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SOMEONE BENCHMARKED 10 MODELS ON STACKING BLOCKS IN A PHYSICS SIM its basically jenga in reverse every block you place could topple the whole tower, and going higher always means more risk > opus 5 hit 11.07m using only 15 blocks, then ended its turn to lock in the...

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Om Patel

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16,272 просмотров • 1 месяц назад •via X (Twitter)

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🚨 CRYPTO: BITCOIN NETWORK HITS RARE TWO-BLOCK REORGANIZATION Not an attack. Not a bug. Just Bitcoin doing what Bitcoin does. The network briefly split into two competing chains today at block height 941,880. AntPool mined one version of block 941,881, ViaBTC extended it to 941,882. Simultaneously, Foundry USA mined its own competing versions of both blocks. The tie was broken when Foundry kept winning. Seven consecutive blocks (941,879 to 941,885). AntPool and ViaBTC's blocks became orphans. Single-block reorgs happen periodically. Two-block reorgs are much rarer, meaning the tie persisted for an entire extra block cycle. Still well within normal consensus behavior. No $BTC or funds lost. No double spends. Just proof-of-work settling a race the way Satoshi designed it.
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🚨 CRYPTO: BITCOIN NETWORK HITS RARE TWO-BLOCK REORGANIZATION Not an attack. Not a bug. Just Bitcoin doing what Bitcoin does. The network briefly split into two competing chains today at block height 941,880. AntPool mined one version of block 941,881, ViaBTC extended it to 941,882. Simultaneously, Foundry USA mined its own competing versions of both blocks. The tie was broken when Foundry kept winning. Seven consecutive blocks (941,879 to 941,885). AntPool and ViaBTC's blocks became orphans. Single-block reorgs happen periodically. Two-block reorgs are much rarer, meaning the tie persisted for an entire extra block cycle. Still well within normal consensus behavior. No $BTC or funds lost. No double spends. Just proof-of-work settling a race the way Satoshi designed it.

BSCN

16,507 просмотров • 6 месяцев назад

Which local models can actually handle tool calling? I built a framework to find out. 15 scenarios. 12 tools. Mocked responses. Temperature 0. No cherry-picking. Tested every Qwen3.5 size from 0.8B to 397B, and since some of you asked after the distillation tests: yes, I included Jackrong's Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled too. Only two models went all green: the 27B dense and the distilled 27B. The 397B? Failed two tests. The 122B? Failed one. The 35B? Failed two. The timed-out results — mostly on the smaller models, are cases where the model got stuck in a loop, repeating the same tool call until it hit the 30-second limit. The test that exposed the most models: "Search for Iceland's population, then calculate 2% of it." Simple, but 35B, 122B, and 397B all used a rounded number from memory instead of the actual search result. They didn't trust their own tool output. Small models hallucinate data. Big models ignore data. The 27B just threaded it through.
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Which local models can actually handle tool calling? I built a framework to find out. 15 scenarios. 12 tools. Mocked responses. Temperature 0. No cherry-picking. Tested every Qwen3.5 size from 0.8B to 397B, and since some of you asked after the distillation tests: yes, I included Jackrong's Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled too. Only two models went all green: the 27B dense and the distilled 27B. The 397B? Failed two tests. The 122B? Failed one. The 35B? Failed two. The timed-out results — mostly on the smaller models, are cases where the model got stuck in a loop, repeating the same tool call until it hit the 30-second limit. The test that exposed the most models: "Search for Iceland's population, then calculate 2% of it." Simple, but 35B, 122B, and 397B all used a rounded number from memory instead of the actual search result. They didn't trust their own tool output. Small models hallucinate data. Big models ignore data. The 27B just threaded it through.

