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Artificial Intelligence / Machine Learning · 5

Automation / Agentic Systems · 5

Research Papers · 2

Embedded Systems · 5

Computer Systems · 5

Developer Tools / Open Source · 5

Cloud / Infrastructure · 5

Archived section

Artificial Intelligence / Machine Learning · 5

Artificial Intelligence / Machine Learning
arXiv8/6/2026
Recently

Challenges in Evaluating Explanation Methods for Static and Evolving Data

This paper addresses the limitations of Explainable Artificial Intelligence (XAI) with respect to insufficient evaluation. They are illustrated through the DetoxAI image recognition system for bias detection and concept unlearning. Then, an example of a human-grounded evaluation of methods for explaining image classification is presented. Authors: Jerzy Stefanowski.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: addresses the limitations of Explainable Artificial Intelligence (XAI) with respect to insufficient evaluation.

Primary paperarxivcs.AI
Original
Artificial Intelligence / Machine Learning
arXiv8/6/2026
Recently

Bias Analysis of L2 Speaking Assessment Systems Using Concept Activation Vectors

Automatic speaking assessment systems are increasingly deployed in high-stakes settings to mark second language (L2) learners' speaking tests, making it critical to show that their scores depend on speaking proficiency rather than irrelevant speaker attributes such as first language (L1) or age. Transformer-based foundation models have improved the accuracy of these L2 speaking graders, but their black-box representations make fairness and interpretability analysis more difficult. Building on prior work that used Concept Activation Vectors (CAVs) to detect bias towards unwanted attributes (`concepts') in feature-based graders, we extend CAV-based analysis to two neural speaking assessment systems: a text-based BERT grader and a speech-and-text multimodal grader based on Whisper. Authors: Arya Labroo, Mengjie Qian, Kate Knill.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Automatic speaking assessment systems are increasingly deployed in high-stakes settings to mark second language (L2) learners' speaking tests, making it critical to show that their scores depend on speaking proficiency rather than irrelevant speaker attributes such as first language (L1) or age.

Primary paperarxivcs.AI
Original
Artificial Intelligence / Machine Learning
arXiv8/6/2026
Recently

RP-OPSD: Reasoning-Pivot-Guided On-Policy Self-Distillation for Multilingual Reasoning Transfer

Multilingual reasoning transfer is crucial for extending reasoning capabilities of large language models (LLMs) beyond high-resource languages. On-policy self-distillation (OPSD) and its variants have emerged as a promising paradigm, providing dense token-level supervision on student-generated rollouts, yet their objectives do not explicitly prioritize reasoning signals most critical to cross-lingual transfer. We characterize that target-language reasoning comprises the generation of both surface text and reasoning pivots, which are decisions that advance or redirect the reasoning process and shape subsequent inference. Authors: Xinye Wang, Junxiao Liu, Shujian Huang.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Multilingual reasoning transfer is crucial for extending reasoning capabilities of large language models (LLMs) beyond high-resource languages.

Primary paperarxivcs.CL
Original
Artificial Intelligence / Machine Learning
arXiv8/6/2026
Recently

Tytan: Interactive Neurosymbolic Construction of Analytic Semantic Schemas from Relational Data

From natural-language query interfaces to automated report generation, data analysis tools need a description of the data: the real-world entities it contains, which columns function as measures or identifiers, and how tables connect into units of analysis. Today, this semantic layer is usually written by hand. This is a knowledge-acquisition bottleneck that limits the scalability of analytic systems, keeps non-technical users dependent on experts, and is itself error-prone. Authors: Donna Hooshmand, Shubham Shahi, Cameron Barrie.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: From natural-language query interfaces to automated report generation, data analysis tools need a description of the data: the real-world entities it contains, which columns function as measures or identifiers, and how tables connect into units of analysis.

