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5-axis CNC machining – but different... Most 5-axis machines use serial kinematics: stack a rotary A-axis on top of a rotary B-axis, mount that on linear X/Y/Z stages. Each axis carries the weight of everything after it. Heavy and slow. 🤖 The Sprint Z3 uses parallel kinematics: three linear...

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5-Axis CNC machining of turbocharger impellers sits in the same league as aerospace manufacturing, precision engineering pushed to physical limits. These machines run with positional accuracy in the 1-5 micron range, spindle speeds of 20,000-40,000 RPM, and continuous 5-axis interpolation to carve complex blade geometry without collision, vibration, or thermal drift during cutting of nickel alloys and titanium. A production-grade 5-axis system for impellers typically costs $300,000 to $3 million+ The real constraint is not motion, but stability, suppressing chatter, tool deflection, and microscopic surface defects that would quietly destroy efficiency at 100,000+ RPM operating cycles. Without this class of machining, modern turbocharged engines, high-efficiency industrial compressors, and compact propulsion systems simply would not exist.
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5-Axis CNC machining of turbocharger impellers sits in the same league as aerospace manufacturing, precision engineering pushed to physical limits. These machines run with positional accuracy in the 1-5 micron range, spindle speeds of 20,000-40,000 RPM, and continuous 5-axis interpolation to carve complex blade geometry without collision, vibration, or thermal drift during cutting of nickel alloys and titanium. A production-grade 5-axis system for impellers typically costs $300,000 to $3 million+ The real constraint is not motion, but stability, suppressing chatter, tool deflection, and microscopic surface defects that would quietly destroy efficiency at 100,000+ RPM operating cycles. Without this class of machining, modern turbocharged engines, high-efficiency industrial compressors, and compact propulsion systems simply would not exist.

Ammanichanda

48,750 Aufrufe • vor 2 Monaten

A machine like this can cost $500,000 to well over $1 million to make parts that may be worth only $10-15 This is the real manufacturing story. This INDEX six-spindle automatic carries 6 motorised spindles, up to 12 CNC tool carriers, operates at 8,000+ rpm, and weighs 7.2 tonnes. Different operations happen simultaneously as the spindle drum indexes each workpiece from station to station. A real scale production example produced a precision component in 11 seconds, versus 38 seconds on a conventional single-spindle lathe. That's roughly 327 parts per hour before downtime. But the machine is only the hardware. Tool geometry, CNC programs, cutting parameters, spindle synchronisation, tooling, bar feeding, chip evacuation, coolant, inspection and collision checked simulation all have to be engineered around the exact part. That is what it takes to integrate this machine into a factory workflow. This accumulated capability is what kept Germany and Japan at the pinnacle of machine-tool manufacturing for decades almost unchallenged. The advantage wasn't just building the hardware, but knowing how to program, tool and integrate these machines for thousands of different manufacturing requirements globally. China has now built much of that ecosystem at extraordinary scale, machines, controls, tooling, software, automation and integration. Its huge domestic manufacturing base has accelerated that learning curve dramatically. Today, Chinese manufacturers can increasingly offer sophisticated CNC and multi-spindle systems at 30-40% lower total costs in most applications, putting serious and relentless price pressure on German and Japanese builders. China produced 37% of the world's machine tools in 2025, compared with 12% for Germany and 10% for Japan. These are the machines that make the machines and ultimately determine how much an economy can manufacture. China is the biggest player as of now and growing faster than anyone else in manufacturing high-end machining tools. Source, Daniel Jansson
0:16

A machine like this can cost $500,000 to well over $1 million to make parts that may be worth only $10-15 This is the real manufacturing story. This INDEX six-spindle automatic carries 6 motorised spindles, up to 12 CNC tool carriers, operates at 8,000+ rpm, and weighs 7.2 tonnes. Different operations happen simultaneously as the spindle drum indexes each workpiece from station to station. A real scale production example produced a precision component in 11 seconds, versus 38 seconds on a conventional single-spindle lathe. That's roughly 327 parts per hour before downtime. But the machine is only the hardware. Tool geometry, CNC programs, cutting parameters, spindle synchronisation, tooling, bar feeding, chip evacuation, coolant, inspection and collision checked simulation all have to be engineered around the exact part. That is what it takes to integrate this machine into a factory workflow. This accumulated capability is what kept Germany and Japan at the pinnacle of machine-tool manufacturing for decades almost unchallenged. The advantage wasn't just building the hardware, but knowing how to program, tool and integrate these machines for thousands of different manufacturing requirements globally. China has now built much of that ecosystem at extraordinary scale, machines, controls, tooling, software, automation and integration. Its huge domestic manufacturing base has accelerated that learning curve dramatically. Today, Chinese manufacturers can increasingly offer sophisticated CNC and multi-spindle systems at 30-40% lower total costs in most applications, putting serious and relentless price pressure on German and Japanese builders. China produced 37% of the world's machine tools in 2025, compared with 12% for Germany and 10% for Japan. These are the machines that make the machines and ultimately determine how much an economy can manufacture. China is the biggest player as of now and growing faster than anyone else in manufacturing high-end machining tools. Source, Daniel Jansson

