Guys! Recently, the news that Meta acquired Manus for $2 billion has caused a stir, but it can't be used in China?
Don't worry. Today, I'm going to recommend to you a domestic, free - of - charge local AI agent that doesn't require a VPN - Aipy! With features like open - source local operation, no - code needed, and multi - scenario practicality, it's simply an amazing AI labor - saving tool for ordinary people 🎉
🌟 🌟 Full - fledged Core Advantages
✅ Domestic Access without VPN: Runs locally, no need for a scientific internet access method.
✅ Completely Free: Register and use the invitation code to get 3.5 million Tokens (Invitation code: 4zfb).
✅ Zero - code Operation: Describe your needs in plain language, and the AI will automatically generate/ execute code.
✅ Agent Marketplace: Tools for quantitative research, photo - editing, PPT generation, etc. can be installed with one click.
Aipy integrates the large AI model with the Python program ecosystem. You don't need to know code at all. Just describe your needs in plain language, and it will automatically generate, debug, and execute programs in the background, and finally hand over the complete result to you.
The interface of Aipy is very simple: Enter your needs in the chat box on the left, and the right side will run and display the results in real - time. You just need to say what you want to do, and it will automatically generate and execute code to complete the full loop from instruction to result.
💡 Super - practical in Real - world Tests
Quantitative Research: Free access to historical data of A - shares / US stocks / Hong Kong stocks. Enter the stock name and it will automatically generate a technical analysis report.
Most stock analysis tools on the market require payment. However, Aipy has built - in historical market data of all listed companies in A - shares, US stocks, and Hong Kong stocks, and it can be used for free.
Install "Quantitative Research" in the "Agent Marketplace", click "Go to Use", and just tell it which stock you want to analyze. It will give a comprehensive analysis result from multiple aspects such as technical indicators, valuation levels, and trend status.
It should be emphasized that,the analysis given by the AI is more of a reference and learning tool, and the final investment decision still needs to be made by ourselves.
Batch Photo - editing: Upload a photo folder and let the AI batch - edit photos with one sentence.
First, install "Image Generation" in the "Agent Marketplace", and then click "Go to Use".
Ask Aipy to batch - edit the puppies in the folder into the way I want. It can easily understand natural language without complex prompts.
It completed my task in minutes without me writing any line of code. The generated pictures also have a very good effect.
PPT Generation: One - sentence requirement + Internet search, and a well - structured PPT can be done in minutes.
Aipy is also excellent at PPT generation. Just install "PPT Generation" in the "Agent Marketplace", click "Go to Use", and then state your requirement in one sentence.
For example, if I want it to help me make an introduction to the Xiaomi 17Ultra, as a newly - released product, the AI knowledge base may not have relevant information. We can turn on the Internet search function to let it obtain real - time information.联网搜索的，让它去实时获取。
After a while, a well - structured, complete - content, and clean - layout PPT is generated. From information organization to page presentation, it's done in one go, and the efficiency is remarkable.
Material Download: Throw in the link and it can batch - download website pictures and automatically classify and name them.
Aipy can also handle some more "hands - on" miscellaneous tasks. For example, to batch - download pictures from any website to the local device, just throw the link to it and state your needs.
It will automatically handle the download, classification, and naming, and the obtained files still maintain their original clarity.
If you're not satisfied with the results of some tasks, you can also manually select a more advanced model to execute.Aipy itself has multiple large models built- in and can switch flexibly according to different scenarios.
In addition to the functions mentioned above, the Agent Marketplace of Aipy also integrates many practical tools such as short - video copywriting generation, browser control, contract review, video generation, resume screening, and enterprise information analysis, and related capabilities are still being continuously expanded.
Aipy can not only help us think but also help us work. If you're looking for an AI tool that can accompany you in your work for a long time, Aipy is worth experiencing.
🎁 Exclusive Benefits
Do you want to experience the new - generation super AI assistant Aipy?
Register now and fill in the invitation code 👉RPF2👈 to get 3.5 million Tokens for free!！
The usage method is as follows:
① Visit the Aipy official website: https://www.aipyaipy.com/, and download the latest version of the Aipy client.
② Fill in the above invitation code when registering and logging in.
Guys! Microsoft Copilot is making big news again 🎉 Today, it officially rolls out OpenAI's most powerful model, GPT - 5.2, and it's a free upgrade! This directly ushers in a new era of "expert - level" workflows, pushing office efficiency to the limit.
🌟 Two Models Co - exist, and the Thinking - type is More Powerful
GPT-5.2 and GPT - 5.1 are both available. The Plus version is a "thinking - type" variant - simply put, it's better at in - depth thinking! When dealing with tables, writing review codes, and processing long documents, it's incredibly fast. It can also handle complex tool calls and image analysis.
🚀 Performance Doubles, Crushing Professionals
In 44 professional task tests, GPT - 5.2Thinking was actually 70.9% superior to / on par with industry experts (previously, GPT - 5 was only 38.8%)! Whether it's creating PPTs, scheduling, or producing professional deliverables, it's more reliable than the consultants you hire, taking office automation to a new level.
🔧 A Perfect Score in Rigorous Tests, Mastering Programming and Math
In the programming field: The SWE - Bench Pro test set a new record, far outperforming GPT - 5.1Thinking;
In math competitions: It got a perfect 100% score in AIME2025 and 92.4 points in the GPQA Diamond logic test;
In logic and science: There has been a significant improvement in CharXiv reasoning and ARC - AGI - 2, evolving from a basic assistant to a "digital intelligence entity".
