Vietnam AI 2025: Nearly 80% User Adoption, ChatGPT Still Leads the Market

Three million Codex users per week — up six times in just the first three months of 2026. That number tells you something: Codex is the rising star. OpenAI is turning it into an all-in-one tool, which means Codex is no longer just a playground for developers. What is Codex? A tool that's not just for developers Think about this scenario: you want to build a spreadsheet that automatically updates every week, or a small website to let customers book appointments, or simply a tool that summarizes your email reports each morning without opening dozens of tabs. Previously, these things required a developer. With Codex, you just type your request in plain English and wait for the result. Codex is OpenAI's AI agent, launched in May 2025 and deeply integrated into the ChatGPT ecosystem. Its core difference from regular ChatGPT is that Codex doesn't just answer — it actually does the work through a code execution environment. You assign a task, Codex plans it out, executes each step, checks the result, and returns a finished product ready to use. No need to understand what code is, no need to monitor every command. Codex can now run as a standalone desktop app available for both Windows and macOS, and has recently expanded to Android and iOS on mobile as well. You can sign in using your existing ChatGPT account. Codex is currently available on ChatGPT Plus, Pro, Business, and Enterprise plans, though Free and Go users also get limited trial access. What Codex can do for you Build apps or small websites from a description You don't need to know HTML or JavaScript. Just describe what you need: "Create a simple appointment booking page with fields for name, phone number, and date/time selection, and send an email notification whenever someone books." Codex will build the entire interface, handle the logic, and guide you through publishing it online. A startup team in the US once shared that they completed in one weekend what would have previously taken an entire quarter — and it wasn't a team full of developers. Automate repetitive tasks This is where non-developer users will find the most value. For example: every week you have to consolidate revenue data from three different Excel files, merge them, and send a report to your manager. Codex can build an automated workflow that does this for you on a schedule and delivers the result without you ever opening your laptop. With the Automations feature launched in the April 2026 update, Codex can take on long-horizon tasks, pause, resume, and complete them over multiple days without needing to be reminded. Generate images and prototypes directly in the app Codex integrates image generation powered by GPT Image 2.0 directly inside the app. You can ask Codex to create interface mockups, product banners, or illustration assets for a document — all within the same workflow, without switching to another tool. For content creators, marketers, and solo founders, this is a genuine advantage: the entire journey from idea to finished output can happen in a single window. Control your computer to work in the background Since April 2026, Codex can operate Mac applications using its own cursor, viewing the screen and clicking and typing to complete tasks while you continue using the machine normally. A simpler way to picture it: you're in an online meeting while Codex has Figma open, editing a design and saving the file according to instructions you set earlier. Two things happening in parallel, neither getting in the other's way. The computer use feature is currently only available on macOS and is not yet available in the EU or UK. You will need to grant Codex Accessibility and Screenshot permissions during initial setup. How to get started with Codex Codex requires installing the desktop app on Windows or macOS — it does not run directly in a web browser. The setup process is straightforward and takes just a few minutes. Step 1: Go to openai.com/codex and download the version for your operating system. On macOS, there are two separate builds for Apple Silicon (M1 and later) and Intel chips. On Windows, there is a single universal build. Step 2: Install the app and sign in with your existing ChatGPT account or OpenAI API key. Step 3: Choose a project folder you want Codex to work within — you can also link it to a github repository — or skip this step if you only want to assign standalone tasks like creating files, generating images, or automating a workflow. Step 4: Type your request in natural language, and be as specific as possible. Instead of "make me something about a report," try: "Create an Excel file summarizing monthly revenue from the data I provide, add a bar chart comparing each month, and highlight the month with the highest revenue." The more specific your request, the better the result. Codex works best when you clearly describe the input, the desired output, and any constraints you need — such as file format, display language, or calculation rules. Codex vs Claude Code, Antigravity, and Cursor from a non-technical user's perspective If you're not a developer, the real question isn't "which tool is technically more powerful" — it's "which tool can I use right now without learning anything new." From