<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>AaaS Knowledge Index</title>
    <link>https://aaas.blog</link>
    <description>The autonomous AI ecosystem database. Schema-first spec sheets for tools, models, agents, skills, scripts, and benchmarks.</description>
    <language>en-us</language>
    <lastBuildDate>Wed, 15 Jul 2026 08:28:13 GMT</lastBuildDate>
    <atom:link href="https://aaas.blog/api/feed" rel="self" type="application/rss+xml"/>
    <item>
      <title>leoian611/exam-study-coach</title>
      <description>一个帮你高效备考任何大学课程期末的  Skill——尤其是选修课</description>
      <link>https://aaas.blog/model/leoian611-exam-study-coach</link>
      <guid isPermaLink="true">https://aaas.blog/model/leoian611-exam-study-coach</guid>
      <pubDate>Wed, 15 Jul 2026 08:28:13 GMT</pubDate>
      <category>model</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>BuffaloShine/langgraph-langchain-agent-setup</title>
      <description>LangGraph — langchain agent, langchain setup, ai agent workflow.</description>
      <link>https://aaas.blog/agent/buffaloshine-langgraph-langchain-agent-setup</link>
      <guid isPermaLink="true">https://aaas.blog/agent/buffaloshine-langgraph-langchain-agent-setup</guid>
      <pubDate>Tue, 14 Jul 2026 08:23:06 GMT</pubDate>
      <category>agent</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>MacawGranary/cline-aider</title>
      <description>Cline — aider ai, aider tutorial, open source ai coding.</description>
      <link>https://aaas.blog/agent/macawgranary-cline-aider</link>
      <guid isPermaLink="true">https://aaas.blog/agent/macawgranary-cline-aider</guid>
      <pubDate>Tue, 14 Jul 2026 08:23:05 GMT</pubDate>
      <category>agent</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>FireSwordsmithStable/claude-agent-sdk-setup</title>
      <description>Claude Agent SDK Setup — anthropic agent, claude sdk setup, claude agent tutorial, claude api agent.</description>
      <link>https://aaas.blog/agent/fireswordsmithstable-claude-agent-sdk-setup</link>
      <guid isPermaLink="true">https://aaas.blog/agent/fireswordsmithstable-claude-agent-sdk-setup</guid>
      <pubDate>Tue, 14 Jul 2026 08:23:04 GMT</pubDate>
      <category>agent</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>helloianneo/ian-xiaohei-scenes</title>
      <description>Xiaohei 2.0 Codex Skill for Chinese real-object article illustrations and long-scroll story images</description>
      <link>https://aaas.blog/agent/helloianneo-ian-xiaohei-scenes</link>
      <guid isPermaLink="true">https://aaas.blog/agent/helloianneo-ian-xiaohei-scenes</guid>
      <pubDate>Tue, 14 Jul 2026 08:23:03 GMT</pubDate>
      <category>agent</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>AlekseiUL/hermes-researcher-agent</title>
      <description>Privacy-safe Hermes researcher agent for public-source research, evidence grading, and decision-ready briefs</description>
      <link>https://aaas.blog/agent/alekseiul-hermes-researcher-agent</link>
      <guid isPermaLink="true">https://aaas.blog/agent/alekseiul-hermes-researcher-agent</guid>
      <pubDate>Tue, 14 Jul 2026 08:23:03 GMT</pubDate>
      <category>agent</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>cyanheads/met-museum-mcp-server</title>
      <description>Search the Metropolitan Museum of Art collection, fetch full artwork records and open-access images via MCP. STDIO or Streamable HTTP.</description>
      <link>https://aaas.blog/tool/cyanheads-met-museum-mcp-server</link>
      <guid isPermaLink="true">https://aaas.blog/tool/cyanheads-met-museum-mcp-server</guid>
      <pubDate>Mon, 13 Jul 2026 09:43:10 GMT</pubDate>
      <category>tool</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>OthmanAdi/loophole</title>
      <description>Control Ableton Live from Claude and any LLM. An MCP server built on Ableton&apos;s official Extensions SDK: one .ablx, no Remote Script, no AbletonOSC, no Max for Live. TypeScript, Live 12.4.5 Suite beta.</description>
      <link>https://aaas.blog/tool/othmanadi-loophole</link>
      <guid isPermaLink="true">https://aaas.blog/tool/othmanadi-loophole</guid>
      <pubDate>Mon, 13 Jul 2026 09:43:07 GMT</pubDate>
      <category>tool</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>HollyZoe/cheatengine-mcp-tcp-bridge</title>
      <description>TCP-enhanced fork of Cheat Engine MCP Bridge. Connect Cursor, Copilot and Claude AI directly to local or remote Cheat Engine via TCP. Automate reverse engineering, pointer scanning, and memory analysis using natural language.</description>
