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Repeating the same experiment but one year later. GPT 5.6 Pro cannot be used vanilla for this prompt because it immediately fires the right CAS command to compute the Galois group. So instead I used a very restrictive prompt. One year has passed since GPT 5 Pro premiere, GPT...

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Bartosz Naskręcki

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77,402 görüntüleme • 1 ay önce •via X (Twitter)

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Had early access to GPT-5.4 and Pro. They are very good. One fun illustration of progress, this is the same prompt I used in GPT-4 below (making a 3D space inspired by Piranesi) now in GPT-5.4 Pro. There were no errors, made in a single prompt plus one to "make it better."
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Had early access to GPT-5.4 and Pro. They are very good. One fun illustration of progress, this is the same prompt I used in GPT-4 below (making a 3D space inspired by Piranesi) now in GPT-5.4 Pro. There were no errors, made in a single prompt plus one to "make it better."

Ethan Mollick

188,387 görüntüleme • 6 ay önce

this is f**king insane Fable 5 goes away in 24 hours from Claude Code and someone just figured out how to get fable 5 reasoning in GPT 5.6 Sol with one prompt you have less than 24 hours to set this up as this takes away 20% of your usage limit here is how: 1) Paste the prompt and ask it to "make an operating manual" 2) Go the Codex App > Settings > Personalisation > Custom Instructions 3) Use GPT 5.5 / GPT 5.6 and now you have Fable 5 reasoning at 1/3 th the price save and bookmark it no matter what
0:32

this is f**king insane Fable 5 goes away in 24 hours from Claude Code and someone just figured out how to get fable 5 reasoning in GPT 5.6 Sol with one prompt you have less than 24 hours to set this up as this takes away 20% of your usage limit here is how: 1) Paste the prompt and ask it to "make an operating manual" 2) Go the Codex App > Settings > Personalisation > Custom Instructions 3) Use GPT 5.5 / GPT 5.6 and now you have Fable 5 reasoning at 1/3 th the price save and bookmark it no matter what

Avid

57,544 görüntüleme • 2 ay önce

GPT-5.6 vs GPT-5.5 on my custom spaceship prompt. I gave both models the exact same custom prompt. This is also the same prompt I previously gave to Fable 5. For context, GPT-5.6 Pro worked for 87 minutes, while GPT-5.5 Extra High worked for 34 minutes and 42 seconds. As I’ve said before, based on great authority GPT-5.6 will be an incremental/soldi improvement over GPT-5.5, not a “Fable killer.” My rough expectation has been that it would trade blows with Fable 5 on some benchmarks, maybe win around half depending on the category, but not clearly surpass it overall. And again fable five will have bigger model smell, but this was expected. After testing this coding output, that view feels pretty accurate. GPT-5.6 is clearly better than GPT-5.5 in several visual areas. The lighting, shading, chairs, object details, and exterior of the spaceship looked noticeably stronger. The scene was also easier to test. I do want to give GPT-5.5 credit though. It built out the rooms much much better and the planets looked better than GPT-5.6’s. It was also interesting that both GPT-5.5 and GPT-5.6 produced better-looking planets than Fable 5 in this specific test. The downside with GPT-5.5 was stability. The game was much glitchier and harder to test compared to GPT-5.6. But when it comes to the core of the demo, which is the spaceship itself, Fable 5 still beat both models pretty comfortably. GPT-5.6 is impressive, but from this test, it looks exactly like what I expected which was a meaningful incremental improvement over GPT-5.5, at least for indie game demos, but not something that replaces Fable 5. In collaboration with Chetaslua
0:42

