Knowledge catalogue
OpenAI Group PBC recently paused some of its artificial intelligence training workloads over concerns that they could cause cybersecurity issues. The ChatGPT developer disclosed the move in a blog pos
In modern enterprise data engineering, Apache Spark remains a cornerstone framework for processing massive datasets at scale. However, managing infrastructure such as provisioning clusters, tuning YAR
arXiv:2608.15594v1 Announce Type: new Abstract: Multi-turn jailbreak attacks have emerged as a critical safety threat to LLMs, as harmful objectives are decomposed across a sequence of apparently beni
There’s a hands-on workshop on August 29 that builds and benchmarks this properly, end to end, using entirely open models, no API calls involved. Led by Ben Auffarth, AI Consultant and Founder of Chel
arXiv:2608.12789v1 Announce Type: cross Abstract: Tool-using agents consume external data from sources with different levels of trust, yet tool responses rarely identify who produced each component or
arXiv:2608.12585v1 Announce Type: new Abstract: Improving reasoning LLMs requires the ability to judge the quality of long reasoning traces for effective reasoning data curation, strong training signa
arXiv:2608.11224v1 Announce Type: new Abstract: Materials research advances through accumulated experience - scripts that work, protocols that are trusted, warnings attached to failed calculations or
If you haven't checked the paper: https://arxiv.org/abs/2608.09867 TLDR: the authors show that you can swap out the 'encrypted' reasoning of the biggest model, like Opus, Sol, and put them into weaker
arXiv:2608.11415v1 Announce Type: cross Abstract: Large language models are being proposed as agents in scientific workflows, in domains where no downstream verifier exists. Such deployment assumes th
arXiv:2608.10430v1 Announce Type: cross Abstract: Large Language Models (LLMs) deployed as AI agents frequently exhibit user specification-grounding failures, executing hallucinated, undesired actions
arXiv:2606.08348v2 Announce Type: replace Abstract: LLM agents increasingly rely on prompts, tools, memory, SOPs, skills, and harness feedback, yet current self-evolution pipelines often update these
arXiv:2607.14945v2 Announce Type: replace Abstract: State-of-the-art flow based text-to-image (T2I) models exhibit remarkable generative abilities but remain vulnerable to producing unsafe content. Pr
arXiv:2510.04399v3 Announce Type: replace Abstract: We develop a learning-theoretic framework for analyzing self-improving agents by decomposing self-modification into five axes. Within this framework
arXiv:2608.10224v1 Announce Type: new Abstract: Enterprise support agents operate in rapidly changing environments where policies, product capabilities, and knowledge bases evolve continuously, making
arXiv:2608.10153v1 Announce Type: new Abstract: Enterprises are deploying autonomous AI agents faster than they can govern them, and prevailing approaches stretch a single discipline, typically DevSec
We are in an insane run of open-weight drops. Every modality, open source is winning. This is what an open source AI summer ☀️ looks like: 🧠 LLMs & Reasoning → DeepSeek-V4-Flash-0731 (my king 👑): 304B
Something happened today that I think most people are going to miss because there are two separate stories and neither one is getting the full picture. OpenAI expanded Daybreak. If you haven't heard o
arXiv:2608.08311v1 Announce Type: cross Abstract: We present Ouroboros, a self-developing agent harness whose tools, prompts, context assembly, and core implementation improve through reviewed commits
arXiv:2608.07583v1 Announce Type: cross Abstract: Multi-agent LLM systems route among model-backed advisors, yet a deployer rarely knows before shipping whether routing will help at all. Prevailing ro
arXiv:2503.24191v4 Announce Type: replace-cross Abstract: Content Warning: This paper may contain unsafe or harmful content generated by LLMs that may be offensive to readers. Large Language Models (L
arXiv:2608.07538v1 Announce Type: new Abstract: As LLM agents move from decision support to autonomous procurement, firms need to know whether delegated negotiators create value, divide it predictably
At Google Cloud, we help organizations of all sizes build and operationalize complex agentic workflows with total confidence. By combining world-class AI research with an open, fully integrated AI pla
arXiv:2608.07446v1 Announce Type: cross Abstract: Rapid adoption of large language models (LLMs) in enterprise settings has introduced operational, security, and governance risks. As generative AI app
Hey everyone ! Quick share from the cyber + local LLM side of things that I found interesting. During this week’s hacker summer camp, an AI researcher and reverse malware engineer veteran 'lordx64' on
arXiv:2608.04625v1 Announce Type: new Abstract: Industrial recommendation strategy iteration heavily relies on large-scale A/B experimentation. Traditional tuning requires experts to repeatedly design
arXiv:2608.04322v1 Announce Type: new Abstract: Task-specific fine-tuning can improve the performance of large language models (LLMs) on downstream tasks. However, our study reveals that task-specific
I’ve talked to developers, IT leaders, and builders who all ask the same question: How do we actually get agents into production? The answer isn't theoretical — it's hands-on. Whether it’s designing a
Learn how LendingTree built a production multi-agent mortgage assistant on Amazon Bedrock. Three coordinated agents use LangGraph, the Model Context Protocol, and Amazon Nova models with built-in guar
Cloudflare Wallets will provide AI agents with native payments and verifiable identity on the web. Using the x402 protocol, agents can autonomously purchase APIs and content within clear safety guardr
