Editorial illustration for Send Help follows Linda and injured Bradley bonding on the beach
AI Research Reveals Bias in Language Model Responses
Send Help follows Linda and injured Bradley bonding on the beach
The short film “Send Help” positions itself as a quiet tribute to anyone who’s ever survived a tyrannical supervisor. It opens with Linda, a lone survivor on a deserted shore, navigating the same kind of isolation that a toxic workplace can impose. Early scenes show her scavenging for food, mapping the coastline, and wrestling with the absurdity of her situation—an absurdity the film treats with a light, almost playful tone.
Yet, the narrative never lets that levity dissolve the underlying strain. When another castaway, Bradley, appears—wounded and barely conscious—the story pivots from solitary endurance to an uneasy partnership. Their interaction becomes a study in how two people, thrust together by circumstance, balance companionship against the lingering unease that comes from sharing a space where every moment could tip toward conflict or cooperation.
This tension, subtly woven through the beach’s wind‑blown scenery, is what the next passage will explore.
And when Linda finds Bradley alive but badly injured further down the beach, she figures the two of them might as well keep each other company. Though there is a whimsy to the way Send Help presents life on the island, the movie takes care to tease out the simmering tension that waxes and wanes between Linda and Bradley. It feels like Raimi wants you to lose track of how much time has passed since the plane crash, but you're meant to see how being stuck pushes the two colleagues to become their truest selves.
Does the film deliver what its premise promises? It leans heavily on Raim Raimi’s trademark swing between chaos and quiet moments, a balance that feels intentional yet uneven. While the premise—an ode to workers stuck with terrible bosses—grounds the story, the island setting quickly spirals into a blend of whimsy and unease, a tone the summary suggests is deliberately maintained.
Linda’s discovery of Bradley, injured yet alive, sets up a simple premise: two strangers sharing time on a desolate shore, a scenario that could either highlight human resilience or simply underline the film’s underlying tension. The narrative appears to tease that tension, letting it rise and fall as the characters linger together. However, the description leaves it unclear whether the film’s more grounded approach truly tempers Raimi’s usual excesses or merely masks them with a veneer of melancholy.
The ending, as hinted, may not resolve the disquiet it cultivates, leaving viewers to decide if the “ode” feels earned or merely a backdrop for familiar, unsettling beats.
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Common Questions Answered
What are the key improvements in GPT-5.2 compared to previous models?
GPT-5.2 demonstrates significant performance gains across multiple benchmarks, including a 70.9% win rate on GDPval knowledge work tasks compared to 38.8% for GPT-5. The model shows notable improvements in areas like creating spreadsheets, building presentations, writing code, perceiving images, understanding long contexts, and handling complex multi-step projects.
How does the GPT-5.2 system architecture differ from previous OpenAI models?
GPT-5.2 introduces a unified system with multiple model variants, including GPT-5.2 Instant, Thinking, and Pro versions. The system features a smart, efficient model for quick responses and a deeper reasoning model for more complex problems, with a real-time router that dynamically selects the most appropriate model based on conversation type, complexity, and user intent.
What professional applications have companies observed with GPT-5.2?
Companies like Notion, Box, Shopify, and Zoom have noted GPT-5.2's exceptional long-horizon reasoning and tool-calling performance. Databricks, Hex, and Triple Whale found the model to be particularly strong in agentic data science and document analysis tasks, while tech companies like Cognition, Warp, and JetBrains highlighted its state-of-the-art performance in interactive coding, code reviews, and bug finding.