AI just dropped another trio of upgrades that crank the tech rivalry into overdrive. From OpenAI’s fastest model leap yet to Google’s autonomous research engine and Runway’s reality-bending simulations, here’s what’s new:

🧠 GPT-5.2 Is Here — And It’s Hitting Google Hard
OpenAI’s newest model series lands with a 400K context window, 38% fewer hallucinations, and three variants built for everything from lightning-fast tasks to deep reasoning. It outperforms humans on 44 occupations, crushes SWE-bench, and arrives just weeks after 5.1—OpenAI’s quickest upgrade ever as the Gemini 3 rivalry heats up.

🔍 Gemini Deep Research Agent — Google’s Autonomous Investigator
Google’s new agent can plan, search, analyze, and re-search like a tireless researcher. Powered by Gemini 3 Pro via the Interactions API, it navigates the web deeply, reduces hallucinations, dominates long-context benchmarks, and is rolling into Search, NotebookLM, Finance, and the Gemini app next.

🌍 Runway GWM-1 — Simulate Anything, In Real Time
Runway’s first General World Model predicts pixels like physics, generating interactive worlds, multi-view robotics training data, and lifelike avatars. Built on Gen-4.5 with audio and long-sequence consistency, it pushes AI toward true real-time simulation and agent training.

AI isn’t competing anymore, it’s going full throttle.-5.2 is Here and It's Killing Google

OpenAI launched GPT-5.2 on December 11, 2025, its most advanced model series yet, designed for developers and professionals amid fierce rivalry with Google's Gemini 3. Available immediately to ChatGPT paid subscribers and via API in three variants—Instant for fast routine tasks like writing and translation; Thinking for complex coding, math, long-document analysis, and planning; Pro for maximum accuracy on tough problems—it features a 400K token context window and August 31, 2025 knowledge cutoff. GPT-5.2 excels in economic productivity, generating spreadsheets, presentations, production-grade code, visual parsing, tool workflows, and multi-step projects, topping benchmarks like GDPval (outperforming humans in 44 occupations) and SWE-bench (80% vs Gemini 3's 76.2%). It reduces hallucinations by 38% over GPT-5.1, improves agentic behavior, long-context handling, and vision, with coding startups praising state-of-the-art agent performance. Following CEO Sam Altman's "code red" after Gemini 3's November debut, this quick upgrade—mere weeks post-GPT-5.1—refines sensitive query responses and advances age-prediction safeguards, unlocking greater real-world reliability.

Gemini Deep Research Agent Unleashed

Google launched the Gemini Deep Research agent via its new Interactions API on December 10, 2025, empowering developers to embed advanced autonomous research into apps using Gemini 3 Pro. This upgraded agent iteratively plans investigations—formulating queries, analyzing results, spotting gaps, and re-searching—with vastly improved web navigation for deep-site data extraction, slashing hallucinations for superior report quality. Optimized for long-context synthesis, it tops benchmarks like Humanity’s Last Exam, DeepSearchQA, and BrowseComp, outperforming base Gemini 3 Pro, while enabling custom agent integration alongside Google's built-ins. Soon rolling out to Google Search, NotebookLM, Google Finance, and the Gemini app, it supports multi-step reinforcement learning for complex landscapes, plus file uploads (PDFs/images) and Drive links for hybrid public-private insights. Amid AI arms race post-OpenAI's GPT-5.2, this "significantly more powerful" tool accelerates enterprise workflows in coding, analysis, and discovery.

Runway GWM-1 Can Now Simulate Anything

Runway announced GWM-1 on December 11, 2025, its first general world model family built on Gen-4.5 for real-time reality simulation—interactive, controllable, and general-purpose. This autoregressive system predicts pixels frame-by-frame, grasping physics, geometry, lighting, and dynamics to enable coherent, long-sequence interactions beyond static video generation. Three variants target key domains: GWM-Worlds crafts explorable 3D environments from prompts for gaming/AI training, with user-defined rules and real-time camera/actions; GWM-Robotics SDK generates multi-view, action-conditioned videos for robot policy training on NVIDIA Blackwell; GWM-Avatars produces lifelike conversational characters, soon via web/API. Gen-4.5 upgrades add native audio generation/editing and multi-shot consistency for extended narratives. Amid AI race with Google's Genie-3, GWM-1 advances agent training, robotics, and virtual worlds via safer, scalable simulations.

