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(1/5) What's the perfect path around first base? Nobody has the answer. Math models give us a theoretical ideal. A new GPS study gives us segment-by-segment speed data. But no one's mapped it with real runners on real dirt — cleat traction, body types, bag placement. Still open.

Kevin Graber

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59,930 просмотров • 11 дней назад •via X (Twitter)

Наука и технологии Образование Спорт

Anya Rossi• Live Now

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No data, no problem introducing agentic synthetic data generation with Cosmos 3 share a few examples, generate more data, automate model training, automatically deploy the latest version with no downtime in a benchmark run with Corning Incorporated's optical fiber manufacturing engineering team, a model trained on 8 real defect images plus synthetic examples generated by Cosmos reached 0.95 mean average precision and perfect recall on the toughest defect class, beating a baseline trained on real data alone. "The Roboflow Agent powered by NVIDIA allows us to generate the training data we need, fine-tune our models, and strengthen model performance and inspection quality while increasing the speed, scalability, and adoption of next-generation technologies,” - Jeremy Knopf, chief information officer, Corning Optical Communications

No data, no problem introducing agentic synthetic data generation with Cosmos 3 share a few examples, generate more data, automate model training, automatically deploy the latest version with no downtime in a benchmark run with Corning Incorporated's optical fiber manufacturing engineering team, a model trained on 8 real defect images plus synthetic examples generated by Cosmos reached 0.95 mean average precision and perfect recall on the toughest defect class, beating a baseline trained on real data alone. "The Roboflow Agent powered by NVIDIA allows us to generate the training data we need, fine-tune our models, and strengthen model performance and inspection quality while increasing the speed, scalability, and adoption of next-generation technologies,” - Jeremy Knopf, chief information officer, Corning Optical Communications

Roboflow

39,115 просмотров • 1 месяц назад

✨Since 2019, Phemex has been on a mission to rewrite what finance can be — open, fair, and built around real users, not just volume. Freedom Through Finance for everyone. 🌍Let's step towards a new era of A User-First Crypto Exchange, together. Meet the new #Phemex and tell us how it feels ⬇️

✨Since 2019, Phemex has been on a mission to rewrite what finance can be — open, fair, and built around real users, not just volume. Freedom Through Finance for everyone. 🌍Let's step towards a new era of A User-First Crypto Exchange, together. Meet the new #Phemex and tell us how it feels ⬇️

Phemex

11,645 просмотров • 8 месяцев назад

DiT4DiT is now open source! As the first humanoid-deployable Video-Action Model built on a world model, DiT4DiT continues to surprise us. In our paper last month, we showed its strong data efficiency. Now, with only slight modifications, it enables real-time whole-body autonomous pick-and-place. Paper: Code: Website:

DiT4DiT is now open source! As the first humanoid-deployable Video-Action Model built on a world model, DiT4DiT continues to surprise us. In our paper last month, we showed its strong data efficiency. Now, with only slight modifications, it enables real-time whole-body autonomous pick-and-place. Paper: Code: Website:

Shuo Yang

14,308 просмотров • 3 месяцев назад

It is the start of a new week. There are many hurts and grievances. Many disappointments. Some explainable, others not. But in all things, we give thanks to God. We give thanks not because we are satisfied or happy with everything or everyone around us. Not because we have the answers to the many niggling questions that keep us awake at night. Not because we know the way. We give thanks because he gave us life. We are still here with a fighting chance, no matter how bleak it may seem. There's a reason we are still breathing and not on a cold morgue slab. That reason is the hope we cling on to. The faith we keep. The process we trust. He has kept us going for a reason. And for that we give thanks. Keep the faith. Pick yourself up. Your final chapter is not yet written. He has got us all. He NEVER fails! Shalom. 🦁🙏🏾

It is the start of a new week. There are many hurts and grievances. Many disappointments. Some explainable, others not. But in all things, we give thanks to God. We give thanks not because we are satisfied or happy with everything or everyone around us. Not because we have the answers to the many niggling questions that keep us awake at night. Not because we know the way. We give thanks because he gave us life. We are still here with a fighting chance, no matter how bleak it may seem. There's a reason we are still breathing and not on a cold morgue slab. That reason is the hope we cling on to. The faith we keep. The process we trust. He has kept us going for a reason. And for that we give thanks. Keep the faith. Pick yourself up. Your final chapter is not yet written. He has got us all. He NEVER fails! Shalom. 🦁🙏🏾