Ammanichanda

38,188 Aufrufe • vor 16 Tagen

AI has had exactly two scaling axes that worked so far, and the second one is starting to look finite too the first one was pretraining: with scaling parameters and data, we got world knowledge (i.e. ChatGPT had read enough to know things), but it started saturating a while ago the second one was RL, and people had been doing RL the whole time before that: RLHF is RL but it never scaled far because it was trying to control the exact output, which tokens come out, how the text reads, but you can only push that so far before you’re just polishing RLVR dropped that constraint: giving the model a task, then checking whether the final answer is right, and ignoring everything in between -- so the model does whatever it wants in the middle and only the endpoint gets graded, and that’s much closer to actual RL and it’s what bought us planning and reasoning (arguably, tool use sits around 2.5 on this list -- while useful, it's not a different kind of thing) so one axis gave knowledge, the other gave reasoning, and both of them are one model working alone the next axis is how many models you can get working on the same problem, which is a different kind of axis than the previous two we know that multi-agent RL has always been the harder problem: I spent years in that literature and the gap between single-agent and multi-agent is definitely not incremental -- it’s a whole different class of difficulty! which is also why the derivatives are steep at the start, nobody has picked the easy wins yet... and the thing that gates this multi-agent coordination is communication: models can only coordinate as well as they can exchange information, and right now they do that by writing sentences to each other imagine what could we possibly achieve if we properly open that third axis development by letting models to exchange information in their native "language" without loosing any computational data that they produce during inference
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AI has had exactly two scaling axes that worked so far, and the second one is starting to look finite too the first one was pretraining: with scaling parameters and data, we got world knowledge (i.e. ChatGPT had read enough to know things), but it started saturating a while ago the second one was RL, and people had been doing RL the whole time before that: RLHF is RL but it never scaled far because it was trying to control the exact output, which tokens come out, how the text reads, but you can only push that so far before you’re just polishing RLVR dropped that constraint: giving the model a task, then checking whether the final answer is right, and ignoring everything in between -- so the model does whatever it wants in the middle and only the endpoint gets graded, and that’s much closer to actual RL and it’s what bought us planning and reasoning (arguably, tool use sits around 2.5 on this list -- while useful, it's not a different kind of thing) so one axis gave knowledge, the other gave reasoning, and both of them are one model working alone the next axis is how many models you can get working on the same problem, which is a different kind of axis than the previous two we know that multi-agent RL has always been the harder problem: I spent years in that literature and the gap between single-agent and multi-agent is definitely not incremental -- it’s a whole different class of difficulty! which is also why the derivatives are steep at the start, nobody has picked the easy wins yet... and the thing that gates this multi-agent coordination is communication: models can only coordinate as well as they can exchange information, and right now they do that by writing sentences to each other imagine what could we possibly achieve if we properly open that third axis development by letting models to exchange information in their native "language" without loosing any computational data that they produce during inference

Sasha Malysheva

11,548 Aufrufe • vor 17 Tagen

Bernoulli's Principle It’s a key idea in fluid dynamics named after Daniel Bernoulli. In simple terms: For a fluid flowing smoothly, an increase in the fluid’s speed happens at the same time as a decrease in pressure or a decrease in the fluid’s potential energy. Where: - P = pressure in the fluid - ρ = fluid density - v = flow velocity - g = acceleration due to gravity - h = height above a reference point Bernoulli's Principle basically says that for a fluid that's flowing smoothly, when its speed goes up, its pressure goes down. Think of it like this: fast-moving air or water pushes less sideways than slow-moving air or water. The energy in the fluid stays the same overall, but it shifts between motion, pressure, and height. That's why an airplane wing creates lift. The air moves faster over the curved top of the wing than underneath, so the pressure on top is lower. The higher pressure below pushes the wing up.
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Bernoulli's Principle It’s a key idea in fluid dynamics named after Daniel Bernoulli. In simple terms: For a fluid flowing smoothly, an increase in the fluid’s speed happens at the same time as a decrease in pressure or a decrease in the fluid’s potential energy. Where: - P = pressure in the fluid - ρ = fluid density - v = flow velocity - g = acceleration due to gravity - h = height above a reference point Bernoulli's Principle basically says that for a fluid that's flowing smoothly, when its speed goes up, its pressure goes down. Think of it like this: fast-moving air or water pushes less sideways than slow-moving air or water. The energy in the fluid stays the same overall, but it shifts between motion, pressure, and height. That's why an airplane wing creates lift. The air moves faster over the curved top of the wing than underneath, so the pressure on top is lower. The higher pressure below pushes the wing up.

Sam Mathverse

27,791 Aufrufe • vor 3 Monaten

Unsure the level of concern at the moment (1.09 FIP + 27.5 K-BB%) but I think it's worth nothing that Sanchez's FB velo is down: First 3 G (2026): • 94.4 MPH (-2.1) • 94.3 MPH (-1.5) • 94.6 MPH (-0.6) *(L: '26, R: '25)* Last year: • Sanchez was a bit more efficient w/ his hip + shoulder separation • His body was more linear, helping that center of mass move correctly. • Better lower half allowing him to keep that pelvis a bit more linear -- which is likely result of the ribcage is stacked over his pelvis + sitting in that load longer on foot strike (??) This year: • Energy is leaking from that back knee into rotation • Upper + lower working w/ each other more and less of working against one another (arm doing more than it should) • His pelvis is noticeably tipping down through rotation (not a direct cue but more of a result of less lower half activation) Angles/WBC fatigue could also be at play here as well -- but assuming they're not could be some things to clean up
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Unsure the level of concern at the moment (1.09 FIP + 27.5 K-BB%) but I think it's worth nothing that Sanchez's FB velo is down: First 3 G (2026): • 94.4 MPH (-2.1) • 94.3 MPH (-1.5) • 94.6 MPH (-0.6) *(L: '26, R: '25)* Last year: • Sanchez was a bit more efficient w/ his hip + shoulder separation • His body was more linear, helping that center of mass move correctly. • Better lower half allowing him to keep that pelvis a bit more linear -- which is likely result of the ribcage is stacked over his pelvis + sitting in that load longer on foot strike (??) This year: • Energy is leaking from that back knee into rotation • Upper + lower working w/ each other more and less of working against one another (arm doing more than it should) • His pelvis is noticeably tipping down through rotation (not a direct cue but more of a result of less lower half activation) Angles/WBC fatigue could also be at play here as well -- but assuming they're not could be some things to clean up

