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Nous Research has expanded the Skills System inside Hermes Agent, its open-source self-improving agent. The new addition is /learn, a command that writes a reusable skill for you. Point it at a document page, a local SDK, a past conversation, or pasted notes. The live agent gathers the material, then authors a SKILL.md on your […]
Generative AI has reshaped how software gets built. What began as line-by-line autocomplete now spans full application generation, multi-agent build pipelines, and natural-language interfaces to entire codebases. Large language models trained on code can read context, follow intent, and produce working frontends, backends, and infrastructure with little manual setup. For early-level AI engineers, software engineers,
16 Best Generative AI Coding Tools in 2026 Compared: Features, and Best Fit Read More »
Autoregressive large language models generate text one token at a time. Each token waits for the one before it. This serial loop leaves modern GPUs underused and keeps inference slow. The cost grows worse with long Chain-of-Thought reasoning models. Their lengthy outputs make latency the dominant part of generation. Speculative decoding is the standard fix.
Datalab has released lift, a 9B open-weights vision model for structured extraction. You pass it a JSON schema, and it returns a JSON object that matches. The model reads PDFs and images directly, then decodes against your schema. This is Datalab’s first model built purely for extraction. The team already ships open-source OCR tools: chandra,
The global surge in AI cyber threats is no longer a distant problem for corporate data centres, according to an urgent public warning from the world’s most powerful intelligence alliance. On June 22, 2026, the cybersecurity chiefs of the Five Eyes nations—comprising the US, UK, Canada, Australia, and New Zealand—issued a rare joint intelligence briefing stating that upcoming artificial
Top spy agencies say AI cyber threats will impact you within months. Here’s why Read More »
Prime Intellect has released prime-rl version 0.6.0. The framework targets reinforcement learning on trillion-parameter Mixture-of-Experts (MoE) models. It focuses on heavy agentic workloads, like long-horizon software-engineering tasks. The research team trained GLM-5 on SWE tasks at up to 131k sequence length. Step times stayed under five minutes. The batch size was 256 rollouts. The run
xAI shipped a new mode called /goal inside Grok Build, its terminal coding agent. The feature targets long-running, autonomous task execution. You hand the agent a larger implementation task, then step back. Most coding sessions require back-and-forth execution and verification. You prompt, the agent acts, and you verify each step. /goal changes that loop. The
Today, Sakana AI launched Sakana Fugu. It is a multi-agent orchestration system that behaves like one model. You send a request to a single endpoint. Fugu decides how to handle it internally. It solves a task directly when that is enough. It also assembles and coordinates a team of expert models when needed. The complexity
MoonMath AI team has released a bf16 forward attention kernel for AMD’s MI300X GPU. It is written in HIP, not hand-written assembly. The code is open-source under the MIT license. The MoonMath.ai team reports it beats AITER v3, AMD’s own optimized kernel, on every tested shape. Bare-metal access came from HotAisle, an AMD cloud provider.
Large language models are stateless by default. Each API call starts fresh. The model forgets your last message once the response returns. That is fine for a single question. It breaks the moment you build an agent. Agents plan, call tools, and run across many steps. They need to remember. Memory is the infrastructure that
The 7 Types of Agent Memory: A Technical Guide for AI Engineers Read More »
