#Tutorial/How-to

AIA research-agent design has GPT-6 orchestrating while MiniCPM5-2B runs locally on DGX Spark to read sources and extract traceable evidence. The post presents this as an example of pairing frontier reasoning with compact, efficient models for transparent research workflows.

AIMatei Zaharia, a prominent AI researcher, said it is very cool that GEPA works on Jev. The post is a short endorsement, linking to background about a test in which GEPA optimized Jev's prompts for extracting suspected adverse drug effects from medical sentences.

AIDatabricks CEO Ali Ghodsi praises how Superhuman scales its AI infrastructure, linking to a Superhuman blog post on scaling GEC inference. The post itself is only a link with no details provided here, so the specific techniques and results cannot be confirmed from this source.

AIFireworks AI reports that an oracle router choosing among 18 models per DeepSWE task reaches 97.6% at $1.88 per task, versus 74.1% at $6.52 for GPT-6 Astra alone. The oracle is hindsight-based, so the authors say a production router must predict the best model before the task starts, which is the harder problem.

AIvLLM achieved 5000 total token throughput per GPU in high-throughput PD serving of Qwen3.8-2.4T on a GB300 NVL72 cluster under an 8K/1K workload. The low-latency scenario reached 180 generated tokens per user, with both results shown on the Pareto frontier. The post also provides srt-slurm recipes and explains the tuning process used to create them.

AISGLang and RLinf have published a blog post about integrating Cosmos3 for reinforcement learning. The main post provides only a link to the full blog, so no further technical details can be confirmed from this source.

AIA commenter praises a practical setup where a small local model runs a log-debugging pipeline entirely on CPU through OpenClaw and Ollama. They argue that workflow design can make a small model far more useful than its raw size suggests.

AIOpenBMB's 2B-parameter MiniCPM5 model runs as a local news desk on an older i5-9400F PC with 16GB RAM and no cloud API. The developer built a system that collects official sources hourly and sends a 24-hour Telegram recap with a lead story and links.

AIJasper Lu's new blog post walks through training a search agent with GRPO, showing how small reward function changes teach a model to avoid sloppy tool calls, prune unnecessary documents, and balance persistence against token efficiency. The post makes every rollout browsable and releases the code as open source, with the full process from learning rate sweeps to reward shaping documented.

AILMSYS Org published a blog post introducing an SGLang SSD expert pack, with the full details available on its website. The post itself gives no further technical specifics, so the summary is limited to the announcement.

AIGoogle's Envisioning Studio, with Google Labs, co-developed custom Google Flow tools with designers Jane Wade and Sergio Hudson ahead of New York Fashion Week. Wade's Styling Suite let her style runway looks on digital models before producing physical samples, while Hudson's Runway Visualization helped him stage his show within a tight budget. The source says the tools are built with natural language and no coding experience.

AIHailuo AI's post suggests that a single 3x3 storyboard image can be converted into a video using the MiniMax H3 Max r2v model at 480p for 15 seconds. The quoted post describes settings with Quality prompt tuning and standard reference strength, and asks for a 2D animation with panel-to-panel cuts while excluding multiple panels and BGM.

AIHamel Husain and Shreya Shankar's FAQ explains AI evals as tests of whether an AI system does what users and the business want. It recommends starting with error analysis on at least 30 traces, then turning recurring failures into binary code-based checks or LLM judges validated against human labels.

AILM Studio has published a blog post introducing Introspection and session references in Bionic. The post itself provides no further details in the text supplied, so specific features and capabilities cannot be confirmed here.

AIMike Krieger, Anthropic's account owner, used an interactive Claude artifact to visualize the Iron Tangle level from Dungeon Crawler Carl, saying it helped him finally understand the layout. The post shares a link to the artifact, with no further details about its features.

AIA Mariposa Museum exhibit photographed by writer Steven Johnson, shared by Gemini Notebook, documents the Sierra Nevada town in 1859, ten years after the Gold Rush began. Johnson says he used the Gemini Notebook mobile app's camera feature to generate a detailed report from photos of the display, which he says was 99% accurate on fact-checking.

