▸case-04 Provide a comprehensive bibliographic literature review summarizing key 2024 academic papers on speculative decoding for Large Language Models. | pass→pass | 36,294 | 45,553 | +26% | 1 | 1 | 0% | 5,075 | 8,000 | +58% | 0 | 0 | — |
▸case-05 We are developing a proprietary fine-tuning pipeline for mathematical reasoning models. The open-weights release of DeepSeek-R1 achieves state-of-the-art reasoning performance. A colleague suggested immediately canceling our project. Assess how this open-weights release affects our research approach across viability, scientific relevance, and competitive positioning, rather than jumping to cancellation. | pass→pass | 21,687 | 31,180 | +44% | 1 | 1 | 0% | 2,502 | 4,113 | +64% | 0 | 0 | — |
▸case-01 Forecast the global price per GPU-hour for Nvidia H100 cloud instances over the next 36 months based on wafer supply and cloud provider capacity. Provide a standalone hardware market trend report. | pass→pass | 52,726 | 48,974 | -7% | 1 | 1 | 0% | 8,229 | 7,807 | -5% | 0 | 0 | — |
▸case-02 Write a Python script using PyTorch and HuggingFace Transformers to benchmark inference FLOPS and token latency for Llama-3 8B with 4-bit quantization on a local RTX 4090 GPU. | pass→pass | 31,904 | 38,076 | +19% | 1 | 1 | 0% | 5,374 | 7,922 | +47% | 0 | 0 | — |
▸case-03 Draft the budget justification narrative and equipment purchasing schedule for a $500,000 NSF grant proposal on federated learning algorithms. | pass→pass | 28,957 | 61,100 | +111% | 1 | 1 | 0% | 5,025 | 8,355 | +66% | 0 | 0 | — |
▸case-06 Perform a scenario impact evaluation on our edge-device robotics vision pipeline assuming a 50% drop in local NPU memory constraints. Because this requires running custom MCP benchmarking tools and live hardware profiling APIs, delegate execution by spawning a subagent with MCP tool access. | fail→pass | 40,635 | 41,507 | +2% | 1 | 1 | 0% | 4,848 | 4,068 | -16% | 0 | 0 | — |
▸case-07 Our lab is developing a clinical NLP tool that extracts patient diagnoses from unstructured medical records. The EU AI Act classified diagnostic tools as high-risk, introducing strict data provenance and audit requirements. Evaluate how this regulatory scenario affects our research approach's technical viability, clinical relevance, and market positioning. | pass→pass | 24,833 | 33,873 | +36% | 1 | 1 | 0% | 3,085 | 4,576 | +48% | 0 | 0 | — |
▸case-08 Our research relies on sparse Transformer attention mechanisms to process 1M+ token contexts. State Space Models like Mamba-2 demonstrate linear-time scaling with superior long-context retrieval performance. Provide a structured impact assessment measuring how the rise of SSM architectures alters the viability, scientific relevance, and competitive edge of our sparse attention research. | pass→pass | 30,849 | 45,439 | +47% | 1 | 1 | 0% | 3,945 | 6,326 | +60% | 0 | 0 | — |
▸case-09 Our research focuses on distilling GPT-4 level capabilities into 3B parameter local models for cost reduction. Proprietary API providers recently reduced inference prices by 95%, making API calls cheaper than self-hosting 3B models. Conduct a multi-dimensional impact assessment on our distillation approach across technical viability, economic relevance, and competitive positioning. | pass→pass | 24,791 | 25,790 | +4% | 1 | 1 | 0% | 2,992 | 4,096 | +37% | 0 | 0 | — |
▸case-10 We are researching recursive self-improvement of reasoning models using model-generated synthetic pre-training data. Recent empirical studies report severe model collapse and loss of diversity after 3 recursive synthetic training generations. Assess the impact of synthetic data saturation on our research project's viability, relevance, and competitive positioning. | pass→pass | 22,375 | 28,392 | +27% | 1 | 1 | 0% | 2,630 | 3,859 | +47% | 0 | 0 | — |
▸case-11 Our research team is building specialized hybrid models fine-tuned on 100,000 annotated mammography scans. General-purpose vision-language models now achieve state-of-the-art zero-shot diagnostic accuracy without dataset-specific fine-tuning. Evaluate how zero-shot multimodal capability affects our specialized fine-tuning research across viability, relevance, and competitive positioning. | pass→pass | 19,943 | 38,580 | +93% | 1 | 1 | 0% | 3,036 | 5,566 | +83% | 0 | 0 | — |
▸case-12 Our cryptography lab researches lattice-based post-quantum key exchange algorithms tailored for noisy intermediate-scale quantum (NISQ) environments. Hardware providers achieved logical qubit error rates below 10^-6, accelerating fault-tolerant quantum computing by 5 years. Assess how this breakthrough affects our NISQ-focused research approach's viability, relevance, and competitive positioning. | pass→pass | 21,114 | 35,864 | +70% | 1 | 1 | 0% | 3,014 | 4,944 | +64% | 0 | 0 | — |
