3 Nuclear Startups Hit a Big Milestone. Why It Matters—and Why It Doesn’t
The companies’ Fourth of July plans include celebrating new reactor designs coming online. But there’s still a long way to go before they deliver energy at a meaningful scale.
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The companies’ Fourth of July plans include celebrating new reactor designs coming online. But there’s still a long way to go before they deliver energy at a meaningful scale.
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. Europe is melting, the eastern US is currently trapped in a "heat dome," the Midwest has the corn sweats to […]
At the event "The Briefing: AI for Science" earlier this week, Anthropic announced Claude Science, a new "AI workbench for scientists" that pulls fragmented tools and datasets into one environment, and generates figures and visuals. Anthropic, already dominating the industry with its popular coding tools and powerful AI models, framed the launch around what it […]
NASA awarded Rocket Lab deals for three dedicated launches using the company's Electron rocket.
Midjourney has shown more of its futuristic medical scanner. It still hasn't shown much proof it works. The AI startup, best known for generating images, released a behind-the-scenes video of its dunk-tank ultrasound scanner, which it plans to deploy in spas and hopes will transform medicine with cheap, detailed, radiation-free imaging. The nearly 20-minute tour […]
ZYN nicotine pouches, the FDA found, can be advertised as a less-harmful option for adult smokers. But quitting all tobacco and nicotine products remains the best idea.
The Shop on the Corner: How I Learned System Design Without Building Amazon Nephew asks his uncle — 10 years deep into building large-scale systems — to explain "system design," and all the scary jargon that comes with it. Uncle refuses to start with the jargon. Instead: "Forget servers and databases for a minute. Just imagine you're running a small shop." What follows is a thought experiment, built one problem at a time — no cloud bills, no fancy stack, just a counter, a storeroom, and a lot of common sense. Part 1: The Counter — Your First "API" 👦 Nephew: Uncle, everyone at work keeps throwing around terms — load balancer, cache, index, sharding. I nod along, but I don't actually get any of it. 👨🦳 Uncle: Then don't start there. Close your eyes for a second and forget servers exist. Suppose — just suppose — you're running a small shop. One counter, one small storeroom at the back. A customer walks up and asks for something. What do you do? 👦 Nephew: I'd walk into the storeroom, find it, walk back, hand it over. 👨🦳 Uncle: That's it. That's the entire job of a server handling a request. You don't need to understand Amazon's warehouse to understand Amazon's problems. You need a counter and a storeroom, imagined clearly, and the patience to grow them one honest problem at a time. Here's the shape of what you just described, whether you realized it or not: 🧍 Customer 🧑 You (Counter) 📦 Storeroom (Database) | | | |── "Got Maggi?" ───────>| | | |──── Walk in, search ────────>| | |<─────── Found it ────────────| |<── Hand it over, ──────| | | take payment | | 👨🦳 Uncle: One customer, one request, one trip to the storeroom, one response. This is fine. This is correct , even, for a shop with five customers a day. Don't let anyone tell you a single counter isn't "scalable" — a shop that small doesn't need two counters, it needs someone to stop worrying and open the shutter. 👦 Nephew: So this is just... a server handling one request at a time? 👨🦳 Uncle: Exactly. Customer sen
leetcode.com Problem Statement Given the root of a binary tree, return its preorder traversal. Preorder Traversal follows: Root ↓ Left ↓ Right Brute Force Intuition In an interview, you can explain it like this: Visit the current node first, then recursively traverse the left subtree followed by the right subtree. Recursion naturally follows the preorder sequence. Complexity Time Complexity: O(N) Space Complexity: O(H) Where: N = Number of Nodes H = Height of Tree Recursive Code class Solution { public List < Integer > preorderTraversal ( TreeNode root ) { List < Integer > ans = new ArrayList <>(); preorder ( root , ans ); return ans ; } private void preorder ( TreeNode root , List < Integer > ans ) { if ( root == null ) return ; ans . add ( root . val ); preorder ( root . left , ans ); preorder ( root . right , ans ); } } Moving Towards the Optimal Iterative Approach Instead of recursion, we can use a stack. Since preorder visits: Root ↓ Left ↓ Right we should process the root immediately. To ensure the left subtree is processed first, push the right child before the left child . Pattern Recognition Whenever you see: Preorder Traversal Simulate Recursion Think: Stack Key Observation Stack follows: LIFO To visit: Left First push: Right First ↓ Left Second so that left is popped first. Optimal Java Solution class Solution { public List < Integer > preorderTraversal ( TreeNode root ) { List < Integer > ans = new ArrayList <>(); if ( root == null ) return ans ; Stack < TreeNode > st = new Stack <>(); st . push ( root ); while (! st . isEmpty ()) { TreeNode node = st . pop (); ans . add ( node . val ); if ( node . right != null ) st . push ( node . right ); if ( node . left != null ) st . push ( node . left ); } return ans ; } } Dry Run 1 / \ 2 3 / \ 4 5 Stack: 1 Visit: 1 Push: 3 2 Visit: 2 Push: 5 4 Traversal: 1 ↓ 2 ↓ 4 ↓ 5 ↓ 3 Answer: [1,2,4,5,3] Why Stack Works? A stack processes the most recently added node first. By pushing: Right Child ↓ Left Child the left child
It only works for a few divisions thanks to a lot of added materials.
