What if an unsupervised model could become a strong classifier with only a handful of labels?
The post You Don’t Need Many Labels to Learn appeared first on Towards Data Science.
Anthropic Launches Claude Opus 4.7 For “Most Difficult Tasks”
Artificial intelligence is rapidly developing. The minute we become accustomed to one breakthrough, another comes to shift our expectations. The new model, Claude Opus 4.7, that Anthropic introduced recently, is one such shift. The release tends to go beyond mere AI chatbots and makes AI a trusted, ...
Roboticists used to dream big but build small. They’d hope to match or exceed the extraordinary complexity of the human body, and then they’d spend their career refining robotic arms for auto plants. Aim for C-3P0; end up with the Roomba. The real ambition for many of these researchers was the robo...
Qwen Team Open-Sources Qwen3.6-35B-A3B: A Sparse MoE Vision-Language Model with 3B Active Parameters and Agentic Coding Capabilities
Qwen Team Open-Sources Qwen3.6-35B-A3B: A Sparse MoE Vision-Language Model with 3B Active Parameters and Agentic Coding Capabilities
The post Qwen Team Open-Sources Qwen3.6-35B-A3B: A Sparse MoE Vision-Language Model with 3B Active Parameters and Agentic Coding Capabilities appeared first on MarkTec...
Portfolio Optimization Proxies under Label Scarcity and Regime Shifts via Bayesian and Deterministic Students under Semi-Supervised Sandwich Training
arXiv:2604.14206v1 Announce Type: new
Abstract: This paper proposes a machine learning assisted portfolio optimization framework designed for low data environments and regime uncertainty. We construct a teacher student learning pipeline in which a Conditional Value at Risk (CVaR) optimizer generate...
Bringing AI-driven protein-design tools to biologists everywhere
Founded by Tristan Bepler PhD ’20 and former MIT professor Tim Lu PhD ’07, OpenProtein.AI offers researchers open-source models and other tools for protein engineering.
NuHF Claw: A Risk Constrained Cognitive Agent Framework for Human Centered Procedure Support in Digital Nuclear Control Rooms
arXiv:2604.14160v1 Announce Type: new
Abstract: The rapid digitization of nuclear power plant main control rooms has fundamentally reshaped operator interaction patterns, introducing complex soft-control behaviors and elevated cognitive risks that are not adequately addressed by existing human reli...
Simulating Human Cognition: Heartbeat-Driven Autonomous Thinking Activity Scheduling for LLM-based AI systems
arXiv:2604.14178v1 Announce Type: new
Abstract: Large Language Model (LLM) agents have demonstrated remarkable capabilities in reasoning and tool use, yet they often suffer from rigid, reactive control flows that limit their adaptability and efficiency. Most existing frameworks rely on fixed pipeli...
Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling
arXiv:2604.14221v1 Announce Type: new
Abstract: Reliable evaluation of anomaly detection methods in multivariate time series remains an open challenge, largely due to the limitations of existing benchmark datasets. Current resources often lack fine-grained anomaly annotations, do not provide explic...
Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making
arXiv:2604.14240v1 Announce Type: new
Abstract: The simulation of complex systems increasingly relies on sophisticated but fundamentally opaque computational black-box simulators. Surrogate models play a central role in reducing the computational cost of complex systems simulations across a wide ra...
Formalizing Kantian Ethics: Formula of the Universal Law Logic (FULL)
arXiv:2604.14254v1 Announce Type: new
Abstract: The field of machine ethics aims to build Artificial Moral Agents (AMAs) to better understand morality and make AI agents safer. To do so, many approaches encode human moral intuition as a set of axioms on actions e.g., do not harm, you must help othe...
OpenAI Launches GPT-Rosalind: Its First Life Sciences AI Model Built to Accelerate Drug Discovery and Genomics Research
OpenAI has officially entered the specialized science race with GPT-Rosalind, a frontier reasoning model designed to slash the 10-15 year timeline of drug discovery through advanced biochemistry and genomic analysis.
The post OpenAI Launches GPT-Rosalind: Its First Life Sciences AI Model Built to Ac...
Building Transformer-Based NQS for Frustrated Spin Systems with NetKet
Learn how to combine Transformer architectures with Quantum Physics using NetKet and JAX. This guide walks through building a research-grade VMC pipeline to solve the frustrated J1-J2 Heisenberg spin chain with Neural Quantum States.
The post Building Transformer-Based NQS for Frustrated Spin System...
Physical Intelligence, a hot robotics startup, says its new robot brain can figure out tasks it was never taught
The new model, called π0.7, represents what the company describes as an early but meaningful step toward the long-sought goal of a general-purpose robot brain.
OpenAI Announces GPT-5.4-Cyber But You Can’t Get it Just Yet
The question around AI, and I mean the pinnacle of AI, not your regular “write me an email”, is shifting. What used to be “what can it do for me?” has now become “who gets to use it?” We saw this recently with Anthropic’s Claude Mythos Preview – a supposed epitome of AI models that […]
The post Open...
The upstream decision no model, or LLM can fix once you get it wrong
The post Your Chunks Failed Your RAG in Production appeared first on Towards Data Science.
InsightFinder raises $15M to help companies figure out where AI agents go wrong
According to CEO Helen Gu, the biggest problem facing the industry today is not just monitoring and diagnosing where AI models go wrong, it's diagnosing how the entire tech stack operates now that AI is a part of it.