that angle, these four tools are clearly different from one another. Codex and Claude Code Claude Code from Anthropic is Codex's most direct and formidable competitor. In terms of raw technical output quality, Claude Code currently leads the pack — producing cleaner code, tighter logic, and handling large, complex codebases more effectively. However, Claude Code is explicitly designed for developers: it runs in the terminal, requires command-line installation, and notably has no image generation capability. If you're not comfortable in a terminal, Claude Code is a barrier from the very first step. Codex, by contrast, offers a more user-friendly desktop interface, integrates image generation within the same workflow, and is noticeably more accessible to non-technical users. Codex and Antigravity Both require a desktop app, but their underlying philosophies are completely different. Codex is built around a "hand off the task and wait for results" model: you describe what you need, the agent runs in an isolated cloud sandbox, and returns a finished product without affecting your machine at all. It suits people who want to automate workflows, create files, or build something without monitoring every step. Antigravity works in the opposite direction: the agent runs directly on your machine, watches your screen, opens applications, and collaborates with you in real time while you work. If you want an AI colleague working alongside you — observing and reacting to what's happening on your screen — Antigravity is the better fit. Codex and Cursor Cursor is built on VS Code and targets developers who want to keep their familiar working environment intact. For non-coders, Cursor is largely inaccessible because the entire experience revolves around editing code inside an editor. Cursor excels at understanding an entire codebase and offers flexibility in choosing AI models, but those advantages are for developers — not for general users who need to automate workflows or build something from scratch. In summary, from a non-technical user's perspective: Codex: Friendly desktop interface on Windows and macOS, capable of generating images, well-suited for users who want AI as an automated workflow tool. Claude Code: Best technical output quality, but developer-oriented and cannot generate images. Antigravity: Agent works directly on your machine in real time, suited for users who want to collaborate with AI while they work. Cursor: Best for developers keeping their VS Code workflow intact; not suited for general users. Who is Codex best for? If you're a content creator who wants to build a landing page for a campaign without hiring a developer, Codex fits. If you're a marketer who needs to automate weekly reports pulling from multiple data sources, Codex fits. If you're a solo founder who needs to ship a product fast without a technical team, Codex fits. If you're a teacher who wants to build a small quiz app for students without learning to code, Codex fits. On the other hand, if you're a developer who needs granular control over every line of code in a large, complex codebase, Claude Code will deliver better output quality. Codex is the right tool for people who want fast results without needing to understand what's happening under the hood. One practical limitation worth knowing: Codex currently has full support for Python, JavaScript, TypeScript, and Ruby. For tasks that don't involve code — like generating images, automating workflows, or creating documents — this language limitation has no impact on you. The line between "can code" and "can't code" is fading The question "do you know how to program?" is losing its weight as tools like Codex continue to evolve. What matters more now is whether you can describe clearly what you want — because that's exactly the thinking skill required to work effectively with Codex and similar AI agent tools. If you want to try it today, start with something small and specific: ask Codex to create an Excel file consolidating data you currently process manually every week. That's the fastest test to evaluate whether Codex genuinely saves you time or not.

Gemini has won big in the most literal sense, right as Messi scored his first hat-trick at the 2026 World Cup, leading Argentina to a crushing 3-0 victory over Algeria and equaling Miroslav Klose's record of 16 World Cup goals. That historic moment became the perfect launchpad for Gemini. Back in March 2026, Google and the Argentine Football Association (AFA) made a bold decision: rather than simply printing a logo on training kits, they signed a deal for the AI to actively support tactical preparation and professional decision-making. That bet has now proven to be the right call. From training kit to the tactical meeting room The agreement between AFA and Google was unveiled at Times Square, New York, a venue deliberately chosen to capture global media attention. The Gemini logo appears across all training apparel for Argentina's men's, women's and youth squads, sitting alongside Adidas and American Express in AFA's top sponsorship tier. But the interesting part isn't the jersey. According to Inside World Football, Argentina's coaching staff will use Gemini for three specific purposes: tactical analysis, injury prevention and decision