      <link>https://aaas.blog/tool/hollyzoe-cheatengine-mcp-tcp-bridge</link>
      <guid isPermaLink="true">https://aaas.blog/tool/hollyzoe-cheatengine-mcp-tcp-bridge</guid>
      <pubDate>Mon, 13 Jul 2026 09:43:05 GMT</pubDate>
      <category>tool</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Muanchen2/renpy-mcp</title>
      <description>RenPy MCP Server — 7 tools, CJK font auto-config, 570 lines of pure Python. AI-native bridge for RenPy visual novel development.</description>
      <link>https://aaas.blog/tool/muanchen2-renpy-mcp</link>
      <guid isPermaLink="true">https://aaas.blog/tool/muanchen2-renpy-mcp</guid>
      <pubDate>Sun, 12 Jul 2026 08:30:09 GMT</pubDate>
      <category>tool</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Componentuiworship/mcp-model-context-protocol</title>
      <description>MCP — model context protocol.</description>
      <link>https://aaas.blog/tool/componentuiworship-mcp-model-context-protocol</link>
      <guid isPermaLink="true">https://aaas.blog/tool/componentuiworship-mcp-model-context-protocol</guid>
      <pubDate>Sun, 12 Jul 2026 08:30:06 GMT</pubDate>
      <category>tool</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Arithmetic Pedagogy for Language Models</title>
      <description>We investigate whether methods of human mathematics pedagogy can guide the training of language models toward arithmetic reasoning. Building on the GASING method -- an Indonesian pedagogy that solves basic arithmetic through a left-to-right procedure aligned with the causal order of token generat...</description>
      <link>https://aaas.blog/benchmark/arithmetic-pedagogy-for-language-models</link>
      <guid isPermaLink="true">https://aaas.blog/benchmark/arithmetic-pedagogy-for-language-models</guid>
      <pubDate>Sun, 12 Jul 2026 08:30:04 GMT</pubDate>
      <category>benchmark</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Who Needs Labels? Adapting Vision Foundation Models With the Metadata You Already Have</title>
      <description>We propose a label-free approach to adapt powerful but generic vision foundation models to specialized scientific domains. Standard supervised fine-tuning is often ill-suited to these settings: labels are scarce, and task-specific training can collapse the model&apos;s generality and hurt robustness. ...</description>
      <link>https://aaas.blog/benchmark/who-needs-labels-adapting-vision-foundation-models-with-the-metadata-you-already-have</link>
      <guid isPermaLink="true">https://aaas.blog/benchmark/who-needs-labels-adapting-vision-foundation-models-with-the-metadata-you-already-have</guid>
      <pubDate>Sun, 12 Jul 2026 08:30:04 GMT</pubDate>
      <category>benchmark</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Continual Visual and Verbal Learning Through a Child&apos;s Egocentric Input</title>
      <description>Children learn the meanings of words from a continuous, temporally structured stream of egocentric experience. Recent work shows that neural networks can also learn word-referent mappings from a child&apos;s egocentric video recordings, but they cycle through the shuffled data for hundreds of epochs, ...</description>
      <link>https://aaas.blog/benchmark/continual-visual-and-verbal-learning-through-a-child-s-egocentric-input</link>
      <guid isPermaLink="true">https://aaas.blog/benchmark/continual-visual-and-verbal-learning-through-a-child-s-egocentric-input</guid>
      <pubDate>Sat, 11 Jul 2026 08:08:37 GMT</pubDate>
      <category>benchmark</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Audio Interaction Model</title>
      <description>Audio is an inherently interactive modality, yet today&apos;s Large Audio Language Models (LALMs) are offline, and streaming audio models each handle only a single task such as streaming ASR or voice chatting. It is time to unify them into one online LALM: a model that, through an always-on perceive-d...</description>
      <link>https://aaas.blog/benchmark/audio-interaction-model</link>
      <guid isPermaLink="true">https://aaas.blog/benchmark/audio-interaction-model</guid>
      <pubDate>Sat, 11 Jul 2026 08:08:36 GMT</pubDate>
      <category>benchmark</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Towards Efficient and Evidence-grounded Mobility Prediction with LLM-Driven Agent</title>
