AltStore, an alternative app store, has raised $6 million in Series A funding from Pace Capital, giving the firm a 15% equity stake. This funding will enable AltStore to expand its team and capitalize on opportunities in the EU and other markets like Australia, Brazil, and Japan.

The company is also launching a Mastodon server to connect with the fediverse, allowing users to receive app updates on platforms like Mastodon and Threads. Developers can opt-in to publish updates to the server, creating a social layer for app discovery and interaction.

AltStore is also donating $500,000 to various fediverse projects, including Mastodon gGmbH and others, to support the ecosystem that will enable its social network.

Oracle has addressed a zero-day vulnerability (CVE-2025-61882) in its E-Business Suite, which was actively exploited by hackers to steal personal information of corporate executives.

The vulnerability allows unauthorized network access without credentials. Indicators of compromise suggest ongoing data theft.

Google's Mandiant reported a mass exploitation campaign in August, after July patches, with Clop group sending extortion emails since last Monday. Oracle urges immediate patching.

Meta's Llama is a family of open-source generative AI models, with the latest version being Llama 4. Unlike many other AI models that are accessible only via APIs, Llama allows developers to download and use it with certain limitations. Meta partners with vendors like AWS, Google Cloud, and Microsoft Azure to make cloud-hosted versions of Llama available.

Key Features of Llama 4:

• Scout: 17 billion active parameters, 109 billion total parameters, and a 10 million token context window.
• Maverick: 17 billion active parameters, 400 billion total parameters, and a 1 million token context window.
• Behemoth: (Not yet released) 288 billion active parameters and 2 trillion total parameters.

Llama 4 models are trained on large amounts of unlabeled text, image, and video data, supporting over 200 languages. These models can perform tasks such as coding, answering math questions, and summarizing documents. Llama 4 Scout is designed for longer workflows, Maverick balances reasoning and speed, and Behemoth is intended for advanced research.

Llama is used in Meta AI chatbot experiences on Facebook Messenger, WhatsApp, Instagram, Oculus, and Meta.ai. It is also available on Llama.com and platforms like Hugging Face. Meta provides tools like Llama Guard, Prompt Guard, CyberSecEval, Llama Firewall, and Code Shield to enhance model safety and security.

Limitations: While powerful, Llama has limitations, including primary support for English in multimodal features. It was trained using datasets that include pirated e-books and articles. Additionally, Llama may produce buggy or insecure code and generate plausible but false information.

Dhravya Shah, a 19-year-old founder, has developed Supermemory, a universal memory API for AI apps that builds a knowledge graph to personalize context for users. The startup extracts insights from unstructured data, enabling applications to better understand context across various data types, including files, chats, and emails.

Supermemory has secured $2.6 million in seed funding led by Susa Ventures, Browder Capital, and SF1.vc, with participation from notable investors, including executives from Google, OpenAI, and Meta. The company already has multiple customers, including Cluely, Montra, and Scira.

Supermemory aims to differentiate itself through lower latency, offering high performance in surfacing relevant context. The solution caters to various AI applications, from email clients to video editors, providing a memory layer that more AI companies will need.