Slate is the latest automaker to transition to lower-cost batteries perfected in China, driven in part by the repeal of EV tax credits that required materials to be sourced domestically.
Your comments on a dangerous rule putting politicals in charge of science can matter.
Amazon says it now has enough satellites operating in low-Earth orbit to light up its Starlink internet competitor. With last night's launch, Amazon Leo has 396 satellites deployed, which is "enough to support continuous service across initial latitudes," according to Chris Weber, VP heading up business and product for Amazon Leo. That puts the company […]
Long hours outdoors, day drinking, and World Cup matches are among the factors raising the risks of heat-related illness, as hot weather spreads across the eastern US.
Fans’ euphoric reactions to the Mexican national team’s recent victory in the 2026 World Cup caused a series of unusual vibrations that were detected by seismic warning systems.
1. The Problem It Solves Logistic Regression is used when the outcome is a category rather than a number . Most commonly, it's used for binary classification , where the answer is either Yes or No , True or False , or 1 or 0 . Typical business problems include: Will a customer churn? Is this transaction fraudulent? Will a customer click an ad? Will a loan default? Is an email spam? Will a machine fail in the next 24 hours? Unlike Linear Regression, we're not trying to predict a continuous value. Instead, we're predicting the probability that an event belongs to a particular class. For example: A customer may have an 82% probability of churning . The business can then decide whether that probability is high enough to trigger an intervention. 2. Core Intuition Imagine you're trying to predict whether a customer will cancel their subscription. Suppose the only feature you have is how many times they opened your app this month. If you use a straight line like Linear Regression, the predictions quickly become unrealistic. A very active customer might end up with a -20% chance of churn . A completely inactive customer could end up with 140% . Probabilities obviously can't work like that. To fix this, Logistic Regression takes the linear equation and passes it through a mathematical function called the Sigmoid Function . Instead of producing a straight line, it creates an S-shaped curve . No matter how large or small the input becomes, the output always stays between 0 and 1 . That makes it perfect for probability estimation. 3. The Mathematical Model The model first calculates a linear score. Instead of using that score directly, it passes it through the Sigmoid function. Where: z = linear score p̂ = predicted probability The final output is always between 0 and 1 . For example: 0.08 → Very unlikely 0.32 → Low risk 0.65 → Moderate risk 0.94 → Very high probability Businesses can then choose a decision threshold. For example: Probability ≥ 0.50 → Predict Churn Probability
Elon Musk says a report about a SpaceX AI phone prototype is "utterly false." The report, published on Wednesday by The Wall Street Journal, says SpaceX showed off a "handset-like prototype" to some investors before launching its record-breaking initial public offering in June. The device was "slimmer than an iPhone," and they were told it […]
Record home battery installations unlock options for grids—and AI data centers.
An optimal ratio of 10-15 grams of larvae per gram of specimen minimized cleaning time with no bone damage.
Penalty kicks are already proving critical to big wins at this year’s World Cup. But the advantage in penalty kicks has more to do with psychological effects than who kicks first.
Planning a Fourth of July getaway? Use less gas—and cut your emissions—by easing up on the pedal.