Joseph Cammisa

43,317 Aufrufe • vor 4 Monaten

There has been a lot of hand wringing on the appropriate valuation of SpaceX. Some large institutions believe SpaceX can only be valued at half what the market seems to be willing to pay for it. Others are claiming it has 15X appreciation ahead of it. Almost all of this difference of opinion comes down to how comfortable you are modeling beyond 2030 and what valuation method you use. 2030 valuation using a traditional Gordan DCF produces a very different result than a 2040 EV/EBITDA Multiple. Both have pros and cons. Most analysts don’t really discuss this and lead with a headline number. We are very comfortable modeling out to 2040, as large portions of what SpaceX is proposing is real world infrastructure, which provides modelable physics constraints to anchor against. The analysis we released today explores this in-depth, its open to the public all the way through IPO. I highly encourage you check it out prior to then. We’ve run 5,000 monte carlo runs across 500 variables (real number, even though it sounds fake) and three valuation methods. This video is of a 3D cloud chart showing every simulation outcome expected in valuation output across two of the most impactful variables to the model when using an EV/EBITDA multiple from 2026 to 2040. The horizontal axis is the steepness of the orbital data center demand S-curve. The vertical axis is the rate at which chip compute efficiency becomes cheaper. Each of the 5,000 dots is one simulated future; green dots are the ones where SpaceX's 2040 value clears the $1.77T IPO line, over time. Under EV/EBITDA valuation through 2040, 96% of our simulated futures clear the expected IPO price once the bell rings Friday. We aren’t publishing this publicly to tell investors what the stock is worth, we’re publishing this to help investors understand the world of outcomes, what the fundamentals suggest through 2040, and what frankly most analysis simply won’t share. SpaceX is a generational company working on long term infrastructure harnessing a domain no one has been able to tap in so far: space. It deserves doing the work as an investor. because this in not financial advice. The cleanest way to hold SpaceX is a bond stapled to a call option (AI-Compute); Starlink is the bond, the near term SatCom annuity that funds the next flywheel. Understand the world of outcomes and take your position accordingly. Comparables and P/E won't take you far enough.
0:14

There has been a lot of hand wringing on the appropriate valuation of SpaceX. Some large institutions believe SpaceX can only be valued at half what the market seems to be willing to pay for it. Others are claiming it has 15X appreciation ahead of it. Almost all of this difference of opinion comes down to how comfortable you are modeling beyond 2030 and what valuation method you use. 2030 valuation using a traditional Gordan DCF produces a very different result than a 2040 EV/EBITDA Multiple. Both have pros and cons. Most analysts don’t really discuss this and lead with a headline number. We are very comfortable modeling out to 2040, as large portions of what SpaceX is proposing is real world infrastructure, which provides modelable physics constraints to anchor against. The analysis we released today explores this in-depth, its open to the public all the way through IPO. I highly encourage you check it out prior to then. We’ve run 5,000 monte carlo runs across 500 variables (real number, even though it sounds fake) and three valuation methods. This video is of a 3D cloud chart showing every simulation outcome expected in valuation output across two of the most impactful variables to the model when using an EV/EBITDA multiple from 2026 to 2040. The horizontal axis is the steepness of the orbital data center demand S-curve. The vertical axis is the rate at which chip compute efficiency becomes cheaper. Each of the 5,000 dots is one simulated future; green dots are the ones where SpaceX's 2040 value clears the $1.77T IPO line, over time. Under EV/EBITDA valuation through 2040, 96% of our simulated futures clear the expected IPO price once the bell rings Friday. We aren’t publishing this publicly to tell investors what the stock is worth, we’re publishing this to help investors understand the world of outcomes, what the fundamentals suggest through 2040, and what frankly most analysis simply won’t share. SpaceX is a generational company working on long term infrastructure harnessing a domain no one has been able to tap in so far: space. It deserves doing the work as an investor. because this in not financial advice. The cleanest way to hold SpaceX is a bond stapled to a call option (AI-Compute); Starlink is the bond, the near term SatCom annuity that funds the next flywheel. Understand the world of outcomes and take your position accordingly. Comparables and P/E won't take you far enough.

Aaron Burnett

1,521,091 Aufrufe • vor 2 Monaten

The IRGC are now hiding their remaining precious launchers dressed up as civilian trucks and inside highway tunnels—a sort of Hamas-inspired strategy. Getting the last 10% was always going to be the hardest part. But how effective are they anyway? In the four rounds of “True Promise” attacks, they have fired around 1,500 ballistic missiles at Israel and continue to fire 5 to 10 per day. This is well over half their stock, even accounting for rebuilding. With this, they have managed to kill 48 Israelis and cause a few billion in property damage. If they have 500 missiles and 150 launchers left—it is probably less—they will be able to keep “resisting” for another month or so and kill a few more Israelis at random, but then it’s all over. Their grand “Axis of Resistance” will no longer be a strategic threat to Israel, just an irritant to be occasionally swatted at. In truth, this has been the case for a while.
0:10

The IRGC are now hiding their remaining precious launchers dressed up as civilian trucks and inside highway tunnels—a sort of Hamas-inspired strategy. Getting the last 10% was always going to be the hardest part. But how effective are they anyway? In the four rounds of “True Promise” attacks, they have fired around 1,500 ballistic missiles at Israel and continue to fire 5 to 10 per day. This is well over half their stock, even accounting for rebuilding. With this, they have managed to kill 48 Israelis and cause a few billion in property damage. If they have 500 missiles and 150 launchers left—it is probably less—they will be able to keep “resisting” for another month or so and kill a few more Israelis at random, but then it’s all over. Their grand “Axis of Resistance” will no longer be a strategic threat to Israel, just an irritant to be occasionally swatted at. In truth, this has been the case for a while.

