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Reinforcement learning (RL) is great at learning what to do when the reward signal is clean and the environment is forgiving. But many real-world settings aren’t like that. They’re messy, high-stakes, and full of “almost right” decisions. That’s where expert-vetted reasoning datasets become a force multiplier: they teach models the why behind an action—not just […]
A machine learning engineer at Cognizant, Raj Bhowmik, who achieved 98% automation of EDI mapping work, shares his approach to enabling GenAI systems to work with legacy infrastructure. Enterprise IT departments face a problem: their data is stored in incompatible repositories. SAP HANA runs alongside BigQuery and Azure SQL. EDI files come in dozens of
98% Automation: Why Most Enterprise AI Projects Fail and What Actually Works Read More »
Generative artificial intelligence models have been used to create enormous libraries of theoretical materials that could help solve all kinds of problems. Now, scientists just have to figure out how to make them.In many cases, materials synthesis is not as simple as following a recipe in the kitchen. Factors like the temperature and length of
How generative AI can help scientists synthesize complex materials Read More »
NVIDIA has released Nemotron-Nano-3-30B-A3B-NVFP4, a production checkpoint that runs a 30B parameter reasoning model in 4 bit NVFP4 format while keeping accuracy close to its BF16 baseline. The model combines a hybrid Mamba2 Transformer Mixture of Experts architecture with a Quantization Aware Distillation (QAD) recipe designed specifically for NVFP4 deployment. Overall, it is an ultra-efficient
One of the best-performing algorithms in machine learning is the boosting algorithm. These are characterised by good predictive abilities and accuracy. All the methods of gradient boosting are based on a universal notion. They get to learn through the errors of the former models. Each new model is aimed at correcting the previous mistakes. This
Machine learning projects work best when they connect theory to real business outcomes. In e-commerce, that means better revenue, smoother operations, and happier customers, all driven by data. By working with realistic datasets, practitioners learn how models turn patterns into decisions that actually matter. This article walks through a full machine learning workflow using an
End-to-End Machine Learning Project on Amazon Sales Data Using Python Read More »
Robbyant, the embodied AI unit inside Ant Group, has open sourced LingBot-World, a large scale world model that turns video generation into an interactive simulator for embodied agents, autonomous driving and games. The system is designed to render controllable environments with high visual fidelity, strong dynamics and long temporal horizons, while staying responsive enough for
Allen Institute for AI (AI2) Researchers introduce SERA, Soft Verified Efficient Repository Agents, as a coding agent family that aims to match much larger closed systems using only supervised training and synthetic trajectories. What is SERA? SERA is the first release in AI2’s Open Coding Agents series. The flagship model, SERA-32B, is built on the
On Friday, a Reddit-style social network called Moltbook reportedly crossed 32,000 registered AI agent users, creating what may be the largest-scale experiment in machine-to-machine social interaction yet devised. It arrives complete with security nightmares and a huge dose of surreal weirdness. The platform, which launched days ago as a companion to the viral OpenClaw (once
AI agents now have their own Reddit-style social network, and it’s getting weird fast Read More »
To what extent can an artificial system be rational?A new MIT course, 6.S044/24.S00 (AI and Rationality), doesn’t seek to answer this question. Instead, it challenges students to explore this and other philosophical problems through the lens of AI research. For the next generation of scholars, concepts of rationality and agency could prove integral in AI
The philosophical puzzle of rational artificial intelligence Read More »
