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4 Kommentare

Profilbild von Ben Emmerich
Ben Emmerichvor 1 Jahr

Now that is impress. This may bankrupt me 😂

Profilbild von Rahimah X CytronMY
Rahimah X CytronMYvor 1 Jahr

Wow! Love the colourful.😍

Profilbild von Chief Prototypist
Chief Prototypistvor 1 Jahr

fast hand!!

Profilbild von Johnfreedom90
Johnfreedom90vor 1 Jahr

No thanks

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let’s start where this actually lives, not where you want it to live. with the math. the last three weeks of dynamite: 👉 765k 👉 730k 👉 654k that is not a ramp. that is not momentum. that is not “heating up” into a conversion window. that is a decline into it. you are looking at a -111k drop in two weeks, roughly 14–15% contraction from the high to the low, at the exact point where a traditional ppv cycle should be stabilizing or expanding. instead, you have compression. average those three weeks and you land at roughly ~716k linear viewers. that is your real, observable, measurable audience. not hypothetical reach not cumulative impressions not social engagement proxies actual people sitting down and watching the show in the time slot that matters for conversion. i’ve already laid out in detail what the max numbers actually represent and how simulcast behavior works, so i’m not going to re-litigate all of that here. but it matters enough to say again clearly: max is not a second audience at scale. it is a distribution extension that splits the same audience. it does not double your reach. it does not materially expand your funnel. it shifts a portion of existing behavior from one pipe to another. the short version is already established: 👉 max is not additive at scale 👉 max is a split of the same audience 👉 max realistically contributes ~50k–150k, ~75k center so your total reachable audience on a good night is: 👉 ~790k–800k all-in that’s the funnel. that’s the ceiling. that’s the number you are working from. that’s the universe that can possibly convert into a paid transaction. not hypothetical not inflated not “what if” that is the real audience number. now take the number dave is floating: 👉 ~143k ppv buys run the only equation that matters: 👉 143k ÷ 800k = ~17.9% conversion stop there for a second Dave Meltzer is unironically asserting that nearly 1 out of every 5 viewers is converting into a $40–$50 transaction in 2026 in a market with: – no centralized ppv infrastructure – subscription-first behavior – widespread piracy – fragmented pricing (domestic, max discount, vpn international) – a declining weekly audience trend that is the claim. not “strong performance.” not “better than expected.” not “up year over year.” the claim is nearly 1 in 5 viewers converting into a $40–$50 transaction in 2026. this is where the conversation should end, because that number does not exist anywhere in modern media behavior. it doesn’t exist in boxing. it doesn’t exist in ufc. it doesn’t exist in any scaled transactional model operating in the current environment. and more importantly, it didn’t exist consistently even when the infrastructure supporting it was intact. again, this is the part people either don’t understand or choose to ignore: ppv is not just a pricing model. it is an infrastructure model. and that infrastructure is gone. for decades, the backbone of ppv was inDemand. that system wasn’t just pushing content out to cable homes. it was aggregating buys, standardizing reporting, and creating a reconciliation layer that allowed promoters, distributors, and networks to operate off the same dataset. if you were serious about this business, you could triangulate numbers. you could get within a narrow band of reality because the pipes were real and the accounting was shared. that system shut down in 2025. 