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You wanted a Chrome extension that would save you 15 minutes a day. You searched the Chrome Web Store, and it's not there. Now you can just describe it in plain English, and PlugThis builds it for you. The code is yours. Want changes? Chat. Need login or a database? Connect Supabase. Ready to publish? We generate the icons, screenshots, and listing copy the store asks for. Everyone else builds web apps. We build Chrome extensions.

Sim is an open-source workspace to build agentic workflows. Connect your AI agents and workflows to 1,000+ integrations and LLMs.

Not another AI bot, a real colleague to work alongside your team. Give your team superpowers or even run your company on autopilot.

Create unlimited business cards, scan any paper card, LinkedIn QR, or badge in seconds, and share via QR, Wallet, or AirDrop. Your private AI remembers who you met and why it mattered, then syncs everyone into your CRM. Encrypted, no public feed. New in v2.0: Team Plan with branded cards and admin controls, AI Note Taker for meeting transcripts and summaries, ShareBack for instant mutual exchange, follow-up reminders, and the full app in 5 languages. Much of it built from user requests.

ChatCut is a lightweight, professional-grade AI video editor anyone can use, even without editing experience. It’s like having a personal video editing assistant that understands your footage, intent, and timeline. Make structural edits, fine-tune cuts, add captions, B-roll, music, voiceover, motion graphics, stock footage, and AI-generated video in one place. Every edit stays editable on a real timeline, with XML export when you want to keep working elsewhere.

GPT-5.6 is rolling out in the API! Our new family of models gives builders three options: Sol (our flagship model for the hardest agentic tasks), Terra (balanced for everyday workflows), and Luna (fast and cost-efficient). GPT-5.6 also introduces Programmatic Tool Calling, Multi-agent (beta) for parallel execution, and explicit prompt caching. On July 23, we're teaming up with Product Hunt for OpenAI Day. The top five launches will each receive $10K in API credits.

A new AI tutoring system has been developed to provide real-time personalized learning experiences for 5-year-olds, adapting to each child's learning pace and style. This technology aims to make early childhood education more interactive and effective through intelligent adaptation.

Run your entire product development cycle in Notion, from customer feedback to a merged PR. Agents handle the triaging, routing, and summarizing. Your team handles the judgment calls.

Plan, create, and distribute content across every channel from one workspace. StoryChief Connect gives Claude, and your marketing team access to the tools, data, workflows, and publishing channels they need to execute real campaigns. Connect your stack. Turn signals into strategy. Create content for every channel. Collaborate, schedule, publish, and improve from one connected content calendar.ryChief helps marketing teams ship more, with less.

The latest model from Meta Superintelligence Labs and a significant upgrade from Muse Spark. Muse Spark 1.1 is a multimodal reasoning model built for agentic tasks, with major gains in tool and computer use, coding, and multimodal understanding.

Researchers have developed a technique to generate AI videos that are specifically optimized to activate target brain regions, opening new possibilities for neuroscience research and understanding visual perception. This approach combines generative AI with neuroscience to create stimuli tailored for brain mapping and cognitive studies.

In this work, we present Canvas360, a two-stage framework for in-context panoramic generation that combines geometry-aware pretraining with downstream task-specific fine-tuning. To address the lack of large-scale, high-quality training data tailored to in-context panoramic tasks, we propose Canvas360Dataset, a collection of 1M high-quality paired panoramic samples for style transfer, inpainting, outpainting, and editing, enabling effective supervision across diverse in-context generation scenari...

Semantic audio applications increasingly require controllable generation on commodity and embedded hardware rather than through framework-heavy datacenter stacks. We present aria, a dependency-free native runtime that runs the complete text-to-music pipeline of Stable Audio~3 (SA3) on ordinary GPUs, CPU-only machines, and a Raspberry~Pi~5, with no Python or deep-learning framework underneath. Our main contribution is a study of quantization: running the model at lower numerical precision to fit ...

Modern Video Object Segmentation (VOS) involves tracking and segmenting user-specified targets. While recent approaches have achieved remarkable performance in single-target scenarios, extending them to multi-target settings typically involves replicating the single-target processing for each individual object, resulting in reduced frame rates (FPS) with unbounded latency as target count increases. Built upon Segment Anything 2 (SAM2), we propose SAM-MT, which addresses this by transforming the ...