Sam 'Dzata' George 🦁🇬🇭

11,086 просмотров • 4 месяцев назад

Fireworks AI is now available first-party in Microsoft Foundry, as part of a multi-year partnership, starting today in private preview. Enterprise AI has a speed problem. Most infrastructure can't keep up with how fast open models are moving. New architectures, fine-tuned weights, models that aren't on anyone's approved list yet. The usual answer was "manage your own serving infrastructure." That's a real cost. Fireworks runs the inference. Azure owns the governance. Your weights stay yours. Beyond custom weights, teams can also access the latest open models on day zero. No waiting for the marketplace to catch up. Serverless inference for prototyping, and a path to production that doesn't require re-architecting anything. Fireworks handles the serving layer. Azure handles the rest. Your boss handles the congratulations. Want in →

Fireworks AI is now available first-party in Microsoft Foundry, as part of a multi-year partnership, starting today in private preview. Enterprise AI has a speed problem. Most infrastructure can't keep up with how fast open models are moving. New architectures, fine-tuned weights, models that aren't on anyone's approved list yet. The usual answer was "manage your own serving infrastructure." That's a real cost. Fireworks runs the inference. Azure owns the governance. Your weights stay yours. Beyond custom weights, teams can also access the latest open models on day zero. No waiting for the marketplace to catch up. Serverless inference for prototyping, and a path to production that doesn't require re-architecting anything. Fireworks handles the serving layer. Azure handles the rest. Your boss handles the congratulations. Want in →

Fireworks AI

51,657 просмотров • 4 месяцев назад

The Pitot Tube — The Tiny Device That Keeps Your Plane Alive ✈️📏 This little metal tube on the nose of the aircraft? Yeah… it’s one of the MOST IMPORTANT instruments in aviation. 🤯 🔥 What it does: It measures the air pressure rushing in, which gives the plane its AIR SPEED. No Pitot = No speed. No speed = No flight. Simple and terrifying. ⚠️ If a Pitot Tube gets blocked (ice, bugs, dirt)… the aircraft can get wrong speed readings, and that has caused real aviation accidents. 💡 That’s why pilots test it, mechanics inspect it, and heaters keep it warm in flight. It’s small. It’s simple. But it’s absolutely critical. 📸 by ig/jet.nerd

The Pitot Tube — The Tiny Device That Keeps Your Plane Alive ✈️📏 This little metal tube on the nose of the aircraft? Yeah… it’s one of the MOST IMPORTANT instruments in aviation. 🤯 🔥 What it does: It measures the air pressure rushing in, which gives the plane its AIR SPEED. No Pitot = No speed. No speed = No flight. Simple and terrifying. ⚠️ If a Pitot Tube gets blocked (ice, bugs, dirt)… the aircraft can get wrong speed readings, and that has caused real aviation accidents. 💡 That’s why pilots test it, mechanics inspect it, and heaters keep it warm in flight. It’s small. It’s simple. But it’s absolutely critical. 📸 by ig/jet.nerd

aircraftmaintenancengineer

702,645 просмотров • 7 месяцев назад

NVIDIA CEO, Jensen Huang, warns that America's lead in AI is far from secure. He breaks down the US-China AI competition into what he calls a "five-layer cake." And while the US dominates some layers, Jensen sees critical vulnerabilities in others... 1) Energy: China has twice as much as the US despite a smaller economy. Which "makes no sense" to Jensen. 2) Chips: The US is "generations ahead," but Jensen warns against complacency. "Anybody who thinks China can't manufacture is missing the big idea." 3) Infrastructure: Standing up a data center in the US takes about three years. In China? "They can build a hospital in a weekend." 4) Models: US frontier models are "unquestionably world class," but "China is well ahead, way ahead on open source." 5) Applications: Public sentiment differs sharply. Ask both populations whether AI will do more good than harm, and "in their case 80% would say AI will do more good than harm. In our case, it'd be the other way around." Jensen's warning is clear. Leading in chips and frontier models isn't enough when you're behind on energy, infrastructure speed, open source, and public trust. Winning the AI race requires strength across the entire stack, and right now, the US has work to do.

