Search is changing.
Websites are no longer competing only for rankings. They’re competing to be understood and recommended by AI.
At Megh Designs, we build AI-first websites with the right structure, context, and content architecture so LLMs can understand what you do and surface your business with confidence.
#aidriven #webdevelopmentmadison #smallbusinessmadison #madisonWI
Andrej Karpathy, a former director of AI at Tesla and founding team member at OpenAI , announced that he had joined Anthropic, the AI safety company behind Claude.
He believes the next few years at the frontier of LLMs will be especially formative. He is very excited to join the team and get back to R&D. He remains deeply passionate about education and plans to resume his work on it in time.
🎉MSI EDGEXPERT AI SUPERCOMPUTER IS HERE!🎉
Learn more about MSI EdgeXpert that has an NVIDIA GB10 SoC supercomputer-level chip in a size of mini PC! Planning to run your own AI agents powered by the world's best LLMs? This mini supercomputer is all you need to get started!
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Every LLM gives a different answer and now I’m the judge #trending #reels #viral #support
Should you understand how LLMs work, or can you just use them?
You do not need a PhD in machine learning. You need to know one level below where you operate.
Most AI engineers will not train models. They integrate them. The exceptional ones know how LLMs actually work: no memory between calls, attention picks what matters, concepts live in vector space.
That is enough to pick the right primitive, not the popular one.
Link in bio → 3 free interactive challenges. 5 minutes.
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#aiengineering #llms #softwareengineering #careeradvice #systemdesign #vectordatabase #rag #juniordeveloper #techcareer #embeddings #ai
Learn how LLM works visually, website link in video
#chatgpt #ai #llm #genai #techexplained
Harvard researchers ran 15,000 strategy prompts through 7 LLMs.
Every model gave you the same trendy answer.
96% chose differentiation. 93% chose augmentation. They call it "trendslop" — buzzy advice dressed up as strategy.
Adding more context to your prompt? It only shifted the answer by 11%. The bias is baked in.
5 rules for using AI in your strategy work:
1. Use it for options, not choices
2. Watch for the hybrid trap (when AI says "do both")
3. Test the opposite answer to expose the bias
4. Demand concrete examples before you act
5. Keep the final call human
Save this for your next planning meeting.
Follow @davesaunders for daily founder moves → davesaunders.net
#founders #aistrategy #leadership #criticalthinking #foundersjourney
Comment “AI” and I’ll send you the link to the AI roadmap course!
If you’re not building AI skills in 2026, you’re already falling behind.
Here are 5 high-value certifications that can make your profile stand out to top tech companies and startups 👇
1. Andrew Ng’s Generative AI Specialization (DeepLearning.AI)
A hands-on program covering LLMs, prompt engineering, RAG, and real-world AI applications.
2. AWS Certified AI Practitioner
Beginner-friendly and highly recognized by recruiters across cloud and AI roles.
3. Google Cloud Machine Learning Engineer
Ideal for developers who want to work on production-grade ML systems.
4. NVIDIA Deep Learning Institute
Practical training in LLMs, computer vision, and GPU-accelerated AI.
5. Stanford Machine Learning Specialization
A world-class foundation in machine learning taught by leading AI experts.
These certifications are especially useful for:
• Software Engineers
• AI/ML Engineers
• Data Scientists
• Cloud Engineers
• Product Engineers
#ArtificialIntelligence #MachineLearning #SoftwareEngineering #GenerativeAI
Episode 222: Can you trust every citation in a scientific paper? Professor Harlan Krumholz discusses how the rise of LLMs has contributed to an increase in fabricated citations.
Listen to the full episode of #HealthAndVeritas at the link in our bio.
#yale #healthandveritas #fyp #explore
Comment "ai" and I'll send you the full path - seven free resources, in the exact order to open them.
Most people trying to learn AI engineering quit in the same place. They treat it as one subject. It's seven, stacked - Python, machine learning, math, LLMs, RAG, building, agents. Each layer only makes sense once the one below it is solid.
The good news is the best resource for each layer is free, and most of them are taught by the people who literally built the field. Andrew Ng, Andrej Karpathy, the LangChain team. You don't have to go looking for them.
The hard part isn't access. It's the order. The temptation is to skip Python and jump straight to agents because agents look like the fun part. The people who actually finish this path don't.
Six months from now you either walked it or you didn't.
The whole world of GenAI is built on LLMs and predictive analytics. Both are probabilistic. Neither is deterministic.
If you look at AI infrastructure right now, there are two pillars holding everything up. Both of them are stochastic. Both operate in a space where we don't fully understand why they work. And then there is a massive amount of use cases sitting on top of that foundation. From a symmetry standpoint, the structure has an obvious gap. If you have a stochastic foundation, you need some deterministic component. Not because it makes the system feel architecturally complete, but because in any domain where correctness is the product, approximate is not close enough.
Axiom is an inevitable addition in all possible futures of AI infrastructure. Not because we are ambitious about our own prospects, though we are, but because the logical structure of the stack requires it. A formal proving layer isn't optional, any more than a type system is optional in software that needs to be trusted.
On the latest episode of Founded & Funded, our Founder Carina Hong joined Madrona's Matt McIlwain to talk about what Axiom is building and where it's going.
Watch the full discussion here: ordnl.link/Sc2McUs