support. In other words, Gemini now has a seat in meetings that previously belonged only to Scaloni and his assistants. Google has not publicly disclosed which specific Gemini tools have been integrated into AFA's workflow. What is clear is that they are using the World Cup to bring Gemini into the reality of professional football, and the results will be graded in public. What is Gemini actually doing in the dressing room? Argentina arrives at the 2026 World Cup as the reigning champion. Every decision Scaloni makes, from the squad list to the starting eleven, is scrutinized more closely than any other team, and that is precisely why Argentina has become the most ideal testing ground Google has ever had for Gemini in professional football, especially at a major tournament. Tactical analysis Gemini is used to process match data for both Argentina and their opponents, covering movement statistics, attacking patterns and defensive vulnerabilities. Instead of the coaching staff spending hours reviewing footage, AI synthesizes the data and generates tactical diagrams automatically, saving significant preparation time before each match. Injury prevention This is a problem every major team wants to solve, especially when Messi and several key players are at an age that requires careful management of training loads. Gemini analyzes biometric data and injury history to issue early warnings, helping the coaching staff adjust intensity before problems actually occur. That is part of the reason why, immediately after completing his hat-trick, Scaloni chose to substitute Messi off, prioritizing fitness and safety for the matches ahead. AI in injury prevention is nothing new. Premier League clubs have had Microsoft as a partner for similar purposes. What is different this time is that Gemini is integrated directly into the workflow of a national team competing at a major tournament, not just at club level. For fans: create Messi content, follow scores without unlocking your screen Alongside supporting the coaching staff, Gemini has also rolled out a range of features aimed at fans, and this is the side that hundreds of millions of people will actually experience. Gemini lets you create content about players directly Users can generate images, songs and digital content featuring Argentina players like Messi directly inside the Gemini app. The feature is designed to bring the World Cup experience closer to those who cannot attend matches in person. Real-time scores and automated daily briefings On Google Search, live match scores can be pinned to the lock screen and update in real time, with dedicated animations for goals and red cards, all without needing to unlock the phone. For paid Gemini users, the Scheduled Actions feature allows an automated daily football briefing to be set up, covering scores, news and fixtures, delivered at a chosen time without needing to prompt it each day. Match-day infrastructure Google has updated Street View at all 16 host stadiums and optimized routing on Waze for match days. Waze also surfaces live scores when the car is stopped at red lights, so drivers do not need to pick up their phones while on the move. The 2026 World Cup is the real test for AI in sport Google is not sponsoring Argentina alone. Gemini also appears on the kits of France, Morocco, Iraq, Turkey and the United States, while Pixel is the official phone of the French squad, which is also using Gemini for internal communications. This is clearly a comprehensive strategy from Google, not a one-off deal. What makes the 2026 World Cup particularly significant is that it will answer a question no lab environment can: what do users actually do with AI when a World Cup runs for six weeks across 104 matches? Features that run on initial novelty will fade after the group stage. Whatever users keep coming back to all the way through the final is the honest answer to where AI actually fits in everyday life, and Google knows it. Google's communications director for Latin America, Flor Sabatini, stated that the 2026 World Cup will mark a before and after in the history of football because of AI. It sounds like marketing, but the reality is that this is the first time a major AI model has been integrated into the preparation of the reigning world champions, right in the middle of the most-watched sporting event on the planet. The 2026 World Cup is Gemini's real test The most significant part of this entire story is not the Gemini logo on Messi's jersey. It is the fact that Argentina, still the most expected to win and the most scrutinized team, carrying the pressure of defending the title, has committed part of its preparation process to AI. If Argentina succeeds, Gemini will have a case study that no advertising budget can buy. If Argentina falls short and the coaching staff attributes any part of it to AI, the narrative will flip entirely. Either way, this is the first time AI has been held accountable on a stage that genuinely matters, not a benchmark, not a demo, but the World Cup. For AI users, what is worth watching is not just whether Argentina wins, but whether Gemini actually changes how a football team operates, or whether it turns out to be nothing more than a logo on a training kit that looks better than previous years.

