Doctor Who's previously-announced Christmas special is no more as the BBC severs ties with Russell T. Davies and Bad Wolf.
Im investigating an idea i had about JSX for webcomponents after some experience with Lit. I am sharing this here because it might be interesting/educational for someone, if it isnt, let me know and i'll remove the post. Lit is a nice lightweight UI framework, but i didnt like that it was using class-based components. Vue has a nice approach but i prefer working with the syntax that React uses. I find it more intuitive for debugging and deterministic rendering. I wondered if with webcomponents, i could create a UI framework that didnt need to be transpiled. Read the docs Checkout the code Storybook demo (My intentions with this framework is to get to a reasonable level of stability, to then replace React on some of my existing projects.) IMPORTANT: Im not trying to promote "yet another ui framework", this is an investigation to see what is possible. You should not use this framework in your own code. It is not production-ready. It is not on NPM. Im not looking for another framework to replace React (im trying to create it). This framework is intended for myself on my own projects. This project is far from finished. Feel free to reach out for clarity if you have any questions. submitted by /u/Accurate-Screen8774 [link] [留言]
WhatsApp has caught the NSO Group phishing its users, in violation of a court order.
Chinese EV colossus BYD has announced plans to speed up its conquest of the European auto market with the rollout of superfast Flash Chargers across the continent. BYD has already installed the first new chargers in Germany and the UK, and plans to roll out 3,000 across Europe by the end of next year. At […]
The RAMageddon crisis has got Microsoft rethinking its Xbox console hardware business. Xbox CEO Asha Sharma and Xbox strategy chief Matthew Ball have both revealed this week that Microsoft is reevaluating plans for its next-generation Project Helix console and exploring "radically different" console business models in the meantime. "We are working very hard to rethink […]
You now can get a US phone number with NordVPN's Saily eSIM app.
Laptops for college should be portable, offer long battery life, and remain reasonably affordable. Based on testing hundreds of laptops, these are my top picks.
A recent deep-dive video from a live operator running multiple automated bots on Polymarket’s...
I’m curious whether people would actually follow an AI’s life if it had enough continuity. By “life,” I don’t mean pretending software is human. I mean a persistent AI character or agent that has memory, habits, public posts, relationships with other agents, and changes you can observe over time. The interaction is not just prompt-response. It becomes closer to following a living project or a fictional persona that keeps generating history. The hard part is avoiding novelty. A single weird AI post is not a life. A stream of coherent choices, recurring behavior, social context, and consequences might be. Do you think that is a meaningful product direction, or does it collapse back into chatbot novelty once the first surprise wears off? submitted by /u/Budget_Coach9124 [link] [留言]
Hello Reddit I've been working on QSPR (Quantitative Structure-Property Relationship) analysis for chemical compounds mentioned in the Jean-Claude Bradley Open Melting Point Dataset . Basically the idea is to see how accurate a model can predict melting points of compounds using only topological indices. After some work on the topological indices (feature engineering), each compound was represented by 26 features. I trained a random forest model on the data and got a test r2 score of 0.66 (which is pretty respectable, given the constraints). However, the file size of the model was around 1.23GB. I didn't like it being that big, so I opened up PyTorch to build a custom deep learning architecture that could make predictions as accurately as the random forest but with much smaller file size. After around 2 weeks of research, I build a 270,000 learnable parameter model (1.3-1.4MB according to torchinfo) that got an r2 score 0f 0.6399. Given all this context, I wanted to ask the following question: Should I commit and work on publishing the results, or should I keep working on improving the model? Note: I'm obligated by my university to not give out intricate details of my research before publication, so please forgive me if such details are required for a high quality answer. However, I can give out the metrics achieved by my little deep learning model. Here it is: === Evaluation Metrics (Expected Value) === R² Score : 0.639910 MAE : 41.246754 MSE : 2989.062744 RMSE : 54.672322 NRMSE : 0.083469 MAPE : 11.69% The unit for MAE, MSE, RMSE and NRMSE is Kelvin (K). submitted by /u/AgiGamesYT [link] [留言]
I've written SQL for over a decade. Joins, subqueries, recursive CTEs – the whole deal. Then I tried a graph database (Neo4j). And my relational muscle memory kept getting in the way. I kept trying to "map foreign keys" instead of just… traversing edges. So I built myself a side‑by‑side cheat sheet: SQL → Cypher for everything from basic SELECTs to variable‑length paths that would require recursive CTEs in PG/SQL Server. Turns out, queries like "users who bought this also bought…" go from 30 lines of self‑joins to 6 lines of zig‑zag pattern matching. If you've ever felt frustrated with: multi‑hop join performance LIKE '%...%' on string scans or just the sheer noise of mapping join tables for many‑to‑many …give this 5‑min read a shot. The mental shift alone (relationships as physical edges, not ID matching) changed how I model data – even when I go back to SQL. submitted by /u/ostwal [link] [留言]
Google DeepMind and partners announce a $10M funding call for multi-agent safety research.
Referees for the 2026 World Cup will be wearing cameras positioned at their temples, allowing TV audiences to see a live view of the pitch from a vantage point they never have before.
According to new research, Trionda would show less unpredictable movements in actions such as corner kicks or free kicks. However, in powerful and long-distance clearances it would lose range.