Primary paperarxivcs.DB
Original
Artificial Intelligence / Machine Learning
Apple Machine Learning Research8/6/2026
Recently

Beyond Next-Token Prediction: A Performance Characterization of Diffusion versus Autoregressive Language Models

Large Language Models (LLMs) have achieved state-of-the-art performance on a broad range of Natural Language Processing (NLP) tasks, including document processing and code generation. Autoregressive Language Models (ARMs), which generate tokens sequentially conditioned on all previous tokens, have been the predominant paradigm for LLMs. While these models have achieved high accuracy across a range of downstream tasks, they exhibit low arithmetic intensity due to the inherent sequential dependency in next-token prediction.

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: Large Language Models (LLMs) have achieved state-of-the-art performance on a broad range of Natural Language Processing (NLP) tasks, including document processing and code generation.

Official source
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv8/6/2026
Recently

HarnessOpt-Bench: Evaluating LLMs at Harness Optimization

As LLMs are increasingly deployed within agentic systems, their capabilities depend not only on the model weights but also on the harness: the prompts, tools, control flow, memory, and orchestration code surrounding them. This makes automated harness optimization -- the iterative and evaluation-guided improvement of a harness by an AI system -- both an important route to improving AI systems and a demanding capability for AI systems themselves. Yet the community lacks a common protocol for measuring how well frontier LLMs perform at this task. Authors: Varun Ursekar, Apaar Shanker, Yash Maurya.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: As LLMs are increasingly deployed within agentic systems, their capabilities depend not only on the model weights but also on the harness: the prompts, tools, control flow, memory, and orchestration code surrounding them.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv8/6/2026
Recently

The Bitter Lesson of Tool Calling

Tool use transforms LLMs into agents that act beyond their training data, and for code-capable models, programmatic tool calling extends this further by replacing rigid JSON calls with scripts that chain and parallelize naturally. However, a systematic evaluation of tools as code on an established benchmark across current and prior model generations under real-world task conditions has not been conducted. In this work, we empirically compare programmatic tool calling (PTC) to native JSON tool calling across 14 language models on BFCL v4. Authors: Ishan Patel, Sahil Sen, Elias Lumer.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Tool use transforms LLMs into agents that act beyond their training data, and for code-capable models, programmatic tool calling extends this further by replacing rigid JSON calls with scripts that chain and parallelize naturally.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
arXiv8/6/2026
Recently

AV-AIVAT: 74x Cheaper Agent Evaluation with Certified Anytime-Valid Stopping in Imperfect-Information Games

Deciding which of two agents is stronger means playing games until skill outweighs luck, and every game costs money, model inference, or expert time. Since the number of games needed is unknown, fixed-budget evaluations either keep paying after the result is settled or stop before the agents can be told apart, while naive optional stopping with an ordinary confidence interval invalidates the stated level. We make such an evaluation stop as soon as its evidence suffices, with the guarantee intact. Authors: Boning Li, Yu Chen, Longbo Huang.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Deciding which of two agents is stronger means playing games until skill outweighs luck, and every game costs money, model inference, or expert time.

Primary paperarxivcs.GT
Original
Automation / Agentic Systems
arXiv8/6/2026
Recently

CalibForge: Adversarial Solver Calibration for Scaling Learnable Terminal Tasks

Training terminal agents requires executable and verifiable tasks that are not merely solvable, but appropriately challenging for learning. Executable validation establishes feasibility, yet does not reveal how a task behaves relative to a given solver setting. In this paper, we present CalibForge, an autonomous terminal-task synthesis system that uses verified solver behavior to revise candidate tasks through adversarial solver calibration. Authors: Fanzhe Meng, Guoxin Chen, Jiale Zhao.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Training terminal agents requires executable and verifiable tasks that are not merely solvable, but appropriately challenging for learning.

Primary paperarxivcs.LG
Original
Automation / Agentic Systems
GitHub Blog8/6/2026
Recently

A guide to slash commands in the GitHub Copilot app

Go beyond chat in the GitHub Copilot app with these slash commands. They'll help you plan, collaborate, automate, and customize your dev workflow. The post A guide to slash commands in the GitHub Copilot app appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Automation / Agentic Systems: Go beyond chat in the GitHub Copilot app with these slash commands.

