NanoClaw, the open-source AI agent platform created by Gavriel Cohen, is partnering with the containerized development platform Docker to let teams run agents inside Docker Sandboxes, a move aimed at one of the biggest obstacles to enterprise adoption: how to give agents room to act without giving them room to damage the systems around them.The announcement matters because the market for AI agents is shifting from novelty to deployment. It... Read more ›
0
For the past three months, Google's Gemini 3 Pro has held its ground as one of the most capable frontier models available. But in the fast-moving world of AI, three months is a lifetime — and competitors have not been standing still.Earlier today, Google released Gemini 3.1 Pro, an update that brings a key innovation to the company's workhorse power model: three levels of adjustable thinking that effectively turn it... Read more ›
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CX platforms process billions of unstructured interactions a year: Survey forms, review sites, social feeds, call center transcripts, all flowing into AI engines that trigger automated workflows touching payroll, CRM, and payment systems. No tool in a security operation center leader’s stack inspects what a CX platform’s AI engine is ingesting, and attackers figured this out. They poison the data feeding it, and the AI does the damage for them.The... Read more ›
0
Late last year, Google briefly took the crown for most powerful AI model in the world with the launch of Gemini 3 Pro — only to be surpassed within weeks by OpenAI and Anthropic releasing new models, s is common in the fiercely competitive AI race.Now Google is back to retake the throne with an updated version of that flagship model: Gemini 3.1 Pro, positioned as a smarter baseline for... Read more ›
0
Despite growing chatter about a future when much human work is automated by AI, one of the ironies of this current tech boom is how stubbornly reliant on human beings it remains, specifically the process of training AI models using reinforcement learning from human feedback (RLHF). At its simplest, RLHF is a tutoring system: after an AI is trained on curated data, it still makes mistakes or sounds robotic. Human... Read more ›
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Traditional ETL tools like dbt or Fivetran prepare data for reporting: structured analytics and dashboards with stable schemas. AI applications need something different: preparing messy, evolving operational data for model inference in real-time. Empromptu calls this distinction "inference integrity" versus "reporting integrity." Instead of treating data preparation as a separate discipline, golden pipelines integrate normalization directly into the AI application workflow, collapsing what typically require Read more ›
3
Agents built on top of today's models often break with simple changes — a new library, a workflow modification — and require a human engineer to fix it. That's one of the most persistent challenges in deploying AI for the enterprise: creating agents that can adapt to dynamic environments without constant hand-holding. While today's models are powerful, they are largely static.To address this, researchers at the University of California, Santa... Read more ›
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Alibaba dropped Qwen3.5 earlier this week, timed to coincide with the Lunar New Year, and the headline numbers alone are enough to make enterprise AI buyers stop and pay attention.The new flagship open-weight model — Qwen3.5-397B-A17B — packs 397 billion total parameters but activates only 17 billion per token. It is claiming benchmark wins against Alibaba's own previous flagship, Qwen3-Max, a model the company itself has acknowledged exceeded one trillion... Read more ›
2
Typically, when building, training and deploying AI, enterprises prioritize accuracy. And that, no doubt, is important; but in highly complex, nuanced industries like law, accuracy alone isn’t enough. Higher stakes mean higher standards: Models outputs must be assessed for relevancy, authority, citation accuracy and hallucination rates. To tackle this immense task, LexisNexis has evolved beyond standard retrieval-augmented generation (RAG) to graph RAG and agentic graphs; it has also built out... Read more ›
3
Anthropic on Tuesday released Claude Sonnet 4.6, a model that amounts to a seismic repricing event for the AI industry. It delivers near-flagship intelligence at mid-tier cost, and it lands squarely in the middle of an unprecedented corporate rush to deploy AI agents and automated coding tools.The model is a full upgrade across coding, computer use, long-context reasoning, agent planning, knowledge work, and design. It features a 1M token context... Read more ›
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The chatbot era may have just received its obituary. Peter Steinberger, the creator of OpenClaw — the open-source AI agent that took the developer world by storm over the past month, raising concerns among enterprise security teams — announced over the weekend that he is joining OpenAI to "work on bringing agents to everyone." The OpenClaw project itself will transition to an independent foundation, though OpenAI is already sponsoring it... Read more ›
