What changes for SOC analysts when the alert queue is clear
Attack Discovery uses large language models (LLMs) to analyze alerts and identify potential attacks. Each discovery groups related alerts into an attack...
31 juil.
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200 articles
S’abonner (RSS)Cost pressures rising
Companies don’t need to adopt large language models to get real benefits from AI, some experts say.
30 juil.
What is K-Search?
Optimizing GPU kernels is critical for efficient modern machine learning systems yet remains challenging due to the complex interplay of design factors and rapid hardware evolution. Existing automated approaches typically treat Large Language Models (LLMs) merely as stochastic code generators within heuristic-guided evolutionary loops. These methods often struggle with complex kernels requiring coordinated, multi-step structural transformations, as they lack explicit planning capabilities and frequently discard promising strategies due to inefficient or incorrect intermediate implementations. To address this, we propose Search via Co-Evolving World Model and build K-Search based on this method. By replacing static search heuristics with a co-evolving world model, our framework leverages LLMs' prior domain knowledge to guide the search, actively exploring the optimization space. This approach explicitly decouples high-level algorithmic planning from low-level program instantiation, enabling the system to navigate non-monotonic optimization paths while remaining resilient to temporary implementation defects. We evaluate K-Search on diverse, complex kernels from FlashInfer, including GQA, MLA, and MoE kernels. Our results show that K-Search significantly outperforms state-of-the-art evolutionary search methods, achieving an average 2.10x improvement and up to a 14.3x gain on complex MoE kernels. On the GPUMode TriMul task, K-Search achieves state-of-the-art performance on H100, reaching 1030us and surpassing both prior evolution and human-designed solutions.
30 juil.
Get started today
Invoke Atlassian-hosted large language models from Forge apps using the @forge/llm SDK.
29 juil.
Bring Google AI directly to your AWS and Azure data
Historically, running advanced analytics or training ML models across clouds meant a cross-cloud tax: high egress fees, network latency, and fragile ETL pipelines. The borderless Lakehouse solves this with Cross-Cloud Interconnects. These private, dedicated links deliver consistent bandwidth and lower latency than the public internet, at a fraction of the cost of traditional cross-cloud connections. The borderless Lakehouse supports zero variable egress costs when accessing your data from AWS1.
29 juil.
Build and scale agents with Gemini Enterprise
Data Agent Kit brings data engineering and science skills, tools, and plugins integrate into VS Code, Claude Code, Codex, and the Antigravity CLI.
29 juil.
Kubeflow Community Showcase 2026: GenAI and MLOps in action
Virtual Event - Kubeflow Community Showcase 2026 is a half-day virtual event highlighting real-world use cases and innovations. Learn how the community applies Kubeflow to Generative AI, MLOps, and LLMOps across cloud, hybrid, and edge environments through demos, practical solutions, and success stories.
29 juil.
Microsoft affirme battre tout le monde en détection de failles avec MAI-Cyber-1-Flash
Microsoft n’hésite pas à déclarer que son modèle, profondément intégré à MDASH, a été « perfectionné par les meilleurs experts en cybersécurité du secteur et renforcé dans le plus grand domaine de sécurité au monde ». Ce qui lui permet, toujours selon Microsoft, de battre tout le monde dans le domaine de la détection de failles, y compris Mythos, GPT 5.6 Sol, GPT 5.5 Cyber et Gemini 3.5 Flash Cyber. Avec 95,95 % au test CyberGym, Microsoft dépasse d’au moins 10 points la concurrence. Mais attent
28 juil.
When it comes to AI, bigger isn’t always better
There is growing concern about trust in AI as the technology is adopted by more people. Large language models (LLMs) continue to face persistent challenges with hallucinations and inaccurate outputs. LLMs are probabilistic systems trained to give answers, even when the correct answer is unclear o...
Choose the right model for the task at hand
Configure large language models for GitLab Duo features.
28 juil.
Gemini Alpha is now Gemini Beta
We’re updating the name of the Gemini Alpha program to "Gemini Beta." This new name more accurately reflects both the scale and the quality of the features that enter this launch stage. Please note that this is solely a branding change. This update does not alter any customer configurations, data privacy constraints, or pricing tiers. | Learn more.