Official sourceAI & MLGitHub Copilot
Original

Archived section

Research Papers · 2

Research Papers
arXiv8/6/2026
Recently

A Sound Translation from Tamarin to ProVerif: Enabling Comparative Analysis

Tamarin and ProVerif are two prominent tools for the formal verification of security protocols. They share the same high-level goal but differ significantly in their underlying formalisms and verification techniques, making a systematic comparison challenging: Tamarin uses multiset rewrite rules with sound and complete verification, whereas ProVerif employs an extension of the applied-pi calculus that provides fast but potentially incomplete results. We present a sound translation from Tamarin to ProVerif that enables a rigorous comparison of the two tools. Authors: Kevin Morio, Yavor Ivanov, Robert Künnemann.

Why it matters

Read this for the paper's specific claim in Research Papers: Tamarin and ProVerif are two prominent tools for the formal verification of security protocols.

Primary paperarxivcs.CR
Original
Research Papers
arXiv8/6/2026
Recently

Game Hopping in Lean

We present HOPSCOTCH, a Lean 4 framework for mechanizing computationally sound, game-based cryptographic proofs. Security definitions are expressed as indistinguishability between stateful probabilistic oracles, and proofs follow the standard game-hopping paradigm. HOPSCOTCH uses a shallow embedding: oracles and reductions are ordinary Lean definitions, enabling direct integration with the full Lean ecosystem, including general mathematical theories from Mathlib, such as finite-group theory. Authors: Stefan Dziembowski, Grzegorz Fabiański, Daniele Micciancio.

Why it matters

Read this for the paper's specific claim in Research Papers: We present HOPSCOTCH, a Lean 4 framework for mechanizing computationally sound, game-based cryptographic proofs.

Primary paperarxivcs.CR
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv8/6/2026
Recently

Distributed coordination for transmission-distribution systems with nonlinear flexibility aggregation

High shares of distributed energy resources (DERs) transform distribution systems into active participants in integrated transmission and distribution (ITD) operations. Linear models enable scalable distribution-level flexibility aggregation but can misclassify AC feasible operating points, whereas direct nonlinear aggregation becomes costly, especially in multiperiod ITD coordination. This paper reformulates transmission-distribution coordination within a hierarchical optimization framework and introduces a non-iterative predictor-corrector aggregation method. Authors: Xinliang Dai, Yanlin Jiang, Frederik Zahn.

Why it matters

Read this for the paper's specific claim in Embedded Systems: High shares of distributed energy resources (DERs) transform distribution systems into active participants in integrated transmission and distribution (ITD) operations.

Primary paperarxiveess.SY
Original
Embedded Systems
Hackster.io8/7/2026
Recently

Looking to Boost Your Software's Performance? Crack an egg, Researchers Say

" "Traditionally, if you wanted to build compilers, optimizers, synthesizers, it's a huge undertaking," Panchekha explains of the problem he set out to solve. "There are a lot of details you have to get right and a lot of tuning you have to do. " There are numerous approaches to optimizing software in order to improve its performance and reduce its memory footprint — the latter becoming increasingly important as years of falling hardware prices are flipped on their head by the artificial intelligence bubble's unceasing demand for memory, which has seen component costs skyrocketing with no end in sight.

Why it matters

Read this for the engineering context in Embedded Systems: " "Traditionally, if you wanted to build compilers, optimizers, synthesizers, it's a huge undertaking," Panchekha explains of the problem he set out to solve.

Trusted source
Original
Embedded Systems
Hackster.io8/7/2026
Recently

Flapping-Wing Drones Get a Stability Boost Thanks to Careful Monitoring and a "Disturbance Observer"

Researchers at Japan's Chiba University have come up with a way to improve the stability of flapping-wing ornithopter-style robots when exposed to outside disturbances — and it may lead to micro- and nano-drones better suited to operating in challenging environments like tunnels, shafts, and industrial infrastructure. "The control method proposed in this study enables FW-MAVs [Flapping-Wing Micro Aerial Vehicles] to fly more stably," says first and co-corresponding author Abner Asignacion, assistant professor at Chiba University's Graduate School of Engineering, "even in environments subject to disturbances. " The researchers' focus is, as Asignacion says, on the development and improvement of flapping-wing micro- and nano-drones — designed around the concept of an ornithopter, with bird-like flapping wings in place of the rotors of a traditional drone.

