#machine-learning

#machine-learning

Currently I'm working on a virtue ethics approach to the issue of whether examples of moral badness should be allowed in machine learning with artificial moral agents. Motivating the side that we should do so is of special interest to me, with a focus on actions that are not wrong yet worse than morally indifferent.

PolarQuant is doing most of the compression, but the second step cleans up the rough spots. Google proposes smoothing that out with a technique called Quantized Johnson-Lindenstrauss (QJL).

While humans have assembled a lot of weather data, flash floods are too short-lived and localized to be measured comprehensively, the way the temperature or even river flows are monitored over time. That data gap means that deep learning models, which are increasingly capable of forecasting the weather, aren't able to predict flash floods.

A maggot's age and species can give essential information to forensic entomologists investigating murders. Combing through these fly larvae, investigators can potentially learn when and where a crime happened, whether the body has been moved or whether toxins were involved. For example, blowflies are among the earliest insect colonizers of corpses; they typically sniff out and lay eggs on a dead body within minutes to hours.

The robotics industry, for now, faces the biggest challenge in teaching robots to operate in the messy real world. The unstructured environment means robots need massive amounts of data to learn. Gathering and structuring that data is the costliest thing in robotics and perhaps the biggest impediment, slowing the entire development process.

This March, we're bringing you a curated lineup of the most exciting Scala and AI events from around the world. Highlights include SCALAR Conference in Warsaw, NVIDIA GTC, QCon London, and SXSW's tech tracks, offering everything from deep technical talks to hands-on AI and functional programming sessions. Whether you're sharpening your Scala skills, exploring AI in production, or connecting with global developers, this month's edition has something for everyone. Don't miss the chance to learn, network, and level up your expertise

Before treatment began, participants underwent neuroimaging. Instead of relying on a single modality, the researchers fused structural connectivity (how regions are physically wired) with functional connectivity (how regions co-activate at rest). The goal was not to throw every possible feature at a black box, but to learn a constrained pattern-what the authors call structure-function "covariation"-that carries the most predictive signal for outcome. In other words, the model tries to find the smallest set of connections that meaningfully forecasts symptom change.

For most of modern finance, one number has quietly dictated who gets ahead and who gets left out: the credit score. It was a breakthrough when it arrived in the 1950s, becoming an elegant shortcut for a complex decision. But shortcuts age. And in a world driven by data, digital behavior, and real-time signals, the score is increasingly misaligned with how people actually live and manage money.

At launch, it's only available for a limited number of tracks, but there are plans to expand it. Bits of trivia and background about songs are presented as short, swipeable cards with information harvested from "third-party sources." The text is generated using machine learning, but Spotify at least cites its sources on the About the Song cards. The company declined to say whether the feature would eventually be available to free users or when it might leave beta.

Researchers at the University of Cambridge's Political Psychology Lab tracked shifts in Americans' views across nearly four decades and found that divisions were broadly stable through the 1990s and early 2000s, before rising steadily from 2008 onward. Using more than 35,000 responses from the American National Election Studies between 1988 and 2024, they estimate that issue polarization has increased 64% since the late 1980s, with almost all of that change occurring after 2008.

They were trying to get to the bottom of how to diminish catalogue distribution without having a negative impact on store and online sales. They were also keen to define the geographic areas where digital content would work best and how to profile those areas to classify digital purchase behaviour. Together with Analytic Partners they were able to uncover opportunities to eliminate 22% of catalogues with negligible sales impact and increasing digital support in high-performing topologies, preserving€ 294 million in sales.

A new PhD track is being added to the Walter S. and Lucienne Driskill Graduate Program in Life Sciences ( DGP) for the 2026 application cycle, to enhance student learning and build community around computational biology and bioinformatics at Feinberg. The computational biology and bioinformatics (CBB) track in the graduate program will prepare students through coursework and lectures to use modern computational approaches, including machine learning and artificial intelligence, to extract biological insight from large-scale datasets to address complex biological problems.