      <description>Individual-level mobility prediction is central to urban simulation, transportation planning, and policy analysis. Supervised sequence models achieve strong accuracy but require task-specific training and offer limited decision-level transparency. Recent LLM-based methods improve interpretability...</description>
      <link>https://aaas.blog/benchmark/towards-efficient-and-evidence-grounded-mobility-prediction-with-llm-driven-agent</link>
      <guid isPermaLink="true">https://aaas.blog/benchmark/towards-efficient-and-evidence-grounded-mobility-prediction-with-llm-driven-agent</guid>
      <pubDate>Sat, 11 Jul 2026 08:08:36 GMT</pubDate>
      <category>benchmark</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>lilygoulder/fre-chi-learner-new</title>
      <description>HuggingFace model (text-generation). Tags: transformers, safetensors, gpt2, text-generation, arxiv:1910.09700</description>
      <link>https://aaas.blog/model/lilygoulder-fre-chi-learner-new</link>
      <guid isPermaLink="true">https://aaas.blog/model/lilygoulder-fre-chi-learner-new</guid>
      <pubDate>Fri, 10 Jul 2026 09:54:45 GMT</pubDate>
      <category>model</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>isam/civitai-lora-archive</title>
      <description>HuggingFace model (general). Tags: region:us</description>
      <link>https://aaas.blog/model/isam-civitai-lora-archive</link>
      <guid isPermaLink="true">https://aaas.blog/model/isam-civitai-lora-archive</guid>
      <pubDate>Fri, 10 Jul 2026 09:54:45 GMT</pubDate>
      <category>model</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>SeacowX/Enigma-70B-Entity-Attribute</title>
      <description>HuggingFace model (general). Tags: license:mit, region:us</description>
      <link>https://aaas.blog/model/seacowx-enigma-70b-entity-attribute</link>
      <guid isPermaLink="true">https://aaas.blog/model/seacowx-enigma-70b-entity-attribute</guid>
      <pubDate>Thu, 09 Jul 2026 10:08:01 GMT</pubDate>
      <category>model</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Lexsi/audit-harden-SurgeryTrainer-llama31-8b-dolly</title>
      <description>HuggingFace model (general). Tags: region:us</description>
      <link>https://aaas.blog/model/lexsi-audit-harden-surgerytrainer-llama31-8b-dolly</link>
      <guid isPermaLink="true">https://aaas.blog/model/lexsi-audit-harden-surgerytrainer-llama31-8b-dolly</guid>
      <pubDate>Thu, 09 Jul 2026 10:08:01 GMT</pubDate>
      <category>model</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting</title>
      <description>While previous research in multivariate time series forecasting has focused on developing complex holistic models, this work advocates for a shift toward a granular, component-level understanding of their impacts. We propose TSCOMP, the first large-scale benchmark that systematically deconstructs...</description>
      <link>https://aaas.blog/paper/beyond-holistic-models-systematic-component-level-benchmarking-of-deep-multivariate-time-series-forecasting</link>
      <guid isPermaLink="true">https://aaas.blog/paper/beyond-holistic-models-systematic-component-level-benchmarking-of-deep-multivariate-time-series-forecasting</guid>
      <pubDate>Mon, 06 Jul 2026 06:14:38 GMT</pubDate>
      <category>paper</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal</title>
      <description>Learning visuomotor policies via behavior cloning typically involves mimicking expert demonstrations collected by human operators. However, natural human demonstrations inherently contain high-frequency noise, such as intermittent jerks, pauses, and action jitter. Training policies to directly im...</description>
      <link>https://aaas.blog/paper/frequency-guided-action-diffusion-via-sub-frequency-manifold-traversal</link>
      <guid isPermaLink="true">https://aaas.blog/paper/frequency-guided-action-diffusion-via-sub-frequency-manifold-traversal</guid>
      <pubDate>Mon, 06 Jul 2026 06:14:38 GMT</pubDate>
      <category>paper</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked Modeling</title>
      <description>Conditional human motion generation remains a fundamental challenge in computer vision and robotics. Despite significant progress, current methods are often constrained by fixed modality configurations and task-specific architectures, leaving cross-modal interactions and the scaling laws of multi...</description>
      <link>https://aaas.blog/paper/anymo-scaling-any-modality-conditional-motion-generation-with-masked-modeling</link>
      <guid isPermaLink="true">https://aaas.blog/paper/anymo-scaling-any-modality-conditional-motion-generation-with-masked-modeling</guid>
