AI Tools & Frameworks Directory

When images, mosaics, and data cubes exist in abundance, but field labels are expensive, rare, and imperfect. The post Small Data, Big Maps: Training Geospatial ML Models When Samples Are Scarce appeared first on Towards Data Science.

Learn how AI agents are reshaping data science workflows and which skills practitioners need in 2026.

Understanding how FPN allows deep learning models detecting small objects and how to implement it from scratch The post FPN Paper Walkthrough: Leveraging the Internal Pyramid appeared first on Towards Data Science.

June’s forecast with GeForce NOW: 100% chance of gaming. GeForce NOW is lining up new adventures for the month, from big-name blockbusters to quirky indies ready for the spotlight. Members can dive into fresh worlds, squad up in new playlists and discover “just one more run” favorites — all streamin...

This article will teach you how to perform a language task like text classification by integrating locally hosted large language models (LLMs) of manageable size, like Mistral, Gemma, and Llama 3: all for free thanks to Ollama — a free repository for local LLMs — and the Scikit-LLM Python library.

Learn how Endava is using AI agents, ChatGPT Enterprise, and Codex to accelerate software delivery, automate workflows, and build an AI-native culture across the enterprise.

A third of the way into a security-operations guide that Anthropic published in April 2026, wedged between a recommendation to patch CISA’s Known Exploited Vulnerabilities list and a suggestion to automate your deployment pipeline is a small recommendation: “Use EPSS to prioritize the rest.” For any...

Most days in her chambers, Judge Maritza Braswell, a federal magistrate judge in Colorado, sifts through stacks of documents written by people without a lawyer. Many of them can’t afford to hire a lawyer, and others have cases too weak or too small to interest one. She reads each one carefully, mind...

Turn policy changes into an operating model for building, monitoring, and governing production agents.

Miso Labs has released MisoTTS, an open-weights 8B text-to-speech model. It uses residual vector quantization (RVQ) to scale its sonic range without scaling parameters, and conditions on both text and audio context to respond to speaker tone. The architecture pairs a 7.7B backbone with a 300M depth ...

Stanford researchers released OpenJarvis, an open-source framework that runs inference, agents, memory, and learning entirely on-device. It decomposes a personal AI system into five composable primitives — Intelligence, Engine, Agents, Tools & Memory, and Learning — and lands within 3.2 points of th...

arXiv:2606.04223v1 Announce Type: new Abstract: Multi-agent systems are commonly designed to reduce disagreement through voting, consensus protocols, debate, or fault-tolerant aggregation. We argue that this objective is insufficient for value-laden tasks, where disagreement may reflect genuine nor...

arXiv:2606.04202v1 Announce Type: new Abstract: As LLMs become more widely deployed, they are increasingly expected to work alongside other AI agents rather than operating in isolation. Effective coordination in these settings requires agents to communicate, share information and make decisions und...

arXiv:2606.04152v1 Announce Type: new Abstract: Large language models are reshaping research practice while quietly eroding researchers epistemic accountability. This commentary introduces PEEL - Protocols for Epistemically Engaged Literacy in AI, a working scaffolding that combines deterministic d...

arXiv:2606.04150v1 Announce Type: new Abstract: Public discourse and emerging policy typically assume that AI emotional support is a deliberate act: a lonely user consciously seeking comfort from a dedicated companion chatbot. In this paper, we draw on emerging empirical evidence and argue that thi...

arXiv:2606.04037v1 Announce Type: new Abstract: Pre-deployment verification of enterprise artificial intelligence (AI) agents remains a critical gap between large language model (LLM) capability benchmarking and production deployment. Post-deployment monitoring, human-in-the-loop controls, and prom...

arXiv:2606.04029v1 Announce Type: new Abstract: Reinforcement Learning (RL) has received increasing attention and adoption in real-world use cases. Most of these systems follow a train-then-fix paradigm, where trained agents do not learn while interacting with the world until performance degrades a...

Microsoft used its own developer conference to show it can live without OpenAI, Florida's attorney general sued OpenAI and went after Sam Altman personally, researchers and a new Workday product made plain that nobody trusts AI agents yet, and Alphabet raised a record $85 billion the same week the F...

MIT researchers use the classic game as a test bed for AI agents, finding a small AI model can outperform the biggest ones at 1 percent of the cost.

Dreambeans is a curated list of AI-illustrated "stories" culled from the personal data in your Google account.

Gemma 4 12B feeds vision and audio straight into the LLM backbone, running locally under an Apache 2.0 license. The post Google DeepMind Releases Gemma 4 12B: An Encoder-Free Multimodal Model with Native audio that runs on a 16 GB laptop appeared first on MarkTechPost.

Your AI agent works great in testing. Then you ship it, and something kinda breaks. A tool called loops forever, like it never learns. A retrieval step returns garbage and costs spike. You have no idea why, at all. That’s the agent observability problem. And if you’re building with LLMs, you need to...