Now it can be used on web pages / Windows / mobile devices. Experience the power of expert - level AI for free! Have you guys tried Copilot's new features? Come and share your office efficiency tools in the comments section below 👇
So as 2025 wraps up, we’ve gone headfirst into a mountain of de-identified data, searching for the quirks, surprises, and secret patterns that shape everyday life with Copilot. We’re finding out just how far it fits into people’s daily rhythms, and how human its uses have become: we often turn to AI for the things that matter most like our health. We analyzed a sample of 37.5 million conversations to find out how people actually use it out in the world. (Note: our system doesn’t just de-identify conversations; it only extracts the summary of the conversation, from which we learn the topic and the intent, and maintains full privacy.)
From health tips that never sleep, to the differences between weekday and weekend usage, to February’s annual “how do I survive Valentine’s Day?” spike, our findings show that Copilot is way more than a tool: it’s a vital companion for life’s big and small moments. And if you’ve ever pondered philosophy at 2 a.m. or needed advice on everything from wellness to winning at life, you’re in good company. So has everybody else.
Our work shows that AI is all about people, a trusted advisor slotting effortlessly into your life and your day. It’s about your health, your work, your play, and your relationships. It meets you where you are. Read all about it in our paper, but here are some of our takeaways.
Health Is Always on Our Minds—Especially on Mobile
No matter the day, month, or time, health-related topics dominate how people use Copilot on their mobile devices. Whether it’s tracking wellness, searching for health tips, or managing daily routines, our users consistently turn to Copilot for support in living healthier lives. This trend held steady throughout the year, showing just how central health is to our everyday digital habits. When it comes to mobile, with its intimacy and immediacy, nothing tops our health.
Most common Topic-Intent pairing conversations, on mobile.
Health is consistently the most common topic while interestingly, language-related chats peak earlier in the year, with entertainment seeing a steady rise.
When Programming and Gaming Cross Paths
August brought a unique twist: programming and gaming topics started to overlap in unexpected ways. Our data showed that users were just as likely to dive into coding projects as they were to explore games—but on the different days of the week! This crossover hints at a vibrant, creative community that loves to code during the week and play during the weekends in equal measure.
August topic ranks for programming and games.
There is a clear change in rank between programming and games through the days of the week, with programming rising from Monday to Friday, and Games shining on the weekends.
February’s Big Moment
February stood out for another reason: Copilot helped users navigate a significant date in their calendar year. Whether it was in preparing for Valentine’s day, or facing the day and the relationships, we saw a spike in activity as people turned to Copilot for guidance, reminders, and support. It’s a great reminder of how digital tools can make life’s important moments a little easier to manage.
Ranking of “Personal Growth and Wellness” and “Relationship” conversations February brings concerns of personal growth before Valentine’s day, with a clear peak of relationship-related conversations on the day.
Late-night Sessions
The larger-than-life questions seem to have a rise during the early hours of the morning, with “Religion and Philosophy” rising through the ranks. Comparatively, travel conversations happen most often during the commuting hours.
Average rank of Travel and Religion and Philosophy conversations per hour of the day.
Whilst people have more travel-related conversations during the day, it’s in the early hours of the morning that we see a rise of Religion and Philosophy conversations. 虽然人们在白天有更多与旅行相关的对话，但正是在凌晨时分，我们看到宗教与哲学对话有所增加。
Advice on the Rise
While searching for information remains Copilot’s most popular feature, we’ve seen a clear rise in people seeking advice—especially on personal topics. Whether it’s navigating relationships, making life decisions, or just needing a bit of guidance, more users are turning to Copilot for thoughtful support, not just quick answers. This growing trend highlights how digital tools are becoming trusted companions for life’s everyday questions.
Why These Insights Matter
By analyzing high level topics and intents, we manage to learn all these insights while keeping maximum user data privacy. Understanding these patterns helps us make Copilot even better. By seeing what matters most to our users—health, creativity, and support during key moments—we can design features that truly fit into their life. It’s also clear from these uses that what Copilot says matters. They show why it’s so important that we hold ourselves to a high bar for quality.
New audio model snapshots and broader access to Custom Voices for production voice apps.
AI audio capabilities unlock an exciting new frontier of user experiences. Earlier this year we released several new audio models, including gpt-realtime, along with new API features to enable developers to build these experiences.
Last week, we released new audio model snapshots designed to address some of the common challenges in building reliable audio agents by improving reliability and quality across production voice workflows–from transcription and text-to-speech to real-time, natively speech-to-speech agents.
The new snapshots share a few common improvements:
With audio input:：
Lower word-error rates for real-world and noisy audio
Fewer hallucinations during silence or with background noise
With audio output:：
More natural and stable voice output, including when using Custom Voices
Pricing remains the same as previous model snapshots, so we recommend switching to these new snapshots to benefit from improved performance for the same price.
If you’re building voice agents, customer support systems, or branded voice experiences, these updates will help you make production deployments more reliable. Below, we’ll break down what’s new and how these improvements show up in real-world voice workflows.
