Sony's recent promotion of an AI-generated game has met with significant backlash from players due to its perceived low quality and questionable gameplay. The controversy highlights concerns about the use of AI in game development and the potential impact on player experience.

Generating charts that accurately reflect complex data remains a subtle challenge in today's data visualization landscape. Charts require not only precise layout, color, and text placement, but also the translation of these visual details into code to reproduce the intended design. However, traditional methods often rely on directly prompting vision-language models (VLMs), such as GPT-4V, which frequently struggle to translate complex visual elements into grammatically correct Python code. Even minor errors can result in charts failing to meet their design objectives.

CNBC reports that Meta is planning a standalone AI assistant app called Meta AI to better compete with OpenAI's ChatGPT and Google's Gemini. The app is expected to launch in the company's next fiscal quarter, between April and June 2025. Currently, Meta AI is only accessible through the company website and Meta's social media apps like Facebook and WhatsApp.

Recently, the Meta AI team launched the video joint embedding prediction architecture (V-JEPA) model, an innovative initiative aimed at advancing machine intelligence. Humans can naturally process information from visual signals and recognize surrounding objects and motion patterns. An important goal of machine learning is to reveal the fundamental principles that drive unsupervised learning in humans. Researchers proposed a key hypothesis—the predictive feature principle—arguing that the representations of continuous sensory inputs should be able to predict each other. Early research methods utilized slow feature analysis.

Recently, Meta officially announced a major project named Project Waterworth. This initiative represents a multi-billion dollar investment spanning several years, aimed at constructing an undersea cable exceeding 50,000 kilometers to support global AI infrastructure. Once completed, this undersea cable project will become the longest in the world, capable of withstanding damage from ship anchors and other hazards. According to the project plan, the cable will extend from the East Coast of the United States to the West Coast, with depths reaching up to 7,000.

Recently, a study led by Meta's Chief AI Scientist Yann LeCun revealed how artificial intelligence can develop a basic understanding of physics by watching videos. This research, conducted by scientists from Meta FAIR, Paris University, and EHESS, shows that AI systems can acquire intuitive physical knowledge through self-supervised learning without predefined rules. The research team employed a new method called Video Joint Embedding Predictive Architecture (V-JEPA).

Meta has recently announced that it will hold the first LlamaCon developer conference on April 29, focusing on the latest advancements in its Llama series of generative AI models. The event aims to provide developers with a platform to share the latest achievements in open-source AI, helping them to better build applications and products. As generative AI technology rapidly evolves, Meta hopes to further promote the development of its ecosystem through this conference. At the upcoming event, Meta plans to showcase several.

Social media giant Meta recently announced that they have developed a new device capable of reading brain neural signals to enable text input. This research achievement is detailed by Meta's scientists in two studies, utilizing advanced brain imaging technology and deep learning AI models to successfully decode the brain signals of individuals while they type, even reconstructing complete sentences. Specifically, this technology relies on a scanning device known as magnetoencephalography (MEG), which can capture the faint magnetic signals emitted by the brain.

Recently, the research team at Meta Reality Labs has jointly released an innovative generative model called 'Pippo', which can generate a dense turnaround video with a resolution of up to 1K from a randomly taken photo. This breakthrough technology marks another significant advancement in the fields of computer vision and image generation. The core of the Pippo model lies in the design of its multi-view diffusion transformer. Unlike traditional generative models, Pippo does not require any additional inputs, such as fitted parameters.

On the technological stage, two giants, Apple and Meta, are quietly embarking on a competition for AI-driven humanoid robots. Despite their rivalry in certain areas, the intertwining of cooperation and competition may usher in a new chapter in technology. As a pioneer in consumer electronics, Apple's innovation capabilities in smart hardware are unquestionable. Recently, reports have revealed that Apple is heavily investing in artificial intelligence and robotics technology, aiming to develop a humanoid robot capable of interacting naturally with humans.

Meta has recently launched a new risk policy framework aimed at assessing and mitigating the risks associated with cutting-edge AI models, with the intention to halt development or restrict the release of these systems when necessary. This framework, named 'Cutting-edge AI Framework', outlines how Meta will categorize AI models into high-risk and critical risk categories, and take appropriate measures to reduce risks to an 'acceptable level'. In this framework, critical risks are defined as those uniquely capable of executing specific threat scenarios, while high risk implies