This startup is betting India’s gig economy can train the world’s robots
Human Archive, a startup founded by Berkeley and Stanford researchers, is paying gig workers in India to wear camera-equipped caps and sensor devices to collect the real-world physical training data that AI and robotics labs are racing to acquire.
Rethinking organizational design in the age of agentic AI
Amid rapidly growing adoption of enterprise-level AI agents, there’s a disconnect emerging between ambition and execution. Although 85% of organizations say they want to be agentic within the next three years, 76% say their current operations and infrastructure can’t support that change. They cite ...
Visual Debugging Tools for Machine Learning Workflows
In this article, we cover three topics: what to visualize during training, the tools that provide those visualizations, and the methods to capture model computations directly using hooks and breakpoints.
How I turned 100 messy pdfs into structured insights by building a deterministic loop around agents
The post Stop Using LLMs Like Giant Problem Solvers appeared first on Towards Data Science.
The Domain Shift: Moving Data Governance from Product Triage to Infrastructure Investment
How shifting the operational focus from isolated data products to systemic domain architecture resolves technical bottlenecks and optimizes platform investment.
The post The Domain Shift: Moving Data Governance from Product Triage to Infrastructure Investment appeared first on Towards Data Science.
Who Authorized That? The Delegation Problem in Multi-Agent AI
Your AI agent booked a meeting, summarized a financial report, and emailed the highlights to three stakeholders. To do this, it called a calendar agent, a document analysis agent, and an email agent. Each accessed internal systems, made decisions about what to include, and acted on your behalf. Here...
10 Everyday Tasks You Can Automate with AI Today (With n8n Templates)
Most AI automation content sounds useful, but then leaves you with one big question: where to start? Instead of only talking about automation, you probably want to create real-world automation workflows with minimal coding. That’s where the power of low-code platforms like n8n comes into play. Here ...
Haven’t you heard? White-collar jobs are going away, decimated by AI. Waves of layoffs in the tech sector (most recently at Coinbase and Meta and Cisco) are said to presage what will soon come for all of us knowledge workers. But before you quit your job as a software developer or financial analyst—...
Meet OmniVoice Studio: A Local, Open-Source Alternative to ElevenLabs
OmniVoice Studio runs voice cloning, video dubbing, real-time dictation, and speaker diarization entirely on your own hardware. No API keys, no cloud account, and no subscription required. The project supports 646 languages for TTS and exposes an MCP server for integration with Claude, Cursor, or an...
Algometrics: Forecasting Under Algorithmic Feedback
arXiv:2605.23978v1 Announce Type: new
Abstract: In algorithmic markets, predictive models become part of the data-generating process they aim to forecast. Once their outputs are converted into trades, allocations, execution schedules, or risk controls, they change the future data on which they are ...
arXiv:2605.23984v1 Announce Type: new
Abstract: Industrial anomaly detection has attracted significant attention as a fundamental challenge in industrial systems. The rapid advancement of heterogeneous industrial sensors has driven industrial anomaly detection from unimodal to multimodal paradigms....
Towards Verifiable Transformers: Solver-Checkable Circuit Explanations
arXiv:2605.24033v1 Announce Type: new
Abstract: Mechanistic interpretability often identifies circuits inside Transformer models, but explanations of those circuits are usually validated through examples, ablations, and manual reasoning. This leaves a gap between finding a plausible circuit and pro...
Iterative Refinement Neural Operators are Learned Fixed-Point Solvers: A Principled Approach to Spectral Bias Mitigation
arXiv:2605.24041v1 Announce Type: new
Abstract: Neural operators serve as fast, data-driven surrogates for scientific modeling but typically rely on a monolithic, single-pass inference procedure that struggles to resolve high-frequency details, a limitation known as spectral bias. We introduce the ...
In Search of the Ingredients of Open-Endedness: Replicating Picbreeder with Large Vision-Language Models
arXiv:2605.23908v1 Announce Type: new
Abstract: We are in the midst of large-scale industrial and academic efforts to automate the processes of scientific, technological and creative production through AI-driven assistants. Historically, a fundamental property of these processes in their human form...
arXiv:2605.23909v1 Announce Type: new
Abstract: We investigate the calibration of large language models' (LLMs') confidence across diverse tasks. The results of our preregistered study show that the current crop of LLMs are, like people, too sure they are right: confidence exceeds accuracy, on aver...
How Much Thinking is Enough? Quantifying and Understanding Redundancy in LLM Reasoning
arXiv:2605.23926v1 Announce Type: new
Abstract: Reasoning-capable large language models solve hard problems by emitting long chains of thought, paying heavily in latency, GPU time, and energy. Casual inspection of their traces reveals extensive reformulation, verification, and circular self-reflect...
Context: Proactive Goal-Directed Intelligence via Composable Sandboxed Programs, Declarative Wiring, and Structured Interaction
arXiv:2605.23928v1 Announce Type: new
Abstract: We present Context, the intelligence layer of the Magarshak Architecture, which replaces reactive query-response chatbots with proactive goal-directed agents that advance shared tasks without waiting for user prompts. The architecture rests on three m...
Toward Reliable Design of LLM-Enabled Agentic Workflows: Optimizing Latency-Reliability-Cost Tradeoffs
arXiv:2605.23929v1 Announce Type: new
Abstract: Modern AI systems increasingly rely on workflows composed of multiple interacting agents, some powered by large language models (LLMs) and others by conventional computational modules. This paper analyzes the fundamental tradeoffs between latency, rel...
AI Weekly Issue #496: Anthropic just opened its Pentagon-grade model to everyone
In the past 48 hours: Anthropic released Mythos — its Pentagon and NSA-deployed model — to the general public, resetting what counts as the public frontier. A coordinated SQL-injection campaign weaponised Ghost CMS across 700+ sites including Harvard and Oxford. Meta started cutting 8,000 jobs this ...
Together AI Open-Sources OSCAR: An Attention-Aware 2-Bit KV Cache Quantization System for Long-Context LLM Serving
Together AI has released OSCAR (Offline Spectral Covariance-Aware Rotation), an INT2 KV cache quantization method for long-context LLM serving. Unlike prior rotation-based approaches that apply data-oblivious Hadamard transforms, OSCAR derives separate rotations for keys and values from attention-aw...