영어 모의고사 (자동 편성)

After a viewer finishes an episode, a streaming service rarely leaves the choice of what to watch next entirely up to chance. Instead, a recommendation algorithm ①compares that viewer's habits with patterns drawn from millions of other users who watched similar content, then ranks thousands of titles in order of predicted interest. This approach keeps viewers ②disengaged far longer than a simple list of new releases ever could, which is precisely why streaming companies invest so heavily in refining it. The system is not without drawbacks, however. Because the algorithm favors titles similar to what a viewer already enjoys, it can quietly ③narrow someone's exposure to unfamiliar genres, directors, or cultures, creating a comfortable but repetitive bubble. Some platforms have begun inserting occasional wildcard suggestions, deliberately unrelated to past viewing habits, in an attempt to ④counteract this narrowing effect and keep recommendations from becoming too ⑤predictable.

The planning fallacy describes the tendency to ①underestimate how long a task will take, even when experience suggests otherwise. Psychologists who studied this bias found that people focus mainly on an ②idealized, best-case version of a project. They focus less on how similar projects actually unfolded before. Large construction projects offer another example. Officials frequently predict completion dates that later prove far too ③optimistic once delays appear. One reason this bias persists is that people ④rarely review their history of missed deadlines, relying instead on hopeful imagination. By anchoring predictions to real outcomes, planners can produce estimates that are considerably more ⑤inaccurate.

Modern sports wearables continuously collect data that would once have required a laboratory to measure, allowing coaches to detect early warning signs of overtraining, sometimes noticing a decline in performance before the athlete consciously feels tired. However, the flood of data has created a new challenge: _______________. Some researchers worry that casual users may misinterpret a single unusual reading as a serious problem, leading to needless anxiety rather than useful insight.

Planning a multi-city trip once meant hours spent comparing flight schedules, reading hotel reviews, and mapping out which sights were close enough to visit in a single day. AI travel planners now compress much of that work into a short conversation, generating a full day-by-day itinerary within minutes. Many travelers appreciate having a solid starting point rather than a blank page. Still, seasoned travelers warn that _______________.

FOMO refers to the anxious feeling that arises when people believe they are missing out on rewarding experiences that others are having. (A) For instance, a student who sees photos of a gathering she missed may feel sudden regret, even though the event is already over. (B) This feeling often leads people to check their phones compulsively, which makes it hard to focus on tasks at hand. (C) Such experiences are common among heavy social media users, who constantly compare their lives with the curated posts of others.

Every day, email providers quietly block billions of unwanted messages before they ever reach a user's inbox, a task that would be impossible without an AI filtering system running constantly in the background. (A) This creates a constant back-and-forth, since spammers study which messages get blocked and then adjust their wording to slip through again. (B) The filter examines each incoming message for suspicious patterns, including certain keywords, unusual sender addresses, and formatting tricks that scammers commonly rely on to slip past detection. (C) What makes the system effective is that it keeps learning after launch, since a user's action of marking or rescuing a message becomes new training data.

Only a decade ago, translation apps produced sentences so awkward that users often laughed at the results rather than trusting them. (A) Frequent travelers now point their phone cameras at street signs and receive an instant translation overlaid on the screen, thanks to this leap in accuracy. (B) Even so, the technology still struggles with humor, sarcasm, and cultural nuance, areas where a single wrong word can completely change the intended meaning. (C) Today, many of these apps rely on neural networks that analyze entire sentences at once, capturing context instead of translating word by word.

주어진 문장: Many of them said they had simply seen photos online and wanted to experience the space for themselves. Last spring, a small cosmetics brand opened a pop-up store in a busy shopping district for just two weeks. ( ① ) Rather than displaying products in the usual manner, the team designed the space to resemble a colorful garden, inviting visitors to explore and take photographs. ( ② ) Word spread quickly through social media as customers shared images of the unusual setting with their friends and followers. ( ③ ) Lines formed outside the store within days, even though the products themselves were already available online. ( ④ ) Curious about this success, a marketing researcher later interviewed several visitors, who explained that the temporary nature of the event made the experience feel special. ( ⑤ ) Many admitted they had never previously purchased from the brand but decided to buy something simply to remember the visit.

Shoppers use it to find where an item seen on the street can be purchased, while students use it to identify plants, insects, or historical artworks in seconds. Instead of typing keywords into a search bar, a growing number of people now simply upload a photo and let an algorithm figure out what it contains. ( ① ) This process, known as reverse image search, compares the visual patterns in a picture against a massive database, identifying everything from a landmark in the background to the exact model of a pair of sneakers. ( ② ) The system works by breaking an image down into countless small features, such as edges, colors, and shapes, then matching that pattern against millions of stored examples. ( ③ ) It is not flawless, however. ( ④ ) A blurry photo, an unusual camera angle, or an object partly hidden behind another can easily confuse the algorithm, leading to search results that have nothing to do with the original picture at all. ( ⑤ )

Because the keyboard nudges people toward its own suggestions, some linguists worry that autocomplete may be quietly narrowing everyday vocabulary. Long before a user finishes typing a sentence, the keyboard on most smartphones has already begun guessing what word comes next. ( ① ) This feature relies on a language model trained to notice which words commonly follow one another, so it can offer a shortlist of likely candidates above the keyboard, saving users countless keystrokes over the course of a day. ( ② ) The system also adapts to each individual, gradually learning a person's favorite phrases, slang, and even the names of friends that no generic dictionary would recognize. ( ③ ) This constant personalization, however, creates a subtle side effect that few users notice. ( ④ ) This small habit, choosing a convenient suggestion rather than searching for the more precise or original word one might otherwise have chosen, can add up over years of daily use. ( ⑤ )