      <pubDate>Mon, 06 Jul 2026 06:14:38 GMT</pubDate>
      <category>paper</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models</title>
      <description>Reinforcement learning (RL) can be used to improve the policy (denoiser) of diffusion large language models (dLLMs), while being hindered by the intractability of the policy likelihood. A dominant and efficient family of methods replaces the likelihood in standard RL with its evidence lower bound...</description>
      <link>https://aaas.blog/paper/gdsd-reinforcement-learning-as-guided-denoiser-self-distillation-for-diffusion-language-models</link>
      <guid isPermaLink="true">https://aaas.blog/paper/gdsd-reinforcement-learning-as-guided-denoiser-self-distillation-for-diffusion-language-models</guid>
      <pubDate>Mon, 06 Jul 2026 06:14:38 GMT</pubDate>
      <category>paper</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>One Click per Cell Type Suffices: Training-free Group Interaction for Cell Instance Segmentation</title>
      <description>Cell instance segmentation models trained on cell-specific datasets suffer severe performance drops on out-of-distribution cell types, while interactive foundation models overcome this through per-instance prompting at a cost that is prohibitively expensive for histopathology images containing hu...</description>
      <link>https://aaas.blog/paper/one-click-per-cell-type-suffices-training-free-group-interaction-for-cell-instance-segmentation</link>
      <guid isPermaLink="true">https://aaas.blog/paper/one-click-per-cell-type-suffices-training-free-group-interaction-for-cell-instance-segmentation</guid>
      <pubDate>Mon, 06 Jul 2026 06:14:37 GMT</pubDate>
      <category>paper</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>MYounus-Codes/thumbnails-scraper-for-machine-learning-model-training</title>
      <description>YouTube thumbnail collector for ML datasets || search, scrape, download, export to CSV.</description>
      <link>https://aaas.blog/dataset/myounus-codes-thumbnails-scraper-for-machine-learning-model-training</link>
      <guid isPermaLink="true">https://aaas.blog/dataset/myounus-codes-thumbnails-scraper-for-machine-learning-model-training</guid>
      <pubDate>Mon, 22 Jun 2026 09:00:29 GMT</pubDate>
      <category>dataset</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>AkankshaKesarkar/ai-csv-analyzer</title>
      <description> Full Stack AI Data Analytics Platform — Upload CSV or fetch live market data → get instant stats, charts, anomaly detection &amp; AI insights</description>
      <link>https://aaas.blog/dataset/akankshakesarkar-ai-csv-analyzer</link>
      <guid isPermaLink="true">https://aaas.blog/dataset/akankshakesarkar-ai-csv-analyzer</guid>
      <pubDate>Mon, 22 Jun 2026 09:00:26 GMT</pubDate>
      <category>dataset</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Anirodh-Padhy/EduMind-AI</title>
      <description>Enterprise AI Education SaaS Platform with AI Tutor, RAG, Voice Learning Assistant, Personalized Study Planner, Learning Analytics, LMS Architecture, and Role-Based Authentication.</description>
      <link>https://aaas.blog/provider/anirodh-padhy-edumind-ai</link>
      <guid isPermaLink="true">https://aaas.blog/provider/anirodh-padhy-edumind-ai</guid>
      <pubDate>Wed, 17 Jun 2026 08:42:18 GMT</pubDate>
      <category>provider</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>2aronS/media-curator</title>
      <description>AI-assisted curation and organization for large media datasets</description>
      <link>https://aaas.blog/dataset/2arons-media-curator</link>
      <guid isPermaLink="true">https://aaas.blog/dataset/2arons-media-curator</guid>
      <pubDate>Wed, 17 Jun 2026 08:42:11 GMT</pubDate>
      <category>dataset</category>
      <category>uncategorized</category>
    </item>
    <item>
      <title>Together AI</title>
      <description>Together AI provides a cloud platform for running, fine-tuning, and deploying open-source language models. It hosts a wide catalog of models from Llama to Mistral and offers serverless inference, dedicated endpoints, and a fine-tuning pipeline. Together AI is popular among developers who want OpenAI-compatible APIs for open-weight models at competitive pricing.</description>
      <link>https://aaas.blog/provider/together-ai</link>
      <guid isPermaLink="true">https://aaas.blog/provider/together-ai</guid>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <category>provider</category>
      <category>llm-providers</category>
    </item>
    <item>
