“Giant superatoms” could finally solve quantum computing’s biggest problem
In the pursuit of powerful and stable quantum computers, researchers at Chalmers University of Technology, Sweden, have developed the theory for an entirely new quantum system – based on the novel concept of ‘giant superatoms’. This breakthrough enables quantum information to be protected, controlle...
By compiling a simple program directly into transformer weights.
The post I Built a Tiny Computer Inside a Transformer appeared first on Towards Data Science.
Comprehension Debt: The Hidden Cost of AI-Generated Code
The following article originally appeared on Addy Osmani’s blog site and is being reposted here with the author’s permission. Comprehension debt is the hidden cost to human intelligence and memory resulting from excessive reliance on AI and automation. For engineers, it applies most to agentic engin...
Moovila Earns Multiple AI Industry Honors, Recognised in Second CRN AI 100
Moovila, the leading AI-driven project automation platform for managed service providers (MSPs), has been named to the 2026 CRN AI 100 list in the AI Software category. This marks the second consecutive year Moovila has been recognized on the prestigious list, which highlights companies driving inno...
Multi-agent orchestration with human-in-the-loop oversight compresses full-scope pentest engagements from weeks to under 48 hours Strobes, a leader in Exposure Management, today announced the launch of its proprietary AI Harness, a multi-agent orchestration engine that powers end-to-end AI Penetrati...
Enterprises power agentic workflows in Cloudflare Agent Cloud with OpenAI
Cloudflare brings OpenAI’s GPT-5.4 and Codex to Agent Cloud, enabling enterprises to build, deploy, and scale AI agents for real-world tasks with speed and security.
MiniMax Releases MMX-CLI: A Command-Line Interface That Gives AI Agents Native Access to Image, Video, Speech, Music, Vision, and Search
MiniMax, the AI research company behind the MiniMax omni-modal model stack, has released MMX-CLI — Node.js-based command-line interface that exposes the MiniMax AI platform’s full suite of generative capabilities, both to human developers working in a terminal and to AI agents running in tools like ...
GNN-as-Judge: Unleashing the Power of LLMs for Graph Learning with GNN Feedback
arXiv:2604.08553v1 Announce Type: new
Abstract: Large Language Models (LLMs) have shown strong performance on text-attributed graphs (TAGs) due to their superior semantic understanding ability on textual node features. However, their effectiveness as predictors in the low-resource setting, where la...
QuanBench+: A Unified Multi-Framework Benchmark for LLM-Based Quantum Code Generation
arXiv:2604.08570v1 Announce Type: new
Abstract: Large Language Models (LLMs) are increasingly used for code generation, yet quantum code generation is still evaluated mostly within single frameworks, making it difficult to separate quantum reasoning from framework familiarity. We introduce QuanBenc...
arXiv:2604.08571v1 Announce Type: new
Abstract: While Large Language Models (LLMs) achieve high performance on standard mathematical benchmarks, their underlying reasoning processes remain highly overfit to standard textual formatting. We propose a perturbation pipeline consisting of 14 techniques ...
Ranked Activation Shift for Post-Hoc Out-of-Distribution Detection
arXiv:2604.08572v1 Announce Type: new
Abstract: State-of-the-art post-hoc out-of-distribution detection methods rely on intermediate layer activation editing. However, they exhibit inconsistent performance across datasets and models. We show that this instability is driven by differences in the act...
OpenKedge: Governing Agentic Mutation with Execution-Bound Safety and Evidence Chains
arXiv:2604.08601v1 Announce Type: new
Abstract: The rise of autonomous AI agents exposes a fundamental flaw in API-centric architectures: probabilistic systems directly execute state mutations without sufficient context, coordination, or safety guarantees. We introduce OpenKedge, a protocol that re...
From Business Events to Auditable Decisions: Ontology-Governed Graph Simulation for Enterprise AI
arXiv:2604.08603v1 Announce Type: new
Abstract: Existing LLM-based agent systems share a common architectural failure: they answer from the unrestricted knowledge space without first simulating how active business scenarios reshape that space for the event at hand -- producing decisions that are fl...
RAMP: Hybrid DRL for Online Learning of Numeric Action Models
arXiv:2604.08685v1 Announce Type: new
Abstract: Automated planning algorithms require an action model specifying the preconditions and effects of each action, but obtaining such a model is often hard. Learning action models from observations is feasible, but existing algorithms for numeric domains ...
Parameterized Complexity Of Representing Models Of MSO Formulas
arXiv:2604.08707v1 Announce Type: new
Abstract: Monadic second order logic (MSO2) plays an important role in parameterized complexity due to the Courcelle's theorem. This theorem states that the problem of checking if a given graph has a property specified by a given MSO2 formula can be solved by a...
AI Weekly Issue #483: 100 years from now : The Ghost in the Contract
This is 100 Years From Now, a weekly series. Once a week, we skip ahead a century and imagine ordinary life in a world that's had a hundred years to absorb the things we're only beginning to build. No predictions — just honest speculation about where our choices lead.
This week: what happens when ac...
Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts
This paper was accepted at the Workshop on Navigating and Addressing Data Problems for Foundation Models at ICLR 2026.
Large language models (LLMs) can struggle to memorize factual knowledge in their parameters, often leading to hallucinations and poor performance on knowledge-intensive tasks. In th...
Meta AI and KAUST Researchers Propose Neural Computers That Fold Computation, Memory, and I/O Into One Learned Model
Researchers from Meta AI and the King Abdullah University of Science and Technology (KAUST) have introduced Neural Computers (NCs) — a proposed machine form in which a neural network itself acts as the running computer, rather than as a layer sitting on top of one. The research team presents both a ...
A Coding Implementation of MolmoAct for Depth-Aware Spatial Reasoning, Visual Trajectory Tracing, and Robotic Action Prediction
In this tutorial, we walk through MolmoAct step by step and build a practical understanding of how action-reasoning models can reason in space from visual observations. We set up the environment, load the model, prepare multi-view image inputs, and explore how MolmoAct produces depth-aware reasoning...
Why storing and retrieving data isn’t enough to build reliable AI memory systems
The post Stop Treating AI Memory Like a Search Problem appeared first on Towards Data Science.
MiniMax Just Open Sourced MiniMax M2.7: A Self-Evolving Agent Model that Scores 56.22% on SWE-Pro and 57.0% on Terminal Bench 2
MiniMax has officially open-sourced MiniMax M2.7, making the model weights publicly available on Hugging Face. Originally announced on March 18, 2026, MiniMax M2.7 is the MiniMax’s most capable open-source model to date — and its first model to actively participate in its own development cycle, a me...