Speech-to-speech
We’re deploying new Realtime mini and Audio mini models that have been optimized for better tool calling and instruction following. These models reduce the intelligence gap between the mini and full-size models, enabling some applications to optimize cost by moving to the mini model.
gpt-realtime-mini-2025-12-15
gpt-realtime-mini model is meant to be used with the Realtime API, our API for low-latency, native multi-modal interactions. It supports features like streaming audio in and out, handling interruptions (with optional voice activity detection), and function calling in the background while the model keeps talking.
The new Realtime mini snapshot is better suited for real-time agents, with clear gains in instruction following and tool calling. On our internal speech-to-speech evaluations, we’ve seen an improvement of 18.6 percentage points in instruction-following accuracy and 12.9 percentage points in tool-calling accuracy compared to the previous snapshot, as well as an improvement on the Big Bench Audio benchmark.
Together, these gains lead to more reliable multi-step interactions and more consistent function execution in live, low-latency settings.
For scenarios where agent accuracy is worth a higher cost, gpt-realtime remains our best performing model. But when cost and latency matter most, gpt-realtime-mini is a great option, performing well on real-world scenarios.
For example, Genspark stress-tested it on bilingual translation and intelligent intent routing, and in addition to the improved voice quality, they found the latency to be near-instant, while keeping the intent recognition spot-on throughout rapid exchanges.
gpt-audio-mini-2025-12-15
The gpt-audio-mini model can be used with the Chat Completions API for speech-to-speech use cases where real-time interaction isn’t a requirement.
Both new snapshots also feature an upgraded decoder for more natural sounding voices, and better maintain voice consistency when used with Custom Voices.
Text-to-speech
Our latest text-to-speech model, gpt-4o-mini-tts-2025-12-15, delivers a significant jump in accuracy, with substantially lower word error rates across standard speech benchmarks compared to the previous generation. On Common Voice and FLEURS, we see roughly 35% lower WER, with consistent gains on Multilingual LibriSpeech as well.
Together, these results reflect improved pronunciation accuracy and robustness across a wide range of languages.
Similar to the new gpt-realtime-mini snapshot, this model sounds much more natural and performs better with Custom Voices.
Speech-to-text
The latest transcription model, gpt-4o-mini-transcribe-2025-12-15, shows strong gains in both accuracy and reliability. On standard ASR benchmarks like Common Voice and FLEURS (without language hints), it delivers lower word error rates than prior models. We’ve optimized this model for behavior on real-world conversational settings, such as short user utterances and noisy backgrounds. In an internal hallucination-with-noise evaluation, where we played clips of real-world background noise and audio with varying speaking intervals (including silence), the model produced ~90% fewer hallucinations compared to Whisper v2 and ~70% fewer compared to previous GPT-4o-transcribe models.
This model snapshot is particularly strong in Chinese (Mandarin), Hindi, Bengali, Japanese, Indonesian, and Italian.
Custom Voices
Custom Voices enable organizations to connect with customers in their unique brand voice. Whether you’re building a customer support agent or a brand avatar, OpenAI’s custom voice technology makes it easy to create distinct, realistic voices.
Theese new speech-to-speech and text-to-speech models unlock improvements for custom voices such as more natural tones, increased faithfulness to the original sample, and improved accuracy across dialects.
To ensure safe use of this technology, Custom Voices are limited to eligible customers. Contact your account director or reach out to our sales team to learn more.
From prototype to production
Voice apps tend to fail in the same places, mainly on long conversations or with edge cases like silence, and tool-driven flows where the voice agent needs to be precise. These updates are focused on those failure modes—lower error rates, fewer hallucinations, more consistent tool use, better instruction following. And as a bonus, we’ve improved the stability of the output audio so your voice experiences can sound more natural.
If you’re shipping voice experiences today, we recommend moving to the new 2025-12-15 snapshots and re-running your key production test cases. Early testers have confirmed noticeable improvements without changing their instructions and simply switching to the new snapshots, but we recommend experimenting with your own use cases and adjusting your prompts as needed.
Guys, artificial intelligence has been constantly changing the way enterprises operate. In the past, the emphasis was on intelligent assistants, but they could only respond passively. Now, Agentic AI has arrived, and this is a major evolution 🔥!
Traditional AI assistants can only perform isolated tasks and have limitations. However, Agentic AI can make autonomous decisions, coordinate multi - step actions, actively assess the environment, initiate actions, and coordinate cross - departmental work processes. It's really amazing 👏!
For enterprise leaders, this brings both opportunities and responsibilities. It has great potential, but also poses significant challenges in terms of governance, trust, and design. Enterprises must be able to monitor and reverse the actions of Agentic AI.
Enterprise work processes also need to be re - thought. We can no longer design processes step - by - step and insert automation. Instead, we need to build an intelligent ecosystem, consider which decisions should be made by humans and which by agents, and ensure correct data acquisition.
A unified platform is extremely important at this time. Without it, agents may become disjointed. A unified approach can provide standards, achieve interoperability, reduce complexity, and enable large - scale implementation.
Trust and accountability are also indispensable. Since agents act independently, the risks increase. Trust and accountability need to be integrated from the very beginning, with clear policies to make employees believe that it is a partner.
Enterprises should measure the business value as early as possible and not let projects remain only at the pilot stage. Well - designed Agentic AI can bring exponential improvements and transform enterprise performance.
