China’s AI models have Trump’s AI world at war with itself
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Over the weekend, several current and former advisors to President Donald Trump on AI publicly lobbed insults at the country’s leading AI companies. David Sacks, ...
Loop Engineering with Adaptive Parsing in Action: Parsing Flat Tables with Azure and Figures with a Vision LLM
Enterprise Document Intelligence [Vol.1 #10B] - The LLM as last line of defence, then two real escalations walked end to end: a flat table to Azure, a figure to a vision model
The post Loop Engineering with Adaptive Parsing in Action: Parsing Flat Tables with Azure and Figures with a Vision LLM appe...
Top 5 MCP Servers for High-Performance Agentic Development
Here are five that are genuinely worth wiring into a high-performance agent development setup, chosen for what they do to an agent's actual capability rather than their star count.
Somewhere in a Singapore data center, a bank is paying for eight H100s that spend most of the night waiting. The cluster was bought for good reasons (discomfort with customer documents leaving the building, a strategy team’s aversion to lock-in), so the bank secured its own sovereign compute. Now th...
Bristol Myers Squibb Building Life Science Industry’s Most Advanced AI Factory on NVIDIA Vera Rubin
Erin Davis calls it the “SuperDuperPOD.” That’s two things in one name: pharmaceutical giant Bristol Myers Squibb (BMS) already runs one of the largest AI clusters in life sciences, with serious results to show for it. And they’re doubling down. BMS announced today it is deploying its second NVIDIA ...
Safety and alignment in an era of long-horizon models
OpenAI shares lessons from deploying long-running AI models, highlighting new safety risks, observed failures, and improved safeguards through iterative deployment.
Structure of the Circular-Dyadic Convolution Error
arXiv:2607.15293v1 Announce Type: new
Abstract: Dyadic and circular convolution can both be computed in $O(N\log N)$ time using the Hadamard transform and the FFT-computed discrete Fourier transform (DFT), respectively. The Hadamard transform is preferable for its real-valued sign flips, yet its su...
Position: Quantum Program Generation Must Prioritize Validity Over Probabilistic Scaling
arXiv:2607.15313v1 Announce Type: new
Abstract: The scaling hypothesis assumes that increasing model parameters yields emergent reasoning capabilities. This position paper argues that applying this probabilistic paradigm to generic quantum circuit synthesis is a directional error. Unlike natural la...
A Transportable Threshold-Based Framework for Interpretable Classification of Medical Data
arXiv:2607.15394v1 Announce Type: new
Abstract: Black-box models limit the adoption of artificial intelligence in medicine due to their lack of interpretability and reproducibility. We introduce a statistically grounded framework that provides fully interpretable, rule-based clinical classification...
AI Trading: Evaluating Large Language Models for Technical Market Analysis
arXiv:2607.15414v1 Announce Type: new
Abstract: Large Language Models (LLMs) have emerged as powerful tools for processing the heterogeneous information environments of modern financial markets. This paper presents a systematic, comparative evaluation of five prominent LLMs: GPT-4 Turbo, Claude 3 O...
GraphDx: A Cost-Aware Knowledge-Enhanced Multi-Agent Framework for Sequential Diagnosis
arXiv:2607.15280v1 Announce Type: new
Abstract: Sequential diagnosis requires balancing diagnostic accuracy against resource costs through iterative information gathering. Existing Large Language Model (LLM) approaches exhibit a critical knowledge-reasoning gap: despite encoding extensive medical k...
Causal-Audit: Explicit and Auditable Graph-based Reasoning via Target-Aware Causal Chain Construction
arXiv:2607.15281v1 Announce Type: new
Abstract: Causal and intervention-based question answering is fundamental to advancing large language models (LLMs) toward reasoning beyond surface-level correlations and understanding underlying causal mechanisms. However, existing LLM-based methods often rely...
arXiv:2607.15314v1 Announce Type: new
Abstract: Healthcare spans high-stakes communication, expert reasoning, and workflow execution, yet specialized LLMs that cover these use cases together remain limited. A healthcare model must handle patient consultation, clinical reasoning over text and images...
AnovaX: A Local, Multi-Agent Voice Assistant with LLM Planning, Typed Executors, and Adaptive Recovery
arXiv:2607.15367v1 Announce Type: new
Abstract: Desktop voice assistants are still dominated by cloud pipelines that ship raw audio off the machine and expose a fixed set of skills. We describe AnovaX, a small local-first assistant that runs entirely on the user's computer and treats the desktop it...
Someone Fine-Tuned OpenBMB’s MiniCPM5-1B on Claude Fable 5 Traces to Ship a 657MB Local Thinking Model
A community developer fine-tuned OpenBMB's MiniCPM5-1B on Claude Fable 5 traces into a 1B model that runs fully local — a 657MB smallest build, 128K context, and visible reasoning. We verify every spec against the Hugging Face cards, separate what a fine-tune actually inherits from real capability, ...
AI Weekly Issue #515: China's AI is redrawing the AI race
Two stories this week, connected by one word: open. A Chinese open-weight model helped touch off the worst week for chip stocks since April, as investors finally asked what $725 billion in AI capex is buying. Days later, when an autonomous agent breached Hugging Face, its own defenders were locked o...
Increasing reliance on language models for legal tasks have led to calls for more information about the likelihood and severity of potential errors. Realizing useful and robust transparency requires an institutional perspective, say the editors of a new special section in PNAS.
Length Value Model: Scalable Value Pretraining for Token-Level Length Modeling
Token serves as the fundamental unit of computation in modern autoregressive models, and generation length directly influences both inference cost and reasoning performance. Despite its importance, existing approaches lack fine-grained length modeling, operating primarily at the coarse-grained seque...
Feyn AI Releases SQRL, a Text-to-SQL Model Family That Inspects the Database Before Writing a Query
Feyn Labs has released SQRL, a family of text-to-SQL models that inspect a database with read-only probes before committing to a query. The flagship SQRL-35B-A3B reports 70.6% execution accuracy on BIRD Dev, edging Claude Opus 4.6, and distills into self-hostable 4B and 9B checkpoints.
The post Feyn...
Backpropagation Explained for Beginners (Part 1): Building the Intuition
Let's discover how neural networks learn, step by step
The post Backpropagation Explained for Beginners (Part 1): Building the Intuition appeared first on Towards Data Science.
Loop Engineering for RAG Question Parsing: The Small Loop That Runs Before Retrieval
Enterprise Document Intelligence [Vol.1 #6quinquies] - Prompt engineering, then context engineering, then loop engineering. On the question side, the loop is small by design: read the doc, ask what is missing, re-parse.
The post Loop Engineering for RAG Question Parsing: The Small Loop That Runs Bef...