GPT-5.6 vs GPT-5.5 on my custom spaceship prompt. I gave both models the exact same custom prompt. This is also the same prompt I previously gave to Fable 5. For context, GPT-5.6 Pro worked for 87 minutes, while GPT-5.5 Extra High worked for 34 minutes and 42 seconds. As I’ve said before, based on great authority GPT-5.6 will be an incremental/soldi improvement over GPT-5.5, not a “Fable killer.” My rough expectation has been that it would trade blows with Fable 5 on some benchmarks, maybe win around half depending on the category, but not clearly surpass it overall. And again fable five will have bigger model smell, but this was expected. After testing this coding output, that view feels pretty accurate. GPT-5.6 is clearly better than GPT-5.5 in several visual areas. The lighting, shading, chairs, object details, and exterior of the spaceship looked noticeably stronger. The scene was also easier to test. I do want to give GPT-5.5 credit though. It built out the rooms much much better and the planets looked better than GPT-5.6’s. It was also interesting that both GPT-5.5 and GPT-5.6 produced better-looking planets than Fable 5 in this specific test. The downside with GPT-5.5 was stability. The game was much glitchier and harder to test compared to GPT-5.6. But when it comes to the core of the demo, which is the spaceship itself, Fable 5 still beat both models pretty comfortably. GPT-5.6 is impressive, but from this test, it looks exactly like what I expected which was a meaningful incremental improvement over GPT-5.5, at least for indie game demos, but not something that replaces Fable 5. In collaboration with Chetaslua

Chris

250,919 görüntüleme • 3 ay önce

OUR NEW KIT IS HERE! 🔥 Sponsored by the Levi Samuels Colwill Project - More information on this will be released soon! We have a small amount of stock available for purchase at our home against Totton on Tuesday. Prices are £45 for Adults and £38 for Juniors Our current stock for the Home Kit is: Kids XS (Up to 4-5 Years) x 4 XXS (5-7 Years) x 4 XS (7-9 Years) x 8 S x 4 M x 3 L x 4 XXL x 1 XXXL x 3 XXXXL x 3 Away: M x 1 L x 2 XXL x 2 #uptheboatmen
1:00

OUR NEW KIT IS HERE! 🔥 Sponsored by the Levi Samuels Colwill Project - More information on this will be released soon! We have a small amount of stock available for purchase at our home against Totton on Tuesday. Prices are £45 for Adults and £38 for Juniors Our current stock for the Home Kit is: Kids XS (Up to 4-5 Years) x 4 XXS (5-7 Years) x 4 XS (7-9 Years) x 8 S x 4 M x 3 L x 4 XXL x 1 XXXL x 3 XXXXL x 3 Away: M x 1 L x 2 XXL x 2 #uptheboatmen

Sholing FC

60,464 görüntüleme • 2 yıl önce

So this is the result of Gemini 4 Pro hiding under the name “Gemini 3.8 Flash” 🙄 I tried this so called rumored “Gemini 4 Pro” against famous "V8 Engine" demo from X and no, this is definitely not what all those posts about Gemini 4 Pro supposedly topping Arena benchmarks made it sound like. It does feel better than any Gemini model I’ve used so far, but it’s still not there. I wouldn’t even put it at Opus 5 level yet. Not sure what this hype is about, tbh.
0:55

So this is the result of Gemini 4 Pro hiding under the name “Gemini 3.8 Flash” 🙄 I tried this so called rumored “Gemini 4 Pro” against famous "V8 Engine" demo from X and no, this is definitely not what all those posts about Gemini 4 Pro supposedly topping Arena benchmarks made it sound like. It does feel better than any Gemini model I’ve used so far, but it’s still not there. I wouldn’t even put it at Opus 5 level yet. Not sure what this hype is about, tbh.