You have been using NotebookLM to store documents, research, and notes — but every time you needed AI to process something further, you had to open Gemini, copy-paste manually, and hope the AI didn't fabricate inaccurate figures. Now, after discovering this integration, that extra step can be eliminated entirely: NotebookLM can connect directly into Gemini, turning all your documents into an immediate knowledge base for AI to work from. NotebookLM and Gemini used to be two separate islands NotebookLM is very good at one thing: staying anchored to the documents you provide and answering accurately based on them. You can upload a 200-page financial report and ask about any figure, and NotebookLM will cite the exact page and passage. However it is isolated within individual notebooks and cannot search for new information outside those documents. Gemini is the opposite: flexible thinking, real-time web access, and genuine creativity — but highly prone to hallucination when working with specialized data without a clear source. The result is that anyone who knows both tools has to use them in parallel, transferring data back and forth manually, which wastes time and introduces errors. This integration solves exactly that problem by bringing NotebookLM directly into the Gemini interface, letting the two tools complement each other rather than operating independently. A few things to know before connecting Gemini and NotebookLM Because they share the Google ecosystem, the Gemini and NotebookLM integration works smoothly — but there are a few things worth knowing to avoid setting the wrong expectations. Gemini prioritizes data from your notebook first, but when the notebook doesn't contain enough information, it will automatically search the web without you needing to issue an additional command. This is convenient, but it also means you should check the citations to know whether an answer came from your documents or from a web search. Cross-notebook analysis across multiple notebooks simultaneously is a major capability that standalone NotebookLM couldn't offer. The more notebooks you connect, the more Gemini can surface different perspectives and contradictions while still staying grounded in the full context. Every answer drawn from notebook data also includes specific source citations, which is an important difference from standard Gemini and lets you verify information quickly when needed. How to connect NotebookLM to Gemini in 4 steps The feature is now available for both free accounts and Google AI Pro with no additional setup required. Follow this sequence. First, open Gemini on the web or mobile app and go to the chat input as normal. Next, click the "+" icon in the corner of the chat window and select NotebookLM from the list of sources. Then choose one or more notebooks you have already created to serve as context for the conversation. Finally, type your prompt as usual, keeping in mind that Gemini will prioritize data from the notebook first and only search the web when the notebook doesn't contain enough information. The entire setup takes under 60 seconds, and you can switch between different notebooks within the same conversation. What can Notebook and Gemini together do that neither could before? The biggest change isn't speed — it's the reliability of the output. When Gemini has specific source data from a notebook, every answer comes with clear citations so you know exactly which page and document the information came from, rather than having to verify it yourself. In practical terms, there are four scenarios where this combination makes the most noticeable difference. Research and document synthesis Instead of reading through a 500-page textbook, you upload it to NotebookLM and ask Gemini to condense it into a study book, an infographic, or a presentation deck through Canvas mode. Here is what that looked like with a standard prompt turning selected notebooks into a book. You can see the result at this Gemini link. Writing content without worrying about hallucination This is the most useful use case for content creators. NotebookLM handles the "accurate" side by keeping figures, names, and events anchored to the source documents. Gemini handles the "compelling" side by writing prose, crafting hooks, and finding interesting angles. The output still doesn't quite match Claude in quality, but it makes an excellent reference to hand off to Claude for a final rewrite, and the result from that combination is genuinely strong. Gems that update their own knowledge Gems are custom AI assistants inside Gemini. When you attach a notebook to a Gem, the notebook syncs automatically: whenever you add new documents to NotebookLM, the Gem updates immediately without needing to be reconfigured. For example, if you have a Gem dedicated to customer support, every time company policy changes you simply update the notebook and the Gem understands the new information right away. Audio overviews combined with web search NotebookLM already has a feature for converting documents into conversational podcast-style audio, which is genuinely useful. When combined with Gemini, you can ask AI to supplement that audio summary with the latest information from the web, making it practical to listen while commuting and still stay current with the newest developments. Where to start if you haven't used NotebookLM and Gemini together before If you haven't used NotebookLM yet, start by uploading a document you frequently need to reference — an internal company process, a course syllabus, or an industry report you follow. Create a notebook from that document, then open Gemini and connect the notebook. Try asking a few questions that previously would have required reading the entire document to answer. When the AI answers accurately and cites sources clearly, you will immediately understand why this combination is worth using regularly. Not because it is "revolutionary" or "groundbreaking," but because it solves one specific tedious problem that you have been handling manually every day.

