Many Companies Use AI. Few Know How to Build an AI-Native Enterprise Data Platform.
A practical enterprise AI architecture with data agents, AI-powered QA, and AI governance. The post Many Companies Use AI.
What data teams need to build with AI to make self-healing data architecture a practical reality The post 7 Crucial Barriers Between Data Teams and Self-Healing Data Architecture appeared first on Towards Data Science .
A practical enterprise AI architecture with data agents, AI-powered QA, and AI governance. The post Many Companies Use AI.
Giving an AI agent access to a data warehouse doesn't automatically make it agent-ready. The real challenge lies in teaching the agent what the data means and when it's reliable enough to use.
What our over-dependence on external consulting teaches us about delegating our minds to machines The post The Big Con of Agentic AI appeared first on Towards Data Science .
Hospitals are rapidly adopting artificial intelligence for triage, imaging, scheduling etc. , yet most deployments remain isolated point solutions locked inside departmental silos, resulting in duplicated effort, hidden risks, and unrealized enterprise value.
arXiv:2608. 06112v1 Announce Type: new Abstract: Hospitals are rapidly adopting artificial intelligence for triage, imaging, scheduling etc.
arXiv:2606. 09408v1 Announce Type: cross Abstract: We present an ethnographic study of an alternative approach to data work, developed by a civic-tech initiative that builds datasets for training and benchmarking online safety systems.
How AI has massively changed my day-to-day workflow The post A Day in the Life of a Data Scientist in 2026 appeared first on Towards Data Science .
Building the Responsible AI, security, and governance layers required for enterprise-ready agents The post From Prototype to Production: The Architecture Behind Secure & Governed AI Agents appeared first on Towards Data Science .
Working together to create open-source and private datasets for AI training.
arXiv:2608. 02949v1 Announce Type: new Abstract: Latin America is missing two foundational layers of AI infrastructure: the dataset layer and the benchmark layer.
How to set the rules that keep agents effective and out of trouble The post What AI Agents Should Never Do on Their Own appeared first on Towards Data Science .
arXiv:2607. 07397v1 Announce Type: new Abstract: Autonomous agents promise substantial gains in speed, scale, and labor efficiency, but their failures can impose abrupt and often irreversible costs.