Grounding AI agents in biological reality: Building blocks for autonomous wet labs
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NVIDIA’s Nemotron 3.5 Bolt ran locally on a Surface Laptop Ultra at up to 65.5 tokens per second, while Super VL showed promise in hosted research and coding tests. After putting both through the same challenges, here’s…
I rated my confidence 4 out of 5, then couldn’t find a planted bug in 8 minutes. Here is the tool, the run, and its limits. The post Do You Still Own the Code Your AI Wrote? I Built CodeOwnership to Measure It appeared…
The tool found the right passage but missed the mismatch, and the audit shows where rule-based checks break down. The post I Built a Claim-Checker for Writing With Codex. It Passed a Wrong Claim. appeared first on…
Getting your data science code running anywhere The post Deploying Data Science Tools: Part 1 appeared first on Towards Data Science.
The same three workloads show a much stronger JIT, but it still doesn't help every program The post I Reran My Python 3.14 JIT Benchmarks on Python 3.15 appeared first on Towards Data Science.
OpenAI’s GPT-Live-1.1 adds 13 voices and promises more natural multilingual conversations. Speech recognition and task accuracy remain unquantified, while safety tests show mixed results.
Meta and Apple have demonstrated Muse Spark Open on connected Mac Studios. With the required hardware reportedly costing more than $40,000, the business case depends on sustained usage and how much cloud spending local…
arXiv:2610.21755v1 Announce Type: cross Abstract: Large Language Model agents operate through closed-loop action policies whose decision space is defined by an agent harness. We investigate how this operating space…
arXiv:2610.21719v1 Announce Type: cross Abstract: Arrested retinal development can cause childhood visual impairment, but grading optical coherence tomography scans is difficult to standardise across devices and…
arXiv:2610.21038v1 Announce Type: new Abstract: Machine learning models for tabular prediction typically assume that training data are representative of the population on which they will be deployed. In practice,…
arXiv:2610.22213v1 Announce Type: new Abstract: Randomized block coordinate descent (RBCD) is a popular optimization algorithm for many large-scale machine learning problems. The existing theoretical analysis of RBCD…
arXiv:2610.21995v1 Announce Type: new Abstract: Weight-space learning across architectures requires representations that respect parameter symmetries and scale to large networks. Existing equivariant tensor encoders…
arXiv:2605.09424v3 Announce Type: replace Abstract: Generative modelling is a demanding test of foundation models, because it requires robust, holistic representation learning for a given data modality, rather than…
arXiv:2610.21403v1 Announce Type: cross Abstract: Distribution shifts pose a fundamental challenge to robust multimodal learning. Existing methods typically promote invariance by suppressing environment-dependent…
arXiv:2610.20841v1 Announce Type: cross Abstract: Many resource-constrained edge devices require artificial intelligence (AI) services but are not powerful enough to store or execute neural networks (NNs). Analog radio…
arXiv:2610.22050v1 Announce Type: cross Abstract: Radio technosignature searches rely on machine learning detectors to shrink the candidate pool before a human looks at it. They are validated on held-out data from the…
arXiv:2610.21393v1 Announce Type: cross Abstract: Vehicle Routing Problems (VRPs) are fundamental to many real-world applications. Recent advances in large language models (LLMs) have spurred progress in solving these…
arXiv:2610.21200v1 Announce Type: new Abstract: Protein foundation models increasingly support the generation of novel biological sequences, yet their reliance on large public datasets creates opportunities for…
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