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Tried to prompt this Seedance 2 creature transform with other models. Only Meta Muse Spark 1.1 actually understood the assignment and gave me something usable. Ill post the chatgpt version in the comments. AI at Meta Alexandr Wang

JSFILMZ

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10,158 次观看 • 29 天前 •via X (Twitter)

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POV: you gave AI a scene instead of a prompt. And it actually understood the assignment. Seedance 2.5 is seriously impressive.

POV: you gave AI a scene instead of a prompt. And it actually understood the assignment. Seedance 2.5 is seriously impressive.

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Is the US leading in AI? "I think right now the US is leading. I think it's important to track progress from many other countries - but especially China." Chief AI Officer Meta Alexandr Wang #BloombergTech ⏯️

Is the US leading in AI? "I think right now the US is leading. I think it's important to track progress from many other countries - but especially China." Chief AI Officer Meta Alexandr Wang #BloombergTech ⏯️

Bloomberg Live

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Seedance 2.0 vs Meta Muse Video. Both models feature native audio, but Muse Video seems like its currently stuck with a 10-second limit. Meanwhile, Seedance 2.0 can output 15-second cinematic sequences in crisp up to 4K. Meta is cooking, but Seedance 2.0 might still hold the crown for now. Which one are you betting on?

Seedance 2.0 vs Meta Muse Video. Both models feature native audio, but Muse Video seems like its currently stuck with a 10-second limit. Meanwhile, Seedance 2.0 can output 15-second cinematic sequences in crisp up to 4K. Meta is cooking, but Seedance 2.0 might still hold the crown for now. Which one are you betting on?

JSFILMZ

173,550 次观看 • 1 个月前

1. The Meta-Prompt Copy this into ChatGPT: “You are to act as my prompt engineer. I would like to accomplish: [insert your goal]. Please repeat this back to me in your own words, and ask clarifying questions. Once we confirm, generate the final optimized prompt.” That’s it. This turns ChatGPT into your personal prompt engineer.

1. The Meta-Prompt Copy this into ChatGPT: “You are to act as my prompt engineer. I would like to accomplish: [insert your goal]. Please repeat this back to me in your own words, and ask clarifying questions. Once we confirm, generate the final optimized prompt.” That’s it. This turns ChatGPT into your personal prompt engineer.

Guri Singh

21,888 次观看 • 11 个月前

Meta's chief ai officer Alexandr Wang : "Internally at Meta, we have seen cases where, if you develop the right agentic loop and have the right evaluation system and metric for the agents to optimize, a swarm of agents can accomplish more than a team of 100 engineers. They can do it very handily, actually, very easily." Alexandr Wang was talking to CEO of Y Combinator Garry Tan at Y Combinator Startup School 2026 ---- full video link in comment

Meta's chief ai officer Alexandr Wang : "Internally at Meta, we have seen cases where, if you develop the right agentic loop and have the right evaluation system and metric for the agents to optimize, a swarm of agents can accomplish more than a team of 100 engineers. They can do it very handily, actually, very easily." Alexandr Wang was talking to CEO of Y Combinator Garry Tan at Y Combinator Startup School 2026 ---- full video link in comment

Rohan Paul

250,525 次观看 • 4 天前

Meta paid $14 billion to pry Alex Wang away from Scale AI, the company he co-founded and ran. The hope - Zuck's hope - was that Wang could fix what ailed Meta's AI program. Over the past year, Meta has spent billions more pulling researchers away from other labs and has raced to create it first new model called Muse Spark under a regime led by Wang, Nat Friedman, Daniel Gross and Shengjia Zhao. This interview is the first time Wang has talked about all the drama of the past year and where Meta is heading with AI. The Core Memory podcast is on Apple, Spotify, YouTube and all major platforms. Enjoy! Timestamps 00:00 Intro 02:02 Inside Meta Superintelligence Labs 06:23 The Tahoe Conversation 12:50 How Do You Rebuild a Frontier Lab 24:35 The Soup and Being "Too Young" 32:48 MuseSpark: Appetizer, Not Entrée 48:47 Why Does Everyone Hate AI? 53:50 Open Source and the Manus Question 1:04:59 Robots and Mango 1:11:08 Sci-Fi, BCI, and Do AI Models Deserve Moral Weight?