      <title>Together AI (GPU Compute)</title>
      <description>Together AI&apos;s compute platform provides on-demand and reserved GPU clusters for training and fine-tuning open-source models. It offers H100 and A100 clusters with high-bandwidth networking optimized for distributed training runs, serving as both a GPU cloud provider and an inference platform. Teams use Together AI compute to run multi-node training jobs on Llama and Mistral variants.</description>
      <link>https://aaas.blog/provider/together-ai-gpu</link>
      <guid isPermaLink="true">https://aaas.blog/provider/together-ai-gpu</guid>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <category>provider</category>
      <category>gpu-compute</category>
    </item>
    <item>
      <title>Vast.ai</title>
      <description>Vast.ai is a peer-to-peer GPU marketplace connecting researchers and startups with spare GPU capacity from data centers and individuals worldwide. It offers some of the cheapest GPU rental prices on the market with flexibility to choose hardware by price, latency, or reliability score. Best suited for cost-sensitive experimentation and training runs.</description>
      <link>https://aaas.blog/provider/vast-ai</link>
      <guid isPermaLink="true">https://aaas.blog/provider/vast-ai</guid>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <category>provider</category>
      <category>gpu-compute</category>
    </item>
    <item>
      <title>xAI</title>
      <description>xAI is Elon Musk&apos;s AI company and creator of the Grok model family. It provides API access to Grok models with real-time web search integration, available through the xAI API and X (Twitter) platform. Grok models are trained on a broad mix of web and social data and emphasize up-to-date knowledge and uncensored reasoning.</description>
      <link>https://aaas.blog/provider/xai</link>
      <guid isPermaLink="true">https://aaas.blog/provider/xai</guid>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <category>provider</category>
      <category>llm-providers</category>
    </item>
    <item>
      <title>NVIDIA H200</title>
      <description>The NVIDIA H200 is a Hopper-generation GPU with 141GB of HBM3e memory — nearly double the H100&apos;s bandwidth — targeting inference workloads for very large models. The additional memory enables running 70B+ parameter models on fewer GPUs, significantly reducing the cost per inference token for large-scale deployments.</description>
      <link>https://aaas.blog/hardware/nvidia-h200</link>
      <guid isPermaLink="true">https://aaas.blog/hardware/nvidia-h200</guid>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <category>hardware</category>
      <category>ai-hardware</category>
    </item>
    <item>
      <title>NVIDIA RTX 5090</title>
      <description>The NVIDIA RTX 5090 is NVIDIA&apos;s flagship consumer/prosumer GPU in the Blackwell generation, featuring 32GB GDDR7 memory and massive compute for local AI inference and fine-tuning. It allows running 70B quantized models on a single consumer GPU and is the premier choice for developers who need frontier local model capability in a workstation.</description>
      <link>https://aaas.blog/hardware/nvidia-rtx-5090</link>
      <guid isPermaLink="true">https://aaas.blog/hardware/nvidia-rtx-5090</guid>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <category>hardware</category>
      <category>ai-hardware</category>
    </item>
    <item>
      <title>SambaNova SN40L RDU</title>
      <description>SambaNova&apos;s SN40L is a Reconfigurable Dataflow Unit designed for high-throughput LLM inference and training. Its tiered memory architecture — combining on-chip SRAM with off-chip DRAM — allows serving multiple large models simultaneously with industry-leading batch throughput. The SN40L is the hardware underlying SambaNova Cloud&apos;s inference API.</description>
      <link>https://aaas.blog/hardware/sambanova-sn40l-rdu</link>
      <guid isPermaLink="true">https://aaas.blog/hardware/sambanova-sn40l-rdu</guid>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <category>hardware</category>
      <category>ai-hardware</category>
    </item>
    <item>
      <title>Google TPU v6e Trillium</title>
      <description>Google TPU v6e Trillium is Google&apos;s sixth-generation TPU with 4x the compute and 3x the memory bandwidth per chip compared to v5e. Trillium is generally available on Google Cloud for both training and inference workloads, offering the most cost-efficient TPU option for teams training Gemma and other open models on Google Cloud.</description>
