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WordLift

@wordliftit

WordLift helps you win at Content Marketing. Focus on writing awesome content, and let us optimize your site and increase your reach.

The Internet Katılım Şubat 2013
1.5K Takip Edilen2.4K Takipçiler
WordLift
WordLift@wordliftit·
Going to #NetcommForum 2026? So are we. We’ll be in Milan talking about how AI is reshaping product discovery—and how you can turn it into real growth. 📍 Find us at the event 👋 Federica Busani
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WordLift@wordliftit·
AI doesn’t just rank products—it decides which brands to trust. On May 14, join us and Renoon to explore how Digital Product Passport (DPP) data boosts visibility, credibility, and conversion 👇 Register here 🔗 eu1.hubs.ly/H0tZBnp0 #AI #Ecommerce #Fashion
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David Riccitelli
David Riccitelli@ziodave·
@cyberandy at #seoweek — It doesn’t search It explores The KG becomes the environment A freely downloadable research paper
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WordLift@wordliftit·
𝗘-𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗲 𝗶𝘀 𝘀𝗵𝗶𝗳𝘁𝗶𝗻𝗴: Search → Click → Checkout ❌ 𝗔𝘀𝗸 → 𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱 → 𝗕𝘂𝘆 ✅ AI agents now complete purchases in chat. 𝗚𝗲𝘁 𝘁𝗵𝗲 𝗴𝘂𝗶𝗱𝗲 𝘁𝗼 𝘀𝘁𝗮𝘆 𝘃𝗶𝘀𝗶𝗯𝗹𝗲: eu1.hubs.ly/H0tHlY70 #Ecommerce #AI #DigitalCommerce
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WordLift@wordliftit·
The future of SEO, AI, and digital growth is being shaped now. SERP Conf. brings together the people driving that change, with @aleyda, @gfiorelli1, and @JudithLewis already confirmed. 𝗦𝘂𝗽𝗲𝗿 𝗘𝗮𝗿𝗹𝘆 𝗕𝗶𝗿𝗱: 𝟰𝟬% 𝗼𝗳𝗳. 🎟️ Secure your ticket: eu1.hubs.ly/H0tJ7jR0
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WordLift@wordliftit·
Is your AI giving you reliable answers about your business? Or is it still guessing? That’s the difference between AI alone and AI + Knowledge Graph. Read the article to discover why it matters👇 eu1.hubs.ly/H0tFzvz0 #AI #KnowledgeGraph #EnterpriseAI
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WordLift@wordliftit·
Publishing more content ≠ better visibility. AI search rewards connected content, not isolated pages. That’s why we’re seeing a shift toward “content compounds” built on entity SEO. Read more 👇 eu1.hubs.ly/H0tk-4P0 #SEO #AI #ContentStrategy
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Andrea Volpini
Andrea Volpini@cyberandy·
As Wikipedia evolved into Wikidata, personal wikis will evolve into linked data graphs. LLMs help extract structure. Ontologies define what matters. Linked data turns notes into memory that agents can use.
Andrej Karpathy@karpathy

Farzapedia, personal wikipedia of Farza, good example following my Wiki LLM tweet. I really like this approach to personalization in a number of ways, compared to "status quo" of an AI that allegedly gets better the more you use it or something: 1. Explicit. The memory artifact is explicit and navigable (the wiki), you can see exactly what the AI does and does not know and you can inspect and manage this artifact, even if you don't do the direct text writing (the LLM does). The knowledge of you is not implicit and unknown, it's explicit and viewable. 2. Yours. Your data is yours, on your local computer, it's not in some particular AI provider's system without the ability to extract it. You're in control of your information. 3. File over app. The memory here is a simple collection of files in universal formats (images, markdown). This means the data is interoperable: you can use a very large collection of tools/CLIs or whatever you want over this information because it's just files. The agents can apply the entire Unix toolkit over them. They can natively read and understand them. Any kind of data can be imported into files as input, and any kind of interface can be used to view them as the output. E.g. you can use Obsidian to view them or vibe code something of your own. Search "File over app" for an article on this philosophy. 4. BYOAI. You can use whatever AI you want to "plug into" this information - Claude, Codex, OpenCode, whatever. You can even think about taking an open source AI and finetuning it on your wiki - in principle, this AI could "know" you in its weights, not just attend over your data. So this approach to personalization puts *you* in full control. The data is yours. In Universal formats. Explicit and inspectable. Use whatever AI you want over it, keep the AI companies on their toes! :) Certainly this is not the simplest way to get an AI to know you - it does require you to manage file directories and so on, but agents also make it quite simple and they can help you a lot. I imagine a number of products might come out to make this all easier, but imo "agent proficiency" is a CORE SKILL of the 21st century. These are extremely powerful tools - they speak English and they do all the computer stuff for you. Try this opportunity to play with one.

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Andrea Volpini
Andrea Volpini@cyberandy·
@karpathy More organizations are building knowledge graphs because LLMs make it easier to define what internal and external agents should know. The shift is moving from flat .md files to ontology-based KB. The best domain assistants will be trained on better-structured knowledge.
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Andrea Volpini
Andrea Volpini@cyberandy·
On my way to Rotterdam for the @seobrein Meetup: we’ll explore (among other things) Google’s latest research on TurboQuant. What happens to SEO when models like Gemini have (near) infinite context? Join me ✈️ 🇳🇱 🧠
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Google Research@GoogleResearch

Introducing TurboQuant: Our new compression algorithm that reduces LLM key-value cache memory by at least 6x and delivers up to 8x speedup, all with zero accuracy loss, redefining AI efficiency. Read the blog to learn how it achieves these results: goo.gle/4bsq2qI

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