Meta paid $14 billion to pry Alex Wang away from Scale AI, the company he co-founded and ran. The hope - Zuck's hope - was that Wang could fix what ailed Meta's AI program. Over the past year, Meta has spent billions more pulling researchers away from other labs and has raced to create it first new model called Muse Spark under a regime led by Wang, Nat Friedman, Daniel Gross and Shengjia Zhao. This interview is the first time Wang has talked about all the drama of the past year and where Meta is heading with AI. The Core Memory podcast is on Apple, Spotify, YouTube and all major platforms. Enjoy! Timestamps 00:00 Intro 02:02 Inside Meta Superintelligence Labs 06:23 The Tahoe Conversation 12:50 How Do You Rebuild a Frontier Lab 24:35 The Soup and Being "Too Young" 32:48 MuseSpark: Appetizer, Not Entrée 48:47 Why Does Everyone Hate AI? 53:50 Open Source and the Manus Question 1:04:59 Robots and Mango 1:11:08 Sci-Fi, BCI, and Do AI Models Deserve Moral Weight?

Ashlee Vance

97,018 次观看 • 2 个月前

Meta is rolling out a new line of AI glasses called the “Muse Spark” glasses, which come in three styles. The glasses can play music, capture images to translate languages and answer questions about a person’s surroundings. CBS News’ Maya Blackstone tried them out.

Meta is rolling out a new line of AI glasses called the “Muse Spark” glasses, which come in three styles. The glasses can play music, capture images to translate languages and answer questions about a person’s surroundings. CBS News’ Maya Blackstone tried them out.

CBS News

90,331 次观看 • 1 个月前

Meta CTO confirmed that over the last year Zuck had to go founder mode. He also really appreciated Alexandr Wang joining the team last year. To build their latest model, Meta executed an emergency pivot, pulling thousands of employees off their normal duties to generate expert traces, which are hand-guided coding examples required to post-train the model. This confirms that the bottleneck for frontier models is not just raw compute, but high-fidelity, human-verified reinforcement data. Good listen. $META

Meta CTO confirmed that over the last year Zuck had to go founder mode. He also really appreciated Alexandr Wang joining the team last year. To build their latest model, Meta executed an emergency pivot, pulling thousands of employees off their normal duties to generate expert traces, which are hand-guided coding examples required to post-train the model. This confirms that the bottleneck for frontier models is not just raw compute, but high-fidelity, human-verified reinforcement data. Good listen. $META

CapexAndChill

92,351 次观看 • 29 天前

Meta just launched its 1st image model after Mark Zuckerberg’s AI shake-up. Muse Image is Meta Superintelligence Labs' first image generator after Muse Spark. They said the model will power new editing features in Meta’s Instagram photo app and be added to its marketer tools for creating platform ads. Meta had relied on Midjourney and Black Forest Labs for generation inside Meta AI. Muse Image brings that layer in-house, so Meta controls quality, cost, and product timing. Consumers get free access through Meta AI, WhatsApp chats, and Instagram Stories. Power users need Meta One or another monthly plan when free limits run out. Users can start from prompts, add photos, annotate edits, or sketch changes directly. Meta says it can erase photobombers, create QR codes, and keep visual text readable. Advertisers get variants through Advantage+ creative, with edits, style swaps, and brand-matched versions. Meta says internal tests trail GPT Image 2 but beat Nano Banana 2 on editing. This is another move in Meta's effort in trying to convert AI infrastructure spending into revenue beyond social ads.

Rohan Paul

20,377 次观看 • 1 个月前

FIRST TEST Seedance 2.0! From my initial tests, this is one of the more impressive AI video models I’ve tried so far. Dynamic motion feels fluid, prompt adherence is solid, and the efficiency really stood out, very little iteration needed. Everything you see here was generated using just one reference image + one prompt. I also tested a 3×3 image grid with no prompt at all, and the results stayed surprisingly consistent. Another highlight: sound design is already included, and it actually works really well. Tested via BytePlus 👉 More detail and access link to try Seedance 2.0 is in the comments.

FIRST TEST Seedance 2.0! From my initial tests, this is one of the more impressive AI video models I’ve tried so far. Dynamic motion feels fluid, prompt adherence is solid, and the efficiency really stood out, very little iteration needed. Everything you see here was generated using just one reference image + one prompt. I also tested a 3×3 image grid with no prompt at all, and the results stayed surprisingly consistent. Another highlight: sound design is already included, and it actually works really well. Tested via BytePlus 👉 More detail and access link to try Seedance 2.0 is in the comments.

