"Exploring LLM Quantization Formats and Methods"

Most people wonder why their AI images still look fake. It’s not the model’s fault. It’s your prompts. Here’s the truth 👇 LLMs and image models don’t think in “natural language.” They think in structure. That’s why I have developed a Nano Banana prompting framework that speaks the model’s native language and delivers hyper-realistic results. I made a 1-page cheat sheet so you can start using it today: → The core JSON formula → Quick examples for portraits, products, and nature → Pro tips to boost realism Save this guide — because if you want world-class outputs, you need to start prompting like the pros.

Most businesses are still stuck optimising for keywords. But today’s search engines reward context-rich, natural language content that solves real problems. Here’s what matters most in search optimisation:

OpenAI's GPT-4 is revolutionizing the way we approach translation. With its ability to understand contextual nuances, it outperforms traditional methods. Businesses can now ensure their communications resonate with diverse audiences by leveraging this tool for tailored translations. Clear prompts and post-translation reviews will maximize its potential.

Exciting news in the world of content delivery! 🚀 Ever thought about how you can make Large Language Models (LLMs) a bit more... user-friendly? Our latest blog post dives into the magic of the Accept header. Say goodbye to the clunky HTML and hello to sleek, efficient Markdown! Discover how this simple tweak can elevate your AI interactions and streamline your content experience. Ready to upgrade how you serve information to your LLMs? Click the link to read the full post: https://ift.tt/u4Wweb1. Happy reading!

AI answers from large language models (LLM) interactions and Search Engine results (SERPs from page ranking) are more different than they we might think. Search says: “You can find the answers in this set of places.” AI says: “Here is your answer.” Search Success = Being chosen from the shelf. AI Success = Being mentioned and cited within the agent's conversational reply. To make the comparison more crisp, search engines can be thought of as "Large Page Models (LPMs)." Like librarians, they catalog and rank whole pages, then hand you a curated list of containers to explore in the form of the SERP. LLMs are pageless. Like research assistants, they work directly with the language inside those containers. Where the two converge is in retrieval-augmented generation: —> Search as Gatekeeper (Librarian Stage): surfacing candidate sources. —> LLM as Arbiter (Research Assistant Stage): chunking sources into passages and synthesizing an answer. Where they diverge is in their signals of authority. Search leans on SEO and keyword weight. LLMs lean on linguistic authority: the density, clarity, and credibility patterns in the language itself, which is why being rank-worthy doesn’t always make you citation-worthy and vice-versa. What makes you citation-worthy? While some aspects remain black-boxed by LLM platform, we know that content surfaces in model responses when it demonstrates semantic density (ideas linked, not just keywords), conceptual clarity (claims that stand alone), linguistic authority (patterns that signal expertise), structural usability (passages easy to identify and reference), and contextual richness (answers that feel complete and connected). When you can begin to combine page and domain authority with precise language and informational authority, you can find concurrently target both the classic Web searching process and the fast emerging LLM-driven answering process. #searchengines

What’s one way you’ve used AI to simplify a task? I've found AI tools like language models super helpful for catching grammar errors and polishing my writing. It's a game-changer for producing high-quality writing.

🌐 AI-generated websites are here—but are they SEO-ready? With the power of Large Language Models (LLMs), businesses can create high-quality, intent-driven content, optimize technical elements, and adapt to evolving search trends. 🚀 👉 Read the full article:- https://lnkd.in/g32cfAZt #AI #LLMs #DigitalMarketingSEOSeo Rank

Large Language Models (LLMs) can be used beyond writing or evaluating text—they can process and create content across formats. This opens exciting new possibilities for how we as scientific communicators develop continuity of message and visualization across channels. Here are 5 examples of cross format use cases: #MedicalAffairs #GenAI #Storytelling #MedicalCommunications #Story #MedAI

AI native product building is still far less mature than AI research. I believe fewer than 20 companies globally have depth in building AI native products. Evidence? deep in your bones intuition - how many do you actually love using? Most interesting AI-native products will look nothing like a prompt box - they’ll feel new, obvious in hindsight, and built for customers we aren’t even serving yet.

What makes GEO different from traditional SEO and SEM? First, it’s AI-powered. We use advanced keyword modeling designed for voice and natural language queries. Second, we implement structured schema markup so AI engines can easily understand and recommend your business.