NEW w/#UdbhavTiwari Mapping the technical reality & privacy/security perils of pushing AI agents into our infra We offer palliatives, but the core issues are paradigmatic: 'agency' relies on pervasive data access + ability to act w/o explicit consent.
DATA
-
Generative AI Tech Stack: Six Layers Powering Autonomous Agents
By
–
The Generative AI ecosystem is evolving into a full tech stack — powering autonomous AI agents.
From infrastructure and LLMs to RAG pipelines, agent behaviors and orchestration layers, this framework shows the 6 layers driving next-gen AI systems. Credit: @goyalshalini #AI -
Why Chasing New Models and More Data Often Fails
By
–
Why chasing new models and more data often fails in AI training. pic.twitter.com/5hqmEYXSWi
— Satya Mallick (@LearnOpenCV) 7 janvier 2026Why chasing new models and more data often fails in AI training.
-
Enterprise AI Agents Fail Without Quality Data Input
By
–
“When AI agents fail, it's not because the agent is not able to reason about data, but because the agent is not getting the right data in the first place.” Databricks Research Director @bemikelive explains the core challenge behind getting enterprise agents to produce
-
Add Datasets to Hugging Face for AI Builders
By
–
you should add the datasets to http://
hf.co/datasets for AI builders to use! -
Instructed Retriever: Enterprise Agents With System-Level Reasoning
By
–
Reliable enterprise agents require system-level reasoning when retrieving across heterogeneous knowledge sources. Traditional RAG often fails to consistently follow instructions, schemas, and constraints end to end. That’s why we’re presenting Instructed Retriever, a new
-
AI for Strategic Forgetting: Systems that Help Organizations Unknow
By
–
For our free newsletter this week, we cover AI for strategic forgetting: systems that decide what organizations should unknow.
@IrenaCronin and I write this newsletter every week.
AI for strategic forgetting is software that looks through an organization’s data, documents, -
Knowledge Assistant transforms unstructured data into searchable intelligence
By
–
[Demo] Explore the Knowledge Assistant for unstructured data 📑
— Databricks (@databricks) 6 janvier 2026
See how unstructured documents can be turned into a searchable knowledge layer. The assistant ingests and parses documents from Unity Catalog files or vector search indexes, then uses a RAG chatbot to return answers… pic.twitter.com/pnY44sCGm0[Demo] Explore the Knowledge Assistant for unstructured data See how unstructured documents can be turned into a searchable knowledge layer. The assistant ingests and parses documents from Unity Catalog files or vector search indexes, then uses a RAG chatbot to return answers
-
BYOAI Workplace Trend: Productivity Gains and Data Security Risks
By
–
The Pros and Cons of BYOAI A new workplace trend is emerging: BYOAI, or Bring Your Own AI. In this video, Bernard Marr explores how employees using their own AI copilots could boost productivity, creativity, and innovation — and why it also raises big questions about data
-
Integrating Cutting-Edge AI Models with Legacy Enterprise Systems
By
–
For AI to work, a technical truth must be achieved: learning to connect cutting-edge models to systems that were never designed to support them. Check out @DominoDataLab Field Chief Data Scientist Jarrod Vawdrey's comments in @CIOonline
: https://
domino.buzz/45uYltJ