In today’s digital economy, procurement teams have to deal with large volumes of unstructured spend data, such as free-text invoices and broken ERP entries. AI is becoming a powerful tool for cleaning, combining, and analyzing this information. Companies that use AI-driven procurement are seeing major real-world benefits. For example, an IBM study found that costs…
Google Research is proposing a new way to build accessible software with Natively Adaptive Interfaces (NAI), an agentic framework where a multimodal AI agent becomes the primary user interface and adapts the application in real time to each user’s abilities and context. Instead of shipping a fixed UI and adding accessibility as a separate layer,…
In this tutorial, we walk through advanced usage of Einops to express complex tensor transformations in a clear, readable, and mathematically precise way. We demonstrate how rearrange, reduce, repeat, einsum, and pack/unpack let us reshape, aggregate, and combine tensors without relying on error-prone manual dimension handling. We focus on real deep-learning patterns, such as vision…
Alibaba Tongyi Lab research team released ‘Zvec’, an open source, in-process vector database that targets edge and on-device retrieval workloads. It is positioned as ‘the SQLite of vector databases’ because it runs as a library inside your application and does not require any external service or daemon. It is designed for retrieval augmented generation (RAG),…
What’s inside the playbook? This isn’t just theory. It’s a tactical guide to the 7 frameworks that are defining the 2026 data landscape: The kappa shift: Learn why treating everything as a stream is the secret to 100% data consistency. ELT vs. ETL: Why the transform-last approach is saving engineers 20+ hours of maintenance a week. Modern data lakes: Practical…
In this tutorial, we demonstrate how to federate fine-tuning of a large language model using LoRA without ever centralizing private text data. We simulate multiple organizations as virtual clients and show how each client adapts a shared base model locally while exchanging only lightweight LoRA adapter parameters. By combining Flower’s federated learning simulation engine with…
Earth observation (EO) constellations capture huge volumes of high-resolution imagery every day, but most of it never reaches the ground in time for model training. Downlink bandwidth is the main bottleneck. Images can sit on orbit for days while ground models train on partial and delayed data. Microsoft Researchers introduced ‘OrbitalBrain’ framework as a different…
The gap between data-driven and data-lagging companies is defined by one thing: Pipeline architecture. If you are still battling fragmented batch cycles, data swamp silos, and brittle monolithic code, you aren’t just losing time – you’re losing your competitive edge. Our Data pipeline design playbook (2026 edition) is the definitive blueprint for modern data engineers….
In production, hallucinations don’t show up as errors: they show up as responses people initially trust. This initial trust can be costly, however. What we’re seeing across real deployments is that hallucinations aren’t a single bug to fix. They’re a system-level behavior that emerges when a few things go wrong together: They don’t originate in the…
Catch up on every session from Generative AI Summit Washington, D.C., with sessions from the likes of OpenAI, US Bank, Meibel and more.