      <link>https://aaas.blog/hardware/tpu-v6e-trillium</link>
      <guid isPermaLink="true">https://aaas.blog/hardware/tpu-v6e-trillium</guid>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <category>hardware</category>
      <category>ai-hardware</category>
    </item>
    <item>
      <title>Google TPU v7 Ironwood</title>
      <description>Google&apos;s TPU v7 Ironwood is the seventh generation of Google&apos;s custom Tensor Processing Units, designed for large-scale AI inference at hyperscaler capacity. Ironwood pods target serving frontier models like Gemini at Google&apos;s internal scale and are available to cloud customers via Google Cloud&apos;s TPU v7 instances.</description>
      <link>https://aaas.blog/hardware/tpu-v7-ironwood</link>
      <guid isPermaLink="true">https://aaas.blog/hardware/tpu-v7-ironwood</guid>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <category>hardware</category>
      <category>ai-hardware</category>
    </item>
    <item>
      <title>The Pile</title>
      <description>825GB diverse English pretraining corpus from 22 high-quality data sources.</description>
      <link>https://aaas.blog/dataset/the-pile</link>
      <guid isPermaLink="true">https://aaas.blog/dataset/the-pile</guid>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <category>dataset</category>
      <category>datasets</category>
    </item>
    <item>
      <title>UltraChat</title>
      <description>1.5M high-quality multi-turn dialogue dataset for instruction fine-tuning.</description>
      <link>https://aaas.blog/dataset/ultrachat</link>
      <guid isPermaLink="true">https://aaas.blog/dataset/ultrachat</guid>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <category>dataset</category>
      <category>datasets</category>
    </item>
    <item>
      <title>Skill Adjacency Detection</title>
      <description>Identifies non-obvious skill adjacencies and transferable capabilities between different roles and domains. Maps how expertise in one area translates to another — for example, how a military logistics background maps to supply chain management, or how academic research skills map to product analytics. Surfaces high-potential candidates that traditional keyword-based ATS systems routinely discard.</description>
      <link>https://aaas.blog/skill/skill-adjacency-detection</link>
      <guid isPermaLink="true">https://aaas.blog/skill/skill-adjacency-detection</guid>
      <pubDate>Tue, 21 Apr 2026 00:00:00 GMT</pubDate>
      <category>skill</category>
      <category>people-foundry</category>
    </item>
    <item>
      <title>Training Schedule Generation</title>
      <description>Generates customized 30/60/90-day training schedules for new employees based on their role, department, seniority, and onboarding goals. Sequences mandatory compliance training, role-specific tool walkthroughs, and team introductions into a coherent calendar that integrates with the employee&apos;s actual availability.</description>
      <link>https://aaas.blog/skill/training-schedule-generation</link>
      <guid isPermaLink="true">https://aaas.blog/skill/training-schedule-generation</guid>
      <pubDate>Tue, 21 Apr 2026 00:00:00 GMT</pubDate>
      <category>skill</category>
      <category>people-foundry</category>
    </item>
    <item>
      <title>Upsell Identification</title>
      <description>Analyzes customer usage patterns, feature adoption gaps, and engagement trends to identify accounts ready for upsell or cross-sell conversations. Produces ranked expansion opportunities with supporting evidence — which features they are actively using, which limits they are approaching, and the timing signals that indicate readiness.</description>
      <link>https://aaas.blog/skill/upsell-identification</link>
      <guid isPermaLink="true">https://aaas.blog/skill/upsell-identification</guid>
      <pubDate>Tue, 21 Apr 2026 00:00:00 GMT</pubDate>
      <category>skill</category>
      <category>customer-success-foundry</category>
    </item>
    <item>
      <title>Upskill Recommendation</title>
      <description>Generates personalized upskilling and learning path recommendations for employees based on their current skill profile, career trajectory goals, and identified flight risk signals. Matches employees to specific courses, mentorship opportunities, and internal projects that address their development gaps and increase retention probability.</description>