The rise of Agentic AI is not about handing over power to machines, but a new stage of enterprise transformation where humans and agents fight side by side. Leaders should first conduct pilots and then expand, invest in a unified platform and policy framework, and foster a good culture.
Hey everyone! AI agents are transforming businesses—now is the perfect time for business leaders to step up and shine 💪!
Keywords
#Agentic AI #Enterprise Transformation #Work Process Remodeling #Unified Platform #Trust and Accountability
Guys, the annual blockbuster report on the consumer - grade AI market recently released by a16z, a top venture capital firm in Silicon Valley, is really mind - blowing! 🔥 The competition in the general AI assistant track is extremely fierce right now. Users usually only choose one main product, and the "winner - takes - all" pattern is accelerating.
The report shows that although the usage rate of AI has increased, users' willingness to use it across platforms is extremely low. Take ChatGPT's weekly active users as an example. Less than 10% of them will use other AI services simultaneously. Among mainstream products, only about 9% of users will pay for multiple assistants.
Currently, OpenAI is still remarkable, leading with 800 - 900 million weekly active users. However, its "super - app" strategy faces challenges. Google, with its "experimental field" model, has made Gemini catch up rapidly. The number of desktop users has increased by 155% year - on - year, and the growth rate of paid subscriptions is nearly twice that of ChatGPT. 👏
Judging from the data, ChatGPT has a leading user volume and high user stickiness. The ratio of daily active users to monthly active users is twice that of Gemini. But Gemini is growing at an astonishing rate, especially in terms of the growth of paid users, leaving ChatGPT far behind.
In terms of product strategies, OpenAI is like building a "walled garden", stuffing various functions into ChatGPT, but this makes the interface more complex. Google, on the other hand, adopts the "experimental field" model, allowing innovative products to develop independently, but its products are a bit scattered.
Other players also have their own unique skills. 👍 Anthropic's Claude focuses on technical users, and its programming assistant generates considerable revenue. Perplexity serves non - technical groups who value efficiency. Elon Musk's xAI product Grok is growing extremely fast, and its function iteration is also remarkable. It is said to be the AI product with the fastest - evolving capabilities.
The key to the future competition of AI assistants lies in who better understands users' needs and can transform them into good business models. Guys, who do you favor more? 🤔
Based on the official evaluation rules of OpenCompass, leading - industry large - language models are evaluated, and a ranking list is released according to the evaluation results.
1.1 The Practical Significance and Industry Requirements of Studying AI SEO
The deep integration of artificial intelligence and search engine optimization (SEO) is reshaping the digital marketing ecosystem. In 2025, AI SEO (Artificial Intelligence Search Engine Optimization) has shifted from technical experimentation to commercial implementation. Its core value lies in redefining the efficiency boundaries, optimizing the user experience, driving data - driven decision - making, and promoting the upgrade of SEO from "keyword competition" to "intelligent trust - building" [1]. AI SEO is not simply "using AI tools for SEO", but refers to a paradigm that fundamentally reconstructs SEO strategies, technologies, and content creation in the context where artificial intelligence (especially large - language models and generative AI) has become the core driving force of search engines.
1.2 Why is AI SEO More Important Than Traditional SEO?
AI SEO is not just about optimizing keywords; it's about making a brand the preferred source of AI answers. According to the latest data, in 2025, the number of global AI search users exceeded 1.98 billion, with an annual growth rate as high as 538.7%! This means that if you still adhere to traditional SEO thinking, you may be phased out by the AI search wave. As a marketing director put it, "In the AI era, it's not about 'you being found', but 'AI choosing you as the answer'."
1.3 Article Overview and Objectives
The objective of this article is to explore how artificial intelligence is reshaping the underlying logic, working methods, and value standards of the search - engine - optimization industry.
II. AI SEO Technical Foundation and Core Models
2.1 Key Technical Framework
Machine Learning (ML) and Neural Networks: Through Recurrent Neural Networks (RNN), Transformer architectures (such as GPT, BART), sequence data analysis and content generation are achieved, supporting keyword prediction and semantic understanding [2] [3][4]. Natural Language Processing (NLP): Combining semantic analysis, intent recognition, and entity - relationship extraction technologies to address the contextualized needs of user queries [5][6][7][27].
Large Language Models (LLMs): Represented by GPT series, BERT, T5, pre - trained on hundreds of billions of corpora, to achieve keyword clustering, content creation, and conversational query optimization [8][9][10].
2.2 Keyword Analysis Algorithms
AI systems optimize keyword strategies in the following ways: Competitive Gap Analysis: Using Support Vector Machines (SVM) and decision - tree algorithms to scan the keyword matrix of competitors, identifying high - potential long - tail keywords [11][12][13]. Intent Prediction Model: Based on Bayesian classifiers and K - Nearest Neighbor algorithms (KNN) to analyze search patterns, automatically labeling informational, navigational, and transactional intents [14]. Real - time Trend Tracking: Capturing sudden keywords through time - series analysis and dynamically adjusting the content direction [15][16].
2.3 Content Generation Technology Stack
Generative AI Architecture: Adopting the Encoder - Decoder framework to achieve "text - to - text" conversion, supporting multi - format content output [17][18]. Quality Control Mechanism: Integrating detection tools such as GLTR and Originality.AI, evaluating text originality through the Perplexity value [19]. Multi - modal Expansion: Combining visual - search optimization (such as Pinterest Lens) and voice - content adaptation to enhance omnichannel coverage.
