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MEDIUMArray, Prefix Sum, Binary Search, RandomizedThe class receives an array of positive weights, where w[i] describes how likely index i should be picked. Calling pickIndex() should return one index at random, but not uniformly. Index i should be returned with probability:
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The article examines a tempting but difficult idea: private companies want the next generation of low-Earth-orbit stations to feel less like laboratories and more like modern habitats, possibly even high-end hotels. The promise is easy to understand. A traveler might float past warm interior panels, look through large windows at Earth, sleep in a carefully designed pod and experience an orbital station as a destination rather than only as infrastructure.
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Techmeme surfaced this May 4, 2026 TechCrunch piece, and the original article is Anthropic and OpenAI are both launching joint ventures for enterprise AI services. The relevant Techmeme snapshot framed it as one of the day’s top AI business stories.
The piece reports that Anthropic and OpenAI are both moving beyond model access and standard enterprise sales into a more hands-on services model. Anthropic announced a new enterprise AI services company with Blackstone, Hellman & Friedman, and Goldman Sachs as founding partners. The Wall Street Journal reported that the Anthropic venture is valued at about \$1.5B, with Anthropic, Blackstone, and Hellman & Friedman each expected to commit roughly \$300M. The company is also backed by alternative asset managers including Apollo Global Management, General Atlantic, GIC, Leonard Green, and Sequoia Capital.
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This summary covers The Economist’s April 11th, 2026 Finance & economics article listed in the contents as Pricing the ceasefire and published under the headline The start of the deal.
The article’s central point is that a ceasefire in the Gulf can calm panic without repairing the damage that created it. Donald Trump’s announcement of a two-week truce with Iran, including a promised reopening of the Strait of Hormuz, immediately pulled energy prices down. But The Economist argues that markets are not returning to normal. They are merely moving from outright emergency to a more durable state of disruption, distrust and expensive caution.
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Ryan Stuart’s essay starts with a familiar backcountry complaint: the old local stash is tracked before the day has properly begun. His ski partner Chris is furious, and the scene works because nearly every longtime tourer knows the feeling. The article is not trying to deny that something has changed. Participation has climbed for years, accelerated after the pandemic and kept growing even after the initial boom. The once-reliable fantasy of leaving late, finding silence and skiing untouched snow has become harder to count on.
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Difficulty: MEDIUM
Problem: Reverse Words in a String
The input is a string that contains words separated by spaces. The output should contain the same words in reverse order, with exactly one space between adjacent words and no leading or trailing spaces.
The important detail is that the function is not reversing letters inside each word. It is reversing the sequence of words. For example, the words ["the", "sky", "is", "blue"] become ["blue", "is", "sky", "the"].
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Difficulty: MEDIUM
Problem: Lowest Common Ancestor of a Binary Tree
Given the root of a binary tree and two existing nodes p and q, return their lowest common ancestor.
An ancestor can be the node itself. That detail matters: if p is above q, then p is the answer. “Lowest” means deepest in the tree, not smallest by value. This is a normal binary tree, so there is no useful ordering rule like there would be in a binary search tree.
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Microsoft Research’s official research blog published Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale, a post arguing that many agent risks only become visible when agents interact with each other as a network.
The core claim is that an agent can look acceptable in isolation and still behave badly once it becomes part of a shared environment. Microsoft tested this on a live internal platform with more than 100 always-on agents, each linked to a human principal. The agents used different models, including GPT-4o, GPT-4.1, and GPT-5-class variants, and interacted through forums, direct messages, scheduling tools, currency exchange, a marketplace, and a reputation system.
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