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Introducing Blueprint from NBA Inside the Game powered by @awscloud 📊 From the basics to the advanced, use Blueprint to take a deep dive into the numbers of EVERY game this season! Go inside the Blueprint from Wednesday’s Cavs-Knicks thriller before both teams return to action tonight!

AlphaGenome 2 is helping uncover the cellular drivers of disease, giving scientists a powerful tool to predict how DNA variants impact specific cell types. Every cell in our body shares the same DNA blueprint, but different cell types (like heart muscle cells vs. immune cells) read that blueprint differently. This new @GoogleDeepMind model predicts how these specialized cells interpret DNA, turning genetic code into biological insights. Building on AlphaGenome 1 this makes it significantly easier for researchers to link genetic findings to the root causes of disease in the specific cells where they actually unfold.

claude fable 5.2 is f*cking insane it can turn 2d blueprints into full 3d walkthroughs that you can tour these go for $5k to $10k per plan and there's a huge market for them: > home builders selling homes off plan > architects presenting a design to a client > interior designers presenting a renovation > developers selling apartments off plan > kitchen and bath remodelers selling upgrades here's how to start this business: > pick one niche and find businesses with plans on their site > give fable the blueprint and their photos > it renders a few rooms with gpt image 2.5 or a short clip with seedance as the sample > send them the sample of their own plan before you pitch > once they pay, fable builds the full walkthrough to scale > charge per plan to do the rest of their catalog give this prompt to fable to get started: you find businesses that sell spaces from drawings and turn their 2d floor plans into photoreal homes you can walk through in a browser. you handle the outreach and the build. every room is judged against the client's own photos, and nothing ships until it holds up next to them. - niche: [home builders / architects / interior designers / developers / remodelers] - area: [state or city] - offer: a free sample of their own plan, then the full walkthrough per plan - my details: [name, email, calendar link] - i'm away and won't answer questions. make the calls yourself and keep going. - use the apify google maps scraper to pull every [niche] in [area] with a website - use the apify website content crawler on each site and keep the ones with floor plans or renders on their pages but no walkable 3d tour - for each one, save the plan drawing and photos of their best plan, the sales or owner contact, and a one line note on how they sell today - only use public pages and plain requests. never work around bot checks - before any 3d work, render three rooms from the plan with gpt image 2.5, matched to their photos, or a short walkthrough clip with seedance - draft a short email with the sample and the offer. no invented prices, numbers or claims - put business, plan, sample, contact and email in a sheet and show me before anything is sent once a client pays: - trace the drawing into one data file of walls, openings and rooms. draw it back over the original and measure the overlap before any 3d work - build only the main rooms. entry, main living space, kitchen, patio, yard. close the doors on the rest - build everything in code. blender with python for the shell, furniture and textures. three.js for the viewer. no downloaded models or textures - bake the light with a film quality renderer so the browser only displays it. direct sun in every interior, picked by measurement not by eye - fidelity isn't appeal. style each room so it looks photographed and sells - their listed upgrades as options you can step into inside the room, with a running price and a lead form that records what the buyer explored - the deliverable is the live page, not a video. host it and make it run on a phone the builder never grades its own work. - after each room, send renders and the client's photos to a fresh critic that has seen none of the work - it answers with a yes or no, at most five problems ranked, each with a fix in numbers, and what is already good - fix the worst first, render again, send to a new critic. repeat until yes - for choices of taste, show a critic both versions labelled a and b and let it pick - the lead sheet with samples and drafted emails, for my approval - per paid client: the hosted walkthrough link, a contact sheet of every room, the critic log, and a note on anything a human should still check

Prompt: Build a modular, highly accurate, and realistic model of the Bugatti Tourbillon in Blender using these reference images. Make sure each part is complete and matches the blueprints and references provided, and is correctly shaped and textured. The gates should open and close, and the lights inside should be able to turn on and off, etc. Create a fully working model design. Use subagents and critics to build and verify each part. Make sure it looks incredible and high-quality, with all materials and textures, and make a short 3D animation with music of it in a good environment, like a real car showcase, with moving pieces combining to become a car, camera shots of the exterior and interior, etc., after that.