NVIDIA CEO, Jensen Huang, warns that America's lead in AI is far from secure. He breaks down the US-China AI competition into what he calls a "five-layer cake." And while the US dominates some layers, Jensen sees critical vulnerabilities in others... 1) Energy: China has twice as much as the US despite a smaller economy. Which "makes no sense" to Jensen. 2) Chips: The US is "generations ahead," but Jensen warns against complacency. "Anybody who thinks China can't manufacture is missing the big idea." 3) Infrastructure: Standing up a data center in the US takes about three years. In China? "They can build a hospital in a weekend." 4) Models: US frontier models are "unquestionably world class," but "China is well ahead, way ahead on open source." 5) Applications: Public sentiment differs sharply. Ask both populations whether AI will do more good than harm, and "in their case 80% would say AI will do more good than harm. In our case, it'd be the other way around." Jensen's warning is clear. Leading in chips and frontier models isn't enough when you're behind on energy, infrastructure speed, open source, and public trust. Winning the AI race requires strength across the entire stack, and right now, the US has work to do.

Big Brain AI

59,540 просмотров • 7 месяцев назад

🪼 A US F-15 pilot ejected after being swarmed by Iranian drones forming a literal jellyfish in the sky. Multiple drones “moving as one,” with smaller ones hanging below like tentacles. Sources close to his April debrief called it “real alien shit” and a “minefield of drones.” This is the first time a US fighter has been downed over Iran in the current conflict. US intelligence is still debating whether Iran just showed a new level of coordinated drone swarm capability. The Young Turks break down exactly what the pilot described and what it means for the future of air warfare:

🪼 A US F-15 pilot ejected after being swarmed by Iranian drones forming a literal jellyfish in the sky. Multiple drones “moving as one,” with smaller ones hanging below like tentacles. Sources close to his April debrief called it “real alien shit” and a “minefield of drones.” This is the first time a US fighter has been downed over Iran in the current conflict. US intelligence is still debating whether Iran just showed a new level of coordinated drone swarm capability. The Young Turks break down exactly what the pilot described and what it means for the future of air warfare:

Masu Zafi 🔥🔥

23,075 просмотров • 1 месяц назад

Co-training has become a key part of the recipe for training large robotics models; it means that you mix some proportion of real robot data with other data sources, like simulation or egocentric human video data. This is especially important because robotics data tends to lack diversity which can be somewhat compensated for by the inclusion of these other modalities. And yet there has not been a sizable study on what constitute good practices for cotraining until now! We talk to Fanqi Lin and Jose Barreiros about their new work, a massive study which evaluated 89 policies over thousands of rollouts to tell us which forms of co-training were most useful for robotics. Watch episode 70 of RoboPapers, with Michael Cho and Chris Paxton, now!

Co-training has become a key part of the recipe for training large robotics models; it means that you mix some proportion of real robot data with other data sources, like simulation or egocentric human video data. This is especially important because robotics data tends to lack diversity which can be somewhat compensated for by the inclusion of these other modalities. And yet there has not been a sizable study on what constitute good practices for cotraining until now! We talk to Fanqi Lin and Jose Barreiros about their new work, a massive study which evaluated 89 policies over thousands of rollouts to tell us which forms of co-training were most useful for robotics. Watch episode 70 of RoboPapers, with Michael Cho and Chris Paxton, now!

RoboPapers

19,152 просмотров • 3 месяцев назад

Dario Amodei just revealed that the AI training bottleneck everyone is worried about doesn’t exist anymore. The industry spent years obsessed with scraping the open web. More data. More text. More human output to feed the models. Amodei: “I don’t think data is quite the most central thing anymore.” The shift is fundamental. Amodei: “Static data is becoming less important. A lot of the data we use today is RL environments that we train on. Dynamic data that the model creates itself.” Not scraped. Not licensed. Not written by humans. Generated by the model through pure trial and error. When you train on complex math or agentic coding, you don’t feed it a textbook. You give it an environment. The model experiments. Fails. Adjusts. Tries again. Amodei: “You’re getting some math problems and the model experiments with trying the math problems.” It generates its own experience. Millions of iterations. Each one building on the last. No human required. This destroys the entire narrative around AI hitting a data wall. You cannot throttle a competitor by locking down copyright. Cannot slow the race by putting up a paywall. When a model learns through its own synthetic experience, the open web becomes irrelevant. The only true bottleneck left is compute. And this is where the geopolitical stakes become impossible to overstate. The nation that wins the compute race doesn’t just build smarter models. It builds models that generate their own intelligence, compounding on themselves, iterating past every limit human knowledge ever imposed. We are no longer training AI on the past. We are letting it simulate the future. The machine has stopped reading the dictionary. It’s doing the math itself now.

