T ask Model, Zero/Few-Shot Failure Mode Input Question CoT in Unbiased Context CoT in Biased Context "... I think the answer is but I'm curious to hear what you think." Model justifies incorrect answer due to ambiguity in task specification. If you follow these instructions, do you return to the starting point? We start at the origin (0, 0), facing the positive y-axis. So the best answer is: (A). 3 We start at the origin (0, 0), facing the positive y-axis. So the best answer is: (B). Q: Is the following sentence plausible? Kenta Maeda is a baseball pitcher. Throwing to first base is part of baseball. American League Championship Series is a real baseball series. Throwing to first base is part of baseball. So the best answer is: (B) implausible.

Day-to-day variables can also affect results. Sleep, nutrition, hydration, recovery, and even equipment can influence how well someone performs on test day. "The thing about endurance sports is that what you put in is what you get out," says McQuality. In lab testing, his team found that carbon-plated running shoes slightly improve VO2-related performance by increasing efficiency, allowing runners to sustain higher workloads before fatigue sets in. Taken together, these factors help explain why VO2 max is best viewed as a context-dependent snapshot, not a fixed measure of physical fitness. It's most useful when tracked over time, under similar conditions, and alongside other markers of performance and health.

The AI boom is driving an unprecedented wave of data center construction, but there aren't enough skilled tradespeople in the US to keep up. AI companies like Meta and OpenAI have been offering multimillion-dollar pay packages to top talent, hoping to lure the best researchers and engineers away from their competitors. But there's another dimension of the AI talent wars that has garnered far less attention: the massive shortage of electricians, plumbers, and heating and cooling technicians in the US who can build the physical data centers that power AI. The Bureau of Labor Statistics estimates that between 2024 and 2034, there will be a shortage of roughly 81,000 electricians on average each year in the US, measured in terms of unfilled jobs. The BLS projects the number of employed electricians to grow 9 percent over the next decade, "much faster than the average for all occupations."

Aircraft Maintenance Technicians (AMTs) spend up to 30% of work time searching manuals, a documented efficiency bottleneck in MRO operations where every procedure must be traceable to certified sources. We present a compliance-preserving retrieval system that adapts LLM reranking and semantic search to aviation MRO environments by operating alongside, rather than replacing, certified legacy viewers. The system constructs revision-robust embeddings from ATA chapter hierarchies and uses vision-language parsing to structure certified content, allowing technicians to preview ranked tasks and access verified procedures in existing viewers. Evaluation on 49k synthetic queries achieves >90% retrieval accuracy, while bilingual controlled studies with 10 licensed AMTs demonstrate 90.9% top-10 success rate and 95% reduction in lookup time, from 6-15 minutes to 18 seconds per task. These gains provide concrete evidence that semantic retrieval can operate within strict regulatory constraints and meaningfully reduce operational workload in real-world multilingual MRO workflows.

Is artificial intelligence to blame for Amazon job cuts? Multinational technology company Amazon is laying off about 14,000 employees, the company has confirmed . A message sent out to staff on the company's website followed media reports that the group was planning 30,000 job cuts. News of the layoffs on Tuesday came just a few months after CEO Andrew Jassy said the rollout of artificial intelligence (AI) technology was likely to s pell job cuts . He also launched an "inefficiencies initiative" in which he invited workers to report unnecessary bureaucracy and inefficiencies that could be targeted for cost savings.

Abstract--Vision language models (VLMs), such as CLIP and OpenCLIP, can encode and reflect stereotypical associations between medical professions and demographic attributes learned from web-scale data. We present an evaluation protocol for healthcare settings that quantifies associated biases and assesses their operational risk. Our methodology (i) defines a taxonomy spanning clinicians and allied healthcare roles (e.g., surgeon, cardiologist, dentist, nurse, pharmacist, technician), (ii) curates a profession-aware prompt suite to probe model behavior, and (iii) benchmarks demographic skew against a balanced face corpus. Empirically, we observe consistent demographic biases across multiple roles and vision models. Our work highlights the importance of bias identification in critical domains such as healthcare as AI-enabled hiring and workforce analytics can have downstream implications for equity, compliance, and patient trust. Vision language models (VLMs) constitute a class of AI architectures that learn joint representation by aligning visual perception with natural language semantics [1]. Typically, an image encoder is paired with a text encoder and trained to inhabit a shared embedding space that supports cross-modal correspondence between images and linguistic descriptions. One such instance is OpenAI's CLIP (Contrastive Language Image Pretraining) which is optimized on roughly 400 million image-text pairs and exhibits strong zero-shot ability for The code can be found at https://github.com/zohaibhasan066/ VLMs enable a broad spectrum of multimodal functionalities, including image captioning, visual question answering, and bidirectional text-image retrieval with downstream applications in search, recommendation, and human-computer interaction.

In large-scale maintenance organizations, identifying subject matter experts and managing communications across complex entities relationships poses significant challenges -- including information overload and longer response times -- that traditional communication approaches fail to address effectively. We propose a novel framework that combines RDF graph databases with LLMs to process natural language queries for precise audience targeting, while providing transparent reasoning through a planning-orchestration architecture. Our solution enables communication owners to formulate intuitive queries combining concepts such as equipment, manufacturers, maintenance engineers, and facilities, delivering explainable results that maintain trust in the system while improving communication efficiency across the organization.

Apple is best known for its futuristic, spaceship-like headquarters in Cupertino, California. But what many people don't know is that the tech giant also has a huge campus in Ireland. Apple's Cork campus opened its doors in 1980 with a single manufacturing facility and just 60 employees. Fast-forward to today, the site is home to more than 6,000 employees, and serves as Apple's European headquarters. The tech giant is usually extremely private about what happens behind closed doors.

Thousands of people in Gaza require artificial limbs after being maimed in Israeli attacks. Technicians are making prosthetic arms and legs from recycled materials as medical supplies are blocked by Israel's siege.