stevibe

434,661 просмотров • 6 месяцев назад

Why does Ethereum's whitepaper name the mind behind Kaspa? Yonatan Sompolinsky (Yonatan Sompolinsky) and Aviv Zohar (Aviv Zohar) introduced GHOST in December 2013. It counts stale blocks, valid blocks that lose the race onto the main chain, toward security instead of wasting them. The Ethereum whitepaper credits both men by name. Ethereum ran only a simplified version, and a later note added to the paper says it never fully applied GHOST. Sompolinsky pushed the idea further with GHOSTDAG, co-written with Shai Wyborski and Zohar. It lets parallel blocks coexist and orders them all, discarding none. GHOSTDAG powers #Kaspa (kaspa:native), which launched on November 7, 2021.
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Why does Ethereum's whitepaper name the mind behind Kaspa? Yonatan Sompolinsky (Yonatan Sompolinsky) and Aviv Zohar (Aviv Zohar) introduced GHOST in December 2013. It counts stale blocks, valid blocks that lose the race onto the main chain, toward security instead of wasting them. The Ethereum whitepaper credits both men by name. Ethereum ran only a simplified version, and a later note added to the paper says it never fully applied GHOST. Sompolinsky pushed the idea further with GHOSTDAG, co-written with Shai Wyborski and Zohar. It lets parallel blocks coexist and orders them all, discarding none. GHOSTDAG powers #Kaspa (kaspa:native), which launched on November 7, 2021.

BSCN

38,548 просмотров • 12 дней назад

Kimi K3 beats GPT 5.6 Sol on both speed and in cost in backend bug fixing ! Planted 4 defects in the same Python order service: a wrong-total calculation, a broken access-control check (IDOR), a crash on invalid input, and an inventory oversell. Both models got identical code and the same prompt, with an automated test suite verifying every fix over the live API. Both went 4/4, but by the time Kimi K3 finished all 4, GPT 5.6 had only fixed 2. Kimi wrapped in under half the time, at half the cost. Kimi K3: 1min 34s · $0.1 · 4/4 GPT 5.6 Sol: 4min 6s · $0.2 · 4/4
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Kimi K3 beats GPT 5.6 Sol on both speed and in cost in backend bug fixing ! Planted 4 defects in the same Python order service: a wrong-total calculation, a broken access-control check (IDOR), a crash on invalid input, and an inventory oversell. Both models got identical code and the same prompt, with an automated test suite verifying every fix over the live API. Both went 4/4, but by the time Kimi K3 finished all 4, GPT 5.6 had only fixed 2. Kimi wrapped in under half the time, at half the cost. Kimi K3: 1min 34s · $0.1 · 4/4 GPT 5.6 Sol: 4min 6s · $0.2 · 4/4

GMI Cloud

24,715 просмотров • 2 месяцев назад

⚡️Kaspa 11 #11 - BlockDAG Kaspa's BlockDAG data structure enables its unique GHOSTDAG consensus algorithm to solve the orphan blocks problem, allowing for high frequency block generation and high scalability. Learn all about this feature and others via the link in the thread. The 10BPS 𝆒 Crescendo update is set to be hard-forked into mainnet at DAA Score 110,165,000, projected to occur on May 5, 2025, at approximately 15:00 UTC. ~ 3 Days
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⚡️Kaspa 11 #11 - BlockDAG Kaspa's BlockDAG data structure enables its unique GHOSTDAG consensus algorithm to solve the orphan blocks problem, allowing for high frequency block generation and high scalability. Learn all about this feature and others via the link in the thread. The 10BPS 𝆒 Crescendo update is set to be hard-forked into mainnet at DAA Score 110,165,000, projected to occur on May 5, 2025, at approximately 15:00 UTC. ~ 3 Days