Dario Amodei just revealed that the AI training bottleneck everyone is worried about doesn’t exist anymore. The industry spent years obsessed with scraping the open web. More data. More text. More human output to feed the models. Amodei: “I don’t think data is quite the most central thing anymore.” The shift is fundamental. Amodei: “Static data is becoming less important. A lot of the data we use today is RL environments that we train on. Dynamic data that the model creates itself.” Not scraped. Not licensed. Not written by humans. Generated by the model through pure trial and error. When you train on complex math or agentic coding, you don’t feed it a textbook. You give it an environment. The model experiments. Fails. Adjusts. Tries again. Amodei: “You’re getting some math problems and the model experiments with trying the math problems.” It generates its own experience. Millions of iterations. Each one building on the last. No human required. This destroys the entire narrative around AI hitting a data wall. You cannot throttle a competitor by locking down copyright. Cannot slow the race by putting up a paywall. When a model learns through its own synthetic experience, the open web becomes irrelevant. The only true bottleneck left is compute. And this is where the geopolitical stakes become impossible to overstate. The nation that wins the compute race doesn’t just build smarter models. It builds models that generate their own intelligence, compounding on themselves, iterating past every limit human knowledge ever imposed. We are no longer training AI on the past. We are letting it simulate the future. The machine has stopped reading the dictionary. It’s doing the math itself now.

Dustin

149,610 просмотров • 5 месяцев назад

I drove a real car while wearing a VR headset 🤯 This might be one of the wildest driving experiences I’ve ever had with BMW M in Germany. They put me behind the wheel, but instead of the real world, I saw a fully digital racing track through the headset. I was driving on an open airport field, but visually I was fully inside a race. I could still see my real hands, the steering wheel, and the dashboard, but through the windows I saw a virtual world and track. And it’s multiplayer. I was racing against another driver on a different field, and our cars and the map were synchronized between us in real time. Insane tech. It felt surreal. Hard to wrap my head around. I know I’m in a real car, actually driving, but visually I’m in a video game. Crazy. Thanks BMW BMWMotorsport for the demo!

I drove a real car while wearing a VR headset 🤯 This might be one of the wildest driving experiences I’ve ever had with BMW M in Germany. They put me behind the wheel, but instead of the real world, I saw a fully digital racing track through the headset. I was driving on an open airport field, but visually I was fully inside a race. I could still see my real hands, the steering wheel, and the dashboard, but through the windows I saw a virtual world and track. And it’s multiplayer. I was racing against another driver on a different field, and our cars and the map were synchronized between us in real time. Insane tech. It felt surreal. Hard to wrap my head around. I know I’m in a real car, actually driving, but visually I’m in a video game. Crazy. Thanks BMW BMWMotorsport for the demo!

Ben Geskin

99,810 просмотров • 3 месяцев назад

Reports say an Iranian F-5 carried out a successful strike on Camp Buehring, breaching layered US air defences. US officials told NBC this is the first such incident in years. The jet, originally designed by Northrop Corporation, reportedly used a low-altitude approach to evade radar, highlighting real-world gaps in even advanced defence systems. The strike challenges claims that Iran’s air force has been neutralized. It also shows how legacy aircraft can still be effective with the right tactics. #IranWar‌ #iran #iranisraelconflict #kuwait #Trump

Reports say an Iranian F-5 carried out a successful strike on Camp Buehring, breaching layered US air defences. US officials told NBC this is the first such incident in years. The jet, originally designed by Northrop Corporation, reportedly used a low-altitude approach to evade radar, highlighting real-world gaps in even advanced defence systems. The strike challenges claims that Iran’s air force has been neutralized. It also shows how legacy aircraft can still be effective with the right tactics. #IranWar‌ #iran #iranisraelconflict #kuwait #Trump

Srijan Pal Singh

24,155 просмотров • 3 месяцев назад

“It was like I’d gotten my mind back.” “This lovely calm kind of came into me and it sort of stayed.” These are real quotes from participants in Iain Campbell, Ph.D.'s newly published study in BJPsych Open looking at ketogenic therapy for bipolar disorder that just dropped today! 📃 Read it here: This new study is one of the first to use advanced brain imaging to evaluate the impact ketosis has on bipolar disorder. Combined with blood biomarker data, this study demonstrated that ketosis can lead to favorable brain and metabolite changes which translated to impressive quality of life improvements in the study participants. The participant stories in this video and in the study as a whole are moving and reinforce the urgent need to fight for new treatments for each individual living with bipolar disorder. This new study contributes to the growing body of research supporting the use of ketogenic therapy as a #newbipolartreatment.

