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LLMs are now playing detective, robots are getting a shortcut, and DeepMind’s new model is eyeing the factory floor.
Catch you tomorrow—same time, same code.
BLADE is a training-free framework that audits how information is used in LLM multi‑agent systems to pinpoint the agent and step responsible for a failure.
BLADE builds on dependency tracing by adding probabilistic judgments via Jev to evaluate whether downstream decisions faithfully use their sources. It selects critical handoffs for auditing rather than inspecting all interactions, aiming to improve failure attribution without retraining agents.
ChunkAct introduces action chunking for agentic robotics, allowing a single LLM call to launch a sequence of primitives that runs autonomously until failure.
By compiling memory‑based routines into reusable chunks, ChunkAct removes the need for per‑primitive LLM reasoning during execution, reducing computational cost and enabling memory‑free test‑time operation. The approach keeps the flexibility of LLM‑guided planning while improving efficiency.
SEAR is a framework and benchmark that evaluates whether language‑model agents truly learn skills that transfer across simulated and real robot tasks.
SEAR runs agents in three modes—code‑as‑policy, agent‑as‑policy, and auto‑research—while controlling for repeated attempts, privileged simulator data, budget size, and luck. The benchmark tests transferability to new tasks, new simulators, and real‑world robots, providing a rigorous measure of autonomous skill acquisition.
Google DeepMind and GovTech Singapore deployed lightweight on‑device Gemma models to detect conversational scams in private chats without sending data to the cloud.
The collaboration focuses on a privacy‑preserving solution that runs entirely on the device, leveraging Gemma's small footprint to intercept scam messages in real time. Zero cloud egress ensures user data remains local, addressing regulatory and security concerns.
Meta’s Generative Ads Model (GEM) is a large recommendation‑system foundation model that the company is scaling with new hardware and extending across its ads ecosystem.
First announced last year as the industry’s largest RecSys foundation model, GEM introduced an LLM‑inspired approach to ads recommendation, yielding notable performance gains. Ongoing work aims to increase compute capacity and improve intelligence transfer to support broader advertising use cases.
DeepMind outlines its approach to responsibly develop Gemini 4 Argon, focusing on safety and ethical considerations.
The post emphasizes rigorous testing, alignment research, and governance frameworks intended to mitigate risks as the model scales. It signals DeepMind’s commitment to transparent, safety‑first development practices for advanced AI systems.
DeepMind announced Gemini 4 Argon, a new robotics‑focused AI model.
Gemini 4 Argon is positioned for robot perception and control tasks, extending DeepMind's Gemini series into embodied AI. No technical specifications were disclosed in the brief announcement.
OpenAI introduced GPT‑6 Astra and GPT‑Image‑2.5 to enable videos longer than ten minutes with higher visual fidelity.
The update also mentions GPT‑Live for voice‑driven filmmaking, suggesting a pipeline from script to video. These tools aim to reduce the need for manual editing in longer content creation.
Hugging Face released LFM2.5‑24B‑A2B, a 24‑billion‑parameter on‑device model for private inference.
The model is optimized for fast execution on edge hardware while keeping data local, targeting privacy‑sensitive applications. No benchmark numbers were provided in the announcement.
The HF trending model autotrust/JEV‑35B has been downloaded 17,426 times and received 657 likes.
JEV‑35B is a text‑classification model, but the post does not list its architecture, size, or performance metrics. Its popularity suggests community interest in its capabilities.
LWN reported security updates for multiple Linux distributions on Tuesday, covering dozens of packages.
Updates span core components such as glibc, the kernel, and OpenSSL‑related libraries across AlmaLinux, Debian, Fedora, Mageia, Oracle, and SUSE. Users should apply the patches promptly to mitigate disclosed vulnerabilities.
Hackaday's "The FPGA Chronicles" series explores probing the Tang Nano 20K using open‑source toolchains.
Recent installments compared GOWIN's proprietary tools with community‑maintained alternatives, highlighting trade‑offs in ease of use versus flexibility. The article links to further reading for detailed build instructions.
Asterinas kernel version 0.19.0 adds a graphics subsystem that can run X.org, minimal 64-bit Arm support, and improved virtualization.
The release continues the project’s goal of a Rust‑based OS kernel, extending hardware compatibility while keeping the codebase small. The new virtualization enhancements aim to simplify VM integration, and the graphics stack remains lightweight for embedded use cases.
Hackers have enabled raw 2.4 GHz radio transmission on ESP32 variants using the ESP‑SDR hack.