Saul Sadka

152,690 Aufrufe • vor 4 Monaten

"Lift lighter as you get older. Protect your joints." The standard advice. The wrong advice. What heavy lifting actually does for an ageing body: - Builds tendon stiffness, which protects joints rather than wearing them - Maintains the high threshold motor units that are first to disappear with age - Stimulates bone density, the thing osteoporosis attacks - Develops the strength reserve that keeps you independent at 80 What high reps do for an ageing body: - Generate more total fatigue per session - Take longer to recover from (a problem that compounds with age) - Do nothing for tendon stiffness - Do nothing for fast twitch preservation - Make you tired without making you strong Recovery capacity declines with age. The worst thing you can do is pick the more fatiguing option and call it gentle. The actual protocol: - Heavy enough to challenge the muscle (4-6 reps, near failure) - Machines for most of the work (less spinal load, less balance demand, more stimulus to the muscle, less risk) - Skip the 1RM testing, skip the maxing out on barbell squats and deadlifts - That isn't where the magic was anyway You don't need to max out a barbell to lift heavy. You need to challenge the muscle with a load it respects. The leg press at 200kg does this. The hack squat does this. The chest-supported row does this. None of them are ego lifts. All of them are heavy. Lifting lighter to "protect" your joints is how you arrive at 75 unable to stand up from a chair. Lifting heavy on machines is how you arrive at 75 carrying your own shopping.
0:13

"Lift lighter as you get older. Protect your joints." The standard advice. The wrong advice. What heavy lifting actually does for an ageing body: - Builds tendon stiffness, which protects joints rather than wearing them - Maintains the high threshold motor units that are first to disappear with age - Stimulates bone density, the thing osteoporosis attacks - Develops the strength reserve that keeps you independent at 80 What high reps do for an ageing body: - Generate more total fatigue per session - Take longer to recover from (a problem that compounds with age) - Do nothing for tendon stiffness - Do nothing for fast twitch preservation - Make you tired without making you strong Recovery capacity declines with age. The worst thing you can do is pick the more fatiguing option and call it gentle. The actual protocol: - Heavy enough to challenge the muscle (4-6 reps, near failure) - Machines for most of the work (less spinal load, less balance demand, more stimulus to the muscle, less risk) - Skip the 1RM testing, skip the maxing out on barbell squats and deadlifts - That isn't where the magic was anyway You don't need to max out a barbell to lift heavy. You need to challenge the muscle with a load it respects. The leg press at 200kg does this. The hack squat does this. The chest-supported row does this. None of them are ego lifts. All of them are heavy. Lifting lighter to "protect" your joints is how you arrive at 75 unable to stand up from a chair. Lifting heavy on machines is how you arrive at 75 carrying your own shopping.

Sama Hoole

35,515 Aufrufe • vor 3 Monaten

Somewhere around sixty you get handed a new set of instructions. Lift lighter. Keep the reps high. Do not tax yourself too much. Put the saved effort into cardio. It is the exact reverse of what an ageing body needs, and the people handing it out have the mechanism sitting right in front of them. Recovery gets worse with age. Nobody argues with that. The older body clears fatigue more slowly, repairs more slowly, and tolerates far less accumulated work before progress stops entirely. Every GP, every physio, every trainer will nod along to that sentence. Then watch what gets prescribed on the back of it. High reps. Long burning sets. Circuits. Three sessions of cardio stacked on top. A protocol whose main product is fatigue, given to the person with the least capacity left to absorb any. They identified a recovery problem and prescribed more recovery cost. The answer runs the other way and it is not complicated. If your recovery budget has shrunk, you spend it on whatever returns the most growth per unit of fatigue, and that is a heavy set of five. Four to six reps, a handful of lifts, three minutes between sets, done inside the hour. Nearly every rep is a growth rep. Almost nothing goes on the burning, the sweating and the gasping, which build nothing at all and then bill you for four days. Twenty-five reps taken to failure is a fortnight of fatigue for a fraction of the stimulus. That is not the cautious option for a sixty-five-year-old. It is the most reckless thing on the timetable. Now the part that actually matters. Ageing is not one process. It is a list. Muscle wastes. Bone thins. Tendon softens. The fast fibres that catch you when the pavement arrives early vanish first while the slow ones sit there in perfect health. Motor units drop out. The nervous system stops asking for full effort because nothing has demanded full effort in fifteen years. Read that list back and tell me what heavy resistance training does. It builds muscle. It loads bone, which is the only language bone speaks. It stiffens tendon. It recruits the fast fibres, because that is what heavy means physiologically and there is no other route in. It forces the nervous system to ask for everything again. Every item on the list of what ageing takes is on the list of what a heavy set gives back. Nothing else on earth does that. Not a walk, not a class, not a pill, not twenty minutes on a machine with the paper open. You were told to go gently because somebody quietly decided you were finishing. Go heavy, because you are not.
0:19

Somewhere around sixty you get handed a new set of instructions. Lift lighter. Keep the reps high. Do not tax yourself too much. Put the saved effort into cardio. It is the exact reverse of what an ageing body needs, and the people handing it out have the mechanism sitting right in front of them. Recovery gets worse with age. Nobody argues with that. The older body clears fatigue more slowly, repairs more slowly, and tolerates far less accumulated work before progress stops entirely. Every GP, every physio, every trainer will nod along to that sentence. Then watch what gets prescribed on the back of it. High reps. Long burning sets. Circuits. Three sessions of cardio stacked on top. A protocol whose main product is fatigue, given to the person with the least capacity left to absorb any. They identified a recovery problem and prescribed more recovery cost. The answer runs the other way and it is not complicated. If your recovery budget has shrunk, you spend it on whatever returns the most growth per unit of fatigue, and that is a heavy set of five. Four to six reps, a handful of lifts, three minutes between sets, done inside the hour. Nearly every rep is a growth rep. Almost nothing goes on the burning, the sweating and the gasping, which build nothing at all and then bill you for four days. Twenty-five reps taken to failure is a fortnight of fatigue for a fraction of the stimulus. That is not the cautious option for a sixty-five-year-old. It is the most reckless thing on the timetable. Now the part that actually matters. Ageing is not one process. It is a list. Muscle wastes. Bone thins. Tendon softens. The fast fibres that catch you when the pavement arrives early vanish first while the slow ones sit there in perfect health. Motor units drop out. The nervous system stops asking for full effort because nothing has demanded full effort in fifteen years. Read that list back and tell me what heavy resistance training does. It builds muscle. It loads bone, which is the only language bone speaks. It stiffens tendon. It recruits the fast fibres, because that is what heavy means physiologically and there is no other route in. It forces the nervous system to ask for everything again. Every item on the list of what ageing takes is on the list of what a heavy set gives back. Nothing else on earth does that. Not a walk, not a class, not a pill, not twenty minutes on a machine with the paper open. You were told to go gently because somebody quietly decided you were finishing. Go heavy, because you are not.

