February 2026

Clinical risk prediction models often underperform in real-world settings due to poor calibration, limited transportability, and subgroup disparities. These challenges are amplified in high-dimensional multimodal cancer datasets characterized by complex feature interactions and a p >> n structure. We present a fully reproducible multimodal machine learning framework for 5-year overall survival prediction in breast cancer, integrating clinical variables with high-dimensional transcriptomic and copy-number alteration (CNA) features from the METABRIC cohort. After variance- and sparsity-based filtering and dimensionality reduction, […]

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How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## Microsoft’s AutoDev: The AI That Builds, Tests, and Fixes Code on Its Own By @microsoft [ 27 Min read ] Microsoft’s AutoDev uses AI agents to write, test, and fix code autonomously, hitting 91.5% on HumanEval in Docker. Read More. How CMOs Win CFO […]

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Agent-based epidemic models (ABMs) encode behavioral and policy heterogeneity but are too slow for nightly hospital planning. We develop county-ready surrogates that learn directly from exascale ABM trajectories using Universal Differential Equations (UDEs): mechanistic SEIR-family ODEs with a neural-parameterized contact rate $κ_φ(u,t)$ (no additive residual). Our contributions are threefold: we adapt multiple shooting and an observer-based prediction-error method (PEM) to stabilize identification of neural-augmented epidemiological dynamics across intervention-driven regime shifts; we enforce positivity and mass conservation and show […]

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The sharper the mind, the more elaborate the justification for staying wrong. Depth of thought becomes the mechanism of loss when it serves identity instead of truth. There is a version of intelligence that protects you in markets. It reads conditions, adjusts frameworks, and knows when to step aside. Then there is another version, far more common, that does the opposite. It builds elaborate cases for positions that should have been closed days ago. The distinction matters more […]

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I keep hearing the same question at every engineering offsite, Slack thread, and investor pitch: “What’s the best model right now — GPT, Claude, or Gemini?” I spent the last several months building and debugging agent-based systems, and I think this is the wrong question entirely. The evidence is now overwhelming: what determines whether an AI agent succeeds in production is not the model underneath it, but the infrastructure wrapped around it. I am going to lay out my hypothesis, test […]

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