificial intelligence (AI) technologies in industrial sectors, experts indicate that high-quality data and data governance will be more important than generative technologies. By 2025, companies must focus more on scalable and flexible solutions when adopting AI, rather than solely relying on Generative AI (GenAI). Image note: The picture is generated by AI, authorized by the image service provider Midjourney, based on the analysis by Qlik, the key to fully harnessing AI's potential lies in companies' investments in high-quality, real-time data.

During the 2024 World Internet Conference held today in Wuzhen, Honor CEO Zhao Ming shared his vision for the future development of mobile phones. He stated that by 2027, phones are expected to be able to incorporate large AI models with 100 billion parameters. This advancement will enable phones to learn, understand, and predict user behaviors and intentions, thereby providing users with more personalized arrangements for their lives and work. Image source note: Image generated by AI, image authorized by service provider Midjourney. Currently, several phones on the market are equipped with models of similar scale.

During the 2024 World Internet Conference in Wuzhen, Alibaba Group CEO Wu Yongming delivered a keynote speech at the Internet Entrepreneurs Forum on November 21, emphasizing the profound impact of artificial intelligence (AI) on the internet industry. He pointed out that the biggest change in the internet industry this year is still the rapid development of AI technology. Wu Yongming stated that the greatest value of AI is not merely the development of one or two super apps on mobile phones, but in driving productivity transformation across various industries. The development of AI requires a prosperous ecosystem of technology, products, and market.

Microsoft has recently made significant progress in the field of enterprise AI intelligences, establishing the world's largest enterprise AI intelligent ecosystem. Since the launch of Copilot Studio, over 100,000 organizations have participated in the creation and editing of AI intelligences. This milestone signifies Microsoft's leading position in the enterprise technology sector. Microsoft executive Charles Lamanna stated that the growth rate exceeded expectations, being faster than the adoption rate of any cutting-edge technology previously released by the company.

Recently, AI large language models (LLMs) have been performing remarkably well in various tasks, effortlessly writing poetry, coding, and chatting; they seem to be capable of anything! But can you believe it? These 'genius' AIs are actually 'math novices'! They often fail dramatically when tackling simple arithmetic problems, leaving people astonished. A recent study unveiled the 'quirky' secret behind LLMs' arithmetic reasoning abilities: they rely neither on powerful algorithms nor solely on memory, but instead adopt a strategy known as 'heuristic hodgepodge'!

A recent study indicates that generative AI models, particularly large language models (LLMs), can be used to create a framework that accurately simulates human behavior across various scenarios. This finding provides a powerful new tool for social science research. The researchers initially recruited over 1,000 participants from diverse backgrounds in the United States and conducted in-depth interviews lasting up to two hours, collecting information about their life experiences, opinions, and values. Subsequently, they utilized these interview records along with a large language model to construct.

Reinforcement learning has seen significant success in recent years, but its low sample efficiency limits its application in the real world. World models, as a type of environment generation model, offer hope for addressing this issue. They can serve as simulated environments to train reinforcement learning agents with higher sample efficiency. Currently, most world models simulate environment dynamics through discrete latent variable sequences. However, this method of compressing into a compact discrete representation may overlook visual details that are critical for reinforcement learning. Meanwhile, diffusion models have become prominent in the field of image generation.

Recently, researchers from ByteDance Research Institute and Tsinghua University jointly released a new study, pointing out that current AI video generation models, such as OpenAI's Sora, while capable of creating stunning visual effects, have significant flaws in understanding basic physical laws. This study has sparked widespread discussion on the capabilities of AI in simulating reality. The research team tested AI video generation models under three different scenarios: predictions under known patterns and predictions under unknown patterns.

In today's technology landscape, CLIP (Contrastive Language-Image Pre-training) is an important multimodal foundational model. It combines visual signals and text signals into a shared feature space using contrastive learning loss on a large-scale dataset of image-text pairs. As a retriever, CLIP supports various tasks such as zero-shot classification, detection, segmentation, and image-text retrieval. Meanwhile, as a feature extractor, it performs well in nearly all...

Recently, NVIDIA unveiled its brand-new Blackwell platform and showcased its initial performance in the MLPerf Training 4.1 benchmark tests. According to the test results, Blackwell achieved a doubling of performance in certain aspects compared to the previous Hopper platform, garnering widespread attention in the industry. In the MLPerf Training 4.1 benchmark tests, the Blackwell platform excels in LLM (Large Language Models).

In the field of generative AI, Apple's efforts seem to be primarily focused on mobile devices, especially the latest iOS 18 system. However, the new Apple M4 chip demonstrates powerful performance in the recently released Mac Mini and MacBook Pro, enabling effective local operation of the most powerful open-source large language models (LLMs) available today, such as Meta's Llama-3.1405B, Nvidia's Nemotron70B, and Qwen.

Microsoft recently announced the launch of a series of artificial intelligence (AI) models specifically designed for the manufacturing, agriculture, and financial services sectors. These models have been developed in collaboration with renowned companies such as Siemens, Bayer, and Rockwell Automation, aiming to integrate advanced AI technology into industries that have long relied on traditional methods. The newly launched dedicated models are now available in Microsoft's Azure AI catalog, marking a significant step for Microsoft in developing AI tools that meet the unique needs of different industries. This initiative reflects Microsoft's commitment to advancing.