Hand Picked Video

In this video, we’ll look at how GPT‑4o’s brand new image generation capabilities let you create stunning, photorealistic visuals—right from a simple prompt. From beautifully rendered text and diagrams to whimsical illustrations and sleek product mockups, 4o blends deep world knowledge with visual precision. We’ll explore how it handles complex scenes, multi-turn edits, and even integrates image inspiration—all natively inside ChatGPT.

Top AI Products from this week

• Korgi - Korgi connects your scattered productivity stack in a single project management app. AI generates your project board with content, steps, and links in less than a minute. You take action while Korgi creates, shares, and launches assets in a click, using your own apps and drives.

• Google Mixboard 2.0 - Mixboard just got a major tune-up! Create presentations from your boards with Nano Banana Pro, support for new file types including PDF / HEIC / TIFF, multi-board projects and more. A faster, smoother way to explore ideas and turn boards into polished outputs.

• Kaily - Meet Kaily, your AI teammate that automates every customer conversation. Handle support, sales, onboarding, bookings, and more across web, mobile, WhatsApp, Slack, email, voice, and video.

• VibeCSS - The fastest way to prototype and experiment with web design directly on live pages. Select any element, describe what you want in plain language, and watch AI instantly apply CSS changes. No code required. No dev tools needed. Just pure creative flow.

• A Visual Editor for the Cursor Browser - Cursor’s new Visual Editor turns your browser into a live coding workspace. Drag, drop, and edit components visually, adjust props in real time, and describe changes with natural prompts bridging design and code in one seamless environment.

• Music Videos by Mozart - Mozart AI now lets you generate sixty second music videos to bring visual resonance to your sonic creations. We're also launching Vibe Sessions — a conversational journey from idea → finished song → short music video. For deeper control, jump into a Studio Session for multitrack editing, clean stem generation, effects, MIDI, and more.

This week in AI

• Cursor Debug Mode - Cursor's Debug Mode fixes tough bugs via runtime logs: describe issue, agent hypothesizes, adds logging, you reproduce—pinpoints root cause for precise fixes. Verify, clean up. Part of 2.2 with multi-agent judging.

• Disney Sora Deal - Disney inks 3-year deal with OpenAI: $1B equity investment, licenses 200+ characters (Disney, Marvel, Pixar, Star Wars) for Sora videos/ChatGPT Images. Curated clips on Disney+ in 2026. No voices/likenesses. Boosts AI tools internally.

• Adobe in ChatGPT - Adobe launches Photoshop, Express & Acrobat in ChatGPT for 800M users: edit images (blur bg, adjust brightness), design invites, manage PDFs via chat prompts. Free on desktop/web/iOS/Android soon.

• Copilot Usage Report - Microsoft's 2025 Copilot report reveals real-world usage: helps think/create across apps, peaks in problem-solving/exploration. MAI emphasizes "approachable intelligence" via Copilot, Bing, Edge.

• Copilot Usage Report - Microsoft's 2025 Copilot report reveals real-world usage: helps think/create across apps, peaks in problem-solving/exploration. MAI emphasizes "approachable intelligence" via Copilot, Bing, Edge. (

Paper of The Day

Researchers at Oak Ridge National Laboratory show large language models (LLMs) transform proposal selection at facilities like the Spallation Neutron Source. Traditional human scoring suffers biases, inconsistencies, and high costs from independent reviews. LLMs enable pairwise preference comparisons via Bradley-Terry modeling, yielding rankings with Spearman ρ of 0.2–0.8 vs. humans (≥0.5 post-outliers) across 20 cycles on three beamlines.

To read the whole paper 👉️ here