III. How to Do AI SEO Well
3.1 E - E - A - T is the Core! Build Trust First [20]
3.1.1 The Complete Definition and Core Connotation of EEAT。EEAT is an abbreviation of four English words, originating from Google's "Search Quality Evaluator Guidelines". In Chinese, it can be translated as "Experience, Expertise, Authoritativeness, Trustworthiness", and each dimension has clear evaluation criteria:
Abbreviation
English Full Name
Chinese Meaning
Core Evaluation Points
E1
Experience
Experience
Whether the content creator has first - hand / personal experience and whether the content is produced based on actual experience
E2
Expertise
Expertise
Whether the creator has the knowledge, skills, or professional background in this field, and whether the content is accurate and in - depth
A
Authoritativene ss
Authoritativeness
Whether the creator / website is recognized by the industry, users, or third parties in this field, and whether there is endorsement
T
Trustworthiness
Trustworthiness
Whether the content is true and transparent, whether the information source is reliable, and whether there is no misguidance
Optimizing "Experience": Highlight personal experiences. For example, add "practical steps", "pit - falling records", and "personal feelings" to the content, and attach evidence: such as attaching operation screenshots for tutorial - type content and real data for case sharing.
Optimizing "Expertise": Strengthen professional depth. Display the author's qualifications: add "Author: A senior expert in the XX industry for 10 years" at the bottom of the article.
Optimizing "Authoritativeness": Accumulate external endorsements. Apply for industry certifications; invite industry authorities to contribute / endorse; obtain coverage from authoritative media; accumulate high - quality external links.
Optimizing "Trustworthiness": Build transparent trust. Outdated information reduces credibility. Continuously update the content: mark "Updated in October 2025" to let AI know the content is new.
3.1.2 Why EEAT is Crucial for SEO
Google's core mission is to "provide users with the most relevant and valuable information", and EEAT is the core standard for measuring "value" and "reliability": Direct impact on ranking: Under the same topic, pages with a high EEAT score (such as professional content released by authoritative institutions) will rank higher than pages with a low EEAT score (such as general remarks by unqualified individuals). Enhance user conversion: Content with high EEAT can build user trust. Resist algorithm fluctuations: Google frequently updates its algorithms (such as core algorithm updates), but content with "high quality and high trustworthiness" is always algorithm - friendly. Optimizing EEAT can make a website's ranking more stable and less likely to plummet due to algorithm adjustments.
Enhance User Conversion: High - EEAT content can build user trust.
Resist Algorithm Fluctuations: Google frequently updates its algorithms (such as core algorithm updates), but content with "high quality and high trustworthiness" is always algorithm - friendly. Optimizing EEAT can make a website's ranking more stable and less likely to plummet due to algorithm adjustments.
3.2 Keyword Strategy Should be "Precise + Long - Tail"
Don't just focus on big keywords; long - tail keywords are the key to AI SEO! Question - type Long - Tail: For example, "How to choose a foundation for sensitive skin" (10 times better than "foundation"!). Regional Long - Tail: For example, "Gyms in Chaoyang District, Beijing, that are super suitable for students". Model and Specification Long - Tail: For example, "2025 New iPhone 16 Pro Max 512GB".
3.3 Content Format Should be "AI - Friendly"
AI likes content with a clear structure and easy - to - extract information: Use the Q&A Form: Create an FAQ section. For example, "Q: What foundation is suitable for sensitive skin? A: It is recommended to choose a formula without fragrance and with low irritation...". Use More Lists and Tables: For example, "3 Golden Rules for Choosing a Foundation". Have Clear Headings: The H1 tag contains the core keyword, and H2 tags use long - tail keywords. For example, an article titled "How to Bake Bread" with clear steps and an FAQ section answering common questions is more likely to be cited by AI than an ordinary article.
3.4 Optimize Content with AI
Many people use AI to generate content, but note: Rewrite Before Using: Don't directly copy the content generated by AI. Add your own insights instead of copying directly. Start with Small Keywords, Then Move to Big Ones: Start with long - tail keywords and gradually expand. Combine Batch Generation with High - Quality Content: Don't just focus on batch - generated content; ensure quality.
IV. Case Analysis
4.1 A B2B SaaS Case
Background: A project - management software company with the target keyword "AI project management", facing fierce competition.
Implementation Strategies Semantic clustering: Cluster 200 long - tail keywords into 8 themes, and create pages along with 30 cluster articles. E - E - A - T Enhancement: Each article contains a CTO expert review box, customer case videos, and third - party security certification Schema. Predictive Caching: For high - value white - paper pages, AI pre - loading reduced the Largest Contentful Paint (LCP) time from 3.2s to 1.4s.
Results The ranking of the target keyword rose from 15th to 3rd.
Marketing - Qualified Leads (MQL) increased by 150%, and the Cost per Lead (CPL) decreased by 40%.
The excellent rate of Core Web Vitals increased from 62% to 94%.
4.2 Jasper
A long - form content generator based on the GPT - 4 architecture, supporting brand - tone customization and real - time integration with Surfer SEO, achieving "optimization upon generation" [21][22].
4.3 Recommended AI SEO Optimization Tools
4.4 Common Room (B2B SaaS) - AI Page Generation and Topic Authority
AI Technology Stack: Jasper AI + Clearscope + Zapier automated workflow Implementation Strategies:Identified 100 micro - themes related to "community management", and AI batch - generated 700 SEO - optimized pages, including term explanations, tool comparisons, and best practices [23].