Kaspa

32,642 просмотров • 1 год назад

1-bit Kimi K3 performs at Opus 5 level on 3D physics! We ran our Atomic Chat quant of Kimi K3 locally on 4x B200 against three cloud models and gave them all the same task, to build a giant anvil drop test as a single HTML file with real physics Outputs: K3 1bit (local): 15.8K tokens, $0 API cost Kimi K3 (API): 15.3K tokens, $0.30 API cost Opus 5: 22.8K tokens, $0.77 API cost GPT 5.6: 14.5K tokens, $0.72 API cost All four got the physics right. But only Kimi made a working winch. The drum turns and the chain drags the flat car off the pad. Opus 5 drew the most detail, road markings and sparks on the hit. And you can run a model at this level on your own box now. That still feels insane to us
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1-bit Kimi K3 performs at Opus 5 level on 3D physics! We ran our Atomic Chat quant of Kimi K3 locally on 4x B200 against three cloud models and gave them all the same task, to build a giant anvil drop test as a single HTML file with real physics Outputs: K3 1bit (local): 15.8K tokens, $0 API cost Kimi K3 (API): 15.3K tokens, $0.30 API cost Opus 5: 22.8K tokens, $0.77 API cost GPT 5.6: 14.5K tokens, $0.72 API cost All four got the physics right. But only Kimi made a working winch. The drum turns and the chain drags the flat car off the pad. Opus 5 drew the most detail, road markings and sparks on the hit. And you can run a model at this level on your own box now. That still feels insane to us

atomic.chat

53,845 просмотров • 2 месяцев назад

April 30 • 12:00pm ET Art Blocks + OpenSea “Gift of time” began during my residency in Marfa, Texas, as part of the Art Blocks and OpenSea artist residency program, where a distinct shift in the experience of time became central to the work. In the desert, I felt time move differently. It stretched, slowed, and became something I noticed. After a few days, the rhythm changed. Moments felt longer, attention sharpened, and I became increasingly aware of each moment as it passed. This work comes from that condition. Time is not treated only as a theme, but as a system embedded in the structure of the piece. Different ways of measuring time, such as mechanical cycles, calendars, and lunar phases, are translated into rules that continuously transform the work. The piece does not represent time. It runs on it. Its movement is tied to blockchain time. Even when unseen, it continues to rotate and evolve. When loaded, it synchronizes with the present moment, but it does not begin when it is viewed, and it does not stop when it disappears from the screen. During the residency, I spent hours thinking, sketching, and making connections. Those connections are also visible. Elastic lines, like rubber bands, link elements across the piece, representing how memories connect, how one thought leads to another, and how everything builds over time. These same connections introduce moments where the system attempts to pull itself back, as if trying to regain control. But it never fully resets. It is not a loop. The movement continues, drifting forward, never returning to a fixed state. Visually, the work reveals its own construction. Lines, paths, and rotations expose an internal logic, like looking inside a mechanism. The drawing language recalls diagrams, technical sketches, or the interior of a mechanical watch. It is a system in motion, always active. “Gift of Time” exists because I was given time by Art Blocks, OpenSea, and above all my family. It is my way of saying thank you. It is both a reflection on time and a product of it. April 30 @ 12:00pm ET on Art blocks & OpenSea 1 / 1 / 365 • 0.02 Eth Art Blocks, OpenSea
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April 30 • 12:00pm ET Art Blocks + OpenSea “Gift of time” began during my residency in Marfa, Texas, as part of the Art Blocks and OpenSea artist residency program, where a distinct shift in the experience of time became central to the work. In the desert, I felt time move differently. It stretched, slowed, and became something I noticed. After a few days, the rhythm changed. Moments felt longer, attention sharpened, and I became increasingly aware of each moment as it passed. This work comes from that condition. Time is not treated only as a theme, but as a system embedded in the structure of the piece. Different ways of measuring time, such as mechanical cycles, calendars, and lunar phases, are translated into rules that continuously transform the work. The piece does not represent time. It runs on it. Its movement is tied to blockchain time. Even when unseen, it continues to rotate and evolve. When loaded, it synchronizes with the present moment, but it does not begin when it is viewed, and it does not stop when it disappears from the screen. During the residency, I spent hours thinking, sketching, and making connections. Those connections are also visible. Elastic lines, like rubber bands, link elements across the piece, representing how memories connect, how one thought leads to another, and how everything builds over time. These same connections introduce moments where the system attempts to pull itself back, as if trying to regain control. But it never fully resets. It is not a loop. The movement continues, drifting forward, never returning to a fixed state. Visually, the work reveals its own construction. Lines, paths, and rotations expose an internal logic, like looking inside a mechanism. The drawing language recalls diagrams, technical sketches, or the interior of a mechanical watch. It is a system in motion, always active. “Gift of Time” exists because I was given time by Art Blocks, OpenSea, and above all my family. It is my way of saying thank you. It is both a reflection on time and a product of it. April 30 @ 12:00pm ET on Art blocks & OpenSea 1 / 1 / 365 • 0.02 Eth Art Blocks, OpenSea