The Bugged Dev

28,496 görüntüleme • 10 gün önce

Quantum mechanics has a reputation for being mystical mainly because people skip the rules and jump to interpretations. In this lecture series, we’re doing the opposite. We start from the rules, follow the algebra, and let the picture be the calculation. Classical Probability Theory combines alternatives by adding their probabilities. Quantum Theory combines them one step earlier…add complex amplitudes first, then square at the end. That swap in order is everything. Expand |a₁ + a₂|² and you don’t just get |a₁|² + |a₂|²…you get a cross-term, 2 Re(a₁ a₂*). Its sign is set by phase, so the same two contributions can reinforce or cancel. Interference is just the algebra of squaring a sum. In the 3D render, the surface height is proportional to |a(x)| (so peaks become bright bands after squaring), while the surface skin is colored by the local phase arg(a(x)). As the phase knob φ(t) is swept on path 2, the cross-term oscillates, and you literally watch the interference ridges slide across the screen. We model a detector screen with coordinates x in R² (think x = (x,y)). A quantum state assigns a complex amplitude a(x). The rule for outcomes is p(x) = |a(x)|² Now the key situation: two coherent alternatives contribute to the same outcome x. Let their amplitudes be a₁(x) and a₂(x). Quantum says a(x) = a₁(x) + a₂(x) So the probability density becomes p(x) = |a₁(x) + a₂(x)|² Expand it (this is the whole episode): p(x) = (a₁ + a₂)(a₁* + a₂*) = |a₁|² + |a₂|² + a₁ a₂* + a₁* a₂ = |a₁|² + |a₂|² + 2 Re(a₁ a₂*) That last term is the interference term. It can be positive or negative. To see phase explicitly, write each contribution in polar form: a₁(x) = r₁(x) exp(i θ₁(x)) a₂(x) = r₂(x) exp(i θ₂(x)) Then a₁ a₂* = r₁ r₂ exp(i(θ₁ − θ₂)) So the cross-term is 2 Re(a₁ a₂*) = 2 r₁ r₂ cos(θ₁(x) − θ₂(x)) That’s the fringe engine: p(x) = r₁² + r₂² + 2 r₁ r₂ cos(Δθ(x)) Now the phase knob we animate: Add a controllable phase shift φ to path 2: a₂(x) → a₂(x) exp(i φ) Then Δθ(x) → Δθ(x) − φ, so p(x; φ) = r₁² + r₂² + 2 r₁ r₂ cos(Δθ(x) − φ) As φ changes smoothly, the bright/dark pattern slides continuously. Same setup, same geometry, same magnitudes r₁,r₂, only phase changed. #QuantumMechanics #WaveInterference #ComplexAmplitudes #DoubleSlit #Physics #Mathematics
1:00

Quantum mechanics has a reputation for being mystical mainly because people skip the rules and jump to interpretations. In this lecture series, we’re doing the opposite. We start from the rules, follow the algebra, and let the picture be the calculation. Classical Probability Theory combines alternatives by adding their probabilities. Quantum Theory combines them one step earlier…add complex amplitudes first, then square at the end. That swap in order is everything. Expand |a₁ + a₂|² and you don’t just get |a₁|² + |a₂|²…you get a cross-term, 2 Re(a₁ a₂*). Its sign is set by phase, so the same two contributions can reinforce or cancel. Interference is just the algebra of squaring a sum. In the 3D render, the surface height is proportional to |a(x)| (so peaks become bright bands after squaring), while the surface skin is colored by the local phase arg(a(x)). As the phase knob φ(t) is swept on path 2, the cross-term oscillates, and you literally watch the interference ridges slide across the screen. We model a detector screen with coordinates x in R² (think x = (x,y)). A quantum state assigns a complex amplitude a(x). The rule for outcomes is p(x) = |a(x)|² Now the key situation: two coherent alternatives contribute to the same outcome x. Let their amplitudes be a₁(x) and a₂(x). Quantum says a(x) = a₁(x) + a₂(x) So the probability density becomes p(x) = |a₁(x) + a₂(x)|² Expand it (this is the whole episode): p(x) = (a₁ + a₂)(a₁* + a₂*) = |a₁|² + |a₂|² + a₁ a₂* + a₁* a₂ = |a₁|² + |a₂|² + 2 Re(a₁ a₂*) That last term is the interference term. It can be positive or negative. To see phase explicitly, write each contribution in polar form: a₁(x) = r₁(x) exp(i θ₁(x)) a₂(x) = r₂(x) exp(i θ₂(x)) Then a₁ a₂* = r₁ r₂ exp(i(θ₁ − θ₂)) So the cross-term is 2 Re(a₁ a₂*) = 2 r₁ r₂ cos(θ₁(x) − θ₂(x)) That’s the fringe engine: p(x) = r₁² + r₂² + 2 r₁ r₂ cos(Δθ(x)) Now the phase knob we animate: Add a controllable phase shift φ to path 2: a₂(x) → a₂(x) exp(i φ) Then Δθ(x) → Δθ(x) − φ, so p(x; φ) = r₁² + r₂² + 2 r₁ r₂ cos(Δθ(x) − φ) As φ changes smoothly, the bright/dark pattern slides continuously. Same setup, same geometry, same magnitudes r₁,r₂, only phase changed. #QuantumMechanics #WaveInterference #ComplexAmplitudes #DoubleSlit #Physics #Mathematics