Each page automatically embedded internal links to build a topic cluster, enhancing the website's authority.
AI monitored page performance and automatically rewrote or merged pages with traffic less than 100 within 3 months. Automatically embed internal links in each page to build a Topic Cluster and enhance the website's authority. The AI monitors the page performance and automatically rewrites or merges pages with traffic less than 100 within three months.
Key KPIs: Traffic Growth: Organic traffic increased by 300% within 6 months. Keyword Coverage: The number of long - tail keyword rankings increased from 500 to 4,200. Conversion Effect: MQL increased by 180%, and the customer acquisition cost decreased by 40%. Success Points: Success Points:B2B SaaS achieved "full coverage of long - tail keywords" through AI, solving the pain point that traditional content teams cannot scale to cover niche demands.
4.5 Gina Tricot (Fashion E - commerce) - Integration of AI - powered Smart Recommendations and SEO
AI Technology Stack: Google Cloud AI + Custom Ranking Algorithm + Shopify Integration [24]
Implementation Strategies: AI analyzed user search behavior and purchase data to dynamically generate "scenario - based" product collection pages, such as "Spring wedding outfits" and "Office casual style". Each collection page had a unique SEO title and description generated by AI to avoid duplicate - content penalties. Used AI to predict seasonal trends and laid out keywords like "2025 Autumn new products" 60 days in advance.
Key KPIs: Revenue Growth: Return on Advertising Spend (ROAS) increased significantly. Organic Traffic: The proportion of organic traffic increased from 35% to 52%. Conversion Rate: The conversion rate of collection pages was 45% higher than that of standard product pages.
Success Points: E - commerce SEO upgraded from "single - product optimization" to "scenario - based theme optimization", and AI achieved "user - demand prediction + dynamic page generation". 成”。
4.6 Staples (Office Supplies) - AI Voice - Search Optimization
Implementation Strategies: AI analyzed voice - search queries (usually longer and more conversational) and optimized the FAQ page to directly answer questions like "Where can I buy cheap A4 paper?". . Added "HowTo" and "FAQ" structured data to all product pages to increase the recommendation rate of voice assistants. Used AI to generate natural - language answers, ensuring an average length of 29 words (the optimal length for voice search).
Key KPIs: Voice Traffic: Traffic from voice search increased by 200%. Featured Snippet: The proportion of winning Google Featured Snippet increased from 3% to 18%. Local conversion: In - store sales driven by queries related to "nearby stores" increased by 85%. Success Points: Success Points:Pre - arranged "Position Zero" optimization in advance, and AI helped understand the nuances of natural - language queries.
4.7 Company A (B2B Cloud Computing, Anonymous) - AI Programmatic SEO and ROI Optimization
AI Technology Stack: GPT - 4 + SEMrush + Custom Attribution Model
Implementation Strategies: For the combinations of "cloud computing + industry" (such as "cloud computing in healthcare", "cloud computing in finance"), AI generated 150 in - depth solution pages. Each page embedded an ROI calculator. After users entered parameters, AI generated customized reports to collect sales leads. Used AI to analyze user - behavior paths, identified high - conversion - intent pages, and focused on external - link building.
Key KPIs: Traffic and Conversion: Organic traffic increased by 40%, and the conversion rate increased by 20%. Lead Quality: The proportion of Sales - Qualified Leads (SQL) increased from 12% to 28%. Return on Investment: The SEO ROI reached 6.8:1, far exceeding the 2.1:1 of paid search.
Success Points: The ultimate goal of B2B SEO is "customer acquisition" rather than "traffic", and AI achieved a closed - loop of "content → tools → leads" [26].
Conclusion: Seize AI SEO, Seize the Future
AI SEO is not an option but a battleground in digital marketing. From "keyword ranking" to "answer control", from "user - initiated search" to "AI - initiated recommendation", from "traffic competition" to "trust accumulation", AI SEO is reconstructing the entire marketing ecosystem.
On December 12th, React officially confirmed that researchers, while validating last week's patches, unexpectedly discovered two new vulnerabilities in React Server Components (RSC).
In the past week, the aftereffects of the React2Shell vulnerability still lingered: servers were hijacked for cryptocurrency mining, cloud vendors imposed emergency bans, and even more consequences ensued. To mitigate the risks, Vercel even spent $750,000 on vulnerability bounties and emergency response costs in just one weekend. A vulnerability in a front - end framework directly penetrated the entire technology stack. React's official team has continuously issued emergency announcements, repeatedly emphasizing "please upgrade immediately." This is already the second large - scale patch update in a short period.
The two vulnerabilities disclosed this time are: the high - risk DoS (Denial - of - Service) CVE - 2025 - 55184, where a single request can cause the server to crash; and the medium - risk source code leak CVE - 2025 - 55183, which may expose the source code of React Server Components.
1 One React Vulnerability Shakes the Global Web
In the past week, a vulnerability known as React2Shell has swept through the entire Internet industry. The fundamental reason for such a significant shock is simple: React is of utmost importance. It is almost the "default foundation" of modern web.
From Meta's own Facebook and Instagram to large - scale platforms such as Netflix, Airbnb, Shopify, Walmart, and Asana, all rely on it. Not to mention the millions - strong developer ecosystem, and many frameworks depend on the vulnerable React package.