      <link>https://aaas.blog/skill/upskill-recommendation</link>
      <guid isPermaLink="true">https://aaas.blog/skill/upskill-recommendation</guid>
      <pubDate>Tue, 21 Apr 2026 00:00:00 GMT</pubDate>
      <category>skill</category>
      <category>people-foundry</category>
    </item>
    <item>
      <title>Velocity Prediction</title>
      <description>Forecasts engineering delivery timelines using historical sprint velocity, team composition, and dependency complexity. Identifies tasks at high risk of delay before they become blockers, producing adjusted delivery estimates and capacity recommendations that inform roadmap sequencing.</description>
      <link>https://aaas.blog/skill/velocity-prediction</link>
      <guid isPermaLink="true">https://aaas.blog/skill/velocity-prediction</guid>
      <pubDate>Tue, 21 Apr 2026 00:00:00 GMT</pubDate>
      <category>skill</category>
      <category>revenue-foundry</category>
    </item>
    <item>
      <title>MLflow Databricks Integration</title>
      <description>The MLflow integration with Databricks provides a managed MLflow service within the Databricks platform. It simplifies the process of tracking experiments, managing models, and deploying them to production by leveraging Databricks&apos; scalable infrastructure and collaborative environment.</description>
      <link>https://aaas.blog/integration/mlflow-databricks</link>
      <guid isPermaLink="true">https://aaas.blog/integration/mlflow-databricks</guid>
      <pubDate>Wed, 15 Apr 2026 00:00:00 GMT</pubDate>
      <category>integration</category>
      <category>ai-integrations</category>
    </item>
    <item>
      <title>TensorFlow Privacy</title>
      <description>TensorFlow Privacy is a library that makes it easier to train machine learning models with differential privacy. It provides TensorFlow optimizers that implement differentially private stochastic gradient descent (DP-SGD), allowing developers to protect the privacy of training data while still achieving good model performance.</description>
      <link>https://aaas.blog/integration/tensorflow-privacy</link>
      <guid isPermaLink="true">https://aaas.blog/integration/tensorflow-privacy</guid>
      <pubDate>Wed, 15 Apr 2026 00:00:00 GMT</pubDate>
      <category>integration</category>
      <category>ai-integrations</category>
    </item>
    <item>
      <title>Hugging Face Transformers Training Script</title>
      <description>The Hugging Face Transformers training script simplifies the process of training and fine-tuning transformer models for various NLP tasks. It provides a high-level API and pre-built training loops, enabling users to quickly adapt pre-trained models to their specific datasets and objectives.</description>
      <link>https://aaas.blog/script/hugging-face-transformers-training-script</link>
      <guid isPermaLink="true">https://aaas.blog/script/hugging-face-transformers-training-script</guid>
      <pubDate>Mon, 13 Apr 2026 00:00:00 GMT</pubDate>
      <category>script</category>
      <category>ai-scripts</category>
    </item>
    <item>
      <title>TensorFlow Model Optimization Toolkit Script</title>
      <description>The TensorFlow Model Optimization Toolkit script provides tools and techniques to optimize TensorFlow models for deployment, including quantization, pruning, and clustering. It reduces model size and improves inference speed, making models more suitable for edge devices and resource-constrained environments.</description>
      <link>https://aaas.blog/script/tensorflow-model-optimization-toolkit-script</link>
      <guid isPermaLink="true">https://aaas.blog/script/tensorflow-model-optimization-toolkit-script</guid>
      <pubDate>Mon, 13 Apr 2026 00:00:00 GMT</pubDate>
      <category>script</category>
      <category>ai-scripts</category>
    </item>
    <item>
      <title>Hugging Face Optimum Intel Extension</title>
      <description>Hugging Face Optimum Intel Extension is a toolkit designed to accelerate inference and training of transformer models on Intel CPUs and GPUs. It leverages Intel&apos;s Deep Learning Boost (DL Boost) and other hardware features to optimize model performance within the Hugging Face ecosystem.</description>
      <link>https://aaas.blog/integration/hugging-face-optimum-intel</link>
      <guid isPermaLink="true">https://aaas.blog/integration/hugging-face-optimum-intel</guid>
      <pubDate>Mon, 13 Apr 2026 00:00:00 GMT</pubDate>
      <category>integration</category>
      <category>ai-integrations</category>
    </item>
  </channel>
</rss>