Happy New Year, world! As a New Year gift, HackerNoon brings you the grandest developer hackathon of 2026. The internet is overflowing with software that looks impressive, sounds intelligent, and quietly fails to help anyone. We’ve normalized pitch decks for products that don’t exist, AI demos with no users, and MVPs that launch with applause and vanish without a trace. Meanwhile, people still need tools that work. So we’re doing something different. Enters the Proof of Usefulness Hackathon! From […]

Ver mais

In parts #1 and #2 of the “Outliers Detection in PySpark” series, I talked about Anomaly Detection, Outliers Detection and the interquartile range (boxplot) method. In this third and last part, I will talk about how one can use the popular K-means clustering algorithm to detect outliers. K-means K-means is one of the easiest and most popular unsupervised algorithms in Machine Learning for Clustering.

Ver mais

The last few weeks we heard from several excellent guests, including Selina Tobaccowala from Survey Monkey, Patrick Collison from Stripe, Nirav Tolia from Nextdoor, Shishir Mehrotra from Google, and Elizabeth Holmes from Theranos. The topic of discussion was scaling beyond the tribe phase to the Village/City phases of a company. My favorite among these was the session with Patrick (video), which I found to be rich with interesting points and mental models. In what follows I will try to […]

Ver mais

arXiv:2601.00102v1 Announce Type: new Abstract: Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a highly effective optimization technique. A primary challenge when applying CMA-ES in high dimensionality is sampling from a multivariate normal distribution with an arbitrary covariance matrix, which involves its decomposition. The cubic complexity of this process is the main obstacle to applying CMA-ES in highdimensional spaces. We introduce a version of CMA-ES that uses no covariance matrix at all. In the proposed matrix-free CMA-ES, an archive […]

Ver mais

arXiv:2601.04286v1 Announce Type: new Abstract: Objective: Stroke is one of the leading causes of disabilities. One promising approach is to extend the rehabilitation with self-initiated robot-assisted movement therapy. To enable this, it is required to detect the patient’s intention to move to trigger the assistance of a robotic device. This intention to move can be detected from human surface electroencephalography (EEG) signals; however, it is particularly challenging to decode when classifications are performed online and asynchronously. In this […]

Ver mais

Plant disease diagnosis is essential to farmers’ management choices because plant diseases frequently lower crop yield and product quality. For harvests to flourish and agricultural productivity to boost, grape leaf disease detection is important. The plant disease dataset contains grape leaf diseases total of 9,032 images of four classes, among them three classes are leaf diseases, and the other one is healthy leaves. After rigorous pre-processing dataset was split (70% training, 20% validation, 10% testing), and two pre-trained […]

Ver mais

EFF has, for many years, raised the alarm about the proliferation of stalkerware—commercially-available apps designed to be installed covertly on another person’s device and exfiltrate data from that device without their knowledge. In particular, we have urged the makers of anti-virus products for Android phones to improve their detection of stalkerware and call it out explicitly to users when it is found. In 2020  and 2021, AV Comparatives ran tests to see how well the most popular anti-virus […]

Ver mais

The second birthday of ChatGPT was only a little over a month ago, and now we have transitioned into the next paradigm of models that can do complex reasoning. New years get people in a reflective mood, and I wanted to share some personal thoughts about how it has gone so far, and some of the things I’ve learned along the way. As we get closer to AGI, it feels like an important time to look at the […]

Ver mais