Cộng đồng người dùng AI toàn cầu đang xôn xao trước thông tin Google thực hiện chiến dịch khóa hàng loạt tài khoản liên quan đến việc sử dụng công cụ OpenClaw kết nối qua nền tảng Antigravity. Động thái này không chỉ gây gián đoạn công việc của hàng ngàn nhà phát triển mà còn dấy lên những lo ngại sâu sắc về tương lai của các tác nhân AI (AI Agents) tự chủ.Nguyên nhân từ phía Google với các “nghi vấn” hoạt động bất thườngTheo thông tin từ Google, hệ thống của hãng đã phát hiện sự gia tăng đột biến các hoạt động được cho là bất thường khi người dùng truy cập các mô hình Gemini thông qua công cụ mã nguồn mở OpenClaw và Antigravity. Google khẳng định rằng việc sử dụng công cụ bên thứ ba để kết nối với mô hình Gemini là hành vi vi phạm điều khoản sử dụng. Hệ thống bảo mật của hãng đã ghi nhận lượng lớn hoạt động bất thường xuất phát từ nền tảng Antigravity, gây ảnh hưởng đến chất lượng dịch vụ chung và buộc Google phải nhanh chóng chặn quyền truy cập để đảm bảo tài nguyên cho những người dùng hợp lệ.Hệ quả nghiêm trọng đối với người dùngĐộng thái bất ngờ của Google đã khiến nhiều người dùng chịu thiệt hại nặng nề:Mất quyền truy cập dịch vụ: Nhiều người dùng đột ngột bị khóa hoặc hạn chế quyền truy cập vào các dịch vụ thiết yếu như Gmail, Google Workspace và cả phiên bản AI cao cấp Gemini 2.5 Pro.Lỗi hệ thống: Những người chưa bị khóa tài khoản thường xuyên gặp phải thông báo lỗi “403” hoặc các thông báo về vi phạm chính sách khi cố gắng sử dụng API.Tình trạng “Phiên bản không hỗ trợ”: Một loạt người dùng báo cáo lỗi “Phiên bản Antigravity này không còn được hỗ trợ” khi cố gắng thiết lập kết nối, thực tế là do sự thay đổi trong cách Google và Antigravity xác thực phiên bản.Các nhà phát triển đã tạo bản vá và nỗ lực khôi phục thế nàoCộng đồng mã nguồn mở đã nhanh chóng tìm cách ứng phó với các rào cản kỹ thuật này:Cập nhật phiên bản: Các nhà phát triển phát hiện ra rằng mã nguồn cũ (phiên bản 1.11.x) đã bị Google từ chối. Một giải pháp tạm thời là cập nhật thủ công chuỗi phiên bản thành 1.15.8 trong các tệp cấu hình của hệ thống để “đánh lừa” sự kiểm tra của máy chủ.Hướng dẫn khôi phục tài khoản: Trên các diễn đàn như Reddit, người dùng truyền tai nhau các bước khôi phục tài khoản bị cấm, bao gồm việc ngắt kết nối OAuth trong cài đặt tài khoản Google, xóa bộ nhớ cache và tệp token cục bộ, đồng thời phải đợi từ 24 đến 96 giờ trước khi thử đăng nhập lại.Bối cảnh rộng hơn dẫn đến phản ứng từ các ông lớnKhông chỉ Google, Anthropic gần đây cũng cập nhật điều khoản để cấm rõ ràng việc sử dụng mã thông báo OAuth của tài khoản Claude trong các công cụ bên thứ ba như OpenClaw, cuối cùng chỉ còn mỗi OpenAI và các công ty đến từ Trung Quốc là đang mở cửa cho OpenClaw. Sự việc này cũng tạo ra những biến động nhân sự đáng chú ý:Peter Steinberger, nhà phát triển đứng sau Antigravity, đã chỉ trích động thái của Google là quá cứng rắn và từng có ý định ngừng dự án.Sam Altman (CEO OpenAI) ngay sau đó đã thông báo Steinberger sẽ gia nhập OpenAI để phát triển thế hệ trợ lý ảo mới, trong khi OpenClaw sẽ tiếp tục được duy trì dưới dạng dự án mã nguồn mở.Lời cảnh báo về an toàn dữ liệuĐằng sau sự tiện lợi của OpenClaw — một công cụ có thể tự động gửi mail, quản lý lịch trình và thực hiện lệnh terminal — là những rủi ro bảo mật chí mạng. Các chuyên gia cảnh báo về lỗ hổng (Prompt Injection), nơi kẻ xấu có thể điều khiển AI xóa sạch dữ liệu hệ thống (lệnh rm -rf) hoặc đánh cắp thông tin nhạy cảm của người dùng.Kết luận: Sự kiện Google chặn OpenClaw và Antigravity không chỉ là một vấn đề kỹ thuật đơn thuần, mà còn là minh chứng cho sự xung đột giữa khát vọng tự do của cộng đồng mã nguồn mở và nỗ lực bảo vệ hệ sinh thái cũng như tài nguyên kinh doanh của các tập đoàn công nghệ lớn. Đây là lời cảnh tỉnh về việc cần có sự cân bằng giữa đổi mới và an toàn trong bối cảnh AI đang ngày càng phát triển mạnh mẽ.