How Starship reduces cognitive overhead by surfacing git branches, environments, containers, and errors in the terminal. Continue reading on Towards AI »
Stop the memory rot TL;DR: You can keep your AI sharp by forcing it to summarize and prune what it remembers (a.k.a. compacting). Common Mistake ❌ You keep a single, long conversation open for hours. You feed the AI with every error log and every iteration of your code. Eventually, the AI starts to ignore your early instructions or hallucinate nonexistent functions. Problems Addressed 😔 Context Decay: The AI loses track of your original goals in the middle of […]
I’m a first-year PhD student and noticed that I’m not funneling down a topic during my PhD but covering a very broad topics within my domain. My core topic is a niche and I’m probably on application side, applying it to very broad range of topics. I’m loving it and I feel it might be a red flag. That instead of mastering an art, I’m just playing around random topics (by how it looks on my CV) submitted […]
I combined two recent approaches, Stanford’s ACE and the Reflective Language Model pattern, to build agents that write code to analyze their own execution traces. Quick context on both: ACE (arxiv): agents learn from execution feedback through a Reflector (LLM-as-a-judge) and SkillManager that curate a Skillbook of strategies. No fine-tuning, just in-context learning. RLM (arxiv): instead of loading full input into context, an LLM writes and executes code in a sandbox to selectively explore the data. The problem […]
Hey r/MachineLearning, I just finished a project/paper tackling one of the hardest problems in AV safety: The Long-Tail Problem. Most safety filters rely on simple rules (e.g., “if brake > 5m/s2, then log”). These rules are brittle and miss 99% of “semantic” safety risks (erratic lane changes, non-normative geometry). I wanted to see if we could automate this using Generative AI instead of manual rules. The Approach: I developed “Deep-Flow,” a framework that uses Optimal Transport Conditional Flow […]
How are you, hacker? 🪐 What’s happening in tech today, March 7, 2026? The HackerNoon Newsletter brings the HackerNoon homepage straight to your inbox. On this day, Bell Receives Patent for Telephone in 1876, and we present you with these top quality stories. From HackerNoon Projects of the Week: Black Market SSP, CutePetPal SudoDocs to Your Life as an RPG: Why Lifespans Feels Uncomfortably True, let’s dive right in. Your Life as an RPG: Why Lifespans Feels Uncomfortably […]
Discover how stepping back to observe symmetry and structure can collapse search space and accelerate machine learning performance. Continue reading on Towards AI »
Patient no-shows disrupt outpatient clinic operations, reduce productivity, and may delay necessary care. Clinics often adopt overbooking or double-booking to mitigate these effects. However, poorly calibrated policies can increase congestion and waiting times. Most existing methods rely on fixed heuristics and fail to adapt to real-time scheduling conditions or patient-specific no-show risk. To address these limitations, we propose an adaptive outpatient double-booking framework that integrates individualized no-show prediction with multi-objective reinforcement learning. The scheduling problem is formulated as […]
Chaotic time series are notoriously difficult to forecast. Small uncertainties in initial conditions amplify rapidly, while strong nonlinearities and regime dependent variability constrain predictability. Although modern deep learning often delivers strong short horizon accuracy, its black box nature limits scientific insight and practical trust in settings where understanding the underlying dynamics matters. To address this gap, we propose two complementary symbolic forecasters that learn explicit, interpretable algebraic equations from chaotic time series data. Symbolic Neural Forecaster (SyNF) adapts […]
Packworks is building the operating system for Southeast Asia’s informal retail economy by digitizing hundreds of thousands of sari-sari stores in the Philippines. Through a mobile ERP platform, data analytics, and AI-driven insights, the company helps micro-retailers manage inventory and sales while enabling FMCG brands to reach fragmented last-mile markets. With over 15 million transactions annually and $272M GMV processed in 2025, Packworks is transforming neighborhood stores into a scalable retail data network.
