raw data
Beyond Market Intelligence keeps raw data in one place: 2 stories so far. The section currently leads with “Bridging the Gap Between Raw Data and Published Results” and “From raw sensor data to deployed model, discover a simpler path to edge ML.”. Reproducing a paper's results often hinges on access to the exact dataset, and when the public raw data doesn't match Table 1, you're left with a frustrating gap. Getting from raw sensor data to a deployed model on an MCU is rarely a smooth path, so seeing a project built specifically to remove that friction is refreshing. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every raw data story on Beyond Market Intelligence, newest first.
Bridging the Gap Between Raw Data and Published Results
Reproducing a paper's results often hinges on access to the exact dataset, and when the public raw data doesn't match Table 1, you're left with a frustrating gap. You've done the diligent work of testing every reasonable preprocessing path, and still the numbers don't align. At that point, the larger-but-valid version you can defend is the honest choice. Document the mismatch clearly, note your attempts to reach the authors, and consider a polite journal escalation after a reasonable wait.
From raw sensor data to deployed model, discover a simpler path to edge ML.
Getting from raw sensor data to a deployed model on an MCU is rarely a smooth path, so seeing a project built specifically to remove that friction is refreshing. The auto-labeling tool stands out because manual labeling of time series data is a genuine bottleneck for many edge projects. It is smart to pair that with a chatbot that offers direct signal insights. Keeping the platform open source invites practical contributions that could shape its evolution. It is worth exploring for anyone working on tinyML.