Mathelirium

81,726 görüntüleme • 9 ay önce

Models like GPT 5.6 or Fable 5 are accelerating the commodification of software. For instance, I gave Fable a screenshot of the Stripe, OpenAI, and Anthropic websites with a simple prompt: “Create a pixel-perfect reproduction of this website.” It took only seconds and a simple prompt to duplicate the design. This is exciting because there are so many poorly designed websites, but now they are just a prompt away from achieving world-class design!!
0:27

Models like GPT 5.6 or Fable 5 are accelerating the commodification of software. For instance, I gave Fable a screenshot of the Stripe, OpenAI, and Anthropic websites with a simple prompt: “Create a pixel-perfect reproduction of this website.” It took only seconds and a simple prompt to duplicate the design. This is exciting because there are so many poorly designed websites, but now they are just a prompt away from achieving world-class design!!

Nicolas Bustamante

37,754 görüntüleme • 2 ay önce

Claude Opus 5 just one-shotted this FPS. Less than 1 hour from prompt to playable demo. Every weapon, enemy, mechanic and environment was generated from scratch. Prompt below 👇 There is no prompt below, because the first section is exactly the kind of post I’m tired of seeing every time a new model drops. A flashy demo, “one-shot” in the caption, “built in under an hour”… anything to farm impressions while conveniently hiding the actual process. If it was really made from a single prompt, show the prompt. That’s what I do on this account. When I claim something is a one-prompt prototype built with GPT-5.6 Sol Ultra and Codex, I share the prompt publicly so anyone can verify it. AI is already making game prototyping incredible. We don’t need fake “one-shot” stories to prove it. Original footage:
0:36

Claude Opus 5 just one-shotted this FPS. Less than 1 hour from prompt to playable demo. Every weapon, enemy, mechanic and environment was generated from scratch. Prompt below 👇 There is no prompt below, because the first section is exactly the kind of post I’m tired of seeing every time a new model drops. A flashy demo, “one-shot” in the caption, “built in under an hour”… anything to farm impressions while conveniently hiding the actual process. If it was really made from a single prompt, show the prompt. That’s what I do on this account. When I claim something is a one-prompt prototype built with GPT-5.6 Sol Ultra and Codex, I share the prompt publicly so anyone can verify it. AI is already making game prototyping incredible. We don’t need fake “one-shot” stories to prove it. Original footage:

Givros

14,794 görüntüleme • 2 ay önce

GPT-6 Astra built this iOS app in 13m 3s using my AppCreator skill. I want to see my weekly mileage, not averages. Apple Health app doesn't make it easy. So I gave this prompt to Astra, and this is the result. No other model has made it work like this from one prompt. OpenAI OpenAIDevs
0:31

GPT-6 Astra built this iOS app in 13m 3s using my AppCreator skill. I want to see my weekly mileage, not averages. Apple Health app doesn't make it easy. So I gave this prompt to Astra, and this is the result. No other model has made it work like this from one prompt. OpenAI OpenAIDevs

