
Founder @wakeout (Apple App of the Year). This is the most sedentary age in history. I'm here to change that. Father, AI optimist, philosophy and sci-fi lover.
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Joined May 2009
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Google’s “don’t be evil” days are long gone.
As someone who has personally spent $500k / mo+ on Google Ads for years, I can tell you with certainty:
This revenue growth in Search is artificial & extremely unhealthy for Google’s business long term
Search volumes are declining as legacy search is being increasingly cannibalized by non-monetized LLM queries
Google’s response?
Manufacture revenue growth via short-sighted, highly extractive, customer-hostile tactics. I.e. charge advertisers more for lower quality clicks, including clicks they do not want and explicitly did not approve Google to charge them for
A few examples to illustrate:
For all of its history until recently, Google operated on a 2nd price auction model
I.e. if you bid $5 CPC and the next highest bidder bids $1 CPC, Google charged you $1.01 for the click (one penny more than the 2nd highest bidder) rather than the $5 you bid
This was a genius move by Google early on as it incentivizes advertisers to input their true maximum willingness to pay rather than trying to play the game of bidding low and constantly adjusting to try to stay just ahead of the next highest bidder while still not paying too much
However recently, Google silently deprecated the 2nd price auction and began charging advertisers as much as their bid and budget caps allow, regardless of what anyone else is bidding
It’s a short-sighted cash grab at the expense of the long term health of the advertiser ecosystem
Making thing worse, Google also recently nerfed keyword targeting precision
Google previously had precise keyword targeting settings that allowed advertisers pick individual search phrases to bid on, defined down to the character w/ exact match or phrase match targeting
This was one of the core features that made search advertising magic, enabling advertisers to run extremely precise campaigns based on exactly what their target customer typed
But now, even if you bid on a specific term or phrase using the strictest exact
-match targeting settings, Google will show your ad across 1000’s of unrelated keywords, labeling them as as “exact match (close variant)”
The definition of “close variant” means whatever they want it to and changes constantly. The result is advertisers get billed for clicks that are totally irrelevant to their business and that their targeting settings explicitly forbid Google from targeting. Google does it anyway and there’s no ability to turn this off
So now exact match is broad match, and broad match is just meaningless spam
This is all very bad for advertisers, but for Google, it allows them to show your ad and bill you for clicks across 1000x more searches that were previously going unmonetized (mainly because they’re garbage queries no one wants)
This is how you grow revenue atop declining search volumes
Lastly, and perhaps most egregiously, Google quietly stopped respecting budget caps by a factor of 2x. For example campaigns we’ve been running for years with $1000 daily budget caps suddenly began spending $2000+ per day
And the extra spend is entirely on the garbage keywords Google arbitrarily throws in as “exact match (close variants)” which have no value to our business, but can’t be turned off
Google offers no refunds nor any recourse for overspend or spend on keywords you explicitly did not target
These are not the actions of a healthy business. These are the actions of company whose core business is in decline but desperately needs to pump quarterly earnings so Wall Street will continue to fund insane capex while hopefully looking through their rapidly deteriorating negative free cash flow
Google operated a benevolent monopoly for the better part of 25 yrs
Meaning the value Google captured from Search was but a small fraction of the value it created, and that spread produced a potential energy that justified expectations of high earnings growth far, far into the future
This is now no longer the case
At the alter of AI capex, Google is sacrificing the golden goose
this take is so hot I had to put on sunscreen.
Bro suggests you should add addiction loops to your apps to get people hooked like a slot machine.
Can't wait to see a meditation app that tickles the brain like gambling!
No bro, build a product worth paying for. No tricks.
I had a chance to get my hands on the Duo yesterday at a workshop in Mexico.
I had adapted my app Wakeout using the simulator weeks prior, but devs, I have to tell you, it's a totally different beast once you get your hands on it, and will require rethinking of your entire app experience.
For one, I think supporting all poses will be crucial. The Duo in my hands felt whimsical, like you want to change its orientation all the time, open it, stand it up, tent it, keep it half folded, etc. Each orientation and pose offers new opportunities for interaction. I suspect a lot of Duo users will keep it on their desk propped up.
