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Online Span Minimization for Flexible Uniform Jobs
arXiv:2606.06681v1 Announce Type: new Abstract: Motivated by the critical need for energy-efficient scheduling in cloud computing, this paper investigates Span Minimization, a fundamental variant of the well-studied BusyTime problem. In the general BusyTime problem, $n$ jobs characterized by release times, deadlines, and processing times must be partitioned into bundles of capacity $B$, where the objective is to minimize the total active duration of the virtual machines. Span minimization...
Job: Head of Stonehenge
Head of Stonehenge - Title - Head of Stonehenge - Location - Stonehenge, Amesbury, Wiltshire, SP4 7DE - Salary - From £64,189 p.a. depending on skills and experience / 36 hours per week / Permanent - Job type - Permanent - Ref - 16449 Heritage is for everybody, and we are here for heritage. Heritage lives in places and people, memories and stories, artefacts and traditions.
Show HN: TakoVM – Isolated model and tool execution used by enterprises
Run untrusted Python safely. Job queues and Docker isolation built-in. Run AI-generated code in isolated Docker containers with optional gVisor sandboxing.
A musical puzzle box, Consume Me on iOS and other new indie games worth checking out
A musical puzzle box, Consume Me on iOS and other new indie games worth checking out Plus, a whole bunch of neat demos ahead of Steam Next Fest. Welcome to our latest roundup of what's going on in the indie game space. This time around, we'll take a look at some projects that might have slipped under your radar amid all the Summer Game Fest ballyhoo.
When AI Builds Itself: Our progress toward recursive self-improvement
For most of AI’s history, humans drove every step in its development cycle. But at Anthropic, we are delegating a growing share of AI development to AI systems themselves, which is speeding up our work. Taken far enough, and given enough compute, that trend points to an AI system capable of fully autonomously designing and developing its own successor.
Twelve quick tips for designing AI-driven HPC workflows
Announce Type: new Abstract: High-performance computing (HPC) clusters remain the backbone of large-scale scientific computation, traditionally executing deterministic, linear pipelines optimised for predictable performance. However, the pervasive integration of artificial intelligence (AI) and foundation models into scientific research has introduced a fundamentally new computational paradigm. AI-driven workflows are characteristically iterative, data-driven, and probabilistic, introducing...
A Human-Sensitive Controller: Adapting to Human Musculoskeletal Disorder-Related Constraints via Reinforcement Learning
Announce Type: replace Abstract: Work-Related Musculoskeletal Disorders continue to be a major challenge in industrial environments, leading to reduced workforce participation, increased healthcare costs, and long-term disability. This study introduces a human-sensitive robotic system aimed at reintegrating individuals with a history of musculoskeletal disorders into standard job roles, while simultaneously optimizing ergonomic conditions for the broader workforce. This research leverages...
SWARM+: Scalable and Resilient Multi-Agent Consensus for Decentralized Data-Aware Workload Management
arXiv:2603.19431v3 Announce Type: replace Abstract: Distributed scientific workflows are increasingly executed across heterogeneous and geo-distributed computing environments, where centralized workload orchestration becomes a scalability and resilience bottleneck. This paper presents SWARM+, a decentralized workload management system that coordinates workload placement through hierarchical multi-agent consensus, reducing coordination overhead and dramatically improving scalability, while...
SWARM+: Scalable and Resilient Multi-Agent Consensus for Decentralized Data-Aware Workload Management
arXiv:2603.19431v2 Announce Type: replace Abstract: Distributed scientific workflows are increasingly executed across heterogeneous and geo-distributed computing environments, where centralized workload orchestration becomes a scalability and resilience bottleneck. This paper presents SWARM+, a decentralized workload management system that coordinates workload placement through hierarchical multi-agent consensus, reducing coordination overhead and dramatically improving scalability, while...
Google's 20% 'project' has become AI's 120% 'attention'
Twenty years ago, a few weeks into my job at Google, I wrote a post about 20% time.1 For anyone who never ran into it: 20% time was Google’s policy of letting engineers spend a day a week, a fifth of their time, on a project of their own choosing. The argument in that post was that you couldn’t just copy it. 20% time worked because of the environment around it, not because someone wrote “20%” in a handbook.