AI Tools & Frameworks Directory

Projects are the bridge between learning and becoming a professional. While theory builds fundamentals, recruiters value candidates who can solve real problems. A strong, diverse portfolio showcases practical skills, technical range, and problem-solving ability.  This guide compiles over 20 solved p...

Why retrieval that looks excellent on paper can still behave like noise in real RAG and agent workflows The post What the Bits-over-Random Metric Changed in How I Think About RAG and Agents appeared first on Towards Data Science.

Tencent AI Lab has released Covo-Audio, a 7B-parameter end-to-end Large Audio Language Model (LALM). The model is designed to unify speech processing and language intelligence by directly processing continuous audio inputs and generating audio outputs within a single architecture. System Architectur...

arXiv:2603.23517v1 Announce Type: new Abstract: Accuracy-based evaluation cannot reliably distinguish genuine generalization from shortcuts like memorization, leakage, or brittle heuristics, especially in small-data regimes. In this position paper, we argue for mechanism-aware evaluation that combi...

arXiv:2603.23550v1 Announce Type: new Abstract: Multi-turn human-AI collaboration is fundamental to deploying interactive services such as adaptive tutoring, conversational recommendation, and professional consultation. However, optimizing these interactions via reinforcement learning is hindered b...

arXiv:2603.23558v1 Announce Type: new Abstract: Uncertainty quantification is a key aspect in many tasks such as model selection/regularization, or quantifying prediction uncertainties to perform active learning or OOD detection. Within credal approaches that consider modeling uncertainty as probab...

arXiv:2603.23562v1 Announce Type: new Abstract: Synthetic data augmentation helps language models learn new knowledge in data-constrained domains. However, naively scaling existing synthetic data methods by training on more synthetic tokens or using stronger generators yields diminishing returns be...

This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.

arXiv:2603.23539v1 Announce Type: new Abstract: We show that PLDR-LLMs pretrained at self-organized criticality exhibit reasoning at inference time. The characteristics of PLDR-LLM deductive outputs at criticality is similar to second-order phase transitions. At criticality, the correlation length ...

arXiv:2603.23610v2 Announce Type: new Abstract: Although large language models (LLMs) have advanced rapidly, robust automation of complex software workflows remains an open problem. In long-horizon settings, agents frequently suffer from cascading errors and environmental stochasticity; a single mi...

arXiv:2603.23625v1 Announce Type: new Abstract: Artificial intelligence (AI) is increasingly being explored in health and social care to reduce administrative workload and allow staff to spend more time on patient care. This paper evaluates a voice-enabled Care Home Smart Speaker designed to suppor...

arXiv:2603.23638v1 Announce Type: new Abstract: Large language models (LLMs) have enabled agentic systems that can reason, plan, and act across complex tasks, but it remains unclear whether they can allocate resources effectively under uncertainty. Unlike short-horizon reactive decisions, allocatio...

arXiv:2603.23660v1 Announce Type: new Abstract: We introduce GTO Wizard Benchmark, a public API and standardized evaluation framework for benchmarking algorithms in Heads-Up No-Limit Texas Hold'em (HUNL). The benchmark evaluates agents against GTO Wizard AI, a state-of-the-art superhuman poker agen...

While scaling laws for Large Language Models (LLMs) traditionally focus on proxy metrics like pretraining loss, predicting downstream task performance has been considered unreliable. This paper challenges that view by proposing a direct framework to model the scaling of benchmark performance from th...

MIT Sea Grant works with the Woodwell Climate Research Center and other collaborators to demonstrate a deep learning-based system for fish monitoring.

AI is the defining technology of our time, quickly becoming core business infrastructure. It’s fueled by a diverse ecosystem of models: large and small, open and proprietary, generalist and specialist.  This variety is essential for a future where every application will be powered by AI, every count...

The first lady sees AI and robotics playing a prominent role in the future of American education.

Google is launching Lyria 3 Pro, an upgraded music model that generates longer, more customizable tracks, as it expands AI music tools across Gemini, enterprise products, and other services.

Learn to build an AI data analyst with Python: analyzes data, detects anomalies, and generates predictions using local LLMs.

Fleet now supports shareable skills, so you equip agents across your team with knowledge for specialized tasks.

Reddit will require suspected automated accounts to verify they’re human, as it ramps up efforts to curb bot-driven spam and manipulation.

Google Lyria teaser

Traditional data pipeline development often requires extensive procedural code to define how data should be transformed and moved between stages. The declarative approach flips this paradigm by allowing data engineers to specify what the end result should be rather than prescribing every step of how...

My last article was about implementing Like-for-Like (L4L) for Stores. After discussing my solution with my peers and clients, I encountered an interesting issue that brought additional requirements to my first solution. This is what I want to discuss here. The post Following Up on Like-for-Like for...