... producthunt fam, Stephan here. quick story on why I built this. I kept watching prospects ask Perplexity "what's the best X tool" and getting answers that named my competitors but never me. six months ranked #1 on Google and invisible to AI. that's the gap a lot of us are about to hit. so I built BrandCited. it tells you where AI cites you and where it cites your competitors

... support tickets across 12 industries. We clustered them by intent and generated 1,000 representative questions. We asked those same 1,000 questions to 5 AI models: ChatGPT (GPT-4), Gemini (Ultra), Perplexity (Pro), Claude (4.5 Sonnet), and Llama (3). We ran the experiment daily for 30 days. We tracked every citation at the source level. The goal: measure citation overlap. How often do these models cite the same source for the same question? The dataset: 1,000 questions ... ... models, the same source was cited in only 23.7% of answers. That means 76.3% of the time, the models were pulling from different places. Model Pair Overlap (%) ChatGPT Perplexity 41.2% ChatGPT Gemini 31.8% ChatGPT Claude 19.4% ChatGPT Llama

... months ago, we ran an experiment with our own data. At Rankfender, we tracked 5 of our own competitors across 8 AI systems. We log their share of voice, citation velocity, content gaps, platform variance. Months of raw numbers sitting in a dashboard. I pulled 6 months of data and fed it into Claude. One question: "Based on this, who is most likely to overtake us in the next 6 months? Show your work. Use the data. Don't summarize ... ... Give me the numbers." The answer changed how I think about competition. The dataset: 5 competitors

... That compress the KV cache (the biggest memory bottleneck during AI inference) by up to 6x with mathematically proven quality preservation. In plain terms: your AI models now use a fraction of the memory without getting dumber. Before vs After On a 16 GB machine: - Before : Llama

... Today, I am shipping v1.0.5 , and we are taking that philosophy to its ultimate conclusion. What s New in v1.0.5: Local AI (Ollama) Integration: You can now connect BrainLoom directly to your local Ollama instance. Run powerful models like Llama3 or Qwen entirely offline. Zero API costs. 100% total privacy. You can now feed your most confidential study materials to the AI, and the data literally never leaves your laptop. Live Flashcard Decks on the Canvas: You can now drop ... ... paid Founders and are officially in the "Architects" batch (Lifetime License is currently $34). Challenge for the Tech Crowd: Download the free trial, turn your Wi-Fi completely OFF, and try generating a flashcard deck using a local Llama

... connects directly to GSC and runs real-time analysis across 50+ SEO aspects: Top Page and Query Performance Top Mover Delta Analysis Growth and Decay Analysis Performance Trends Rank Disparity Analysis CTR Uplift Analysis Impression and CTR Segmentation Brand vs. Non-Brand Performance Cannibalization Analysis Topical Cluster Performance Device Parity Analysis Device Distribution Country Performance Long Tail Performance Trust and Authority Analysis Then it doesn't just report it. It moves from Performance Opportunity Analyze Fix Apply. Automatically. Comes with ... ... Search Audit Issues Suggestions Fix Apply Covering single URL audits, bulk URL audits, and full site audits. Then: AI Brand Visibility Brand Analysis Prompt Run Prompt Tracking Competition Tracking Citation Tracking Monitored across Gemini, ChatGPT, Claude, Perplexity, Grok, and LLaMA

... like button. Benchmarks, benchmarks, benchmarks Benchmarks should always be taken with a grain of salt . They are effectively a snapshot of a models capabilities under near perfect conditions. Sort of like the Big Mac you see on the ads vs the Big Mac you get in the bag. It gives you a good idea, but they're far from a perfect measure of real world usage. Math (AIME 2025, no tools): 94.6 percent Real-world coding (SWE-bench Verified ... ... Multilingual programming (Aider Polyglot): 88.0 percent Multimodal understanding (MMMU): 84.2 percent Medical reasoning (HealthBench Hard): 46.2 percent Graduate-level logic (GPQA without tools, via GPT-Thinking Pro): 88.4 percent In production, GPT-5 Thinking cuts hallucinations by 45 percent versus

... they say, it feels to me like the nightmare of AI, because everything moves so fast and everyone is building more stuff (and barely maintaining it) There are a lot of AI frameworks to begin with: LangChain. LlamaIndex. AutoGen. CrewAI. DSPy. OpenDevin. Semantic Kernel... They re all trying to answer one basic question: 'The best way to reliably interact with an LLM so that you can bolt things like memory, tools, and MCP to your AI agent' Everyone Wants ... ... contexts, ephemeral memories, and LLMs that hallucinate confidently, making up stories. So each platform has a different belief system, each one with a large group of fans backing them up: LangChain says: break the world into tools and chains. LlamaIndex

... Meta just launched the Llama Startup Program, a new initiative to empower early stage startups to innovate and build generative AI applications with Llama

... Yesterday, Meta announced that they have released a new collection of AI models, Llama 4 , in its Llama

... everyone! I m part of the team behind Ontosight.ai , a platform that helps researchers, clinicians, and data scientists turn complex biomedical data into real insights. We just integrated Meta s LLaMA 4 into our platform, and the results have been wild. Here s what you can now do with Ontosight + LLaMA

... name is Diego, I'm the Startup Lead in the AI Partnerships team at Meta. If you are a startup using Llama to build AI-powered products/services, I'd love to learn more about what you're doing! How are you using Llama

... Introduction: Hey Product Hunt! my name is Diego Guerra and I'm the Startup Lead in the AI Partnerships team at Meta. Meta is excited to see startups using Llama to build incredible products and services. To refine our model and make it the best possible resource for startups, we need your detailed feedback in these key areas: 1. Ease of Integration: How smooth is the integration of our model into your existing tech stack? What hurdles did you face ...

... everyone! My name is Diego Guerra. I work at Meta and I'm the Startup Lead in the AI Partnerships team. If you're building on Llama, I'd love to learn how you're using ...

... ChatGPT/ Claude/ Llama almost daily for copy-writing, brainstorming, coding. But I have this FOMO that I may not be fully utilizing the power of AI to work more efficiently and productively. Which tools are you using other than ChatGPT for productivity? Let me know ...

... used to compare Llama 2 7b, 13b and 70b (chat-hf fine-tuned) vs

... Meta just made it's Large Language Model, Llama2 free for commercial use. You can use it in your projects without paying any licensing fee or api costs. So just host and use.. What would you like to build with ...