Max out the ram to 512. 256 gb is not future proof nor upgradable.

Q3, recently:

📸¿Solo tienes selfies y quieres lucir profesional? GUARDA este PROMPT para que Gemini transforme tu selfie en una foto de estudio lista para tu CV o tus perfiles profesionales. 1. Abre Gemini 2. Sube tu selfie 3. Ingresa el prompt 4. Genera tu imagen

Friday night. 3 Claude Code agents running. Hands-On Machine Learning with Scikit-Learn and Pytorch ebook next them My AI agents building out 3 multi-million $$ ideas while I study machine learning and grow the size of my brain 10x I feel bad for people going out getting drunk

I ❤️ @obsdmd @kepano

AI agents are getting better at looking at different types of data in businesses to spot patterns and create value. This is making data silos increasingly painful. This is why I increasingly try to select software that lets me control my own data, so I can make it available to my AI agents. Because of AI’s growing capabilities, the value you can now create from “connecting the dots” between different pieces of data is higher than ever. For example, if an email click is logged in one vendor’s system and a subsequent online purchase is logged in a different one, then it is valuable to build agents that can access both of these data sources to see how they correlate to make better decisions. Unfortunately, many SaaS vendors try to create a data silo in their customer’s business. By making it hard for you to extract your data, they create high switching costs. This also allows them to steer you to buy their AI agent services — sometimes at high expense and/or of low quality — rather than build your own or buy from a different vendor. Unfortunately, some SaaS vendors are seeing AI agents coming for this data and working to make it harder for you (and your AI agents) to efficiently access it. One of my teams just told me that a SaaS vendor we have been using to store our customer data wants to charge over $20,000 for an API key to get at our data. This high cost — no doubt intentionally designed to make it hard for customers to get their data out — is adding a barrier to implementing agentic workflows that take advantage of that data. Through AI Aspire (an AI advisory firm), I advise a number of businesses on their AI strategies. When it comes to buying SaaS, I often advise them to try to control their own data (which, sadly, some vendors mightily resist). This way, you can hire a SaaS vendor to record and operate on your data, but ultimately you decide how to route it to the appropriate human or AI system for processing. Over the past decade, a lot of work has gone into organizing businesses’ structured data. Because AI can now process unstructured data much better than before, the value of organizing your unstructured data (including PDF files, which LandingAI’s Agentic Document Extraction specializes in!) is higher than ever before. In the era of generative AI, businesses and individuals have important work ahead to organize their data to be AI-ready. P.S. As an individual, my favorite note-taking app is Obsidian. I am happy to “hire” Obsidian to operate on my notes files. And, all my notes are saved as Markdown files in my file system, and I have built AI agents that read from or write to my Obsidian files. This is a small example of how controlling my own notes data lets me do more with AI agents! [Original text: deeplearning.ai/the-batch/is… ]

Once you learn how to use the Shortcuts app properly, it’s over. Greatest iOS app ever made.

Why intelligent people are always alone - Alan Watts

How Telegram CEO starts his presentation

"Nobody ever complains about gravity." — @JackCanfield

Dark mode isn’t a preference; it’s a personality trait.

👀

if you're wondering why you're hitting your limits on claude usage...

This is going to break your brain 🤯 New research just proved that being RUDE to AI makes it smarter. Penn State researchers tested ChatGPT-4o with 250 questions across 5 politeness levels. The results are wild: - Very polite prompts: 80.8% accuracy - Polite prompts: 81.4% accuracy - Neutral prompts: 82.2% accuracy - Rude prompts: 82.8% accuracy - Very rude prompts: 84.8% accuracy Statistical tests confirmed this isn't random - impolite prompts consistently outperformed polite ones. Here's the kicker: older models like GPT-3.5 behaved the OPPOSITE way. But GPT-4 and beyond? They actually perform better when you're harsh. Stop saying "please" to your AI. Start getting results.

By popular demand, we're rolling out another fix today: You can now view the customization prompt used for your studio outputs! 🥳 Whether it's audio or video overviews, flashcards, or quizzes, just tap the three dots by the output to revisit your creative genius.

Very soon

New on the Anthropic Engineering blog: tips on how to build more efficient agents that handle more tools while using fewer tokens. Code execution with the Model Context Protocol (MCP): anthropic.com/engineering/co…