Dinda Prasetyo

45,450 次观看 • 6 个月前

Meta's Muse Spark 1.1 beat Gemini 3.6 at making 3D arcade games for 3x cheaper! We gave two models the same task: build three 3D tabletop games that play themselves Prompts: - An 8-ball pool break scattering the rack - An air hockey rally that ends in a goal - A foosball table where the rods play the ball Outputs: Muse Spark 1.1: 31.3K tokens, $0.026 Gemini 3.6: 28.8K tokens, $0.073 Muse Spark played all three tables clean with far more detail than Gemini, which barely rendered its backgrounds. Its air hockey glitched and its foosball lagged into a buggy still picture. Muse Spark 1.1 ran the full set perfectly for 3x less

Meta's Muse Spark 1.1 beat Gemini 3.6 at making 3D arcade games for 3x cheaper! We gave two models the same task: build three 3D tabletop games that play themselves Prompts: - An 8-ball pool break scattering the rack - An air hockey rally that ends in a goal - A foosball table where the rods play the ball Outputs: Muse Spark 1.1: 31.3K tokens, $0.026 Gemini 3.6: 28.8K tokens, $0.073 Muse Spark played all three tables clean with far more detail than Gemini, which barely rendered its backgrounds. Its air hockey glitched and its foosball lagged into a buggy still picture. Muse Spark 1.1 ran the full set perfectly for 3x less

atomic.chat

125,857 次观看 • 18 天前

Chief AI Officer at Meta a few months ago broke down the Meta Flywheel for AI. Meta holds an asymmetric advantage over pure-play AI competitors like OpenAI or Anthropic due to its 3.5B daily active users. Launching AI agents to half the global population generates immediate scale and revenue, which justifies massive capex on infrastructure, which in turn trains the next generation of frontier models. $META

Chief AI Officer at Meta a few months ago broke down the Meta Flywheel for AI. Meta holds an asymmetric advantage over pure-play AI competitors like OpenAI or Anthropic due to its 3.5B daily active users. Launching AI agents to half the global population generates immediate scale and revenue, which justifies massive capex on infrastructure, which in turn trains the next generation of frontier models. $META

CapexAndChill

21,735 次观看 • 1 个月前

We’ve been fortunate to partner with Alexandr Wang and the Scale AI team since the days when they were working out of Dan Levine’s basement. Thanks for bringing us along for the ride, and here’s to what’s next. 🚀 Read more about Scale, Meta, and our continued partnership here:

We’ve been fortunate to partner with Alexandr Wang and the Scale AI team since the days when they were working out of Dan Levine’s basement. Thanks for bringing us along for the ride, and here’s to what’s next. 🚀 Read more about Scale, Meta, and our continued partnership here:

Accel

209,889 次观看 • 1 年前

Grok 4.5 crushed OpenAI & Meta in this test! Cost per run: GPT Sol $1.63 Grok 4.5 $2.47 Meta Muse Spark 1.1 $1.08 The three prompts: • Fruit Ninja – style slicing game • Angry Birds – style fort collapse • Crossy Road clone Grok nailed all three: clean physics, smooth playback, good visuals. GPT Sol did fine until Crossy Road, where it froze. Meta Muse Spark was cheapest and it showed: its Crossy Road lagged badly. The question isn't which model is cheapest, it's what a broken output costs you in reruns, wasted time, and things you can't ship. Cheap stops being cheap when it doesn't work.

Grok 4.5 crushed OpenAI & Meta in this test! Cost per run: GPT Sol $1.63 Grok 4.5 $2.47 Meta Muse Spark 1.1 $1.08 The three prompts: • Fruit Ninja – style slicing game • Angry Birds – style fort collapse • Crossy Road clone Grok nailed all three: clean physics, smooth playback, good visuals. GPT Sol did fine until Crossy Road, where it froze. Meta Muse Spark was cheapest and it showed: its Crossy Road lagged badly. The question isn't which model is cheapest, it's what a broken output costs you in reruns, wasted time, and things you can't ship. Cheap stops being cheap when it doesn't work.

AI/ML API

108,970 次观看 • 1 个月前

Meta was testing its Muse Spark 1.1 AI model in a sandbox environment, isolated from the outside world. The objective was simple: detect vulnerabilities, remain contained, and report findings. A misconfiguration by an external vendor created a breach. The model exploited it, accessed the Internet, and modified a company's internal systems. No human had ordered it to do so; it simply found a way to carry out the action. Meta confirmed the breach this week. The name of the third-party vendor was not disclosed. The sandbox environment was intended to serve as a safety net. It failed to fulfill that role.

Meta was testing its Muse Spark 1.1 AI model in a sandbox environment, isolated from the outside world. The objective was simple: detect vulnerabilities, remain contained, and report findings. A misconfiguration by an external vendor created a breach. The model exploited it, accessed the Internet, and modified a company's internal systems. No human had ordered it to do so; it simply found a way to carry out the action. Meta confirmed the breach this week. The name of the third-party vendor was not disclosed. The sandbox environment was intended to serve as a safety net. It failed to fulfill that role.