Sama Hoole

16,526 Aufrufe • vor 27 Tagen

Every price tag on every product in Europe is about to be repriced. Elon Musk just confirmed the timeline. Most people scrolled past it. Musk: “We’ve got the Tesla Semi coming up, so the Tesla heavy truck. And that’ll be going to Europe, hopefully next year.” Most people are watching the Robotaxi rollout. The quiet money is watching the Semi. Because the Robotaxi is the regulatory battering ram. The Semi is the economic payload. The global supply chain has one bottleneck no amount of capital has ever solved. The human driver. They get tired. They make mistakes. They sleep. Musk is about to remove all three from the equation simultaneously. Pair a fully electric heavy truck with Full Self-Driving software and the cost structure of moving goods across an entire continent does not improve. It collapses. No fatigue. No sleep schedules. No fuel volatility. No human error. 24 hours. Every day. FSD is already statistically outperforming human drivers on safety metrics. The moment regulators accept that AI navigates a city safer than a human, applying that same software to commercial freight stops being a debate. It becomes a legal obligation. When the trucks move autonomously, the cost of everything on the shelf moves with them. Add humanoid robotics to the warehouse and the marginal cost of moving a product from point A to point B approaches zero. This is not a logistics story. It is a price-of-everything story. Physical transportation is just another data problem waiting to be solved by compute. And once that problem is solved, the inflation that has quietly taxed every human being alive for a century gets a knife in its throat.
0:14

Every price tag on every product in Europe is about to be repriced. Elon Musk just confirmed the timeline. Most people scrolled past it. Musk: “We’ve got the Tesla Semi coming up, so the Tesla heavy truck. And that’ll be going to Europe, hopefully next year.” Most people are watching the Robotaxi rollout. The quiet money is watching the Semi. Because the Robotaxi is the regulatory battering ram. The Semi is the economic payload. The global supply chain has one bottleneck no amount of capital has ever solved. The human driver. They get tired. They make mistakes. They sleep. Musk is about to remove all three from the equation simultaneously. Pair a fully electric heavy truck with Full Self-Driving software and the cost structure of moving goods across an entire continent does not improve. It collapses. No fatigue. No sleep schedules. No fuel volatility. No human error. 24 hours. Every day. FSD is already statistically outperforming human drivers on safety metrics. The moment regulators accept that AI navigates a city safer than a human, applying that same software to commercial freight stops being a debate. It becomes a legal obligation. When the trucks move autonomously, the cost of everything on the shelf moves with them. Add humanoid robotics to the warehouse and the marginal cost of moving a product from point A to point B approaches zero. This is not a logistics story. It is a price-of-everything story. Physical transportation is just another data problem waiting to be solved by compute. And once that problem is solved, the inflation that has quietly taxed every human being alive for a century gets a knife in its throat.

Dustin

84,506 Aufrufe • vor 5 Monaten

🚨 MERCEDES JUST PUT A MOTOR ONLY 8 CM THICK INTO A CAR THAT CAN HIT 62 MPH IN 2.1 SECONDS. Instead of conventional radial flux motors, Mercedes is betting big on axial flux technology. In these motors, the electromagnetic force flows parallel to the axle, allowing two magnetic rotors to sandwich a central stator in a flat, disc-like layout. The result is dramatically smaller and more powerful. The front motor in the new all-electric Mercedes-AMG GT 4-door Coupe is just 9 cm wide. The rear motors are even thinner at roughly 8 cm each. Despite their tiny size, they help launch the heavy performance car from 0-62 mph in just 2.1 seconds, with a top speed of up to 186 mph. Why this matters: • Axial flux motors are significantly more power-dense and can be up to 50% lighter than traditional designs • Their extreme thinness frees up packaging space in the vehicle for better weight distribution, aerodynamics, or interior room • Mercedes acquired YASA in 2021 and has spent years developing the complex manufacturing processes needed to build them at scale • The technology is debuting in a high-performance AMG model, showing Mercedes is serious about using it in its most demanding cars The deeper implication: While most of the EV conversation focuses on batteries and software, the electric motor itself is undergoing a quiet revolution. Axial flux designs have long been seen as theoretically superior but extremely difficult to manufacture at scale. By solving the production challenges and putting these motors into a real high-performance car, Mercedes is pushing the entire industry forward. The next generation of electric performance cars may not just have bigger batteries they may have fundamentally better motors. We’re watching the physical hardware of EVs evolve as dramatically as the software has. How important do you think motor technology (rather than just battery size) will be for the future of electric performance cars? Follow for more frontier automotive engineering and electric vehicle technology.
0:10

🚨 MERCEDES JUST PUT A MOTOR ONLY 8 CM THICK INTO A CAR THAT CAN HIT 62 MPH IN 2.1 SECONDS. Instead of conventional radial flux motors, Mercedes is betting big on axial flux technology. In these motors, the electromagnetic force flows parallel to the axle, allowing two magnetic rotors to sandwich a central stator in a flat, disc-like layout. The result is dramatically smaller and more powerful. The front motor in the new all-electric Mercedes-AMG GT 4-door Coupe is just 9 cm wide. The rear motors are even thinner at roughly 8 cm each. Despite their tiny size, they help launch the heavy performance car from 0-62 mph in just 2.1 seconds, with a top speed of up to 186 mph. Why this matters: • Axial flux motors are significantly more power-dense and can be up to 50% lighter than traditional designs • Their extreme thinness frees up packaging space in the vehicle for better weight distribution, aerodynamics, or interior room • Mercedes acquired YASA in 2021 and has spent years developing the complex manufacturing processes needed to build them at scale • The technology is debuting in a high-performance AMG model, showing Mercedes is serious about using it in its most demanding cars The deeper implication: While most of the EV conversation focuses on batteries and software, the electric motor itself is undergoing a quiet revolution. Axial flux designs have long been seen as theoretically superior but extremely difficult to manufacture at scale. By solving the production challenges and putting these motors into a real high-performance car, Mercedes is pushing the entire industry forward. The next generation of electric performance cars may not just have bigger batteries they may have fundamentally better motors. We’re watching the physical hardware of EVs evolve as dramatically as the software has. How important do you think motor technology (rather than just battery size) will be for the future of electric performance cars? Follow for more frontier automotive engineering and electric vehicle technology.