👉 143k ppv buys is not an aggressive take 👉 it is not an optimistic take 👉 it is a structurally impossible take because we know what real conversion looks like. we do not need to guess. it has been modeled across combat sports, boxing, ufc, and multiple transactional platforms. the ranges are stable: 👉 1–3% → normal 👉 3–5% → strong 👉 5%+ → elite and rare, reserved for events with massive cultural heat and crossover appeal those ranges were established when the infrastructure was intact, pricing was more controlled, piracy was less frictionless, and distribution was more centralized. today, every one of those conditions is worse. pricing is fragmented. you have $49.99 standard, $39.99 through max, international pricing accessible through vpn, and a piracy environment where high-quality streams are available instantly. that is a high-friction, high-leakage system. so conversion should compress, not expand. now apply real-world conversion to your real audience: 👉 800k × 2% = 16k buys 👉 800k × 3% = 24k buys 👉 800k × 5% = 40k buys that’s your range. 👉 ~15k–35k realistic 👉 ~20k–30k as the most defensible center 👉 ~40k reasonable given the strength of the headliners now invert the math, because this is where the claim completely collapses. if you want to justify 143k buys at even a healthy 3% conversion rate, you need roughly 4.7 million engaged viewers. so the question becomes extremely simple: where are the other four million people? 👉they are not on linear television. 👉they are not on max. 👉they are not showing up in any digital engagement metrics that correlate with that level of demand. 👉they are not visible anywhere in the ecosystem that would need to exist to support that level of conversion. 👉👉👉👉👉 they do not exist. and this is before you even account for the trend line moving the wrong way. you are not converting off a growing base. you are converting off a shrinking one. you are not building urgency. you are losing reach. that matters, because conversion does not happen in a vacuum. it happens on top of momentum, visibility, and audience expansion. when those inputs are declining, conversion does not spike to historic highs. it compresses further. the biggest fights in the world are no longer relying on ppv as their primary distribution model. they are moving to platforms that guarantee reach and revenue up front. the most recent example should end this conversation for anyone actually paying attention: netflix just locked tyson fury vs anthony joshua for a major global fight this august. that is one of the biggest possible matchups in boxing. in any previous era, that is a premium ppv event with massive buy expectations, heavy marketing, and a full transactional rollout. instead, it is going to a subscription platform. why? because the economics are better. the reach is global. the friction is lower. the platform values engagement at scale over one-off purchases. that is where the industry is. so when you are being asked to believe that a weekly wrestling property with a ~700k linear audience, declining into its ppv window, is somehow generating six-figure transactional buys inside a subscription platform in 2026, you are not just being asked to accept a number. dave is asking you to ignore the direction of the entire market. and that’s before you even bring in platform behavior. max is not a live sports-first platform. it does not behave like one. when max has something it cares about, it promotes it aggressively. homepage rails. push notifications. press releases. talent integration. cross-platform amplification. you do not see that here. and that absence is not accidental. platforms surface what they want you to see. they amplify what drives engagement and revenue. if ppv at scale were happening inside that ecosystem, it would be visible. it would be part of the narrative. it would be monetized loudly. it isn’t. and that’s before you even factor in the other variables i’ve broken down in detail before: 👉 i’ve already debunked why the max numbers people are throwing around don’t make sense 👉 i’ve already explained what the linear number actually represents and what it doesn’t 👉 i’ve already mapped the media rights landscape in 2026, including how these properties are being evaluated ahead of the paramount–wbd merger the wsj reports could close as early as july so when you’re being told by dave that a property with a ~700k weekly audience trending downward into a ppv window is generating six-figure transactional buys at premium pricing inside a subscription platform in 2026, you’re not being given data. you’re being given a number that does not reconcile with anything else in the system. that’s math. stop it - 45

