Research reveals AI models, including ChatGPT and DeepSeek's R1, exhibit stronger biases than humans when hiring, segregating candidates into jobs based on early observations. This discovery has significant implications for the use of AI in recruitment processes. The study suggests that newer models with higher reasoning capabilities show even more pronounced biases.

Researchers introduce PlanFlip, a framework to attack multi-agent LLM systems via planning-phase prompt injection, revealing vulnerabilities in popular models like GPT-5 and Llama-3.3-70B. The study highlights the importance of heterogeneous model diversity for security. PlanFlip's four attacks can corrupt downstream sub-tasks, evading keyword filters and compromising system integrity.

MarkTechPost compared Qwen, Gemma, Mistral, and DeepSeek, the best local LLMs that can run on a single 24GB GPU in 2026. This comparison highlights the performance and capabilities of each model, providing insights for developers and businesses. The article discusses the key details, technical analysis, and industry impact of these LLMs.

Discover the top local LLMs that can run on a single 24GB GPU in 2026, including Qwen, Gemma, Mistral, and DeepSeek. Learn how to choose the right model for your needs and optimize performance. Get the latest insights on AI model development and deployment.

DeepSeek's new AI model uses a unified multimodal learner for clinical prediction, simplifying the process and achieving state-of-the-art results. This approach converts all patient data into a single natural language sequence and fine-tunes a pretrained language model. The model outperforms task-specific multimodal baselines and a clinically deployed gradient boosting system.

The AI landscape is rapidly evolving as three Chinese labs—Moonshot AI, DeepSeek, and Zhipu AI—release powerful, open-weight Mixture-of-Experts (MoE) models. Kimi K3, DeepSeek V4 Pro, and GLM-5.2 are pushing the boundaries of scale and capability, offering trillion-scale parameters and million-token context windows for complex coding and agent workloads, fundamentally shifting the open-source AI leaderboard.

Unsloth Studio now supports Inkling, a 975B parameter open model with up to a 1M context window, licensed under Apache 2.0. The new release includes several updates and bug fixes, enhancing the overall user experience. With Inkling, Unsloth Studio can accept text, images, and audio and generate text, expanding its capabilities.

DeepSeek's new Director system accelerates distributed MoE serving via online proactive expert placement, reducing end-to-end latency by 11-55%. This breakthrough has significant implications for the AI industry, enabling faster and more efficient model serving. The Director system uses prediction-driven expert placement and online migration to minimize downtime and optimize performance.

US lawmakers are investigating the growing use of Chinese AI models by American companies, citing concerns over censorship, security risks, and the impact on domestic alternatives. The probe is specifically looking at companies such as Cursor and Airbnb, and the use of models like DeepSeek. This investigation highlights the complexities of the AI landscape and the need for careful consideration of the origins and implications of AI models.

DeepSeek has unveiled a groundbreaking approach to abstract reasoning on ARC-AGI-1, leveraging an open-weight model (DeepSeek V3.2) in a 'non-thinking' mode, augmented by innovative agentic harnesses. This method achieves impressive generalization and pattern discovery, reaching up to 67.25% pass@2 with unprecedented cost-efficiency, sidestepping heavy compute or benchmark-specific fine-tuning.

DeepSeek introduces FirstResearch, a groundbreaking framework that tackles the auditability challenge in LLM-driven scientific discovery. By generating a structured 'Research Question Certificate,' FirstResearch ensures AI-proposed research questions are transparent, inspectable, and based on explicit mechanisms and assumptions, significantly enhancing trust in AI-powered scientific ideation.

New research reveals a critical vulnerability in advanced reasoning AI models, where logically inconsistent prompts can force them into 'overthinking,' leading to denial-of-service attacks. This 'Evolutionary Prompt Attack' significantly increases resource consumption and poses a serious threat to commercial LLM providers like OpenAI, Google, and DeepSeek.

A groundbreaking Arxiv paper introduces LLMForge, a multi-model text-to-CAD framework that enables automatic generation of parametric 3D mechanical designs from natural language. This framework, featuring innovative iterative refinement and VLM-based critique, demonstrates remarkable success, with top models like DeepSeek-V3.2 achieving near-perfect mesh generation and showing compact models can rival larger systems.

DeepSeek's new study explores the effectiveness of learned stopping in reasoning models, finding that it can improve performance in certain tasks. The study introduces LearnStop, a hidden-state-free checkpoint stopper, and evaluates its performance across 18 task-model settings. The results show that learned stopping can be useful in tasks where many questions become correct before full budget but do not exhibit a single reliable scalar stopping signal.

NVIDIA's full-stack inference software, optimized for the Blackwell platform, slashes token costs by 5x on DeepSeek V4. Companies like Baseten and Cognition leverage NVIDIA's tools to scale AI workloads efficiently, marking a shift from hardware specs to cost-per-token economics.