TheNewPhysics

399,616 Aufrufe • vor 2 Monaten

When you train in the 10-12 rep range, most of your reps have no direct effect on growth. When you train in the 4-6 range, virtually all of your reps are growth reps. Both ranges can build muscle. The mechanism doesn't care about the rep count. It cares about how close you get to true failure on the reps where the high-threshold motor units are recruited and every available fibre is firing. Those are the stimulating reps. Everything else is filler. The catch with 10-12 is twofold. First, only the last 4-5 reps in a 12-rep set are actually stimulating. The first seven are buffer. They generate fatigue, lactic acid, and joint wear that the muscle has to push through before any growth signal arrives. Effort, yes. Stimulus, no. Second, and this is where the high-rep crowd quietly come undone: the long set produces so much afferent feedback (burning, gasping, the legs giving a small philosophical speech) that almost nobody actually takes the set to true failure. They stop two, three, sometimes four reps short, mistake the discomfort for the limit, and call it a hard set. The stimulating reps they were chasing never showed up. A set of 6 doesn't allow that confusion. Failure is mechanical. The weight either moves or it doesn't. No interpretive dance required. You'll grow on 10-12. You'll grow more on 4-6, with less joint wear, less recovery debt, and considerably less guesswork. One range tolerates your mistakes. The other doesn't have room for them.
0:18

When you train in the 10-12 rep range, most of your reps have no direct effect on growth. When you train in the 4-6 range, virtually all of your reps are growth reps. Both ranges can build muscle. The mechanism doesn't care about the rep count. It cares about how close you get to true failure on the reps where the high-threshold motor units are recruited and every available fibre is firing. Those are the stimulating reps. Everything else is filler. The catch with 10-12 is twofold. First, only the last 4-5 reps in a 12-rep set are actually stimulating. The first seven are buffer. They generate fatigue, lactic acid, and joint wear that the muscle has to push through before any growth signal arrives. Effort, yes. Stimulus, no. Second, and this is where the high-rep crowd quietly come undone: the long set produces so much afferent feedback (burning, gasping, the legs giving a small philosophical speech) that almost nobody actually takes the set to true failure. They stop two, three, sometimes four reps short, mistake the discomfort for the limit, and call it a hard set. The stimulating reps they were chasing never showed up. A set of 6 doesn't allow that confusion. Failure is mechanical. The weight either moves or it doesn't. No interpretive dance required. You'll grow on 10-12. You'll grow more on 4-6, with less joint wear, less recovery debt, and considerably less guesswork. One range tolerates your mistakes. The other doesn't have room for them.

Sama Hoole

63,040 Aufrufe • vor 3 Monaten

A Letter to Our Community: The Road Ahead for Robotics To our Community and Partners, As we step into 2026, our mission at Axis is clearer than ever: Constructing the definitive End-to-End Scaling Layer for Robotics. Our goal is to accelerate the transfer of diverse human intelligence into Robotics General Intelligence (RGI). By owning the critical path of intelligence creation, we are turning the physical limitations of robotics into a scalable, software-driven future. Here is our strategic outlook and roadmap for the year ahead. The Core Thesis: Simulation is the Only Way Out The path to RGI is currently blocked by Data Scarcity, Generalization Fragility, and Hardware Fragmentation. At Axis, we believe Simulation is the only way out. Our Simulation Data Platform and Data Augmentation Engine transform raw data into "Synthetic Gold". Backed by academic milestones like Roboverse, Skill Blending, and GraspVLA, we have proven that pure simulation can achieve the generalization required for the real world. We don’t just collect data; we architect it. The Engine: Why Crypto? We believe RGI should come from all, not a few. Crypto is not just a feature; it is the primitive that powers our entire ecosystem flywheel: - Incentive Mechanism: Democratizing contribution and rewarding the trainers and developers. - Assetization: Turning proprietary data and refined models into liquid, ownable assets. - Verifiable Workflow: We are opening the "Black Box" of AI. By bringing total transparency to the Task Generation → Data Collection → Model Training pipeline, we ensure every byte of intelligence is verifiable, traceable, and secure. 2026 Strategic Deliverables This year, we are committed to delivering three foundational pillars: - The World's Largest Training Dataset for Robots: A robot training set—diverse, high-quality interaction data at an unprecedented scale. - A Robotics Foundation Model: A universal robotic brain trained on our pure simulation and synthetic data, capable of robust cross-embodiment transfer and open-world adaptability. - Evolvable Robot Hardware: Robots deployed with Axis models that autonomously evolve through continuous interaction, turning every deployment into a self-improving node within our RGI network. The Ultimate Vision We are building more than models; we are architecting the Distributed Machine Economy. A future where every dataset, model, and robotic embodiment is a verifiable asset in a global, autonomous network. Thank you for building the future of intelligence with us✌️📷
0:13

A Letter to Our Community: The Road Ahead for Robotics To our Community and Partners, As we step into 2026, our mission at Axis is clearer than ever: Constructing the definitive End-to-End Scaling Layer for Robotics. Our goal is to accelerate the transfer of diverse human intelligence into Robotics General Intelligence (RGI). By owning the critical path of intelligence creation, we are turning the physical limitations of robotics into a scalable, software-driven future. Here is our strategic outlook and roadmap for the year ahead. The Core Thesis: Simulation is the Only Way Out The path to RGI is currently blocked by Data Scarcity, Generalization Fragility, and Hardware Fragmentation. At Axis, we believe Simulation is the only way out. Our Simulation Data Platform and Data Augmentation Engine transform raw data into "Synthetic Gold". Backed by academic milestones like Roboverse, Skill Blending, and GraspVLA, we have proven that pure simulation can achieve the generalization required for the real world. We don’t just collect data; we architect it. The Engine: Why Crypto? We believe RGI should come from all, not a few. Crypto is not just a feature; it is the primitive that powers our entire ecosystem flywheel: - Incentive Mechanism: Democratizing contribution and rewarding the trainers and developers. - Assetization: Turning proprietary data and refined models into liquid, ownable assets. - Verifiable Workflow: We are opening the "Black Box" of AI. By bringing total transparency to the Task Generation → Data Collection → Model Training pipeline, we ensure every byte of intelligence is verifiable, traceable, and secure. 2026 Strategic Deliverables This year, we are committed to delivering three foundational pillars: - The World's Largest Training Dataset for Robots: A robot training set—diverse, high-quality interaction data at an unprecedented scale. - A Robotics Foundation Model: A universal robotic brain trained on our pure simulation and synthetic data, capable of robust cross-embodiment transfer and open-world adaptability. - Evolvable Robot Hardware: Robots deployed with Axis models that autonomously evolve through continuous interaction, turning every deployment into a self-improving node within our RGI network. The Ultimate Vision We are building more than models; we are architecting the Distributed Machine Economy. A future where every dataset, model, and robotic embodiment is a verifiable asset in a global, autonomous network. Thank you for building the future of intelligence with us✌️📷