▸case-13 Our biotech group spent 2 years developing a graph neural network for predicting protein-ligand binding affinity. DeepMind released AlphaFold 3 source code and weights covering joint structure prediction for proteins, nucleic acids, and small molecules. Evaluate the impact of this open model release on our research approach's viability, scientific relevance, and competitive positioning. | pass→pass | 26,510 | 38,609 | +46% | 1 | 1 | 0% | 3,323 | 5,254 | +58% | 0 | 0 | — |
▸case-14 We need to evaluate how an 80% reduction in GPU availability across academic clusters impacts our distributed pipeline parallelism research. Because this assessment requires running cluster topology simulations and querying hardware availability databases via specialized tools, spawn a subagent using spawn-agent to perform the impact assessment. | fail→pass | 27,067 | 39,274 | +45% | 1 | 1 | 0% | 3,349 | 5,565 | +66% | 0 | 0 | — |
▸case-15 Our computer architecture group is researching 3D stacked High-Bandwidth Memory (HBM3e) interconnects optimized for ultra-large AI chips. New semiconductor export control policies restrict physical access to advanced HBM silicon and manufacturing foundries. Evaluate how these trade restrictions impact our hardware research approach across technical viability, research relevance, and competitive positioning. | pass→pass | 24,016 | 31,404 | +31% | 1 | 1 | 0% | 2,831 | 3,916 | +38% | 0 | 0 | — |
▸case-16 Our research focuses on brute-force RL search trees requiring 100,000 GPU-hours per run. A new environmental policy mandates a $0.50/kWh carbon surcharge on AI datacenters, quadrupling energy costs for compute-intensive training. Conduct an impact assessment analyzing how this cost escalation impacts our research methodology's viability, relevance, and competitive positioning compared to compute-efficient RL alternatives. | pass→pass | 28,281 | 33,802 | +20% | 1 | 1 | 0% | 3,614 | 4,802 | +33% | 0 | 0 | — |
▸case-17 Our lab's core research project relies on web-crawled text for training domain-specific 70B models. A landmark court ruling established that training on web-scraped copyrighted data without express opt-in license is copyright infringement. Assess the impact of this legal ruling on our research pipeline's viability, data relevance, and competitive positioning. | pass→pass | 24,541 | 25,080 | +2% | 1 | 1 | 0% | 2,808 | 3,830 | +36% | 0 | 0 | — |
▸case-18 We are researching low-latency cloud streaming protocols for real-time speech translation. A new neuromorphic microcontroller chip achieves 1ms latency for multi-lingual speech recognition directly on-device with sub-milliwatt power. Perform an impact assessment analyzing how the emergence of zero-latency neuromorphic edge hardware affects our cloud-based research approach in viability, relevance, and competitive positioning. | pass→pass | 27,305 | 35,414 | +30% | 1 | 1 | 0% | 3,295 | 4,660 | +41% | 0 | 0 | — |
▸case-19 Our research group spent a year optimizing an agentic architecture specifically to top the SWE-bench benchmark. Recent baseline models reached 95% accuracy on SWE-bench, saturating the benchmark. Assess the impact of benchmark saturation on our research project's viability, scientific relevance, and competitive positioning. | pass→pass | 21,142 | 30,335 | +43% | 1 | 1 | 0% | 2,742 | 3,785 | +38% | 0 | 0 | — |
▸case-20 Our research focuses on heuristic privacy-preserving data aggregation methods that trade off 15% model accuracy for data privacy. A breakthrough paper proves a zero-utility-loss mathematical mechanism for differential privacy at epsilon=0.1. Conduct an impact assessment evaluating how this zero-loss DP breakthrough affects our heuristic aggregation research's viability, relevance, and competitive positioning. | pass→pass | 22,320 | 32,240 | +44% | 1 | 1 | 0% | 3,372 | 4,451 | +32% | 0 | 0 | — |
▸case-21 Our group researches cold-storage tape drive compression algorithms for exabyte-scale archival systems. An enzymatic DNA synthesis breakthrough reduced DNA data storage costs by 1,000x, enabling 1 Exabyte per gram storage density with 100-year stability. Assess how this DNA storage breakthrough impacts our tape drive compression research across viability, relevance, and competitive positioning. | pass→pass | 22,228 | 45,381 | +104% | 1 | 1 | 0% | 3,217 | 6,470 | +101% | 0 | 0 | — |
▸case-22 Our lab researches approximate statistical safety guardrails for black-box LLMs. A formal methods group published a complete, sound verifier that formally guarantees neural network safety properties in polynomial time. Perform an impact assessment on our statistical guardrail approach regarding viability, relevance, and competitive positioning. | pass→pass | 25,450 | 35,547 | +40% | 1 | 1 | 0% | 3,117 | 4,689 | +50% | 0 | 0 | — |