Google Releases Conductor: a context driven Gemini CLI extension that stores knowledge as Markdown and orchestrates agentic workflowsMarkTechPost Google has introduced Conductor, an open source preview extension for Gemini CLI that turns AI code generation into a structured, context driven workflow. Conductor stores product knowledge, technical decisions, and work plans as versioned Markdown inside the repository, then drives Gemini agents from those files instead of ad hoc chat prompts. From chat based coding
The post Google Releases Conductor: a context driven Gemini CLI extension that stores knowledge as Markdown and orchestrates agentic workflows appeared first on MarkTechPost.
Google has introduced Conductor, an open source preview extension for Gemini CLI that turns AI code generation into a structured, context driven workflow. Conductor stores product knowledge, technical decisions, and work plans as versioned Markdown inside the repository, then drives Gemini agents from those files instead of ad hoc chat prompts. From chat based coding
The post Google Releases Conductor: a context driven Gemini CLI extension that stores knowledge as Markdown and orchestrates agentic workflows appeared first on MarkTechPost. Read More
More than 230 malicious packages for the personal AI assistant OpenClaw (formerly known as Moltbot and ClawdBot) have been published in less than a week on the tool’s official registry and on GitHub. […] Read More
In response to user feedback on AI integration, Mozilla announced today that the next Firefox release will let users disable AI features entirely or manage them individually. […] Read More
A new GlassWorm malware attack through compromised OpenVSX extensions focuses on stealing passwords, crypto-wallet data, and developer credentials and configurations from macOS systems. […] Read More
Microsoft has announced a three-phase approach to phase out New Technology LAN Manager (NTLM) as part of its efforts to shift Windows environments toward stronger, Kerberos-based options. The development comes more than two years after the tech giant revealed its plans to deprecate the legacy technology, citing its susceptibility to weaknesses that could facilitate relay […]
Every week brings new discoveries, attacks, and defenses that shape the state of cybersecurity. Some threats are stopped quickly, while others go unseen until they cause real damage. Sometimes a single update, exploit, or mistake changes how we think about risk and protection. Every incident shows how defenders adapt — and how fast attackers try […]
Chinese state-sponsored threat actors were likely behind the hijacking of Notepad++ update traffic last year that lasted for almost half a year, the developer states in an official announcement today. […] Read More
The data breach notification service Have I Been Pwned says that a data breach at the U.S. food chain Panera Bread affected 5.1 million accounts, not 14 million customers as previously reported. […] Read More
Fake high-yield investment platforms are surging worldwide, promising “guaranteed” returns that mask classic Ponzi schemes.CTM360 explains how HYIP scams scale through social media, recycled templates, and referral abuse. […] Read More
Semi-Autonomous Mathematics Discovery with Gemini: A Case Study on the ErdH{o}s Problemscs.AI updates on arXiv.org arXiv:2601.22401v1 Announce Type: new
Abstract: We present a case study in semi-autonomous mathematics discovery, using Gemini to systematically evaluate 700 conjectures labeled ‘Open’ in Bloom’s ErdH{o}s Problems database. We employ a hybrid methodology: AI-driven natural language verification to narrow the search space, followed by human expert evaluation to gauge correctness and novelty. We address 13 problems that were marked ‘Open’ in the database: 5 through seemingly novel autonomous solutions, and 8 through identification of previous solutions in the existing literature. Our findings suggest that the ‘Open’ status of the problems was through obscurity rather than difficulty. We also identify and discuss issues arising in applying AI to math conjectures at scale, highlighting the difficulty of literature identification and the risk of ”subconscious plagiarism” by AI. We reflect on the takeaways from AI-assisted efforts on the ErdH{o}s Problems.
arXiv:2601.22401v1 Announce Type: new
Abstract: We present a case study in semi-autonomous mathematics discovery, using Gemini to systematically evaluate 700 conjectures labeled ‘Open’ in Bloom’s ErdH{o}s Problems database. We employ a hybrid methodology: AI-driven natural language verification to narrow the search space, followed by human expert evaluation to gauge correctness and novelty. We address 13 problems that were marked ‘Open’ in the database: 5 through seemingly novel autonomous solutions, and 8 through identification of previous solutions in the existing literature. Our findings suggest that the ‘Open’ status of the problems was through obscurity rather than difficulty. We also identify and discuss issues arising in applying AI to math conjectures at scale, highlighting the difficulty of literature identification and the risk of ”subconscious plagiarism” by AI. We reflect on the takeaways from AI-assisted efforts on the ErdH{o}s Problems. Read More