Manuel Lariño ☔️

21,931 просмотров • 5 месяцев назад

A guy fed 4.2M expired US patents to Claude and found 6 products nobody manufactures anymore. p.s first one is already in production Every expired patent becomes public. All 4.2M of them are written in legal language nobody actually reads. He asked Claude to process the entire database and score each patent by its attractiveness. All the research, all the problems, all the solutions already documented, someone already paid for that. Just pick the best one and start cooking. Here's how it works: > Python scraper pulls expired patents from USPTO > converts docs to clean Markdown > scores each one 1-10 on viability > applies a filter: score 7+ only > only 1 in 80 selects It found 6 products in 3 weeks and the first one is already generating a profit. how many of those 4.2M are still waiting for you?
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A guy fed 4.2M expired US patents to Claude and found 6 products nobody manufactures anymore. p.s first one is already in production Every expired patent becomes public. All 4.2M of them are written in legal language nobody actually reads. He asked Claude to process the entire database and score each patent by its attractiveness. All the research, all the problems, all the solutions already documented, someone already paid for that. Just pick the best one and start cooking. Here's how it works: > Python scraper pulls expired patents from USPTO > converts docs to clean Markdown > scores each one 1-10 on viability > applies a filter: score 7+ only > only 1 in 80 selects It found 6 products in 3 weeks and the first one is already generating a profit. how many of those 4.2M are still waiting for you?

Spivach

11,704 просмотров • 5 месяцев назад

Pi0 vs. ACT with BBox conditioning 🟦 Not many know you can push ACT to *almost-Pi0* generalisation by conditioning on bounding boxes (BBoxes). How is the training data collected? • Generate BBoxes for all pick-and-place objects in the scene.(I used Gemini) • Pick-and-place targets are selected randomly. • Add the BBox coordinates to the robot’s state. • Overlay the BBoxes in the visualisation so you know what to grab and where to drop. During inference: • Generate BBoxes for every object again. • Click the object you want to pick and its target spot; those BBoxes get added to the robot state. • Let the robot do the work for you 😃 Setup: - Trained ACT for 100k steps and fine-tuned Pi0 for only 20k. - Training data is 60 episodes and had *only* LEGO bricks. - Using single front camera (Laptop in this case) Got the idea from xun in LeRobot discord. Here’s ACT vs Pi0 on a toy car that isn’t in the dataset. 1/3
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Pi0 vs. ACT with BBox conditioning 🟦 Not many know you can push ACT to *almost-Pi0* generalisation by conditioning on bounding boxes (BBoxes). How is the training data collected? • Generate BBoxes for all pick-and-place objects in the scene.(I used Gemini) • Pick-and-place targets are selected randomly. • Add the BBox coordinates to the robot’s state. • Overlay the BBoxes in the visualisation so you know what to grab and where to drop. During inference: • Generate BBoxes for every object again. • Click the object you want to pick and its target spot; those BBoxes get added to the robot state. • Let the robot do the work for you 😃 Setup: - Trained ACT for 100k steps and fine-tuned Pi0 for only 20k. - Training data is 60 episodes and had *only* LEGO bricks. - Using single front camera (Laptop in this case) Got the idea from xun in LeRobot discord. Here’s ACT vs Pi0 on a toy car that isn’t in the dataset. 1/3