Why it matters

Read this for the engineering context in Embedded Systems: Researchers at Japan's Chiba University have come up with a way to improve the stability of flapping-wing ornithopter-style robots when exposed to outside disturbances — and it may lead to micro- and nano-drones better suited to operating in challenging environments like tunnels, shafts, and industrial infrastructure.

Trusted source
Original
Embedded Systems
Hackster.io8/6/2026
Recently

Espressif Sets ESP RainMaker Free, Releases Permissively-Licensed ESP RainMaker Neo

Espressif has announced a new release of its ESP RainMaker platform, launched six years ago — splitting it into the existing ESP RainMaker Classic and launching a new permissively-licensed open source version called ESP RainMaker Neo. 0," explains Espressif's Amey Inamdar. "It is production-ready and can be deployed directly into your own AWS [Amazon Web Services] account, giving you control over the infrastructure, data, and product experience.

Why it matters

Read this for the engineering context in Embedded Systems: Espressif has announced a new release of its ESP RainMaker platform, launched six years ago — splitting it into the existing ESP RainMaker Classic and launching a new permissively-licensed open source version called ESP RainMaker Neo.

Trusted source
Original
Embedded Systems
arXiv8/6/2026
Recently

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation

Vision-Language-Action (VLA) models have become a powerful paradigm for robot manipulation, but training a single generalist policy for heterogeneous robot embodiments remains an open problem. Existing methods have two main limitations. First, they underuse dynamics priors shared across diverse visual and interaction data, limiting cross-embodiment transfer. Authors: Junfeng Li, Junjie He, Zhide Zhong.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Vision-Language-Action (VLA) models have become a powerful paradigm for robot manipulation, but training a single generalist policy for heterogeneous robot embodiments remains an open problem.

Primary paperarxivcs.RO
Original

Archived section

Computer Systems · 5

Computer Systems
Netflix Tech Blog8/7/2026
Recently

How and Why Netflix Built a Real-Time Distributed Graph: Part 3 — Querying the graph with gRPC…

How and Why Netflix Built a Real-Time Distributed Graph: Part 3 — Querying the graph with gRPC execution API Authors: Nilesh Mishra and Ajit Koti This is the third entry of a multi-part blog series describing how we built a Real-Time Distributed Graph (RDG). In Part 1, we discussed the motivation for creating the RDG and the architecture of the data processing pipeline that populates it. In Part 2, we discussed how we designed the storage layer to handle billions of nodes and edges while maintaining single-digit-millisecond latency.

Why it matters

Read this for the engineering context in Computer Systems: How and Why Netflix Built a Real-Time Distributed Graph: Part 3 — Querying the graph with gRPC execution API

Trusted source
Original
Computer Systems
arXiv8/6/2026
Recently

Routing LLM Inference to the Cleanest Grid in Real Time

Large-language-model inference is a fast-growing electricity load whose marginal carbon intensity varies by more than an order of magnitude across grid regions and across the day, making request placement an attractive lever: no retraining, no hardware change. We report a live validation of carbon-aware inference routing on multi-region GPU testbeds driven by marginal operating emissions rate (MOER) signals, with three properties uncommon in prior work: a blind baseline that is an actual production pressure-based router rather than uniform placement; per-request energy attributed from GPU telemetry (NVIDIA DCGM) via measured concurrency curves rather than nameplate TDP; and carbon settlement of every request against historical MOER, not only the forecast that drove the decision. The central live result is feasibility: a MOER signal steered inference across regions with no observed dispatch failures, as a strict and reversible overlay on the production router. Authors: Aleks Bernhard, Arif Baran Yardimci.