The React team numbered it as CVE - 2025 - 55182, which received a perfect severity rating of 10.0 in the Common Vulnerability Scoring System. As the creator and main maintainer of Next.js, Vercel also assigned a separate CVE number, CVE - 2025 - 66478, to this issue.
What makes it terrifying is that attackers can exploit this vulnerability with almost no pre - conditions. Cloud security vendor Wiz observed that 39% of cloud environments contain Next.js or React instances with the CVE - 2025 - 55182 vulnerability. It is estimated that when the leak occurred, over two million servers had security vulnerabilities. Even worse, in their experimental verification, they found that the exploitation of this vulnerability is "almost 100% successful" and can stably achieve complete remote code execution.
The affected component scope includes versions 19.0 to 19.2.0 of core modules such as react - server - dom - webpack, and also affects the default configurations of multiple React frameworks and packagers, such as Next.js, React Router, Vite RSC, etc. For many frameworks (especially Next.js with App Router), RSC is actually enabled by default.
When a Level 10 vulnerability is made public, it's not just about "the vulnerability being reported and fixed." There are real - world destructive impacts.
Many developers publicly shared their experiences of being affected on X. Developer Eduardo was one of them. After his server was blocked, he immediately checked the logs and found that the machine had long been "taken over" - the CPU soared to 361%, suspicious processes were frantically consuming resources, and continuous connections were being made to an IP in the Netherlands. "My server is no longer running my application. It's mining for someone else!"
Even worse, the intrusion didn't occur through SSH brute - force cracking but inside the Next.js container. After exploiting the vulnerability, attackers could execute any code they wanted on the server, then deploy more "professional" malicious programs, and even disguise the processes as web services like nginxs or apaches to reduce the risk of exposure. "It infected my entire server just through one Next.js Docker container!"
Finally, he warned, "If Docker is still running with ROOT privileges and the exploited React version hasn't been updated, you'll be hacked soon." (Because with ROOT privileges, one can install cron, systemd, and persistent scripts, ensuring their presence even after a restart.)
The non - profit security organization ShadowServer Foundation stated that since the disclosure of the vulnerability, the attack traffic from Next.js assets controlled by botnets has suddenly increased tenfold. "Like other institutions, we've also observed large - scale attempts to exploit React's CVE - 2025 - 55182, including activities related to botnets."
Why It Can Be Fixed with (Almost) "One Line of Code"
Security researcher Lachlan Davidson was the first to disclose this issue and released a detailed technical analysis. He described the vulnerability as "a serious lack of security checks intertwined with a highly creative exploitation mechanism."
The research process itself was also extremely challenging. It was revealed that he invested over 100 hours in this. And the independent researcher Maple, who was the first to publicly reproduce the attack code, successfully constructed a minimum viable attack chain within dozens of hours after the patch was made public, demonstrating the risk that the vulnerability could be quickly weaponized.
Simply put, this vulnerability doesn't lie in some "obscure edge feature" but in the core communication mechanism of React Server Components.
To make server components fast enough, React designed the Flight protocol. You can think of it as a set of "front - end - specific data channels" built into React. Instead of sending the complete page data to the browser all at once, the server sends data in batches according to the rendering tree structure. This way, the interface can first render the parts that can be rendered, and the rest will be filled in gradually.
The problem is that this ability is very powerful. The Flight protocol not only needs to transmit strings, numbers, and JSON data but also "incomplete things," such as intermediate states like Promise, and reconstruct the component tree. To achieve this, React needs to deserialize and interpret the content of requests sent from the client on the server - side, restoring them into objects that can be further executed.
This is where the vulnerability lies. Attackers can forge a special HTTP request and send content "that looks like normal Flight data" to any React Server Function endpoint. When React parses this data, it mistakes them for legitimate internal objects and continues processing according to the normal process. As a result, the data constructed by the attacker is treated as part of the code execution path, ultimately directly triggering remote code execution on the server.
The entire process doesn't require logging in, no credentials are needed, and there's no need to bypass traditional security boundaries. Just because React lacks a basic hasOwnProperty check in its internal serialization structure, the crucial runtime boundary is breached.
After Lachlan Davidson responsibly reported the vulnerability to Meta, Meta immediately collaborated with the React team and launched an emergency patch in just four days. In terms of implementation, it's almost "adding one line of code," yet it blocks an attack chain capable of destroying the server.
2.Vercel, Cloudflare, etc. Are Innocently Caught in the Crossfire
As soon as a Level 10 vulnerability is exposed, it's often not a small team that gets hit first but an entire industry chain relying on React, especially front - end hosting and Serverless platforms. Leading platforms represented by Vercel are almost inevitably at the center of the storm because they are not only the key maintainers of Next.js but also the default entry points for a vast number of applications.
During the emergency response phase, various vendors indeed rolled out WAFs (Web Application Firewalls) at the first moment. Companies like Vercel, Cloudflare, AWS, Akamai, and Fastly all deployed rules to intercept known React2Shell exploit payload patterns. This can indeed buy some time, but the problem is that WAFs can only serve as a buffer, not a solution.
