Turning AI Ideas Into University Patent Strategy
A practical guide to turning AI ideas into patents through university invention rules, prototype planning, and claim-ready differentiation.
845 articles · Page 5 / 36
A practical guide to turning AI ideas into patents through university invention rules, prototype planning, and claim-ready differentiation.
A look at UAV-MARL, which treats medical drone delivery as multi-agent collaborative decision-making, not just routing.
Why SBOMs miss agentic AI runtime behavior, environment drift, and exploitability context—and how active provenance AIBOMs address it.
ML-based NIDS can be evaded via adversarial examples like FGSM and GAN. Evaluate robustness and compare ensemble defenses.
AI co-writing can shift users from ideation to reactive selection, affecting expressed claims and even post-writing attitudes.
A curated link roundup from recently collected official updates and tech news.
Compare monthly cash vs future unlimited generative AI using ROI, including review, security, and policy-compliance costs.
Industrial LLM hallucinations framed as a reproducibility problem, comparing five prompt strategies to reduce output variance across repeated runs.
Reframes RF channels as sensors and jointly learns quantum probes with models under 5 ms/sample and pipeline constraints.
A LatAm-focused QA set (26k+) links Wikidata and Wikipedia to measure LLM gaps by country and cultural context.
Don’t equate tokens/sec or speedups with research automation; fix success, time budget, retries, and verification to forecast.
UniPINN targets three bottlenecks in multi-flow PINNs: shared vs specific features, negative transfer, and loss-scale imbalance.
A curated link roundup from recently collected official updates and tech news.
Defines skills as executable function code and manages them online via create-run-update-on-fail-save-on-success loops.
FuzzingRL combines fuzzing and reinforcement fine-tuning to automatically generate questions that induce VLM failures and reveal weak spots.
Overview of an LLM framework that automates superconducting qubit control and measurement via schema-less tool generation, plus safety and logging needs.
Guardian turns messy case docs into schema-aligned spatiotemporal states, builds Markov risk surfaces, plans with RL, then validates via LLM QA.
Because citations can be non-deterministic, treat visibility as a sampled distribution and compare it statistically over time.
Guardian proposes a multi-LLM pipeline with a consensus engine for early missing-child searches, emphasizing auditable TEVV operations.
arXiv:2603.09356 discusses dataset condensation for medical data, extending to trees and Cox via DP and zero-order optimization.
In one-pass non-stationary streams, evaluate PEFT limits and use routing/gating plus stability budgets to reduce forgetting and latency.
As AI-driven R&D loops accelerate, alignment-faking signals (12%) raise operational risk. Lock in TEVV, independent review, and monitoring.
Clinical LLM recommendations can shift with intersecting SDoH (gender, insurance, housing). Test cross-profiles and measure over-refusal before deployment.
Using executable per-instance checkers to provide verifiable rewards for multi-turn tool agents, reducing labeling while surfacing risks.