25 juil.
The data moat
McKinsey estimates that generative AI, combined with other computational tools, could cut drug discovery timelines by as much as 50%. But every AI model is only as good as its training data. In drug discovery, that means ample quantities of high-quality biological data. Experiments can provide a rich source of such data. Whether they succeed or fail, each experiment generates a signal about what does and does not work. “Data is our differentiator,” says Sapra, explaining how the company’s datase
23 juil.
Data layer takes center stage
Generative AI can solve a litany of data challenges — filling gaps, extracting information from documents, and improving data quality — but experts say to exercise caution and use it in conjunction with traditional approaches.
23 juil.
Beyond Vulnerability Discovery
Since ChatGPT arrived in late 2022, we have been bullish on what large language models could do for reverse engineering and malware analysis. The early models were useful for teaching but too rudimentary for production work; that changed with the advent of reasoning models. OpenAI’s o1-preview, in September 2024, was the first to show the kind of sustained problem-solving the work demands, and within months Sean Heelan had used o3 to find a net-new vulnerability in the Linux kernel. In cybersecu
22 juil.
A new kind of attack surface
Traditional web applications have defined operations: check a bank balance, make a transfer. You can write deterministic rules to secure those interactions. AI-powered applications and agents are different. They accept natural language and generate unpredictable responses. There's no fixed set of operations to allow or deny, because the inputs and outputs are probabilistic. Attackers can manipulate large language models to take unauthorized actions or leak sensitive data. Prompt injection, sensi
22 juil.
Find and fix vulnerabilities with AI
Google introduces Gemini 3.5 Flash Cyber to help defenders find, validate, and patch software vulnerabilities quickly and efficiently.
21 juil.
CodeMender in AI Threat Defense
Google AI Threat Defense gives cybersecurity teams an autonomous, continuous security system designed to outpace AI-driven attacks.
21 juil.
Les API réduisent les barrières à l’entrée… ou pas
Dans la lignée d'un avis axé essentiellement sur l'amont de la chaîne de l'IA générative, l'autorité s'intéresse aux chatbots.
20 juil.
IA générative et massification des contrôles
France Travail déploie actuellement des robots visant à automatiser et massifier le contrôle des personnes inscrites à France Travail. Depuis le 1 janvier 2025, cela inclut également les personnes au RSA. Il s'agit d'une nouvelle étape du dangereux projet de gestion algorithmique des personnes sans-
20 juil.
Use Gemini to find your destination
Are you an avid Wazer and would like to start Beta testing? Sign up to be join our Beta community! Why should I join Waze's Beta community? As a member of the Beta program, you
19 juil.
NotebookLM is now Gemini Notebook
We’re renaming NotebookLM to Gemini Notebook. While it remains a standalone product focused on being your premier research tool, the new name reflects how it will evolve to do more across the Google ecosystem. | Learn more.
18 juil.
Expanded language support for Gemini in Google Docs
We are now expanding support for these features to 11 more languages, including Mandarin, Dutch, Malay, Hebrew, Polish, Turkish, Czech, Indonesian, Swedish, Danish, and Norwegian. These new additions join our previously supported languages: English, Spanish, Portuguese, Japanese, French, Korean, German, and Italian. | Learn more.
18 juil.
Generate higher quality AI video clips and edit any video with Gemini Omni in Vids
Users now have access to Gemini Omni directly within Google Vids. Omni provides higher quality video generation with significant improvements over previous models. Additionally, Omni’s world understanding unlocks simple video edits so you can ask Omni to tweak the video you have to get the video you need. | Learn more.
18 juil.
Cast yourself in AI video clips using your personal avatar with Gemini Omni in Vids
Users now have access to Gemini Omni directly within Google Vids. With Gemini Omni, you can create videos using your personal avatar to scale your presence without the studio time. Use a secure verification process to capture your likeness and then select it as a character in Omni generations within Vids. | Learn more.
18 juil.