Paul Solt

202,731 görüntüleme • 25 gün önce

Indeed 108 = 2^2 3^3 Remember that 432 Hz music fad? It's 108 x 4. Actually it's semi-related to another cosmic numerological coincidence like the connection between phi and pi that I showed you: 3^12 / 2^19 = 1.01364 -- very close to one. This is called the Pythagorean coma and it's the reason the Piano is even possible as a practical instrument. [Aside: The next in the prime-power product series is 2^2 3^3 5^5 = 337,500. This number, for whatever reason, shows up in the Book of Numbers, 31:36. I have no opinion as to why.]
2:25

Indeed 108 = 2^2 3^3 Remember that 432 Hz music fad? It's 108 x 4. Actually it's semi-related to another cosmic numerological coincidence like the connection between phi and pi that I showed you: 3^12 / 2^19 = 1.01364 -- very close to one. This is called the Pythagorean coma and it's the reason the Piano is even possible as a practical instrument. [Aside: The next in the prime-power product series is 2^2 3^3 5^5 = 337,500. This number, for whatever reason, shows up in the Book of Numbers, 31:36. I have no opinion as to why.]

Korobochka (コロボ) 🇦🇺✝️🇷🇺

14,777 görüntüleme • 1 ay önce

this is f**king gold someone just figured out how to run Claude Fable 5 and GPT 5.6 Sol in the same loop gpt-5.6 came out yesterday. fable 5 leaves in 48 hours. this window has never existed before and never will again. here is how to use it: 1. open claude code. install openai's codex plugin 2. type /model. choose fable 5. 3. drop one ROUTING.md in your repo root (full file in comments). 4.paste the prompt (in comments), write what feature you want. boom. save and bookmark this no matter what. it will be the most productive thing you do this weekend
0:20

this is f**king gold someone just figured out how to run Claude Fable 5 and GPT 5.6 Sol in the same loop gpt-5.6 came out yesterday. fable 5 leaves in 48 hours. this window has never existed before and never will again. here is how to use it: 1. open claude code. install openai's codex plugin 2. type /model. choose fable 5. 3. drop one ROUTING.md in your repo root (full file in comments). 4.paste the prompt (in comments), write what feature you want. boom. save and bookmark this no matter what. it will be the most productive thing you do this weekend

Avid

140,906 görüntüleme • 2 ay önce

🧵 [Day 1] The 5-Step ANIME ENGINE Framework: How I Built a Full AI Anime Short for the Morphic x Framer Contest I just joined the Morphic x contest — and made a full anime short "Dreamsplice" using AI. Here’s the 5-Step ANIME ENGINE Framework I used to go from idea → full short film in 2 DAYS (A main thread to update later. Bookmark this)
0:51

🧵 [Day 1] The 5-Step ANIME ENGINE Framework: How I Built a Full AI Anime Short for the Morphic x Framer Contest I just joined the Morphic x contest — and made a full anime short "Dreamsplice" using AI. Here’s the 5-Step ANIME ENGINE Framework I used to go from idea → full short film in 2 DAYS (A main thread to update later. Bookmark this)

Tú Michael 🇻🇳

15,253 görüntüleme • 10 ay önce

🚨 More DeepSeek V4 Pro GA Leaks and it's looking seriously impressive. It also looks like DeepSeek may have heavily distilled from Fable 5 the coding style, iteration behavior, and overall output feel very similar. It was tested it on the same prompt used for Kimi K3 and GPT-5.6 Sol, and the result had strong scene composition, solid environmental detail, and surprisingly good design choices. Still early, but this could become one of the most disruptive coding models yet. 👀🔥 cc huangserva
0:54

🚨 More DeepSeek V4 Pro GA Leaks and it's looking seriously impressive. It also looks like DeepSeek may have heavily distilled from Fable 5 the coding style, iteration behavior, and overall output feel very similar. It was tested it on the same prompt used for Kimi K3 and GPT-5.6 Sol, and the result had strong scene composition, solid environmental detail, and surprisingly good design choices. Still early, but this could become one of the most disruptive coding models yet. 👀🔥 cc huangserva