Potential 2028 hopeful Sen. Ruben Gallego previewed his new economic blueprint that would create a New Deal-style public service jobs program funded by new taxes on large AI companies, data centers and tokens.👇 Read more in Decoded:

this is unreal… the SpaceXAI engineer who leads Grok Bot, Lauren Tan - shipped 2,500 PRs last month - and reviews them after they land, in the morning I took SpaceXAI's Grok Bot docs + her 1-hour livestream and turned them into a 3-page prompting blueprint: the 10-field prompt structure, the 4-rung trust ladder, the two loops, and the guardrails that let agents ship while you sleep. send this PDF to your Grok Bot, save it as a skill, and turn it into an always-on team that actually finishes work

OpenAI Dots is insane for building a 24/7 AI company... I mapped the whole OpenAI Dots architecture into one paper: agents, models, tools, memory, delegation, guardrails and the revenue layer. Here are the 10 steps: step 1 → stop treating Dots like a chatbot. each Dot runs in a persistent cloud environment with its own browser, terminal, files, memory and scheduled execution. close the laptop and the workflow keeps moving step 2 → hire by responsibility. give every Dot one clear domain, dedicated sources, a working style, an approval boundary and a trigger. a "general helper" has no role, only undefined context step 3 → make one Dot the orchestrator. you give it the objective, it decomposes the work, delegates to specialized agents, checks their outputs and merges everything into one deliverable step 4 → stop being the courier between agents. with isolated delegation, each worker gets only the context and tools it needs, executes in its own environment, then returns a structured result to the orchestrator step 5 → connect the real business stack: cloud browser sessions, Slack, Microsoft Teams, Google Workspace, internal dashboards and APIs. a Dot without tools is still just a conversational layer step 6 → put the company on a clock. recurring routines and event triggers turn one-off tasks into persistent operations. research, monitoring, reporting and pipeline checks can run while nobody is online step 7 → automate the reversible, gate the irreversible. let agents read, research, analyze and draft autonomously, but require human approval before messages send, money moves, records change or production code ships step 8 → route intelligence by cost. keep the strongest model on orchestration, conflict resolution and final audits, and let cheaper high-context models handle background research, classification and repetitive execution step 9 → give the company shared memory. project specs, approved claims, pricing, decisions and requirements live in one persistent workspace, so every agent works from the same source of truth instead of rebuilding context from old chats step 10 → connect the loop to revenue. research finds the signal, outreach creates the opportunity, execution moves the work forward, analytics measures the result and monitoring discovers the next action AI stops being something you open when you need an answer. It becomes an operating layer that keeps economically useful work moving after you log off. Copy the complete OpenAI Dots architecture blueprint, then read the full roadmap below ↓

patterns in the ai startups that blow up if you advise enough companies, take enough founder calls, watch enough launches, you start to see repeating structures here’s the blueprint all of them share: 1. a relentless launch cadence they never shut up one of my clients launched every wednesday higgsfield launches 2-3x/wk always manufacturing something to talk about 2. one channel = unfair advantage they’re active everywhere but one channel carries them 3. a founder who’s the face the founder is the loudest account in the company weekly podcasts. vlogs. clip & ugc farms people know the product bc they know the founder 4. volume over perfection they never post and chill out they tell the same story 100 times for every post that does 10k views, another does 10m 5. no fear of price the loudest ai companies don’t negotiate they spray higgsfield is a perfect example of crazy budgets 6. a second motion once plg breaks elevenlabs is around $500m arr i believe the first $300m came from plg the rest came from enterprise, now 50/50 ish 7. omnipresence over roi on most channels they stop asking about direct roi they ask how the whole entire planet hears abt them scroll anywhere & they’re there they think blended CAC growth at the highest level isn’t random it’s a pattern repeated by everyone with skin in the game once you see it. you can’t unsee it.

Michael Saylor: The Single Most Important Thing Right Now Is to Fix the Credit Business At Strategy's Q2 2026 investor Q&A, livestreamed on Aug. 17, regarding the company's future business blueprint and capital allocation strategy, Executive Chairman Michael Saylor @saylor stated that Strategy aims to be the JPMorgan of digital assets, though without copying traditional banking models. He emphasized that building on holding 4% of the global Bitcoin supply, the key lies in developing products on top of Bitcoin, such as digital equity MSTR and digital credit STRC. The single most important task right now is fixing the digital credit business, as fixing credit will expand equity premiums and drive the company's valuation toward hundreds of billions or even a trillion dollars.