The modification leverages undocumented radio sample access inside the ESP32, turning the chip into a low‑cost software‑defined radio. While the post notes the speed of the discovery, it does not provide performance metrics or regulatory guidance.
At Kangrejos 2026, a patch series introduced an Ownable trait to let Rust code manage cleanup of C‑allocated objects in the Linux kernel.
The Ownable trait bridges Rust’s ownership model with existing C APIs, allowing Rust developers to safely wrap C resources without taking over deallocation. The proposal seeks consensus after months of mailing‑list discussion and could streamline future Rust‑for‑Linux integrations.
PostgreSQL 19 beta has seen about forty feature reverts, each averaging a three‑line fix, due to faster LLM‑assisted code review exposing defects.
Peter Eisentraut notes that many reverted features had deep architectural flaws, while others were minor edge‑case issues that would normally be patched over years. The accelerated discovery pace creates overhead that threatens the beta schedule.
A VirtIO‑based virtual network implements IEEE 802.1Qbv‑like scheduling to give time‑triggered VMs predictable inter‑VM communication latency.
The design integrates the network layer into a global schedule that also covers computation and virtualization, enabling end‑to‑end timing guarantees without static partitioning. It targets mixed‑criticality systems where deterministic networking is essential.
ARCADE decouples authorization from MySQL and PostgreSQL by externalizing policy decisions to a verifiable engine such as Cedar, adding an ABAC layer via lightweight plugins.
The architecture lets databases enforce decisions made by the external engine, preserving existing data‑management performance while supporting expressive attribute‑based policies. It also facilitates auditing and formal verification of access control rules.
Demonstrates that Graphcore IPUs can accelerate spiking network simulations using a group-based mapping to exploit distributed on-chip SRAM, aiming toward the community's 100× speedup target.
Prior speedups were limited to custom FPGA systems; this work shows commercial hardware can approach real‑time performance for plastic connectivity models. The approach tackles spike‑routing bottlenecks inherent in many‑core systems.
Introduces OpenMQPI, an MLIR dialect and OpenMP extension that lets quantum circuits be offloaded from HPC applications via the standard OpenMP target infrastructure.
OpenMQPI defines the QPIR dialect to embed quantum code inside OpenMP regions and provides a compilation pipeline with quantum‑specific optimizations, aiming to reduce ecosystem lock‑in and improve reuse across heterogeneous compilers.
Presents QEDIA, a Lean 4 library that formalizes quantum Hoare logic QHL+ and enables verification of quantum programs with classical variables.
The library covers mathematics, syntax, semantics, and proof rules, proving soundness for both partial and total correctness, and reduces the manual effort typically required for quantum program verification.
Soliduzz detects miscompilations in EVM smart‑contract compilers by compiling assertion‑driven product programs and using fuzzers or symbolic execution to find violated equivalence assertions.
Unlike prior fuzzers that focus on crashes or differential testing, Soliduzz encodes semantic equivalence as executable checks, requiring no compiler‑specific modifications and exposing subtle bytecode errors that could affect high‑value contracts.
SGLang‑Omni is a high‑performance serving framework for audio (TTS, ASR) and unified multimodal models.
The project targets low‑latency inference workloads and integrates with existing model pipelines, aiming to simplify deployment of large‑scale speech and multimodal systems.
MaxKB is an open‑source platform for building enterprise‑grade AI agents.
The platform emphasizes ease of use and extensibility, providing tools for knowledge management, retrieval, and agent orchestration suitable for large‑scale business applications.
PersonaPlex is a Python repository providing code for the PersonaPlex project.
The repository contains the implementation of the PersonaPlex system, which can be used as a reference or starting point for developers interested in persona-based AI models. It includes example scripts and documentation to help users get started quickly.
Unlimited OCR is a Python library that enables one-shot long-horizon parsing for OCR tasks.
The project claims to handle arbitrary-length text extraction from images without needing multiple passes or fine‑tuning. It is positioned as a step toward more flexible OCR pipelines, especially for documents with complex layouts.
f3d is a C++ minimalist 3D viewer focused on speed and low resource usage.
The viewer supports common 3D formats and provides a simple API for integration into other tools. Its design emphasizes minimal dependencies, making it suitable for embedded or performance‑critical applications.
MoneyPrinterTurbo is a Python tool that generates HD short videos from a topic or keyword using AI models and automation.
The system combines large language models with video synthesis pipelines to produce high‑resolution clips without manual editing. It targets content creators who need rapid video generation based on textual prompts.
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