Catch up with the fast moving field of data science. Even for us it has been difficult to stay up to date with the latest news and developments in the industry. We are putting together some of the top sources such as MIT, NVIDIA, ARXIV and others. These articles are aggregated from well trusted sources in the community. We will continue to add more sources and refine the type of articles showcased here over time.
Data Science
The recent developments in the field of data science and AI. Sources: Explosion.ai, Rasa, fast.ai, MIT, Berkley, Uber, IBM and Google AI Blog and other trusted sources.
- How to build AI scaling laws for efficient LLM training and budget maximizationby Lauren Hinkel | MIT-IBM Watson AI Lab on September 16, 2025 at 3:00 pm
MIT-IBM Watson AI Lab researchers have developed a universal guide for estimating how large language models will […]
- Machine-learning tool gives doctors a more detailed 3D picture of fetal healthby Alex Shipps | MIT CSAIL on September 15, 2025 at 2:00 pm
MIT CSAIL researchers developed a tool that can model the shape and movements of fetuses in 3D, potentially assisting […]
- DOE selects MIT to establish a Center for the Exascale Simulation of Coupled High-Enthalpy Fluid–Solid Interactionsby Institute for Soldier Nanotechnologies on September 10, 2025 at 3:45 pm
The research center, sponsored by the DOE’s National Nuclear Security Administration, will advance the simulation of […]
- AI and machine learning for engineering designby Anne Wilson | Department of Mechanical Engineering on September 7, 2025 at 4:00 am
Popular mechanical engineering course applies machine learning and AI theory to real-world engineering design.
- A greener way to 3D print stronger stuffby Rachel Gordon | MIT CSAIL on September 4, 2025 at 8:30 pm
MIT CSAIL researchers developed SustainaPrint, a system that reinforces only the weakest zones of eco-friendly 3D […]
News
- How AI is Reshaping Enterprise Analytics – Hackernoonon September 17, 2025 at 11:27 pm
How AI is Reshaping Enterprise Analytics Hackernoon
- Data-efficient Quantum Noise Modeling Via Machine Learning Enables Accurate Noise Models from Existing Data – Quantum Zeitgeiston September 17, 2025 at 11:21 pm
Data-efficient Quantum Noise Modeling Via Machine Learning Enables Accurate Noise Models from Existing Data Quantum Zeitgeist
- Beyond Visuals: Designing Cross-Platform Data Experiences that Drive Machine Learning Adoption – Hackernoonon September 17, 2025 at 11:14 pm
Beyond Visuals: Designing Cross-Platform Data Experiences that Drive Machine Learning Adoption Hackernoon
- Can Artists Stop the AI Slop Machine? – Hyperallergicon September 17, 2025 at 9:00 pm
Can Artists Stop the AI Slop Machine? Hyperallergic
- 100 Leaders Shaping the Future of Artificial Intelligence – observer.comon September 17, 2025 at 7:20 pm
100 Leaders Shaping the Future of Artificial Intelligence observer.com
White Papers
Latest research and developments in the field of machine learning and deep learning. Sources: ARXIV, Papers with Code and others
- xOffense: An AI-driven autonomous penetration testing framework with offensive knowledge-enhanced LLMs and multi agent systems
arXiv:2509.13021v1 Announce Type: cross Abstract: This work introduces xOffense, an AI-driven, multi-agent penetration […]
- Metacognitive Reuse: Turning Recurring LLM Reasoning Into Concise Behaviors
arXiv:2509.13237v1 Announce Type: cross Abstract: Large language models (LLMs) now solve multi-step problems by […]
- LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems
arXiv:2509.10682v1 Announce Type: cross Abstract: The success and wide adoption of generative AI (GenAI), particularly […]
- Lightweight Metadata-Aware Mixture-of-Experts Masked Autoencoder for Earth Observation
arXiv:2509.10919v1 Announce Type: cross Abstract: Recent advances in Earth Observation have focused on large-scale […]
- Convex Regularization and Convergence of Policy Gradient Flows under Safety Constraints
arXiv:2411.19193v2 Announce Type: replace-cross Abstract: This paper examines reinforcement learning (RL) in […]