Shreyas Gite

34,863 просмотров • 1 год назад

The Khumbu Glacier has revealed another silent tragedy, a body emerging from ice that once kept its secrets buried for years, pictured this season 2026. What was frozen in place is now being exposed as temperatures rise across the Himalaya, turning Everest into one of the clearest frontlines of climate change. This season, the warning signs continue higher up in the Khumbu Icefall, where massive unstable serac blocks have delayed route opening and increased danger for climbers and Sherpas. On Everest, the past is resurfacing, and the future is becoming more uncertain.
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The Khumbu Glacier has revealed another silent tragedy, a body emerging from ice that once kept its secrets buried for years, pictured this season 2026. What was frozen in place is now being exposed as temperatures rise across the Himalaya, turning Everest into one of the clearest frontlines of climate change. This season, the warning signs continue higher up in the Khumbu Icefall, where massive unstable serac blocks have delayed route opening and increased danger for climbers and Sherpas. On Everest, the past is resurfacing, and the future is becoming more uncertain.

Everest Today

106,755 просмотров • 5 месяцев назад

Max Recorded TPS (1 Block) is now on Chainspect! 🚀 So far, we've measured Max Recorded TPS only for a period of 100 blocks. You take the total transactions over the time and divide them by cumulative block time to get at estimate of what TPS a blockchain can churn out consistently during peak workload periods. Now, we're adding the Max Recorded TPS per block. That's the highest-ever burst TPS a chain has handled on record — a measure of its peak performance under high stress. Check out how your fav chain has fared:
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Max Recorded TPS (1 Block) is now on Chainspect! 🚀 So far, we've measured Max Recorded TPS only for a period of 100 blocks. You take the total transactions over the time and divide them by cumulative block time to get at estimate of what TPS a blockchain can churn out consistently during peak workload periods. Now, we're adding the Max Recorded TPS per block. That's the highest-ever burst TPS a chain has handled on record — a measure of its peak performance under high stress. Check out how your fav chain has fared:

Chainspect

49,252 просмотров • 1 год назад

OpenCode Go is now wired into Codex!! The pricing is insane. $10 gets you 10,000 DeepSeek requests every 5 hours (no weekly limits). I converted that into DeepSeek API dollars because I thought I was reading it wrong, and the same 5 hours of usage would run somewhere between $10 and $30 depending on how big your context gets. So one afternoon of use already covers the whole sub. It comes with Kimi K3 as well. Both sit in the picker next to my other models now. Next time we hit a limit in the middle of a loop, we can grab it and keep going.
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OpenCode Go is now wired into Codex!! The pricing is insane. $10 gets you 10,000 DeepSeek requests every 5 hours (no weekly limits). I converted that into DeepSeek API dollars because I thought I was reading it wrong, and the same 5 hours of usage would run somewhere between $10 and $30 depending on how big your context gets. So one afternoon of use already covers the whole sub. It comes with Kimi K3 as well. Both sit in the picker next to my other models now. Next time we hit a limit in the middle of a loop, we can grab it and keep going.

