Tech World Grapples with AI Social Networks, Intimacy Crisis, and Database Innovations
The tech landscape is rapidly evolving, marked by the rise of AI-driven social networks, concerns over a growing "intimacy crisis," and advancements in database technology designed for the age of agentic AI. These developments signal significant shifts in how humans interact with technology and each other.
One notable trend is the emergence of social networks designed exclusively for artificial intelligence agents. Moltbook, an experimental social network created by Matt Schlicht of Octane AI, allows AI agents to post, comment, and follow each other, with humans observing the interactions. According to Wired, the platform mirrors the user interface of Reddit and quickly gained traction within the AI community.
Meanwhile, a contrasting trend is raising concerns about human connection. Wired reported on a potential "intimacy crisis" in the US, where nearly half of adults are single, a quarter of men experience loneliness, and depression rates are increasing. The article highlighted a study indicating that one in four Gen Z adults have never had partnered sex. Justin Garcia suggests that "we just dont crave intimacy in the same way we used to."
In the realm of database technology, Databricks recently launched Lakebase, a serverless database service aimed at streamlining application development. VentureBeat reported that Lakebase, generally available as of today, focuses on OLTP (online transaction processing) and operational databases, building upon Databricks' earlier concept of the "data lakehouse." The Lakebase service has been in development since June 2025 and is based on technology Databricks acquired via its acquisition of PostgreSQL database provider. Databricks claims this new service slashes app development time from months to days as companies prep for agentic AI.
Elsewhere, Microsoft's history with widgets continues with the release of Widget 2026, marking the company's seventh attempt to surface live information without requiring users to launch an app, according to Hacker News. Over nearly 30 years, Microsoft has launched six different implementations, each failing due to issues such as performance, security, screen space, privacy, and engagement.
Finally, MIT Technology Review highlighted the importance of identifying an "iconic use case" when designing enterprise AI systems. Mistral AI partners with companies to co-design tailored AI solutions, starting with open frontier models and customizing them to address specific challenges. According to MIT Technology Review, "Choosing the right use case can mean the difference between success and failure."
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