Meta launches "ghost posts" on Threads, letting users share "unfiltered thoughts" in posts that disappear after 24 hours; replies will appear as a DM (Marcus Mendes/9to5Mac)

Recent reports highlight the troubling trend of users of Meta's Ray-Ban glasses filming and harassing workers at massage parlors. This misuse of covert recording technology raises serious concerns about privacy and consent, as individuals seek likes and online fame at the expense of others' dignity and safety. It's a stark reminder of the potential dangers of technology when used irresponsibly.

In the rapidly evolving world of AI, there's a growing trend of teams, from solo founders to large enterprises, racing to implement AI features. While major companies like OpenAI, Google, and Meta are investing heavily in new models, you don't need a massive budget to create impressive AI applications. The key lies in leveraging the right open-source tools and frameworks that offer control, transparency, and the freedom to innovate. This article highlights five essential open-source repositories that can empower developers to build exciting AI apps without breaking the bank.

A new method called META-RAG has been introduced to enhance retrieval-augmented generation in evidence-based medicine. This approach aims to improve how medical professionals access and utilize high-quality evidence, which is crucial for reducing misdiagnoses. By leveraging large language models, META-RAG addresses the challenges faced in distinguishing reliable medical information, ultimately supporting better clinical decision-making. This innovation is significant as it could lead to improved patient outcomes and more effective healthcare practices.

The introduction of the Look and Tell dataset marks a significant advancement in the study of multimodal communication. By utilizing Meta's Project Aria smart glasses and stationary cameras, researchers captured synchronized gaze, speech, and video from participants as they guided others in identifying kitchen ingredients. This innovative approach not only enhances our understanding of referential communication from different perspectives but also sets a new benchmark for future studies in spatial representation. It's an exciting development that could lead to improved human-computer interaction and communication technologies.

A recent study highlights the advancements in Big Language Models (LLMs) and their transformative impact on businesses and daily life. Companies like Google, Anthropic, OpenAI, and Meta are at the forefront of developing these models, each with unique strengths in performance, ethical considerations, and usability. Understanding these differences is essential as they shape the future of technology and its integration into various industries.

Meta has recently laid off 600 employees from its AI division as part of a significant restructuring effort. This move comes as the company consolidates leadership under Wang Jian to enhance its AI strategy. While such layoffs can be tough for those affected, they also signal a shift in Meta's approach to AI, which could lead to more focused and innovative developments in the future.

In a significant shift within Meta, Vishal Shah, who previously led the company's metaverse unit, is now taking charge of AI product management. This change comes as Meta aims to enhance its competitive edge against OpenAI's Sora, which has been rapidly developed. This move highlights Meta's commitment to advancing its AI capabilities and adapting to the fast-evolving tech landscape, making it a noteworthy development in the ongoing race for AI innovation.

Meta's Threads is introducing disappearing posts, a feature designed to promote more candid sharing among users. This move aims to create a space where people can express their thoughts without the worry of permanence, encouraging a more authentic interaction on the platform. As social media evolves, this feature could attract users looking for a more relaxed and genuine way to communicate.

This article provides a practical guide on using APIs for real-time data collection with Python. It explains the importance of APIs, how they function, and offers step-by-step instructions for beginners. Understanding APIs is crucial in today's data-driven world, as they enable seamless integration and access to valuable information.

Amazon has launched Project Rainier, a groundbreaking $11 billion AI data center in Indiana, spanning 1,200 acres. This facility is set to enhance the capabilities of Anthropic's AI models, utilizing over 500,000 Amazon Trainium 2 chips. This development is significant as it not only showcases Amazon's commitment to advancing AI technology but also promises to create jobs and stimulate the local economy in Indiana.

In a recent discussion, UL's Professor Donna O'Shea emphasized the critical role of cybersecurity in digital engineering, highlighting the need for cyber resilience in our increasingly interconnected systems. This conversation is particularly relevant as digital sovereignty becomes a central theme in protecting sensitive data and infrastructure. As technology evolves, understanding these concepts is essential for businesses and individuals alike to safeguard against cyber threats.

BIWIN's Mini SSD has been honored by TIME magazine as one of the Best Inventions of 2025, marking a significant achievement as the only storage product to make this year's esteemed list. This recognition highlights the innovative technology behind the Mini SSD and its impact on the storage industry, showcasing BIWIN's commitment to excellence and advancement in data storage solutions.

AI is transforming the software development landscape, particularly within Agile methodologies. By following six essential rules, teams can enhance their productivity and improve the quality of their projects while being mindful of the significant risks involved. This shift is crucial as it not only streamlines processes but also empowers developers to focus on innovation and creativity, making it a pivotal moment for the industry.

In the October 2025 edition of AIhub's monthly digest, we explore key developments in AI, including insights from the AIES and ECAI conferences. This month highlights the challenges in energy supply, the role of wearable sensors, and advancements in atomic-scale simulations. These topics are crucial as they reflect ongoing innovations and discussions in the AI community, shaping future technologies and policies.