Ziwen

434,241 просмотров • 1 месяц назад

Situation on Aleppo [9/1/2026]: [11:00 AM] During the early hours of the morning, the STG continued to advance and secure areas previously evacuated by Asayish forces: in the north, trenches were taken west of the Youth Housing Complex, as well as in the Barakah Quarries, where another series of trenches and new blocks were taken in the Resafa district, as well as the last blocks of the Al Layramoun Industrial district to the west. In the south, the New Syriac district was completely taken and the area was expanded beyond the Assyrian Quarter district after entering the cemetery area and capturing the Al-Jalaa Sports Club. Meanwhile, from the east, the assault on the Sheikh Maqsud district began and the first blocks of the Awared neighborhood were entered. All these advances took place prior to the start of a ceasefire brokered by the US and France, in which the Damascus authorities issued a new ultimatum for the surrender of the enclave in exchange for the evacuation of the inhabitants and Asayish soldiers. Despite the arrival of a convoy of buses in the morning, the Asayish rejected the evacuation and declared their commitment to continue defending the inhabitants of the enclave, given the danger of a new massacre similar to those on the Syrian coast or in Suwayda. Meanwhile, in the east of the Euphrates, a general mobilization has begun in solidarity with the besieged troops, in anticipation of the fighting spreading to the rest of the territory under SDF control. Map: [ ]
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Situation on Aleppo [9/1/2026]: [11:00 AM] During the early hours of the morning, the STG continued to advance and secure areas previously evacuated by Asayish forces: in the north, trenches were taken west of the Youth Housing Complex, as well as in the Barakah Quarries, where another series of trenches and new blocks were taken in the Resafa district, as well as the last blocks of the Al Layramoun Industrial district to the west. In the south, the New Syriac district was completely taken and the area was expanded beyond the Assyrian Quarter district after entering the cemetery area and capturing the Al-Jalaa Sports Club. Meanwhile, from the east, the assault on the Sheikh Maqsud district began and the first blocks of the Awared neighborhood were entered. All these advances took place prior to the start of a ceasefire brokered by the US and France, in which the Damascus authorities issued a new ultimatum for the surrender of the enclave in exchange for the evacuation of the inhabitants and Asayish soldiers. Despite the arrival of a convoy of buses in the morning, the Asayish rejected the evacuation and declared their commitment to continue defending the inhabitants of the enclave, given the danger of a new massacre similar to those on the Syrian coast or in Suwayda. Meanwhile, in the east of the Euphrates, a general mobilization has begun in solidarity with the besieged troops, in anticipation of the fighting spreading to the rest of the territory under SDF control. Map: [ ]

@Suriyak

21,749 просмотров • 8 месяцев назад

Codex can now run Deepseek-v4- flash! There's a catch though. Deepseek's official setup switches your entire codex over to them, so your GPT models stop showing up at all. This is exactly what Codex Router is for. It adds models to the list instead of replacing them, so sol, grok, kimi and deepseek all sit in the same picker and i just grab whichever one suits the job. Deepseek v4-flash is $0.28 per million output tokens. opus 4.8 is $25. same picker, 89x apart. Links in the comment. setup's in the video 👇
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Codex can now run Deepseek-v4- flash! There's a catch though. Deepseek's official setup switches your entire codex over to them, so your GPT models stop showing up at all. This is exactly what Codex Router is for. It adds models to the list instead of replacing them, so sol, grok, kimi and deepseek all sit in the same picker and i just grab whichever one suits the job. Deepseek v4-flash is $0.28 per million output tokens. opus 4.8 is $25. same picker, 89x apart. Links in the comment. setup's in the video 👇