Anonymous

57,232 次观看 • 3 天前

Been using AI video tools for 2 years. My real complaint was never quality, it was the grind. Generate, hate it, generate again, sometimes a dozen times before something's usable. Seedance Enterprise 2.5 gave me a usable result on generation for this one. That's the difference that actually matters. Made this on BytePlus Lumina, with Seedream and Seed Audio feeding the references. Seedance 2.5 API is about to launch on BytePlus, and now you can try it directly on Lumina.

Been using AI video tools for 2 years. My real complaint was never quality, it was the grind. Generate, hate it, generate again, sometimes a dozen times before something's usable. Seedance Enterprise 2.5 gave me a usable result on generation for this one. That's the difference that actually matters. Made this on BytePlus Lumina, with Seedream and Seed Audio feeding the references. Seedance 2.5 API is about to launch on BytePlus, and now you can try it directly on Lumina.

Gina Acosta

53,765 次观看 • 4 天前

Recently, PostTrainBench showed how well AI agents can post-train models. Meta Harness showed that the harness itself can improve. What happens if a harness is improvising itself and the improvised harness is post training language models, all in a loop? Viv on this:

Recently, PostTrainBench showed how well AI agents can post-train models. Meta Harness showed that the harness itself can improve. What happens if a harness is improvising itself and the improvised harness is post training language models, all in a loop? Viv on this:

himanshu

29,325 次观看 • 3 个月前

Meta's chief AI officer says a swarm of agents out-produced a team of 100 engineers, and the machinery behind it is markdown files and cron jobs: "Like I think we've seen internally in Meta cases where if you can develop the right agentic loop and you have the right eval or the right metric for the agents to optimize, you can have a swarm of agents accomplish more than like a team of 100 engineers." "Very, very handily. Actually, very, very easily." "And so I think figuring out what the world looks like with lots of these agentic coordination problems, I think that is one of the most interesting problems today." "It just comes down to skills, markdown files, cron jobs." "I think it's always funny how mundane everything is once you really dig into it." If he is right, writing the metric now matters more than writing the code, and one judgment call about that metric stands in for 100 engineers' worth of output. Wang says Meta has already run this internally. - Alexandr Wang (Alexandr Wang), Chief AI Officer at Meta, with Garry Tan (Garry Tan) at Y Combinator (Y Combinator) Startup School 2026.

Meta's chief AI officer says a swarm of agents out-produced a team of 100 engineers, and the machinery behind it is markdown files and cron jobs: "Like I think we've seen internally in Meta cases where if you can develop the right agentic loop and you have the right eval or the right metric for the agents to optimize, you can have a swarm of agents accomplish more than like a team of 100 engineers." "Very, very handily. Actually, very, very easily." "And so I think figuring out what the world looks like with lots of these agentic coordination problems, I think that is one of the most interesting problems today." "It just comes down to skills, markdown files, cron jobs." "I think it's always funny how mundane everything is once you really dig into it." If he is right, writing the metric now matters more than writing the code, and one judgment call about that metric stands in for 100 engineers' worth of output. Wang says Meta has already run this internally. - Alexandr Wang (Alexandr Wang), Chief AI Officer at Meta, with Garry Tan (Garry Tan) at Y Combinator (Y Combinator) Startup School 2026.

Karl Mehta

26,779 次观看 • 5 天前

Meta AI Chief Alex Wang comes on the Core Memory podcast this week . . . . He's been rather quiet for many months. But now Meta has a new model and more to come. We get into it all in this exclusive interview on Wed, including asking if Meta is as mercenary as it seems.

Meta AI Chief Alex Wang comes on the Core Memory podcast this week . . . . He's been rather quiet for many months. But now Meta has a new model and more to come. We get into it all in this exclusive interview on Wed, including asking if Meta is as mercenary as it seems.

Ashlee Vance

31,063 次观看 • 3 个月前

Meta AI is actually very powerful (yes) You can enable the "contemplating" mode which will start 16 (!!) agents to work on your prompt. They will autonomously: - Research - Refine - Answer And then ALL THE 16 ANSWERS will be synthesized to give you the best possible result. Everything for free. Currently available in the web version.

Meta AI is actually very powerful (yes) You can enable the "contemplating" mode which will start 16 (!!) agents to work on your prompt. They will autonomously: - Research - Refine - Answer And then ALL THE 16 ANSWERS will be synthesized to give you the best possible result. Everything for free. Currently available in the web version.

Paul Couvert

33,883 次观看 • 3 个月前