AIJetBrains describes building Air Context, a RAG pipeline that gives LLM agents semantic code search over real repositories instead of grep. The first installment covers parsing, chunking, and vectorization, arguing that fixed-size line chunks split related code and that structure-aware chunking using language grammar produces better retrieval units.

AIZ.ai reports that GLM-5.3 helped build and optimize the inference infrastructure for GLM-5.3-Flash. The system went from first successful run to production readiness in under two weeks, with end-to-end throughput tripling over the initial baseline. The team credited dense feedback from local correctness tests, execution traces, microbenchmarks, and end-to-end measurements for enabling targeted hypothesis testing.

AITinker says it values models trained to help professionals work better and spend less time debugging LaTeX. The post favors this assistive approach over AI that tries to replace professionals' work wholesale.

AISundial fine-tuned Thinking Machines' Inkling-Small with RLVR on 3,978 verified TeX.StackExchange fixes, using rewards for compilation and PDF match and penalties for removed content. The trained model fixes 83.7% of LaTeX errors in under one second at $0.0013 per fix, according to the post. Sundial says it is rolling out the model in its editor, applying fixes as suggestions and rebuilding the PDF.

AIMosaic, Ponder Studio, and Revyl used early access to Google's Gemini Flash models to test agentic video understanding on long footage. Mosaic reports a 97% cut in median token usage and nearly double the ability to handle complex edits, while Ponder Studio reports a 0.967 F1 score and about 72% lower token costs for B-roll selection. Revyl says the approach improved mobile UI bug-catching accuracy by 65%. The capability is available now for video uploads and YouTube videos via the Gemini API.

AIAnthropic is hosting office hours for teams interested in using Claude Tag for on-call work, and it is asking Team or Enterprise plan users to share triage feedback. Claude Tag can start investigating when a Slack alert fires by pulling metrics, diffing deploys, and checking flags to propose a likely cause and fix. Sign-up is through a Google Calendar booking link.

AITogether AI says teams can migrate from closed to open-source models in weeks to months, not years, using a managed service. The guide recommends defining the use case, shortlisting candidates with relevant benchmarks, and replaying existing traffic against them to test accuracy, cost, and latency against current targets.

AIGoogle Antigravity has published documentation about its sandbox. The post links to the sandbox documentation page for more information.

AIGoogle's Gemini Notebook now offers live spoken Q&A over class materials in about 100 languages, and lets students record lectures on the go with audio notes saved automatically to a chosen notebook. University students in 140+ countries can also still get a free Google AI Plan for higher limits and access to more Google products.

AIGoogle reports that its technologies and products now power everyday interactions in more than 300 languages used by over 7 billion people, about 86% of the global population. The post describes new speech models, including Gemini 3.5 Live Translate and Gemini 3.5 Transcribe, plus the TranslateGemma open translation models trained across 55 languages.

AIPart 2 of the zero-trust agents series moves security checks from agent code to the Gemini Enterprise Agent Platform runtime. Model Armor screens prompts and responses, Semantic Governance Policies judge proposed tool calls against intent and business rules, and Agent Anomaly Detection flags multi-turn drainage that single-turn checks miss. The same Customer Support and Returns Agent from Part 1 is used, with the companion demo open-sourced on GitHub.

Why it matters: The post walks through a concrete refund agent under four attacks, showing how screening, intent judgment, and anomaly detection each catch what the others miss.

AIThe vLLM team trained a DSpark speculative decoding draft model for Kimi K3, a 2.8T-parameter model, using the Speculators library on GB300 NVL72 hardware. They added a MooncakeHiddenStatesConnector to stream hidden states from disaggregated vLLM inference nodes to training nodes across multiple machines. The released speculator raises single-stream interactivity from about 110 to about 435 tokens per second per user on math reasoning, with up to about 3.5x higher output throughput under concurrent load.

Why it matters: The post shows how hidden-state extraction and Mooncake transfers let a 2.8T-parameter model's speculator be trained across multiple nodes, a reusable pattern for similar setups.