Generating realistic 3D human motions in real-time within interactive applications is key for animation, simulation, and humanoid robotics. While recent offline motion generation approaches offer precise control via text and kinematic constraints, they lack the inference speed required for interactive settings. Conversely, existing online methods enable real-time synthesis but often sacrifice controllability or struggle with complex text semantics and long-horizon goals due to limited context wi...

In long-horizon tasks, decision-relevant state is often scattered across an expanding trajectory, while the action agent must surface it and act. As trajectories grow, task requirements, environment facts, prior attempts, diagnoses, and open subgoals can be buried in the context window or pushed beyond it, failing to influence decisions when needed. We call this failure mode "behavioral state decay". We study memory as an active intervention mechanism rather than passive retrieval. A separate me...

The rapid development of large language models and multimodal large language models has accelerated the emergence of proactive agents capable of operating everyday tools and assisting users in real-world environments. However, existing benchmarks struggle to evaluate such agents effectively, as they often rely on sandboxed environments and single-turn evaluation paradigms. Moreover, their scenario-based task taxonomies mix multiple model capabilities within the same task category, making it diff...

Reasoning has become a core capability for large models, especially when reliable decisions require understanding logical consequences. Recent video generation models offer a reasoning path distinct from previous Chain-of-Thought (CoT): reasoning can unfold through temporally connected frames, known as Chain-of-Frame (CoF) reasoning. However, existing video generators are primarily trained on general video corpora, still lacking diverse supervision and dedicated designs for CoF reasoning. To add...

Recovering high-quality video from sparse event streams is a challenging task. Regression methods often blur textures, while existing generative models struggle with long-term stability. We propose LongE2V, a novel approach that leverages pre-trained video diffusion priors to jointly handle event-based video reconstruction, prediction, and frame interpolation. By fine-tuning a foundational video model, our approach achieves high data efficiency and superior perceptual quality. We introduce Autor...

Large language models (LLMs) increasingly act as integrated data-science agents, combining abstract reasoning with advanced tool use. Yet the relevant benchmark landscape largely divides into symbolic causal reasoning benchmarks without realistic data analysis or data analysis benchmarks without a principled causal data-generating structure. Furthermore, existing causal evaluation datasets are often restricted to curated examples from existing sources, with diversity coming from limited templati...

We propose OPSD-V, an on-policy self-distillation paradigm for post-training few-step autoregressive (AR) video diffusion models. Existing few-step AR video generators can produce long videos with low latency, but still suffer from error accumulation and weakened motion dynamics during long autoregressive rollout. OPSD-V reduces long-horizon degradation while preserving the original few-step inference path. The key idea is to introduce real long-video data as temporal context during training and...

Scientific ideas rarely start from a blank page. They inherit mechanisms, repair known limitations, and recombine pieces of earlier work, much like biological genomes. Current benchmarks still say little about whether AI systems can follow this inheritance structure. We present IdeaGene-Bench (IG-Bench), a benchmark for scientific lineage reasoning and lineage-grounded idea generation. IG-Bench is organized around the IdeaGene framework: each paper or proposal is represented as a set of minimal,...

Current computational approaches for drug design typically focus on generating molecules conditioned on specific targets or general molecular properties, often neglecting the influence of disease context on target behavior and therapeutic outcomes. To address this gap, we introduce DrugGen-2, a novel generative model that designs small molecules conditioned on both disease ontology and target protein sequences. DrugGen-2 was developed by fine-tuning a pre-trained GPT-2 model on a curated dataset...

Unified Memory architecture enables mini PCs and smaller systems to run large 70 billion parameter models that would otherwise require high-end GPUs, improving memory efficiency and accessibility. This breakthrough demonstrates how intelligent memory management can overcome traditional hardware limitations.

According to the New York Times, OpenAI falsely claimed it lacked the ability to search its training data while actually maintaining billions of logs, raising concerns about transparency and data handling practices. The report suggests OpenAI may have deliberately misrepresented its data retention and searchability capabilities.

How Deutsche Telekom is becoming an AI-native telco with OpenAI-transforming customer service, employee workflows, network operations, and the future of voice.