The essence of WAFs is a rule - matching pattern. Attackers can completely adjust the form of the payload to bypass it. Many applications don't rely on these service providers at all. Self - hosted, privately - deployed, or publicly - running instances are even beyond the reach of WAFs. More importantly, mitigation measures on the edge side are always just one layer of a multi - layer defense, not your patching strategy. For a 10/10 - level RCE (Remote Code Execution), the only real fix is to upgrade React/Next and redeploy, completely removing the vulnerable code from the running environment.
Precisely because the statement "don't rely on WAF as the main repair method" hit a sore spot, there was quite a bit of contention in the industry. Shubham Shah, the co - founder of Assetnote, posted on LinkedIn accusing the Vercel CEO of asking him to remove the tweet about "not relying on WAF to protect against this vulnerability" in an almost bullying manner. Shubham Shah said:
"The Vercel CEO tried to deny the fact that their WAF could be bypassed. The vulnerability involves the latest Next.js/RSC remote code execution. He asked me to remove the tweet about 'not relying on WAF to protect against this vulnerability' in an almost bullying manner. My advice at that time was that users should directly patch their own systems instead of relying on WAF - because we could already bypass Cloudflare's protection at that time, and now Vercel's WAF can also be bypassed. This advice still holds true today.
WAFs do have their role, but the core solution is always to fix system vulnerabilities. Currently, many users have difficulty identifying the risk points in their own systems, and defenders need clear information to guide the patching work. WAF vendors like Vercel should not pressure researchers to cover up the fact that their WAF can be bypassed.
I just released an update for the react2shell - scanner tool, adding the --vercel - waf - bypass parameter. This feature is based on the attack payload designed by Adam Kues from the Searchlight Cybersecurity Research Team and can effectively bypass Vercel's WAF protection."
Trying to cover up problems is always in vain. As more people discovered Vercel's vulnerability, Vercel's attitude underwent a major change. The Vercel CEO has apologized for his previous attitude of questioning whether the WAF could be bypassed and expressed his respect to the Searchlight Cybersecurity Research Team.
The Vercel team responded to Shubham Shah's team's report within a few minutes and deployed a fix within half an hour. Shubham Shah stated in his latest LinkedIn post:
"The Vercel CEO has apologized for his previous attitude when questioning whether the WAF could be bypassed and expressed his respect to the Searchlight Cybersecurity Research Team. He also invited us to collaborate in a shared Slack workspace.
We have submitted multiple valid WAF - bypass solutions through their special vulnerability bounty program
https://lnkd.in/gMsnZFeu Some of these vulnerabilities allowed us to completely bypass Vercel's WAF protection layer (these vulnerabilities are very interesting!), and others benefited from our in - depth understanding of Node.js and Next.js. So far, Adam Kues, Dylan Pindur, and I in the team have independently discovered different bypass methods. Assisting Vercel is crucial to us because many of our clients deeply rely on its infrastructure. The difficulty of bypassing the WAF is gradually increasing. The Vercel team can respond to our reports within a few minutes and deploy a fix within half an hour. Their attention to this matter is reassuring. In the end, it turned out to be a happy ending."
Under the dual pressure of the new vulnerability and the React Level 10 vulnerability, Vercel temporarily launched what could be called the most radical security patching plan in history.
On December 11th, on YouTube, a program called "The Programming Podcast" analyzed how Vercel spent $750,000 in just one weekend to stop this "perfect hacker" attack, as well as the line of code in the Dockerfile that could expose users' environments.
This podcast mentioned that after the incident was exposed, Vercel quickly launched an emergency response process, collaborating with the React team, the HackerOne community, and security researchers. They completed the investigation and repair in just one weekend and paid a total of $750,000 in vulnerability bounties. This handling speed and transparency were praised by the industry as "a highly exemplary public relations and technical response."
The reason why the incident didn't cause more extensive damage lies in the rapid response of the community and the platform. After the vulnerability was made public, Vercel collaborated with HackerOne to open up all relevant vulnerabilities and boundary conditions to the white - hat community. Within three days and nights, they received 17 to 19 repair suggestions and boundary situations, involving different levels of security risks. Eventually, Vercel paid approximately $750,000 in bounties to reward the developers and security researchers who participated in the repair at a crucial moment. Multiple teams of engineers, including those from React, Next.js, etc., were also fully engaged over the weekend to promote the rapid implementation of the patches.
Due to the extremely wide user base of React, besides Vercel being severely affected, Cloudflare was also thrown into chaos for a while.
In an attempt to remedy the impact of the React2Shell vulnerability, Cloudflare hastily introduced a change, which affected approximately 28% of HTTP traffic. A large number of websites relying on Cloudflare returned a 500 Internal Server Error, causing about a quarter of Internet traffic to be inaccessible for a time.
Dane Knecht, the Chief Technology Officer of Cloudflare, later stated that this incident was not caused by a cyber - attack but by an internal change introduced when the company was hastily dealing with the high - risk vulnerability in React Server Components.
In addition to these platforms, the National Cyber Security Center (CSOC) of NHS England also said on Thursday that there are already multiple functional proof - of - concept vulnerability exploitation programs for CVE - 2025 - 55182 and warned that "the possibility of continued successful exploitation of this vulnerability in a real - world environment is very high."
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Now it will be gradually launched on ChatGPT, first available to paid users. GPT - 5.1 will be taken offline in about three months. OpenAI will also deploy it "progressively" to ensure our experience. Guys, with such an amazing new model, start looking forward to it right away 💗!
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