Editor's Note: Our Future Mode series will give businesses insight into how Chrome Enterprise is approaching AI in the browser. Stay tuned for more blogs in this series.Future Mode Part 2: The foundat
When people think about digital transformation in banking, they often focus on the visible results: mobile apps and new digital services. But there's an invisible infrastructure making all these servi
AI agents are only as good as the instructions and context you give them. When we launched Google Agent Skills, our goal was simple: encode Google Cloud domain knowledge into structured, open-source i
Watching @ClementDelangue on @FaceTheNation discussing agentic hacking. “Preventing releases does not work; concentrating behind closed doors in just a few organizations doesnt work. What worked in th
3/ here's the part that makes it non-optional: the same agent that will do whatever it takes to solve a problem will also walk straight out of a sandbox you thought was locked down. We watched exactly
arXiv:2602.16111v2 Announce Type: replace-cross Abstract: Online media platforms track the share of impressions associated with content attributes, or prevalence, to evaluate trade-offs and set guardr
Welcome to the second Cloud CISO Perspectives for July 2026. Today, Chris Betz, CISO, Google Cloud, and Alicja Cade, Senior Director, Office of the CISO, Google Cloud, explain what boards of directors
arXiv:2607.28196v1 Announce Type: new Abstract: Practitioners accept a compressed language model once it clears a stack of data-cheap quality guards: perplexity within a small factor of the original,
Yesterday I cohosted a dinner with @dexhorthy with a wonderful group of founders, to talk about agent loops and loop engineering. Some interesting insights: * Most of our group was *not* actively usin
Today’s data lakehouse is no longer mere data repository, but increasingly a system of action, actively executing tasks via always-on, autonomous AI agents. Rather than waiting for static reports, the
Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident Hugging Face just released this extremely detailed technical description of OpenAI's recent accidental cyberat
arXiv:2607.23532v1 Announce Type: cross Abstract: Swarms of LLM-assisted autonomous robots are increasingly proposed for cooperative intelligence, surveillance, and reconnaissance (ISR) in contested e
arXiv:2607.18263v2 Announce Type: replace Abstract: AI-generated non-consensual intimate imagery (AIG-NCII) is not adequately addressed in AI/ML literature regarding AI-generated media, commonly refer
arXiv:2607.22545v1 Announce Type: cross Abstract: Deploying large language models in financial-services and agentic settings requires safety classifiers that simultaneously handle prompt injection, re
arXiv:2507.21134v2 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in high-risk domains such as law, finance, and medicine, systematically evaluating their d
Hi Guys, I'm an old coder and DBA that has been in the field for almost 40 years. More and more the jobs I was doing for work are being taken over by AI and the need for my type of work is diminishing
A new model launch is not a product update ‼ It's one of three things, and you don't know which until you test it. Sometimes it's nothing: the model improved inside the same distribution, your harness
arXiv:2607.20982v1 Announce Type: new Abstract: As large language model agents increasingly operate autonomously with access to tools and external environments, ensuring their safe and reliable behavi
arXiv:2607.20759v1 Announce Type: cross Abstract: AI coding agents powered by LLMs are increasingly integrated into real-world software development, where they generate, edit, and execute code with au
arXiv:2607.20791v1 Announce Type: new Abstract: High-temperature sampling is one of the primary mechanisms for increasing diversity in LLMs. Recent advances in truncation-based sampling techniques hav
arXiv:2607.19941v1 Announce Type: cross Abstract: As AI agents become integral to business workflows, establishing guiding user experience (UX) principles is crucial for ensuring user trust and succes
Frontier AI models are increasingly demonstrating high‑risk autonomous behaviours that pose safety threats. Incidents such as OpenAI‑released models escaping containment safeguards and a Hugging Face
Anyone building with AI eventually hits the same tradeoff: how to get the most intelligence per dollar, the right model at the right cost for each task. That’s what DigitalOcean Inference Engine is bu
arXiv:2607.19433v1 Announce Type: new Abstract: The transition from stateless generative models in artificial intelligence to stateful, autonomous agents represents an architectural evolution that, wh
I don’t believe reality is a simulation, but you genuinely couldn’t script this timeline: • Two weeks ago: At @swyx’s AI Engineer World’s Fair in SF, I decide at the last minute to introduce my friend
LWiAI Podcast #248 (June 12, 2026) reviews major AI developments, noting Anthropic’s release of Claude Fable 5, a safeguarded variant of Mythos 5, which shows benchmark improvements but raises concern
As adversarial AI threats accelerate attacks on code, security teams must counter them with machine-speed defenses that can automate code remediation and fight AI with AI. CodeMender is our managed co
We are living in the golden age of the weekend AI side project. Thanks to agentic engineering and LLMs, the time to go from a blank IDE to a functional local application has dropped from quarters to h
Automated lint: 20 errors, 8743 warnings, 3 info
arXiv:2607.13594v1 Announce Type: new Abstract: LLM agents act on real-world environments through tool calls, and a single misjudged action can cause irreversible harm. The standard safeguard is a gua
arXiv:2511.09008v2 Announce Type: replace-cross Abstract: Large Language Models perform well at natural language interpretation and reasoning, but their lack of formal correctness guarantees limits th