Why it matters

Read this for the paper's specific claim in Computer Systems: Large-language-model inference is a fast-growing electricity load whose marginal carbon intensity varies by more than an order of magnitude across grid regions and across the day, making request placement an attractive lever: no retraining, no hardware change.

Primary paperarxivcs.DC
Original
Computer Systems
arXiv8/6/2026
Recently

Breaking Memory Bottlenecks in Quantum Control Systems for More Precise Experiments and Higher Throughput Computing

As quantum computing continues to demonstrate promise and attract growing attention, there is an increasing need for more precise experiments to advance the development of quantum devices, as well as higher circuit throughput to validate more domain applications. However, this need is hindered by a memory bottleneck at the quantum control system layer, arising from limited on-chip BRAM capacity and the non-deterministic latency of DRAM. To break this bottleneck, we present Ant-Q, a memory hierarchy design that integrates DRAM with BRAM to support pipelined quantum circuit execution while ensuring deterministic inter-circuit timing. Authors: Yicheng Guang, Neel Vora, Yilun Xu.

Why it matters

Read this for the paper's specific claim in Computer Systems: As quantum computing continues to demonstrate promise and attract growing attention, there is an increasing need for more precise experiments to advance the development of quantum devices, as well as higher circuit throughput to validate more domain applications.

Primary paperarxivcs.AR
Original
Computer Systems
Microsoft Azure Blog8/6/2026
Recently

Microsoft named a Leader in the 2026 Gartner® Magic Quadrant™ for AI-Augmented Code Modernization Tools

GitHub Copilot and Azure are helping organizations modernize legacy applications, reduce technical debt, and prepare for AI innovation. The post Microsoft named a Leader in the 2026 Gartner® Magic Quadrant™ for AI-Augmented Code Modernization Tools appeared first on Microsoft Azure Blog.

Why it matters

Read this for the official technical update in Computer Systems: GitHub Copilot and Azure are helping organizations modernize legacy applications, reduce technical debt, and prepare for AI innovation.

Official sourceComputeContainers
Original
Computer Systems
arXiv8/6/2026
Recently

Timestep-Conditioned Transformers for Global Weather Forecasting

Existing machine-learning weather forecasting models rely on predetermined and fixed autoregressive timesteps. g. g. Authors: Sam Levang, Fran Bartolic, Ty Dickinson.

Why it matters

Read this for the paper's specific claim in Computer Systems: Existing machine-learning weather forecasting models rely on predetermined and fixed autoregressive timesteps.

Primary paperarxivcs.LG
Original

Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
arXiv8/6/2026
Recently

Automatic Translation of Unstructured Requirements into Linear Temporal Logic through Large Language Models

Automatically translating unstructured natural language requirements into formal specifications remains a challenge in requirements engineering and formal methods, particularly for safety- and mission-critical systems whose verification depends on mathematically precise specifications. This paper evaluates whether contemporary off-the-shelf Large Language Models (LLMs) can help bridge this gap by generating Linear Temporal Logic (LTL) formulas directly from unstructured requirements. The study examines six modern LLMs using a few-shot prompting strategy on a heterogeneous benchmark of 15 structurally varied requirements. Authors: Alexandra Newcomb, Omar Ochoa.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Automatically translating unstructured natural language requirements into formal specifications remains a challenge in requirements engineering and formal methods, particularly for safety- and mission-critical systems whose verification depends on mathematically precise specifications.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
CNCF Blog8/7/2026
Recently

Does Kubernetes DRA Replace HAMi?

Projects that want to share a GPU on Kubernetes have to work around an API instead of with it. com/gpu: 1. It meant one...

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Projects that want to share a GPU on Kubernetes have to work around an API instead of with it.

Official sourceBlog
Original
Developer Tools / Open Source
GitHub Blog8/6/2026
Recently

How we took malware advisories beyond npm

GitHub malware advisories no longer stop at npm. Here's how we wired OpenSSF's malicious-packages data into the Advisory Database, and why we built the pipeline paranoid. The post How we took malware advisories beyond npm appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: GitHub malware advisories no longer stop at npm.