WorldofAI

28,190 görüntüleme • 2 ay önce

Do you actually know what convex optimization is in the geometric, guarantee-theoretic sense or have you only met it through solvers and loss curves? Convexity is rare comfort in optimization...there are no spurious local minima, no surprise traps, and inequalities you can use like tools instead of prayers. So, what is this convexity? Let x = (x₁, x₂) and let f(x) be convex. Plot the surface z = f(x). Pick a contact point x₀. The local slope is the gradient p = ∇f(x₀). That p is exactly the data that defines the supporting plane: z = f(x₀) + p · (x − x₀). Thus, f is said to be convex because for every x, f(x) ≥ f(x₀) + p · (x − x₀). So the plane at x₀ can slide under the surface, but it never slices through it. Not near the point...everywhere. Now for here is the interesting part: The slope becomes a coordinate system! Rewrite the same plane as z = p · x − b, where b is the offset. Because the plane passes through (x₀, f(x₀)), the offset is forced to be b = p · x₀ − f(x₀). And that number isn’t just geometry trivia. It’s the convex conjugate: f*(p) = sup over x ( p · x − f(x) ). At a differentiable contact point, the supporting plane touches f tightly enough that the supremum is achieved at x₀, giving the identity f*(p) = p · x₀ − f(x₀) when p = ∇f(x₀). So one moving contact point gives two linked readouts: primal position x₀ dual position (slope) p = ∇f(x₀) dual offset f*(p) One surface. Two worlds. #ConvexOptimization #Optimization #MachineLearning #SignalProcessing #AppliedMath #Engineering
0:50

Do you actually know what convex optimization is in the geometric, guarantee-theoretic sense or have you only met it through solvers and loss curves? Convexity is rare comfort in optimization...there are no spurious local minima, no surprise traps, and inequalities you can use like tools instead of prayers. So, what is this convexity? Let x = (x₁, x₂) and let f(x) be convex. Plot the surface z = f(x). Pick a contact point x₀. The local slope is the gradient p = ∇f(x₀). That p is exactly the data that defines the supporting plane: z = f(x₀) + p · (x − x₀). Thus, f is said to be convex because for every x, f(x) ≥ f(x₀) + p · (x − x₀). So the plane at x₀ can slide under the surface, but it never slices through it. Not near the point...everywhere. Now for here is the interesting part: The slope becomes a coordinate system! Rewrite the same plane as z = p · x − b, where b is the offset. Because the plane passes through (x₀, f(x₀)), the offset is forced to be b = p · x₀ − f(x₀). And that number isn’t just geometry trivia. It’s the convex conjugate: f*(p) = sup over x ( p · x − f(x) ). At a differentiable contact point, the supporting plane touches f tightly enough that the supremum is achieved at x₀, giving the identity f*(p) = p · x₀ − f(x₀) when p = ∇f(x₀). So one moving contact point gives two linked readouts: primal position x₀ dual position (slope) p = ∇f(x₀) dual offset f*(p) One surface. Two worlds. #ConvexOptimization #Optimization #MachineLearning #SignalProcessing #AppliedMath #Engineering

Mathelirium

38,506 görüntüleme • 9 ay önce

How does GPT-5 become GPT-6? Everything on the internet was already trained on a year, year and a half ago. New data is being added but it's marginal and a lot of it is AI slop. There is interesting private data (like JP Morgan's data) but nobody is opening that up. You don't go from GPT-5 to GPT-6 in isolation because that's not how learning works. Every learning that has ever occurred comes from having information to learn. You can't learn no information. cc Ground Zero / pod with Curtis from Handshake AI.
3:08

How does GPT-5 become GPT-6? Everything on the internet was already trained on a year, year and a half ago. New data is being added but it's marginal and a lot of it is AI slop. There is interesting private data (like JP Morgan's data) but nobody is opening that up. You don't go from GPT-5 to GPT-6 in isolation because that's not how learning works. Every learning that has ever occurred comes from having information to learn. You can't learn no information. cc Ground Zero / pod with Curtis from Handshake AI.

himanshu

10,684 görüntüleme • 4 ay önce