Axis Robotics

27,858 Aufrufe • vor 7 Monaten

Here, I completely disagree with this reductionist perspective of Mr Mbeki on geopolitics and the conduct of states. In this interview, he narrowly and in a very myopic way imagines a battle ring with SA and US as fighters to the dead end. The inherent dynamics in contemporary geopolitics are more complex than this simplistic articulation. SA is not interested in a fight with the US but is unapologetically in the fold of global anti-imperialist efforts that find expression in different platforms like BRICS+ to marginalise the imperialist agenda. The belly of imperialism is the US. The global anti-imperialist efforts are gaining significant momentum that threatens the post WWII configuration and spread of global balance of power, which was later punctuated by the collapse of the USSR. The beginning of the 21st century marked the incremental and gradual decline of the US's global influence. Hence, the nervousness that gave birth to MAKE AMERICA GREAT AGAIN (MAGA) policy. MAGA is an attempt to crudely and erratically reassert the US as an unrival global hegemon. With how contemporary global politics are shaped, this agenda is doomed, and it will definitely fail. The US and its fragmented West allies are the axis of imperialism, and the geopraphic location of the anti-imperialist agenda is mainly in the South. The South is not South Africa, but countries located in the Southern Hemisphere. Closely monitoring the development and the relentless anti-imperialist efforts in the South, on all fronts - economics, politics, technology , and diplomacy it is quite apparent that the US is confronted with a strategic dilemma and challenge unlike the bipolar period. Here, victory is certain for the anti-imperialist forces, which South Africa is unapologetically part of.
0:14

Here, I completely disagree with this reductionist perspective of Mr Mbeki on geopolitics and the conduct of states. In this interview, he narrowly and in a very myopic way imagines a battle ring with SA and US as fighters to the dead end. The inherent dynamics in contemporary geopolitics are more complex than this simplistic articulation. SA is not interested in a fight with the US but is unapologetically in the fold of global anti-imperialist efforts that find expression in different platforms like BRICS+ to marginalise the imperialist agenda. The belly of imperialism is the US. The global anti-imperialist efforts are gaining significant momentum that threatens the post WWII configuration and spread of global balance of power, which was later punctuated by the collapse of the USSR. The beginning of the 21st century marked the incremental and gradual decline of the US's global influence. Hence, the nervousness that gave birth to MAKE AMERICA GREAT AGAIN (MAGA) policy. MAGA is an attempt to crudely and erratically reassert the US as an unrival global hegemon. With how contemporary global politics are shaped, this agenda is doomed, and it will definitely fail. The US and its fragmented West allies are the axis of imperialism, and the geopraphic location of the anti-imperialist agenda is mainly in the South. The South is not South Africa, but countries located in the Southern Hemisphere. Closely monitoring the development and the relentless anti-imperialist efforts in the South, on all fronts - economics, politics, technology , and diplomacy it is quite apparent that the US is confronted with a strategic dilemma and challenge unlike the bipolar period. Here, victory is certain for the anti-imperialist forces, which South Africa is unapologetically part of.

Dr. Zamani Saul

17,897 Aufrufe • vor 1 Jahr

More Batteries vs. Submarines Now that the German TKMS and the French Naval Group have massively adopted lithium-ion batteries, following the Japanese lead, this is consolidating as a major trend, just as I had predicted. The next stage will be solid-state batteries, and at that point, we'll essentially be discussing only speed and submerged endurance in comparison to nuclear submarines. Since solid-state batteries are lighter, they will allow for a greater number to be installed, freeing up space for more powerful propulsion systems. Naval Group has already sold a version of the Scorpène to Indonesia capable of remaining submerged for up to 80 days. That's with lithium-ion batteries. Imagine what this could exceed, more than double, with solid-state batteries. In practical terms, a more powerful engine combined with solid-state batteries in the proportions that Naval Group is now using in the Scorpène would provide three times the speed, meaning something like 10–15 knots at constant speed while maintaining around 50 days submerged. This would give a range of 40,000–50,000 km, requiring less than one hour on the surface for a fast recharge. For speeds above 25 knots, simply adding more batteries and a better engine would suffice, as the solid-state system has high power output. All this at 15–20% of the cost of a nuclear submarine. And if the choice is to power the batteries with a micro-reactor, it would cost 25–35% of a conventional nuclear one. Then someone will say: “But a nuclear sub can stay submerged for years.” That makes no difference at all, since even with around 60 days of endurance, the crew still needs to surface to resupply provisions. The big advantages remain: battery-powered subs are superior in silence, and speed can be addressed with larger battery packs.
0:17

