标签：#Science

Congress pauses the OMB's attempt to rewrite how research is funded.

This is Optimizer, a weekly newsletter sent from Verge senior reviewer Victoria Song that dissects and discusses the latest gizmos and potions that swear they're going to change your life. Opt in for Optimizer here. My mom was a dramatic woman prone to overreacting. When I was a snotty teen, I told her she needed […]

Why “Behind the Scenes” Isn’t Optional in Machine Learning There’s a version of Machine Learning that treats models as interchangeable black boxes: Import the library. Call .fit() . Tune a few hyperparameters. Ship it. It works — until it doesn’t. When a model fails, the real question isn’t just “How do I fix it?” It’s “Why is it failing in the first place?” The engineers who can answer that question are the ones who understand what’s happening beneath the API. Not because knowing the internals is intellectually satisfying — although it is — but because that understanding is what separates applying a model from engineering one . Knowing that Gradient Descent exists is not the same as understanding why it becomes preferable to closed-form solutions as problems scale. Knowing that Softmax outputs sum to one is not the same as understanding why that alone doesn’t make its outputs true probabilities. Knowing what a technique does is useful. Understanding why it works, when it works, and what assumptions it depends on is what allows you to adapt it when the problem doesn’t look like the textbook example. And you can’t meaningfully customize something you don’t understand. That’s the idea behind #MLUnboxed — a series where I’ll break down Machine Learning and Statistics concepts, including many that are already well documented, but without stripping away the mechanics that make them work. The goal isn’t to reinvent established ideas. It’s to understand them deeply enough to use them intelligently. This series is for people who already know the “what” and are ready to spend more time with the “why.” If that sounds like you, let’s get into it.

If you see a Prop 65 warning, don’t fret. Here’s what you need to know.

September is full of opportunities to expand your knowledge of the night sky. Mark your calendars.

"Black hole stars," making cookies from plastic, tiny sound-powered drones, and more.

Episode 1: Was in einer ZST-Datei passiertEpisode 1: Was in einer ZST-Datei passiertZST-Dateien begegnen uns immer häufiger bei großen Downloads, Softwarepaketen, Backups und Serverdaten. Sie sind oft deutlich kleiner als die ursprünglichen Dateien und lassen sich trotzdem sehr schnell wieder entpacken. Doch wie funktioniert das? Warum werden Dateien komprimiert? Eine Datei besteht aus Daten. Je mehr Daten sie enthält, desto mehr Speicherplatz wird benötigt und desto länger dauert ihre Übertragung. Kompression versucht, dieselben Informationen mit weniger Daten darzustellen. Beim späteren Entpacken muss daraus wieder exakt die ursprüngliche Datei entstehen. Nach dem Entpacken ist die Datei Bit für Bit identisch mit dem Original. Es wird nichts weggelassen und nichts vereinfacht. Wiederholungen benötigen unnötig viel Platz Betrachten wir diesen Satz: Kleine Katzen kuscheln auf kleinen Kissen, junge Katzen kuscheln auf bunten Kissen und alte Katzen kuscheln auf weichen Kissen.Die folgenden Teile kommen mehrfach vor: A = Katzen kuscheln auf B = KissenWenn wir die wiederkehrenden Textteile durch die Variablen A und B ersetzen, können wir den Satz kürzer darstellen: Kleine A kleinen B, junge A bunten B und alte A weichen B.Damit ist der Text noch nicht vollständig. Zusätzlich müssen wir speichern, wofür A und B stehen: A = Katzen kuscheln auf B = KissenAus diesen Informationen lässt sich der ursprüngliche Satz wiederherstellen. Jedes A wird durch Katzen kuscheln auf und jedes B durch Kissen ersetzt. Das ist bereits die grundlegende Idee der verlustfreien Kompression: Wiederkehrende Daten werden nicht jedes Mal vollständig gespeichert. Stattdessen werden sie einmal gespeichert und anschließend durch kürzere Verweise ersetzt. ### Zstandard verwendet keine Variablen Unsere Variablen A und B dienen nur dazu, das Prinzip verständlich zu machen. Zstandard versteht weder Wörter noch Sätze. Es weiß nicht, was Katzen oder Kissen sind. Für das Programm besteht eine Datei lediglich

NASA's cost estimate for SR-1 Freedom is $2.1 billion, but that doesn't include the helicopters.

How an alliance of tech startups, MAHA operatives, and actual medical experts made millennial women the new face of hormone therapy.