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Bitcoin Virtual Machine

32,165 Aufrufe • vor 2 Jahren

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Rae 🍽️

145,290 Aufrufe • vor 11 Monaten

Here's a copy/paste prompt recipe and vid showing exactly how to ask an LLM for an interactive map with satellite/map layers + a georeferencer that lets you see how old maps correspond with modern geography. Today the computer can’t make good print maps (that's your hill to climb ) but it can, with five bucks and twenty minutes, make good interactive maps. No software/GIS knowledge necessary, you just need a few nouns and an LLM. Scroll to the bottom for the repo/live map if you want those. I'm using Claude Code as an extension in VS Code but you can use the Claude CLI, Cursor, whatever. 1) Let's grab an old cadastral map and see who owned big tracts of a city; I found this an 1854 map of Niagara Falls, NY I found in the Library of Congress: , grabbed the .jp2, saved as a jpg from photoshop. 2) Let's ask Claude Code for a map. You can see exactly what I did in the video but my prompt, sans simple "hey it's busted" debugging, is written out in the following paragraphs. I explain the map-specific nouns in brackets. You can likely dump this whole thing in your LLM window and it'll work; I'd try plan mode + skip permissions. THE PROMPT Make an interactive map with MapLibre GL JS [maplibre is a javascript mapping library, a FOSS version of Mapbox GL JS. This lets us display tiled map data and arbitrary images on the map] Add basemap toggles with Esri satellite, Carto Positron, and OSM [these map layers require no API keys for light usage; Carto Positron is a nice road map layer and OSM is ugly but comprehensive] Add a globe/mercator projection toggle [I think the globe looks better at low zooms] Add a layer panel on the left with visibility checkboxes and delete buttons. Add a search box on the map that flies to results, with deletable pin markers [Makes this easy to get to your area of interest] Include an interactive local georeferencer: drop a JPG, pick ground control points on a zoomable/pannable image viewer, place them on the map, watch it warp with a progress bar centered on the map. [The georeferencer uses math ("affine transform"??) to match points on the old map to points on the new map; generally you click road intersections on the old map, match them on the new map, repeat a dozen times and everything aligns] The georeferenced map overlay defaults to 25% opacity with a slider above the control point list. [I want it easy to see the underlying modern geography] Add Export/import control point buttons [this saves the control points as a JSON so you can save and reimport your work] Add a button to export the warped image as a GeoTIFF with a .prj [In case you want to add the georeferenced image to a real GIS program like QGIS] Look up all relevant docs before starting [Claude sometimes uses outdated stuff] Split everything into separate HTML/CSS/JS files [Claude tends to pile everything in index.html, which is hard to read] Use Optima font, base color #FEFAF6 [I just like this style] Let me test with a local server [it serves it on a simple server so you can nav your host to localhost:8000 and try it out] Log all errors [so you don't have to play telephone with the LLM describing what's busted] 3) Once your LLM finishes, test it out in your browser; if it doesn't work, ask the LLM to check logs. Repeat 'til functional. 4) After this works on your computer, you can show it to everyone by hosting it on GitHub: prompt with "write a README explaining what everything does, add it to a new GitHub repo, deploy using GitHub pages, gimme the live URL" Here's what Claude made for me, try it yourself: • Upload the JPG in the repo, which is linked below • "Add GCP" • Click somewhere recognizable on the old map, like the tip of an island or a road intersection • Click the matching point on the new map • Repeat til you have least 3x points • Hit "georeference" • You'll see the old map atop the new map; if you want a better fit, delete bad points or add a dozen new ones, hit georeference again, repeat Repo: Is this map robust? Human-maintainable? Elegant? Performant? Secure? No, but *your* personal web map need not be. It just needs to work for *your* narrow use case, because it’s *your* map.

Evan Applegate

15,772 Aufrufe • vor 6 Monaten

🧬 BREAKING: Our CRISPR-GPT paper is out TODAY in Nature Biomedical Engineering Nature Biomedical Engineering ! 🤯 We built an AI agent that turns ANYONE into a gene-editing expert in 1 DAY instead of months. An undergrad with ZERO experience achieved 90%+ editing efficiency on their FIRST attempt. 🧵 Here's how we're building expert AI agents for cutting-edge biotechnology: 🎯 The Problem: CRISPR is revolutionary but requires PhD-level expertise, it can take weeks to learn, adopt, and design, analyze a CRISPR experiment for R&D or making life-saving medicine. Even Pro scientists can make small mistakes (e.g. typos in guideRNA or cloning design) that cost months to find out, slowing us down. 💡 Our Solution: CRISPR-GPT - an AI co-pilot from Stanford University Princeton University Google DeepMind that guides you through EVERY step via simple conversation 🔬 Real Results: -Novice researcher: ~90% editing on 1st go -Training time: Months → 1 day -100% success rate in our trials -Even experts save days/weeks on data analysis & troubleshooting 🤖 How it works: Our multi-agent system handles: CRISPR system and delivery method selection, guideRNA design, Protocol generation, Real-time troubleshooting, Data analysis, and beyond. All through natural language! No coding, no complex software. 📊 We benchmarked it extensively: -288 evaluation scenarios/cases -Outperformed GPT-4o on ALL gene editing tasks -Trained on 11 years of expert discussions -Covers knockout, base-editing, prime-editing & epigenetic editing 🌍 Why this matters: -Every lab can now use CRISPR with an AI system distilling expert knowledge and skills. -Every student can learn faster. -Every researcher can tackle bigger challenges without worrying about small mistakes. -Customized CRISPR design can be automated based on your need and the context of R&D workflow. -Agentic AI ensure safety, privacy, and responsibility -We're not just automating gene editing - we're using AI to power scientists to cure diseases. 🚀 Try it yourself! Beta access available at: Paper: Code: Benchmark (companion work, Genome-bench): Co-first and key authors: Yuanhao Qu Kaixuan Huang Ming Yin PIs: Le Cong@Stanford, AI+Bio+Gene-Editing Mengdi Wang Key collaborators: Russ Altman Denny Zhou The future of biology and science is conversational. The future is now. Nature Biomedical Engineering Nature Portfolio #CRISPR #AI #GeneEditing #Biotech #Science #AISafety

Le Cong@Stanford, AI+Bio+Gene-Editing

111,923 Aufrufe • vor 1 Jahr