How Diffusion Controller unifies and simplifies AI image generation
Algorithms & Theory
Daily edition · AI Research
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Top topics: AI · AI Research · Python
Algorithms & Theory
Benchmarking the impact of fewer, larger files across three SQL workloads The post I Compacted 1,000 Apache Iceberg Files Into 6. Here’s What Happened to Query Performance. appeared first on Towards Data Science.
Two independent papers found three families of plasma equilibria long thought unlikely to exist. One researcher credits GPT-6 Astra Pro with helping discover two of them. Here’s what the results prove and what they mean…
The real shift is bigger than productivity: AI is reshaping ownership, judgment, and the career path of data scientists. The post AI Made Data Scientists Faster. Now It’s Expanding the Job. appeared first on Towards…
Not every decision needs a decoder, generation Is not always a decision The post When All You Have Are Decoders, Every Decision Looks Like Generation appeared first on Towards Data Science.
A coding-trained AI leaves subtle traces of what it learned even when choosing ordinary words. New research shows another model can learn from those traces and emerge better at coding without ever seeing the teacher’s…
Agent design patterns every data engineer must know The post How to Design Architectural Guardrails Around AI Agents appeared first on Towards Data Science.
Here’s how to solve it exactly. The post Building Fair Evaluation Sets Is a Combinatorial Problem appeared first on Towards Data Science.
Anthropic’s newest workhorse model beats GPT-6 Astra on some agentic coding and professional-work benchmarks while charging one-fifth as much per token.
OpenAI’s decision to withhold GPT-6.1 Astra shows an internal safety process can stop a model from shipping.
Anthropic says Claude now leads 26% of its measured AI R&D work, while OpenAI has reached its “automated research intern” milestone. But neither proves AI is caught in a runaway self-improvement loop. The harder…
arXiv:2609.30643v1 Announce Type: cross Abstract: We consider the problem of learning the underlying causal directed acyclic graph (DAG) structure corresponding to a structural equation model (SEM) with non-Gaussian…
arXiv:2605.24981v2 Announce Type: replace-cross Abstract: Choosing a Large Language Model (LLM) for a given task requires comparing many strong candidates, yet standard evaluation relies on costly annotations over fixed…
arXiv:2609.30276v1 Announce Type: new Abstract: We analyze the original same-step coordinate-wise AdaGrad under generalized smoothness and heavy-tailed noise with bounded variance. In this setting, local curvature may…
arXiv:2510.02259v3 Announce Type: replace Abstract: Computational simulations play a central role in scientific discovery, and machine learning (ML) has emerged as a promising alternative to traditional physics-based…
arXiv:2609.30819v1 Announce Type: new Abstract: In many safety-critical applications, control of uncertain dynamical systems relies on observers that estimate states and external disturbances. Neural network observers…
arXiv:2609.31315v1 Announce Type: new Abstract: Unobserved common causes are pervasive in real-world time series and can induce spurious associations that causal discovery methods mistake for direct edges. We propose…
arXiv:2609.31498v1 Announce Type: cross Abstract: Search is one of the most important features in e-commerce, directly driving customer engagement and business growth. A good product search system must show both…
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