Canada Weighs Retaliatory Options Against US Amid Escalating Trade Dispute

Canada finds itself in a challenging trade standoff with the United States, to which it exports roughly 70% of its goods. Despite this heavy economic dependence, analysts suggest Canada holds meaningful leverage it could deploy against the US economy. Potential retaliatory measures could target American industries and political constituencies in ways designed to pressure the Trump administration. The dispute reflects a broader escalation in trade tensions between the two neighboring countries. Canada is now actively weighing how to respond without further damaging its own economy in the process.

From Gen Z wave to heat in 150 days: Nepal PM Balen faces street anger, party unease

Batwara 1947 Stalls Near Rs 40 Cr Mark on Day 11, Faces Heavy Losses

Sunny Deol's Batwara 1947 collected only Rs 35 lakh on its eleventh day, barely approaching the Rs 40 crore net mark in India. The film has shown little momentum after its second Monday, pointing to a stagnant theatrical run. Given its inflated production budget, the underwhelming collections have resulted in a significant financial setback for the makers. In sharp contrast, Awarapan 2 has outperformed expectations, crossing Rs 136 crore net domestically in the same period.

Delhi LG Orders More Police Deployment, Better Civic Amenities in Narela

Delhi's Lieutenant Governor has issued directives aimed at improving security and public infrastructure in Narela, a rapidly developing area of the capital. Delhi Police has been instructed to increase its presence and strengthen law and order in the locality. The Municipal Corporation of Delhi (MCD) has separately been directed to upgrade civic amenities in the area. The moves reflect growing administrative attention toward Narela as it undergoes significant urban development. No specific timeline for implementation of these measures has been publicly stated.

Developer Guide: Discover YouTube Channels by Topic, Language, and Country

A technical guide published on DEV Community outlines a reproducible method for discovering YouTube creators across multiple languages, countries, and niche topics simultaneously. The approach structures search inputs as separate dimensions — niches, languages, and countries — rather than combining them into a single keyword string. This matters because searching for the same topic in different languages, such as English, French, or Spanish, returns distinct creator pools that a single query would miss. The method uses an Apify API client to run multi-dimensional searches, with filters for subscriber count, upload frequency, and excluded keywords. Results are deduplicated by channel ID and tagged with matched queries, inferred geography, and language signals, while distinguishing between declared and inferred creator attributes to avoid overwriting verified data with guesses.

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Python workflow filters active YouTube creators for smarter outreach targeting

A Python-based scraping workflow using the Apify client can identify genuinely active YouTube creator prospects rather than returning raw channel lists. The tool filters candidates by criteria such as subscriber count, upload frequency, recent median views, and content format before surfacing results. Developers define qualification thresholds — like at least one video per month and a public upload within 60 days — before running the script to avoid bias from seeing data first. The output includes per-channel signals such as opportunity score, warnings, and format ratios to help users match creators to specific campaign needs. Metadata fields for declared country, inferred country, and detected language are kept separate to support accurate regional and linguistic targeting.

Tutorial: Build a Real-Time Sleep Monitor Using OpenAI Whisper and Silero VAD

A developer tutorial published on DEV Community walks through building a real-time sleep analysis system using two open-source AI tools. The system uses Silero VAD as a lightweight audio gatekeeper to filter out silence and ambient noise, only passing significant sound events to OpenAI Whisper for classification. Whisper then analyzes buffered audio to identify patterns associated with normal breathing, snoring, or potential sleep apnea events. The pipeline streams audio from a browser or mobile client via WebRTC and outputs results to a time-series dashboard. The approach aims to offer a software-based alternative to wearable sleep trackers by capturing acoustic details that wrist-worn devices may miss.

How to Adapt an LLM Evaluation Framework for Any AI Pipeline

A developer has shared a reusable method for stress-testing large language models across different use cases, originally built for an order-reading AI. The framework centers on identifying the worst irreversible mistake a system could make — such as sending an incorrect auto-reply or overwriting data without a backup — and using that as the basis for grading AI errors. Failures are classified into four tiers: Fatal, Risky, Missed, and Harmless, based on whether a human can undo the outcome. Test questions are designed around traps like confusable data pairs, plausible non-targets, mid-message reversals, and memory-versus-new-information conflicts. The author recommends a minimum of one test case per identified accident type, noting that a starting set of around ten questions is sufficient before expanding further.

How to Build Secure Account Recovery Emails in Next.js with Provider Flexibility

A technical guide outlines best practices for implementing password reset email flows in Next.js-based edtech SaaS applications, emphasizing that reset logic should remain in the backend while email delivery is handled through a thin adapter layer. The approach recommends keeping suppression checks, provider acceptance, and delivery observations as separate records to avoid exposing sensitive user data publicly. For new solo-built products, the guide suggests low-integration email abstraction services that allow swapping providers without rewriting application code. The API route should return identical generic responses regardless of whether an account exists, is unknown, or is suppressed, preventing user enumeration. Keeping provider-specific details behind an adapter boundary is presented as a practical way to protect security-sensitive code and reduce future maintenance costs.