Official sourceSupply chain securityGitHub Advisory Database
Original
Developer Tools / Open Source
Vercel Blog8/7/2026
Recently

Grok Imagine Image 2.0 now available on Vercel AI Gateway

0 Preview from xAI The model follows detailed instructions closely and plans typography and layout together, so dense, multi-part visuals like infographics, posters, and title screens hold their structure and small text stays legible. 0 Preview also supports image editing, keeping subjects and details consistent across repeated generations.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: 0 Preview from xAI The model follows detailed instructions closely and plans typography and layout together, so dense, multi-part visuals like infographics, posters, and title screens hold their structure and small text stays legible.

Official source
Original
Developer Tools / Open Source
arXiv8/6/2026
Recently

Predicting Agile Success: The Critical Few Factors

While Agile projects are more successful than traditional software development project management approaches, their overall success rate remains relatively low, with a high percentage of projects still deemed challenged or failed. This low project success rate is attributed to projects not being rigorously evaluated against critical success factors (CSF) of Agile projects and contemporary project success criteria. To identify the CSF that contribute to Agile software development project success as perceived by Agile practitioners, this study used a positivist approach to investigate the CSF of Agile software development projects. Authors: Ridewaan Hanslo, Maureen Tanner.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: While Agile projects are more successful than traditional software development project management approaches, their overall success rate remains relatively low, with a high percentage of projects still deemed challenged or failed.

Primary paperarxivcs.SE
Original

Archived section

Cloud / Infrastructure · 5

Cloud / Infrastructure
CNCF Blog8/7/2026
Recently

Shadow AI in CI/CD: Threat-modeling the path from developer laptop to Kubernetes

Artificial intelligence is becoming part of daily software delivery, often before it becomes part of the security architecture. That gap has a name: Shadow AI. It is any AI tool, model, agent, extension, or integration used...

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Artificial intelligence is becoming part of daily software delivery, often before it becomes part of the security architecture.

Official sourceBlog
Original
Cloud / Infrastructure
Cloudflare Blog8/7/2026
Recently

Introducing Radar Researcher: An AI tool for exploring Internet data in plain language

Cloudflare Radar Researcher is a new AI-powered tool that lets you explore global Internet trends and traffic data using plain language. Built entirely on Cloudflare's Developer Platform, it turns natural language queries into real, interactive charts.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Cloudflare Radar Researcher is a new AI-powered tool that lets you explore global Internet trends and traffic data using plain language.

Official sourceAgentsAgents Week
Original
Cloud / Infrastructure
Cloudflare Blog8/6/2026
Recently

The next generation of MCP

The next version of MCP has a rewritten, stateless core that just works on Workers. We cover upgrades to the protocol, the new feature lifecycle and SDK migration path, and hear from early adopters already running it in production.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: The next version of MCP has a rewritten, stateless core that just works on Workers.

Official sourceAgentsAgents Week
Original
Cloud / Infrastructure
Cloudflare Blog8/7/2026
Recently

Unifying Workers AI and AI Gateway into a single AI control plane

Cloudflare is unifying AI Gateway and Workers AI into a single control plane, giving developers observability, billing, and dynamic routing across both managed GPUs and external providers. Learn how unified bindings and model-first routing simplify building resilient AI applications.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Cloudflare is unifying AI Gateway and Workers AI into a single control plane, giving developers observability, billing, and dynamic routing across both managed GPUs and external providers.

Official sourceAgentsAgents Week
Original
Cloud / Infrastructure
Cloudflare Blog8/7/2026
Recently

Unveiling good and bad behaviors on the Agentic Internet

Cloudflare is shifting bot mitigation from point-in-time Risk assessment to continuous Trust evaluation. Learn how new good and bad behaviors from bots and agents are assessed by our systems, including BotBase and Precursor — and try out our Precursor Trace simulation to see how your own cursor movements would be assessed as human or bot.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Cloudflare is shifting bot mitigation from point-in-time Risk assessment to continuous Trust evaluation.

Official sourceAgentsAgents Week
Original