Strava is using "Machine Learning" (ML) models to help clean up logged riding errors, intentional or not. James, an engineer at Strava, explained in the post that the recent crackdowns were threefold. First, they introduced a new ML model, specifically aimed at catching e-bikes. This "Enhanced E-Bike Detection" flags and removes activities logged as a normal ride, but that were clearly recorded with electric assist.

The NFL is no stranger to innovation. Over the years, teams have adopted new strategies, technologies, and data-driven approaches to stay ahead of the competition. One of the most significant advancements in recent years is the rise of sophisticated analytics and modeling. These tools have become essential for teams seeking to improve player performance, game strategy, and overall team development.

Rainbow Weather has raised $5.5 million in seed funding to push weather forecasting further into the short-term, high-precision territory it believes the industry still underserves. The Warsaw-based climate tech startup focuses on hyperlocal, minute-by-minute forecasts, zeroing in on what happens in the next few hours rather than days out. The round was backed by a syndicate of investors, including Yuri Gurski, founder of Flo Health, one of Europe's best-known consumer tech unicorns.

Paramount Skydance is planning to add a heavy dose of short-form video to its flagship streaming service, according to internal presentations and emails viewed by Business Insider. Dan Reich, the head of global product and design for Paramount+, emailed fellow executives in mid-January, asking to set up a meeting with Paramount product chief Dane Glasgow to discuss "Short Form Clips." "We are trying to figure out how to jump-start efforts to get a million clips into our Short Form UX as quickly as possible," Reich wrote in an email.

Warsaw, Poland 26 January 2026 - Rainbow Weather has raised $5.5 million in seed funding to push weather forecasting further into the short-term, high-precision territory it believes the industry still underserves. The Warsaw-based climate tech startup focuses on hyperlocal, minute-by-minute forecasts, zeroing in on what happens in the next few hours rather than days out. The round was backed by a syndicate of investors, including Yuri Gurski, founder of Flo Health, one of Europe's best-known consumer tech unicorns.

I'm thrilled to announce that I'm stepping up as Probabl 's CSO (Chief Science Officer) to supercharge scikit-learn and its ecosystem, pursuing my dreams of tools that help go from data to impact. Scikit-learn, a central tool Scikit-learn is central to data-scientists' work: it is the most used machine-learning package. It has grown over more than a decade, supported by volunteers' time, donations, and grant funding, with a central role of Inria.

Finding the time to create great content for your users is an essential part of growing your publishing business,

XRP ( ) sits near $1.90 with sentiment hitting levels not seen since before its last major rally. The Crypto Fear & Greed Index dropped to 24 in late December 2025-extreme fear territory-while analytics platform Santiment shows bearish commentary running 20-30% higher than November 2025's already-subdued averages. These extremes have appeared before XRP rallies that delivered over 1,000% gains. The pattern matters because sentiment analysis isn't guesswork-machine learning models achieve 70-91% accuracy predicting crypto price movements

An AI-powered appointments system developed by UK health-tech company DrDoctor could save the NHS up to £300 million a year by dramatically reducing missed hospital appointments, one of the health service's most persistent and costly problems. Missed outpatient appointments cost the NHS close to £1 billion annually, tying up staff time, wasting clinical capacity and lengthening waiting lists. DrDoctor believes its new AI platform, Smart Centre, can cut non-attendance rates by around 30% by predicting which patients are most likely not to turn up and adjusting clinic capacity in advance.

For instance, when a user watches a romantic comedy on Netflix, the system identifies similar titles liked by others with comparable viewing habits. On Spotify, listening to a few indie tracks might prompt the algorithm to suggest playlists featuring similar artists. These systems continuously learn from user activity, refining their precision over time.

Professor Xiaoxiang Zhu, who leads the project and is the chair of data science in Earth observation at TUM, says the real achievement is that the new map is a three‑dimensional picture of how much space people actually inhabit. "3D building information provides a much more accurate picture of urbanization and poverty than traditional 2D maps," she explains. With 3D models "we see not only the footprint but also the volume of each building."