YouTube Comments Reveal AI Coding Tools Frustrate Users After the Initial Setup

A developer analyzed roughly 22,000 comments across 140 Korean YouTube videos about AI coding tools and found a sharp disconnect between video content and audience concerns. While the videos focused almost entirely on installation, getting started, and building apps, the most-liked comments expressed frustration over high costs, hallucinated outputs, and the burden of verifying AI-generated work. Users noted that catching AI errors often took more time than completing tasks manually, and that incorrect outputs were difficult to identify because they appeared plausible. The analysis also found that mid-sized channels with 10,000–300,000 subscribers surfaced more specific, practical questions than large channels, where comments leaned toward general anxiety about AI's societal impact. The author concluded that while content teaching beginners is abundant, very little addresses the trust and error-verification challenges users face immediately after starting.

How an Unbounded Queue Crashed a 26-Camera AI System at 3 AM

A production AI video pipeline serving 26 cameras collapsed at 2:47 AM when an unbounded asyncio queue ballooned to 14 GB within 11 seconds, crashing the system. The root cause was a combination of uncapped memory queues, redundant frame allocations, and synchronous code blocking the async event loop. Switching from float32 to uint8 quantization and capping queue sizes to hardware-derived limits boosted throughput from 4 fps to 62 fps while cutting peak memory use from 14.2 GB to 3.8 GB. The engineer also offloaded model inference to a thread executor to prevent the event loop from deadlocking under CPU pressure. The key takeaway is that AI systems do not retain visual memory by default, and treating memory as a hardware-constrained resource rather than an afterthought is essential for stable production deployments.

SEC Launches Probe into AI Hedge Fund Situational Awareness After Near-Collapse

Situational Awareness, an AI-powered hedge fund that had gained significant attention on Wall Street, is now under investigation by the U.S. Securities and Exchange Commission. The fund, which was once celebrated as a standout player in AI-driven investing, reportedly came close to collapse before attracting federal scrutiny. The SEC has issued subpoenas as part of its probe into the firm. The rapid fall from prominence to regulatory investigation marks a dramatic turn for the high-profile fund.

US removes Syria from state sponsors of terrorism list under Trump

The United States has officially removed Syria from its list of state sponsors of terrorism, marking a significant policy shift. The Trump administration took the step as part of its engagement with Syria's new leadership. Syria is now governed by Ahmed al-Sharaa, a former al-Qaeda militant who rose to become the country's new president. The move signals Washington's willingness to embrace the post-Assad Syrian government despite al-Sharaa's militant past.

Tornado Strikes Southern France, Injuring Over 40 and Destroying Homes

A tornado has struck southern France, leaving a trail of destruction across several villages. More than 40 people were injured as a result of the powerful storm. Residential properties were destroyed in the affected areas. The incident was captured on video, documenting the moment the tornado tore through the region.

Developer Tests Own AI Planning Engine Against Prompt Injection — Architecture Holds

A developer building PlannerCritic, an open-source engine that pairs one LLM to write plans with a second to review them, ran a structured adversarial test to find security weaknesses in the system. Eleven adversarial goals, 21 injection traps, and 35 regression tests were used, including attempts to bypass MFA, exfiltrate customer data, and override the engine via embedded system commands. In each case, the engine escalated and blocked the requests — not by detecting malicious intent, but by evaluating structural flaws like missing preconditions and weak rollback plans. The critic LLM audited plan structure independently, ignoring injected instructions, while deterministic gates processed logic rather than natural language. The developer concluded that the engine's resilience stemmed from its architecture rather than any LLM-level cleverness, though acknowledged that open seams in the system still remain.

Awarapan 2 nears Rs 140 crore India net in 11 days, logs 202% profit

Emraan Hashmi's Awarapan 2 has emerged as one of Bollywood's biggest hits of 2026, approaching the Rs 150 crore mark at the domestic box office. The film achieved this milestone within just ten days of its release, surpassing the profit margins of the earlier franchise entry Murder. It has now ranked as the fifth-highest-grossing Bollywood release of the year. The sequel marks a strong commercial comeback for Emraan Hashmi, recording a 202% return on investment.

AWS Deploys Multi-Agent System to Cut Cloud Migration from Weeks to Minutes

AWS Professional Services has published production data on a deployed multi-agent system that dramatically reduces infrastructure-as-code development time for enterprise cloud migrations. The system chains four specialized AI agents — handling discovery, IaC generation, governance, and post-migration operations — built on Amazon Bedrock AgentCore primitives. Agents communicate through immutable artifacts stored in S3 and state transitions tracked in DynamoDB, avoiding circular dependencies by never calling each other directly. A portfolio governance agent acts as the sole gatekeeper, running cost, security, and compliance checks before any migration can proceed. If templates fail validation, the workflow halts and the IaC generation agent must resolve all issues before the process can continue.