@antirez It depends on the task. GPT is much worse than Opus at creative tasks - which includes early software planning stages.
When you know precisely what you want then GPT is better. Which I assume is your case most of the time.
DO YOU UNDERSTAND WHAT JUST HAPPENED AT THE ENHANCED GAMES..
Peter Thiel and Donald Trump Jr. spent millions to create a steroid Olympics.
They promised to "redefine human limits" and put up $25M in prize money.
After 5 hours in Las Vegas, here’s the scoreboard:
- 1 world record (not recognized by anyone)
- Thor Björnsson failed his 515kg deadlift (managed only 475kg)
- olympic sprinter Fred Kerley missed the 100m WR by 0.4s - without even taking drugs
- the only "record" came from a Greek swimmer who finished 5th at Paris 2024. He wore a supersuit banned since 2009 and beat the clean record by just 0.07s
the whole pitch was that drugs would shatter the limits of clean sport.
instead they proved the gap between juiced and clean is now 7 hundredths of a second - in a suit banned 17 years ago.
the only thing they actually proved was how good the clean athletes already are.
You think the Enhanced Games exposed anything or just embarrassed themselves?
@Devon_Eriksen_@IsaMacedaAli Why are you being disingenuous? I think you do understand the problem with the measure but are too busy sucking up to Trump due to audience capture.
Pity.
@Necronomion@RafaMerinPelaez@juansotoivars Yo voy en coche y en bici. Y considero el impacto que tienen mis acciones en los demás en ambos casos. Cuando me toca esperar detrás de un imbécil como tú, me espero.
No voy de chuloplaya por ahí pensando que soy lo más importante del planeta y que los demás tienen que joderse.
@ferrenet@PabloGrueso No es absurdo cuando las finanzas no son centralizadas. Cuesta un pastizal un punto limpio y la gestión de los residuos.
Si permites el turismo de basuras unos municipios hacen freeloading de los otros.
Esto debiera motivar al gobierno a hacer puntos limpios estatales.
@paureinatech@RuSoKoBo@xMigma Ojo que no necesariamente se espera que aciertes en todo o que mientras más mejor. Eso es parte de un perfil de IQ y otras habilidades y puedes ser descartada por exceso.
@Recuenco@EstIdeologicos Cualquier adulto semi funcional es capaz de diferenciar entre elegir helado de dulce de leche y cerrarle la puerta en la cara a un negro que no conoces de nada por que te da miedo por ser negro.
El helado de vainilla no sufre daño alguno.
@WEB03dotpng@QuenL2K@underachievr@hellobye1024500 Not really tried that though, that was a political maneuver to make noise. So it's similar to this.
I'm not saying it was useless, just that feeding people was not the objective. It's strange that they felt they needed to pretend it was.
Respectfully, I think this reads better than it argues.
On the bitter lesson: Sutton’s point was stop encoding human priors, let scale do the work. He never said minimize sensors. LIDAR is more data for the network to learn from, not hand-engineering. Every serious multimodal transformer in 2026 fuses heterogeneous inputs end-to-end. That’s literally what scale looks like now.
On Waymo being “stuck”: they’re running actual driverless robotaxis at commercial scale in SF, LA, Phoenix, Austin, and Miami. Tesla FSD still needs a human hand on the wheel. Geofenced but driverless beats “works everywhere, supervised.” That’s Level 4 versus Level 2. The framing in the tweet has this exactly backwards.
The biology argument cuts the other way too. Bats evolved echolocation, sharks have electroreception, pit vipers do IR sensing. Evolution uses every modality a carbon body can grow. It just can’t grow lasers. And “two eyes, one brain” humans kill around 40,000 people a year on US roads, so that’s probably not the benchmark you want.
Also, Sébastien Loeb drives with a co-driver reading pre-recorded pace notes from stage recon. That’s pre-mapped external data fused with his vision in real time. The example actually proves the opposite point.
I build AI in a safety-critical domain (clinical decision support for African hospitals), and the one thing you learn fast is that redundancy is not technical debt, it’s how you buy back the last 9s of reliability. Commercial aircraft carry pitot tubes and GPS and inertial and radar altimeters. Not because Airbus lacks conviction. Because physics doesn’t care about your aesthetic preferences. Vision fails in fog, heavy rain, direct sun glare, and weird lighting. LIDAR doesn’t. When lives are the loss function, you take the redundancy.
Sensor fusion also stopped being “handcrafted” years ago. End-to-end multimodal nets fuse LIDAR and vision the same way they fuse text and images. This critique would have landed in 2019.
Cost angle is settled too. Solid-state LIDAR is under $500. XPeng, Nio, Li Auto, Huawei-powered cars, BYD’s premium lines, they all ship with it. The industry picked a side and it wasn’t vision-only.
The Marxism analogy is the tell for me. It’s a vibes argument, not an engineering one. Using richer inputs isn’t central planning, it’s just physics. Calling redundancy “Soviet” is rhetoric doing the work that evidence should be doing.
“Never bet against Elon.” Robotaxis have been “next year” since 2016. Waymo shipped. That bet already settled.
Vision-only might get there eventually. I’d genuinely love it to. But betting human lives on one modality when cheap redundancy exists isn’t Occam’s razor, it’s an aesthetic preference dressed up as one.