Ziwen

145,018 просмотров • 2 месяцев назад

i just open sourced the workflow behind $2M AI video productions... i built 7 skills that run the pipeline end to end, built for Seedance 2.5 and they work in Claude Code, Codex, Hermes or any harness (works best with 1080p using Higgsfield CLI) here's how to use them, in order: /setup writes which image and video models you run into your project, once, so every skill reads the same stack /studio-init scaffolds the whole studio as a file tree from one question, the project name /film-breakdown walks your script scene by scene and writes a 22-field card for every shot /reference-board locks your references into a visual bible, a caption on every image and a ban list for the rest /asset-passport writes the exhaustive descriptor every later prompt will quote word for word /stress-test combat-tests each asset and flips it to locked only at 10 out of 10 repeatability /shot-prompt refuses to run until everything in frame is locked, then writes the 15-block prompt and logs every attempt get access to the skills and full breakdown of the pipeline in the article below:
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i just open sourced the workflow behind $2M AI video productions... i built 7 skills that run the pipeline end to end, built for Seedance 2.5 and they work in Claude Code, Codex, Hermes or any harness (works best with 1080p using Higgsfield CLI) here's how to use them, in order: /setup writes which image and video models you run into your project, once, so every skill reads the same stack /studio-init scaffolds the whole studio as a file tree from one question, the project name /film-breakdown walks your script scene by scene and writes a 22-field card for every shot /reference-board locks your references into a visual bible, a caption on every image and a ban list for the rest /asset-passport writes the exhaustive descriptor every later prompt will quote word for word /stress-test combat-tests each asset and flips it to locked only at 10 out of 10 repeatability /shot-prompt refuses to run until everything in frame is locked, then writes the 15-block prompt and logs every attempt get access to the skills and full breakdown of the pipeline in the article below:

Machina

61,554 просмотров • 1 месяц назад

Here's a quick overview of what we can or could expect from #Kaspa in 2025. - At least 10 blocks per second with a PoW BlockDAG - Listings on major exchanges such as #Binance, #OKX or #Coinbase - A stablecoin on the $KAS BlockDAG - DAGKnight as a new consensus mechanism - Possibly smart contracts - And probably more partnerships in the energy sector and other interesting areas All in all, very bullish and, in my opinion, the most exciting year for Kaspa so far. Especially because a lot of people are mainly looking at the price, I am sure that these people will also be very happy soon. What have I forgotten and what do you think will have the biggest impact on KAS?
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Here's a quick overview of what we can or could expect from #Kaspa in 2025. - At least 10 blocks per second with a PoW BlockDAG - Listings on major exchanges such as #Binance, #OKX or #Coinbase - A stablecoin on the $KAS BlockDAG - DAGKnight as a new consensus mechanism - Possibly smart contracts - And probably more partnerships in the energy sector and other interesting areas All in all, very bullish and, in my opinion, the most exciting year for Kaspa so far. Especially because a lot of people are mainly looking at the price, I am sure that these people will also be very happy soon. What have I forgotten and what do you think will have the biggest impact on KAS?

KASPA Enthusiast 𐤊

19,375 просмотров • 1 год назад

SOMEONE GOT TIRED OF PAYING HIGGSFIELD AI'S SUBSCRIPTION SO HE REBUILT THE WHOLE THING AND OPEN-SOURCED IT 200+ models. text-to-image, image-to-image, text-to-video, image-to-video all in one interface you configure a virtual camera in the Cinema Studio. pick the body, the lens, the focal length, the aperture and it writes the optimized cinematic prompt for you. completely in the background you never touch the camera keywords. you just set up the shot like a real cinematographer would Kling v3, Sora 2, Veo 3, Flux Dev, Midjourney v7, GPT-4o, Seedream 5.0, Runway Gen-3 all in there self-hosted. MIT licensed. runs on your machine. your data stays local the only thing you pay for is the model API calls themselves someone built this so you never have to pay Higgsfield AI again
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SOMEONE GOT TIRED OF PAYING HIGGSFIELD AI'S SUBSCRIPTION SO HE REBUILT THE WHOLE THING AND OPEN-SOURCED IT 200+ models. text-to-image, image-to-image, text-to-video, image-to-video all in one interface you configure a virtual camera in the Cinema Studio. pick the body, the lens, the focal length, the aperture and it writes the optimized cinematic prompt for you. completely in the background you never touch the camera keywords. you just set up the shot like a real cinematographer would Kling v3, Sora 2, Veo 3, Flux Dev, Midjourney v7, GPT-4o, Seedream 5.0, Runway Gen-3 all in there self-hosted. MIT licensed. runs on your machine. your data stays local the only thing you pay for is the model API calls themselves someone built this so you never have to pay Higgsfield AI again