Dyson is once again expanding its line of personal care products with a device that focuses on your teeth instead of your hair. As the name implies, the $499 CameraJet is the first electric toothbrush to incorporate a camera into the brush head. Available starting today in ceramic blue or ceramic pink color options, it […]

Every developer writes code that "just works" thousands of times without thinking about what happens between hitting save and seeing output on screen. This article pulls back that curtain. We're going to walk through, in real depth, how source code — plain text you typed — becomes a running program, covering lexing, parsing, abstract syntax trees, semantic analysis, and the actual difference between interpretation and compilation (including why that difference is far blurrier than most explanations make it sound). This is one of those topics where understanding the fundamentals pays off across your entire career — it changes how you read error messages, how you reason about performance, and how you evaluate new languages and tools. 1. The Big Picture: Two Broad Strategies At the highest level, there are two strategies for running code: Compilation — translate the entire source program into another form (often machine code, but not always) before running it. The translation and the execution are separate steps. Interpretation — read and execute the source program directly, translating and running it (roughly) simultaneously, statement by statement. In practice, almost no real system is purely one or the other. Python "compiles" your source to bytecode before interpreting the bytecode. Java compiles to bytecode, then a JIT (Just-In-Time) compiler compiles hot paths of that bytecode to native machine code while the program runs . JavaScript engines like V8 do something similar. The clean binary of "compiled vs. interpreted" that gets taught early on is really a spectrum, and most production language runtimes today live somewhere in the middle. But to understand any point on that spectrum, you need to understand the pipeline every one of these systems shares. Let's build it up stage by stage. 2. Stage One: Lexical Analysis (Lexing / Tokenizing) The first thing that has to happen to your source code is the least glamorous: it gets chopped into pieces. Source code, to a c

Finding reveals an overlooked way that water can damage surfaces.

“One more warning sign here of what we're facing in a warmer world.”

"We would need over half a million 4K TVs to fully display the single Roman image from our largest survey."

While Trump administration cuts have contributed to the epidemic of foodborne illnesses this summer, there are also deeper issues that make the American food supply chain susceptible to parasites and bacteria outbreaks.

If you've done LeetCode's Design HashMap , you've implemented put , get , and remove . What that exercise usually skips is the part that actually breaks in production: what happens when someone mutates the map while another piece of code is iterating over it. I ran into this directly while building MyHashMap , a from-scratch single-threaded HashMap (separate chaining, resize on load factor). Getting put / get / remove right was the easy 80%. Getting entrySet().iterator() to correctly detect concurrent mutation — including the case where a second, completely separate iterator is the one that should notice — took three wrong turns before landing on the pattern the JDK actually uses. The problem, concretely Iterator < Entry < K , V >> it = map . entrySet (). iterator (); it . next (); map . put ( someNewKey , someValue ); // structural change, mid-iteration it . next (); // ??? — undefined behavior if we don't guard against this Without a guard, next() might return a stale entry, skip entries entirely, or throw an unrelated exception depending on internal bucket-array state. Java's real collections handle this with ConcurrentModificationException (CME) — but the interesting part isn't the exception, it's the mechanism that detects when to throw it. First idea: a boolean "dirty" flag Obvious first attempt: a boolean modified field on the map, flipped to true on any put / remove , checked by the iterator. This works for exactly one iterator. It falls apart the moment two iterators are alive at once: Iterator A calls next() , sees modified == false , proceeds. Something else mutates the map. modified flips to true . Iterator B — created after that mutation — checks the same shared modified flag, sees true , and incorrectly throws, even though nothing has changed since B was created. A single shared boolean can't represent "changed since this specific iterator was created" for more than one iterator at a time. Resetting it on read doesn't help either — now the other iterat

After funding struggles and a name change, the Nancy Grace Roman Space Telescope has been successfully launched. It will now make a three-month, one-million-mile journey to its orbit at the second Sun-Earth Lagrange point (L2) beyond the Moon. From this vantage point, Roman will conduct an unprecedented survey of the universe. Its field of view […]

As I have started my Data analysis and science curriculum, Microsoft excel is the first tool we have learnt. In my life before getting into this course, I used to underestimate the power of Microsoft excel. Definition of Microsoft Excel This is a spreadsheet software developed by Microsoft that allows you to collect, organize, analyze, calculate and visualize data efficiently. The Excel Interface When open Microsoft excel, you first an interface made of various tools We start with the ribbon. The ribbon contains a toolbar that contains all the commands organized into tabs such, Home, Insert, Page Layout , Formulas, Charts and Data There is a formula Bar that content and formulas appear. In addition, we have Quick access toolbar that contains icons for Save, Undo and Redo. A row is a horizontal line of cells that runs from left to right across the grid while a column is a vertical line of cells that runs from top to bottom down the grid. A cell is where row and column intersect and form a single box. Cleaning A Dirty Dataset As we learnt about Data cleaning with Excel on dataset that was a bit very disorganized. We first started with sorting that data which basically means arranging the data in specific order. The sorting can be Text sorting which is A-Z or Z-A, Number sorting which is from largest to small and vice versa, Date sorting which is Oldest to Newest and vice vera. Next was filtering which allows you display data that meet certain criteria and hide the rest temporarily. Next, Number formatting changes how numbers display without altering their actual value. Conditional Formatting highlights cells automatically based on rules or criteria, helping spot trends or outliers. The dataset we were cleaning had a lot of duplicates, so it was important for us to remove the duplicates. Text functions for Cleaning Data Text functions are used to remove extra spaces , standardize text ,extract parts of strings or find and replace sub strings. text functions include UPP

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The discovery redefines how large atoms need to be to produce the extreme state of matter found in the early universe.