“It was like I’d gotten my mind back.” “This lovely calm kind of came into me and it sort of stayed.” These are real quotes from participants in Iain Campbell, Ph.D.'s newly published study in BJPsych Open looking at ketogenic therapy for bipolar disorder that just dropped today! 📃 Read it here: This new study is one of the first to use advanced brain imaging to evaluate the impact ketosis has on bipolar disorder. Combined with blood biomarker data, this study demonstrated that ketosis can lead to favorable brain and metabolite changes which translated to impressive quality of life improvements in the study participants. The participant stories in this video and in the study as a whole are moving and reinforce the urgent need to fight for new treatments for each individual living with bipolar disorder. This new study contributes to the growing body of research supporting the use of ketogenic therapy as a #newbipolartreatment.

Metabolic Mind

21,800 просмотров • 1 год назад

What's really ironic about this argument is that it actually works against atheism. You have an ape-like creature, it has a baby... but now this* baby is a "human" with real value and human dignity? That makes no sense. Why do humans have any more value or worth than a fish, a spider, or a rock? The answer is we don't. This is the truth on atheism, and this is why atheist regimes didn't hesitate to murder anyone that got in their way, the same way we indifferently poison ants that annoy us. What's the difference? Let me put it this way. If you believe humans have actual value, and that there's a real and meaningful moral difference between stepping on an ant vs stepping on a baby, you should categorically reject atheism.

What's really ironic about this argument is that it actually works against atheism. You have an ape-like creature, it has a baby... but now this* baby is a "human" with real value and human dignity? That makes no sense. Why do humans have any more value or worth than a fish, a spider, or a rock? The answer is we don't. This is the truth on atheism, and this is why atheist regimes didn't hesitate to murder anyone that got in their way, the same way we indifferently poison ants that annoy us. What's the difference? Let me put it this way. If you believe humans have actual value, and that there's a real and meaningful moral difference between stepping on an ant vs stepping on a baby, you should categorically reject atheism.

Darwin to Jesus

29,977 просмотров • 3 месяцев назад

Kimi K3 passed Fable 5 on Code Arena just 6 weeks after Fable's release, landing #1 in 6 of 7 frontend domains. We sat down with Arena CEO and co-founder Anastasios Nikolas Angelopoulos for a rapid fire conversation on what the data from real-world use tells us 👇 0:00 Biggest release of the year, or overreaction? 0:33 Kimi K3 beats Fable on Code Arena: verifying the votes 1:35 1679 points: a 17-place jump from K2.6 2:37 #1 in 6 of 7 frontend domains — but still #2 in gaming 3:15 Permanent shift or snapshot? Labs distilling Chinese models 4:23 Regulating Chinese models: the case for and against 6:30 $3 in, $15 out: open source is no longer 10% of the price 7:30 If you're Anthropic or OpenAI, what's your move? 8:09 How long before the leaderboard flips again?

Kimi K3 passed Fable 5 on Code Arena just 6 weeks after Fable's release, landing #1 in 6 of 7 frontend domains. We sat down with Arena CEO and co-founder Anastasios Nikolas Angelopoulos for a rapid fire conversation on what the data from real-world use tells us 👇 0:00 Biggest release of the year, or overreaction? 0:33 Kimi K3 beats Fable on Code Arena: verifying the votes 1:35 1679 points: a 17-place jump from K2.6 2:37 #1 in 6 of 7 frontend domains — but still #2 in gaming 3:15 Permanent shift or snapshot? Labs distilling Chinese models 4:23 Regulating Chinese models: the case for and against 6:30 $3 in, $15 out: open source is no longer 10% of the price 7:30 If you're Anthropic or OpenAI, what's your move? 8:09 How long before the leaderboard flips again?