Secondly, it feels like it will especially benefit apps that can be used hands free. Exercise apps, entertainment apps, and apps that can be voice or camera controlled from a short distance feel advantageous in the Duo. This is because it can stay upright in a variety of poses. I can see this being great for learning where you talk with an AI teacher, for example.
Finally, it does feel niche. While playing with it, I kept asking myself who is the Duo for? Perhaps the answer is related to the second point above: a future of interactions where we don't touch our phones, but talk to them. For now, this means power users, techies, enthusiasts. In the near future, even grandmama.
But this doesn't mean you shouldn't put in a week to relayout your app for Duo--just the exercise of adapting our apps to a the new 1.4:1 aspect ratio, especially the outer tiny screen, will expand what you think your apps can do. This alone is worth it.
Good luck out there devs!
Playtest 20261011 has been rolled out! Featuring completed Dune 2000 campaign, the Random Map Generator, smarter AI, auto-save, visual and control polish, and major map editor improvements. Read more at openra.net/news/playtest-202… and grab the latest build for OpenRA
#openra
Pedro retweeted
One of the most universal causes of self-doubt and depression: trying to impress people you don’t like.
Pedro retweeted
Here's a blogpost detailing what we achieved in September:
dorf-rts.com/dev-blog/end-of…
Pedro retweeted
Introducing FLUX 3 Action.
An open weights 7B World Action Model that achieves first place on the RoboLab benchmark.
It outperforms the previous best open model by 6.1 percentage points while using 56% fewer parameters and running up to 3.95x faster.
FLUX 3 Action removes the usual trade-off between world action model performance and VLA speed: it still predicts video and actions together, but plans more than twice as far ahead and runs faster per second of robot motion than the strongest open VLA.
Teams can fine-tune FLUX 3 Action on their own demonstrations to create policies for a particular robot and task. Together with @nvidia, we also integrated FLUX 3 Action natively into @huggingface's LeRobot, with fine-tuning recipes included and edge deployment on NVIDIA Jetson.
Beyond robotics, we’re also seeing promising results training task-specific policies for acting in simulated environments like gaming, controlling a vehicle, computer use, and wherever else a model needs to understand a visual environment and then choose what to do next.
FLUX 3 Action builds on the same image, video, and audio pretraining as FLUX 3, but uses a smaller architecture designed for practical deployment. In midtraining, we trained the model to predict actions and future frames together.
We’re releasing the weights, code, fine-tuning recipe, benchmarks, and reproducible examples so researchers and developers can build on the model with their own robots, environments, and tasks (see below).
Pedro retweeted
We just launched what I believe is the best video model in the world.
• Faster than real-time generation at both 480p and 768p
• SOTA-level quality, built on MiniMax H3
• Prompt upsampling in ~1 second
This was a massive ML + engineering achievement by the @PrunaAI team.
And somehow, what we’re shipping next week is even more exciting.
Today, we launch P-Video-2-Pro, based on MiniMax H3: The best quality. The best speed.
Text or image in. Video and audio out.
• 𝗜𝗻𝗽𝘂𝘁: Text or first-frame image, with optional last-frame conditioning
• 𝗦𝗽𝗲𝗲𝗱: ~2.0s for a 5s clip at 480p · ~4.3s at 768p in Speed mode
• 𝗣𝗿𝗶𝗰𝗶𝗻𝗴: From $0.02/s Speed · $0.04/s Quality
• 𝗠𝗼𝗱𝗲𝘀: Speed or Quality
• 𝗖𝗼𝗻𝘁𝗿𝗼𝗹: First and last frame, seed, aspect ratio, and prompt upsampling with Off, Turbo, or Max
Available via our inference partners @replicate, @Cloudflare, @eachlabs, @scenario_gg, @TellersAI, @wavespeed_ai, @wiroai, @runware, and @togethercompute
Validated by our benchmark partners @datapointai, @RapidataAI, and @DesignArena. Benchmarks to be released soon 👀
👉 Free Playground: playground.pruna.ai/
📚 Model docs: docs.api.pruna.ai/guides/mod…
🧩 API: dashboard.pruna.ai/login
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