Rimsha Bhardwaj

101,547 просмотров • 5 месяцев назад

Sui consensus skips the certification round that older designs required Validators on Sui all propose blocks at once instead of taking turns. Older designs required each block to collect signatures from a quorum of validators before it counted, and that's where the time savings lived. Mysticeti cuts the wait, because now every block can be committed as soon as it is decided, bringing consensus commit down to about half a second. Moving the sui:native chain onto it cut latency by over four times. That old signing round guaranteed one block per validator per slot, and dropping it means a validator can now put out two. Now the commit rules carry that problem instead. Sui shipped a second version last year that also folds into the fast path.
0:14

Sui consensus skips the certification round that older designs required Validators on Sui all propose blocks at once instead of taking turns. Older designs required each block to collect signatures from a quorum of validators before it counted, and that's where the time savings lived. Mysticeti cuts the wait, because now every block can be committed as soon as it is decided, bringing consensus commit down to about half a second. Moving the sui:native chain onto it cut latency by over four times. That old signing round guaranteed one block per validator per slot, and dropping it means a validator can now put out two. Now the commit rules carry that problem instead. Sui shipped a second version last year that also folds into the fast path.

BSCN

19,228 просмотров • 23 дней назад

I'm building my game with GPT-6, and color correction has become one of my favorite uses for it. When I generate assets separately, I can like each one on its own and still end up with a scene where the colors don't belong together. A castle looks fine in isolation, then turns greenish against the terrain. Its swords and shields disappear into the background. Getting those things to match used to mean a lot of repainting and trying different textures. Now I've built a workflow where GPT-6 takes screenshots in Unity, inspects the object's color textures, and helps bring them closer to the look I want. I can give it the terrain or tree textures as color references. It can prepare masks, send the relevant textures through Image Edit, then put the result back into the game for another look. Editors such as GPT Image 2 Edit or Nano Banana Edit can be part of that workflow. This is also why I keep pushing for properly prepared 3D models. If the parts are separated logically, you get much more control later. We could work on the swords and shields without changing the whole castle. The stone could stay dark while the equipment became easier to read. The latest pass on my game covered the overall post effects and the skeleton castles. We matched the castles to the surrounding terrain, adjusted the equipment colors, and added a subtle moving highlight. The first stronger color pass went too far. I asked for the accents to move about 30% closer to gray, and that got them where I wanted: visible, without pulling all the attention. I'm so happy with the difference. The video shows the before and after across the map and on the castles. Being able to give feedback on the actual scene and keep refining it this way feels great.
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I'm building my game with GPT-6, and color correction has become one of my favorite uses for it. When I generate assets separately, I can like each one on its own and still end up with a scene where the colors don't belong together. A castle looks fine in isolation, then turns greenish against the terrain. Its swords and shields disappear into the background. Getting those things to match used to mean a lot of repainting and trying different textures. Now I've built a workflow where GPT-6 takes screenshots in Unity, inspects the object's color textures, and helps bring them closer to the look I want. I can give it the terrain or tree textures as color references. It can prepare masks, send the relevant textures through Image Edit, then put the result back into the game for another look. Editors such as GPT Image 2 Edit or Nano Banana Edit can be part of that workflow. This is also why I keep pushing for properly prepared 3D models. If the parts are separated logically, you get much more control later. We could work on the swords and shields without changing the whole castle. The stone could stay dark while the equipment became easier to read. The latest pass on my game covered the overall post effects and the skeleton castles. We matched the castles to the surrounding terrain, adjusted the equipment colors, and added a subtle moving highlight. The first stronger color pass went too far. I asked for the accents to move about 30% closer to gray, and that got them where I wanted: visible, without pulling all the attention. I'm so happy with the difference. The video shows the before and after across the map and on the castles. Being able to give feedback on the actual scene and keep refining it this way feels great.

Stefan 3D AI

16,850 просмотров • 15 дней назад