Arena.ai

48,526 просмотров • 3 дней назад

AI BASKETBALL ANALYSIS. A FULL COMPUTER VISION SYSTEM. BUILT ON YOLO, OPENCV, AND PYTHON. Take any NBA broadcast. Any camera angle. Any resolution. Feed it into the system. YOLO finds every player and the ball. Frame by frame. No manual annotation. No pre-labeled data.The model just sees the court and understands it. Zero-shot classification looks at jersey pixels and decides who plays for whom. Two teams separated in milliseconds. Without ever being told the team names. But here's where it gets wild. Court keypoint detection identifies the geometry of the playing surface. Homography transforms the broadcast camera into a top-down tactical map. Real meters. Real coordinates. From a flat 2D video. Now every player has a position on a real court. Every movement becomes a data point. Every pass becomes a vector. Speed. Distance. Possession time. Pass networks. All extracted from nothing but pixels. No GPS. No chips in the ball. No million-dollar Second Spectrum setup. A Python script and a GPU. The full pipeline is open source. The tutorial walks through every line of code. From detection to transformation to analytics output. Teams used to pay six figures for this data. Now you build it in an afternoon. Computer vision didn't just enter basketball. It democratized it.

AI BASKETBALL ANALYSIS. A FULL COMPUTER VISION SYSTEM. BUILT ON YOLO, OPENCV, AND PYTHON. Take any NBA broadcast. Any camera angle. Any resolution. Feed it into the system. YOLO finds every player and the ball. Frame by frame. No manual annotation. No pre-labeled data.The model just sees the court and understands it. Zero-shot classification looks at jersey pixels and decides who plays for whom. Two teams separated in milliseconds. Without ever being told the team names. But here's where it gets wild. Court keypoint detection identifies the geometry of the playing surface. Homography transforms the broadcast camera into a top-down tactical map. Real meters. Real coordinates. From a flat 2D video. Now every player has a position on a real court. Every movement becomes a data point. Every pass becomes a vector. Speed. Distance. Possession time. Pass networks. All extracted from nothing but pixels. No GPS. No chips in the ball. No million-dollar Second Spectrum setup. A Python script and a GPU. The full pipeline is open source. The tutorial walks through every line of code. From detection to transformation to analytics output. Teams used to pay six figures for this data. Now you build it in an afternoon. Computer vision didn't just enter basketball. It democratized it.

zostaff

230,194 просмотров • 3 месяцев назад

There's a horse carved into a hillside in England. 🏴󠁧󠁢󠁥󠁮󠁧󠁿🇬🇧 3,000 years old. Grass covers chalk in twenty years. If you stop maintaining it, it disappears. No one has ever stopped. Nobody knows who carved it. A tribe on these hills. A thousand years before the Romans arrived. We don't know why. But it mattered enough to keep. Romans marched beneath it. Saxons farmed around it. Normans built castles in its shadow. Every one of them climbed that hill. When the Black Death killed half the country... Someone still climbed that hill. Nobody told them to. 3,000 years. Ordinary people. Choosing to remember. That's not a monument. That's a promise. And no one's broken it yet. Every story needs someone to climb the hill. Without you, the grass grows back. Every video we make is funded by people who chose to climb. No sponsors. No ads. Just people who believe our history is worth saving. Be part of us: Be Proud Of Us. 🇬🇧

There's a horse carved into a hillside in England. 🏴󠁧󠁢󠁥󠁮󠁧󠁿🇬🇧 3,000 years old. Grass covers chalk in twenty years. If you stop maintaining it, it disappears. No one has ever stopped. Nobody knows who carved it. A tribe on these hills. A thousand years before the Romans arrived. We don't know why. But it mattered enough to keep. Romans marched beneath it. Saxons farmed around it. Normans built castles in its shadow. Every one of them climbed that hill. When the Black Death killed half the country... Someone still climbed that hill. Nobody told them to. 3,000 years. Ordinary people. Choosing to remember. That's not a monument. That's a promise. And no one's broken it yet. Every story needs someone to climb the hill. Without you, the grass grows back. Every video we make is funded by people who chose to climb. No sponsors. No ads. Just people who believe our history is worth saving. Be part of us: Be Proud Of Us. 🇬🇧

Proudofus.uk

154,179 просмотров • 4 месяцев назад

For robots to be useful, they must be able to interact with a wide variety of environments; and yet, scaling interaction data is difficult, expensive, and time consuming. Instead, much research revolves around sim-to-real manipulation — but mostly this has not been mobile manipulation. Recently, though, this has begun to change. Two recent papers from Tairan He and Haoru Xue show us how to unlock the potential of this technique, building policies which, without any real data at all, can move objects around in the world and open doors in the real world with a humanoid robot. Watch Episode #60 of RoboPapers now to learn more, hosted by Chris Paxton and Jiafei Duan. In this episode, we cover two papers:. First is VIRAL: Visual Sim-to-Real at Scale for Humanoid Loco-Manipulation; and second is DoorMan: Opening the Sim-to-Real Door for Humanoid Pixel-to-Action Policy Transfer.