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Building retrieval-augmented generation (RAG) systems for AI agents often involves using multiple layers and technologies for structured data, vectors and graph information. In recent months it has also become increasingly clear that agentic AI systems need memory, sometimes referred to as contextual memory, to operate effectively.The complexity and synchronization of having different data layers to enable context can lead to performance and accuracy issues. It's a challenge that SurrealDB is... Read more ›
2
As AI-powered coding tools flood the market, a critical weakness has emerged: by default, as with most LLM chat sessions, they are temporary — as soon as you close a session and start a new one, the tool forgets everything you were just working on. Developers have worked around this by having coding tools and agents save their state to markdown and text files, but this solution is hacky at... Read more ›
26
The gap between ransomware threats and the defenses meant to stop them is getting worse, not better. Ivanti’s 2026 State of Cybersecurity Report found that the preparedness gap widened by an average of 10 points year over year across every threat category the firm tracks. Ransomware hit the widest spread: 63% of security professionals rate it a high or critical threat, but just 30% say they are “very prepared” to... Read more ›
3
From miles away across the desert, the Great Pyramid looks like a perfect, smooth geometry — a sleek triangle pointing to the stars. Stand at the base, however, and the illusion of smoothness vanishes. You see massive, jagged blocks of limestone. It is not a slope; it is a staircase.Remember this the next time you hear futurists talking about exponential growth.Intel’s co-founder Gordon Moore (Moore's Law) is famously quoted for... Read more ›
15
The average Fortune 1000 company has more than 30,000 employees and engineering, sales and marketing teams with hundreds of members. Equally large teams exist in government, science and defense organizations. And yet, research shows that the ideal size for a productive real-time conversation is only about 4 to 7 people.The reason is simple: As groups grow larger, each person has less opportunity to speak and must wait longer to respond,... Read more ›
19
Your developers are already running OpenClaw at home. Censys tracked the open-source AI agent from roughly 1,000 instances to over 21,000 publicly exposed deployments in under a week. Bitdefender’s GravityZone telemetry, drawn specifically from business environments, confirmed the pattern security leaders feared: employees deploying OpenClaw on corporate machines with single-line install commands, granting autonomous agents shell access, file system privileges, and OAuth tokens to Slack, Gmail, and SharePoi Read more ›
2
Researchers at Nvidia have developed a technique that can reduce the memory costs of large language model reasoning by up to eight times. Their technique, called dynamic memory sparsification (DMS), compresses the key value (KV) cache, the temporary memory LLMs generate and store as they process prompts and reason through problems and documents.While researchers have proposed various methods to compress this cache before, most struggle to do so without degrading... Read more ›
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Chinese AI startup MiniMax, headquartered in Shanghai, has sent shockwaves through the AI industry today with the release of its new M2.5 language model in two variants, which promises to make high-end artificial intelligence so cheap you might stop worrying about the bill entirely. It's also said to be "open source," though the weights (settings) and code haven't been posted yet, nor has the exact license type or terms. But... Read more ›
0
OpenAI on Thursday launched GPT-5.3-Codex-Spark, a stripped-down coding model engineered for near-instantaneous response times, marking the company's first significant inference partnership outside its traditional Nvidia-dominated infrastructure. The model runs on hardware from Cerebras Systems, a Sunnyvale-based chipmaker whose wafer-scale processors specialize in low-latency AI workloads.The partnership arrives at a pivotal moment for OpenAI. The company finds itself navigating a frayed relationship with. Read more ›
0
When an AI agent visits a website, it’s essentially a tourist who doesn’t speak the local language. Whether built on LangChain, Claude Code, or the increasingly popular OpenClaw framework, the agent is reduced to guessing which buttons to press: scraping raw HTML, firing off screenshots to multimodal models, and burning through thousands of tokens just to figure out where a search bar is.That era may be ending. Earlier this week,... Read more ›
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20.03.2026 08:30
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