For robots to be useful, they must be able to interact with a wide variety of environments; and yet, scaling interaction data is difficult, expensive, and time consuming. Instead, much research revolves around sim-to-real manipulation — but mostly this has not been mobile manipulation. Recently, though, this has begun to change. Two recent papers from Tairan He and Haoru Xue show us how to unlock the potential of this technique, building policies which, without any real data at all, can move objects around in the world and open doors in the real world with a humanoid robot. Watch Episode #60 of RoboPapers now to learn more, hosted by Chris Paxton and Jiafei Duan. In this episode, we cover two papers:. First is VIRAL: Visual Sim-to-Real at Scale for Humanoid Loco-Manipulation; and second is DoorMan: Opening the Sim-to-Real Door for Humanoid Pixel-to-Action Policy Transfer.

RoboPapers

30,767 просмотров • 6 месяцев назад

US export-control disable Claude Fable 5 overnight. Not for what it said - for what one trader did with it. He turned an $11,000 wreck into $300,000 profit in five days. Then they pulled Claude Fable 5 from public hands. Too late - his bot's still running. His wallet: Every other Claude model still works. The two best ones don't. Anthropic's calling it a misunderstanding. Maybe. But think about what gets a model killed by export control overnight, no warning. Here's what Fable 5 actually did for him. It doesn't predict price. It computes the whole probability surface of a market - every outcome, weighted, faster than the market can correct itself. It finds the bets the crowd writes off as impossible, runs the real math, and buys them for pennies when the math disagrees. One of those just paid x205. A regular guy, a model this sharp, a market no regulator polices. They closed that door overnight - one night too late. He's holding one of the last builds that ever touched a live market. It's still on Polymarket right now, hunting the same mispriced tails. Fable 5 is locked. The algorithm it wrote is loose. You can't open the model anymore. You can still copy the wallet it built in two clicks:

US export-control disable Claude Fable 5 overnight. Not for what it said - for what one trader did with it. He turned an $11,000 wreck into $300,000 profit in five days. Then they pulled Claude Fable 5 from public hands. Too late - his bot's still running. His wallet: Every other Claude model still works. The two best ones don't. Anthropic's calling it a misunderstanding. Maybe. But think about what gets a model killed by export control overnight, no warning. Here's what Fable 5 actually did for him. It doesn't predict price. It computes the whole probability surface of a market - every outcome, weighted, faster than the market can correct itself. It finds the bets the crowd writes off as impossible, runs the real math, and buys them for pennies when the math disagrees. One of those just paid x205. A regular guy, a model this sharp, a market no regulator polices. They closed that door overnight - one night too late. He's holding one of the last builds that ever touched a live market. It's still on Polymarket right now, hunting the same mispriced tails. Fable 5 is locked. The algorithm it wrote is loose. You can't open the model anymore. You can still copy the wallet it built in two clicks:

cvxv666

77,213 просмотров • 1 месяц назад

There's a fruit fly walking around right now that was never born. eon just released a video where they took a real fly's connectome — the wiring diagram of its brain — and simulated it. Dropped it into a virtual body. It started walking. Grooming. Feeding. Doing what flies do. Nobody taught it to walk. No training data, no gradient descent toward fly-like behavior. This is the opposite of how AI works. They rebuilt the mind from the inside, neuron by neuron, and behavior just... emerged. It's the first time a biological organism has been recreated not by modeling what it does, but by modeling what it is. A human brain is 6 OOM more neurons. That's a scaling problem, something we've gotten very good at solving. So what happens when we have a working copy of the human mind?

There's a fruit fly walking around right now that was never born. eon just released a video where they took a real fly's connectome — the wiring diagram of its brain — and simulated it. Dropped it into a virtual body. It started walking. Grooming. Feeding. Doing what flies do. Nobody taught it to walk. No training data, no gradient descent toward fly-like behavior. This is the opposite of how AI works. They rebuilt the mind from the inside, neuron by neuron, and behavior just... emerged. It's the first time a biological organism has been recreated not by modeling what it does, but by modeling what it is. A human brain is 6 OOM more neurons. That's a scaling problem, something we've gotten very good at solving. So what happens when we have a working copy of the human mind?

hattie

9,355,055 просмотров • 4 месяцев назад