More Batteries vs. Submarines Now that the German TKMS and the French Naval Group have massively adopted lithium-ion batteries, following the Japanese lead, this is consolidating as a major trend, just as I had predicted. The next stage will be solid-state batteries, and at that point, we'll essentially be discussing only speed and submerged endurance in comparison to nuclear submarines. Since solid-state batteries are lighter, they will allow for a greater number to be installed, freeing up space for more powerful propulsion systems. Naval Group has already sold a version of the Scorpène to Indonesia capable of remaining submerged for up to 80 days. That's with lithium-ion batteries. Imagine what this could exceed, more than double, with solid-state batteries. In practical terms, a more powerful engine combined with solid-state batteries in the proportions that Naval Group is now using in the Scorpène would provide three times the speed, meaning something like 10–15 knots at constant speed while maintaining around 50 days submerged. This would give a range of 40,000–50,000 km, requiring less than one hour on the surface for a fast recharge. For speeds above 25 knots, simply adding more batteries and a better engine would suffice, as the solid-state system has high power output. All this at 15–20% of the cost of a nuclear submarine. And if the choice is to power the batteries with a micro-reactor, it would cost 25–35% of a conventional nuclear one. Then someone will say: “But a nuclear sub can stay submerged for years.” That makes no difference at all, since even with around 60 days of endurance, the crew still needs to surface to resupply provisions. The big advantages remain: battery-powered subs are superior in silence, and speed can be addressed with larger battery packs.

Patricia Marins

103,224 Aufrufe • vor 8 Monaten

The situation in northern Israel is getting surprisingly little attention in the West. Here’s some background and an explanation of just how dire it is. World War Three gets closer by the day, and I’m not exaggerating. UNSC resolution 1701 (2006) is that Hezbollah agree to stay north of the river Litani in Lebanon. This puts Israeli settlements out of anti-tank rocket range. However, Hezbollah have broken this and since 7th October have fired thousands of rockets into Israel, displacing some 60,000 Israelis from their homes. To be clear, Hezbollah is a direct Iranian proxy, who live like a virus inside the almost-dead body of the Lebanese state. Their fighters are far superior to Hamas, having gained serious experience in the Syrian civil war. They have no real ground manoeuvre or air power, but their tunnels in the chalk rock of southern Lebanon are better than Hamas’ and they have an estimated 150,000 rockets. There are UN Peacekeepers in Lebanon, but (shockingly for the UN, I know) they’re as much use as a bacon sandwich at a Bar Mitzvah. One very senior Israeli source described them to me as “an umbrella that folds when it rains”. So Israel has a real, very serious problem. They do not have the manpower to assault into Lebanon for any kind of sustained campaign, especially whilst Gaza is ongoing. So, in polite terms, they are kicking the shit out of it from the air (over which they have total superiority) and relying on missile defences. Thousands of targets have been struck in the last 9 months but Hezbollah retain very significant missile capability. This is why Israel are beholden to the USA to offer obscenely generous ceasefire terms to Hamas (that Hamas appear to be declining). They cannot afford to lose American military aid with this threat on their northern border. In the videos below, in the first vid you see the war zone northern Israel has become. The second one is the settlement of Katzrin in the Golan Heights. Surrounded on all sides by fires. In a statement to Qatari-funded Muslim Brotherhood mouthpiece Al Jazeera, yesterday Hezbollah said, “We simultaneously attacked 15 bases in the Golan and the Galilee using 150 rockets and 30 drones. This is the most extensive attack carried out by the organization since October 8, this attack came in response to the assassination in Joya and in order to deter Israel from carrying out further assassinations of this type.” On top of that, Iranian proxies in Iraq took responsibility last night for the joint operation they carried out together with the Houthis (Iranian proxies in Yemen), which launched these ballistic missiles and UAVs towards the Israeli cities of Ashdod and Haifa (third video). Iran is besieging Israel on all sides, and Israel is bending, not breaking. This situation is genuinely dire. It explains why Hamas will not sign a ceasefire deal, and why other non-Iran aligned Gulf states are meeting with IDF commanders. The entire region is teetering on the edge of a much more widespread conflict with Iran, and Israel is taking the brunt of it. If this situation deteriorates, our allies in the Gulf may call for aid. As a second front in the war against the Iran-Russia-China-Qatar axis of malign global actors, this could not be more serious or worrying. And all the while we see subversive Iranian proxy organisations organising protests about Gaza on Western streets. Hopefully the West is not defeated domestically before the war even starts in earnest.
1:00

The situation in northern Israel is getting surprisingly little attention in the West. Here’s some background and an explanation of just how dire it is. World War Three gets closer by the day, and I’m not exaggerating. UNSC resolution 1701 (2006) is that Hezbollah agree to stay north of the river Litani in Lebanon. This puts Israeli settlements out of anti-tank rocket range. However, Hezbollah have broken this and since 7th October have fired thousands of rockets into Israel, displacing some 60,000 Israelis from their homes. To be clear, Hezbollah is a direct Iranian proxy, who live like a virus inside the almost-dead body of the Lebanese state. Their fighters are far superior to Hamas, having gained serious experience in the Syrian civil war. They have no real ground manoeuvre or air power, but their tunnels in the chalk rock of southern Lebanon are better than Hamas’ and they have an estimated 150,000 rockets. There are UN Peacekeepers in Lebanon, but (shockingly for the UN, I know) they’re as much use as a bacon sandwich at a Bar Mitzvah. One very senior Israeli source described them to me as “an umbrella that folds when it rains”. So Israel has a real, very serious problem. They do not have the manpower to assault into Lebanon for any kind of sustained campaign, especially whilst Gaza is ongoing. So, in polite terms, they are kicking the shit out of it from the air (over which they have total superiority) and relying on missile defences. Thousands of targets have been struck in the last 9 months but Hezbollah retain very significant missile capability. This is why Israel are beholden to the USA to offer obscenely generous ceasefire terms to Hamas (that Hamas appear to be declining). They cannot afford to lose American military aid with this threat on their northern border. In the videos below, in the first vid you see the war zone northern Israel has become. The second one is the settlement of Katzrin in the Golan Heights. Surrounded on all sides by fires. In a statement to Qatari-funded Muslim Brotherhood mouthpiece Al Jazeera, yesterday Hezbollah said, “We simultaneously attacked 15 bases in the Golan and the Galilee using 150 rockets and 30 drones. This is the most extensive attack carried out by the organization since October 8, this attack came in response to the assassination in Joya and in order to deter Israel from carrying out further assassinations of this type.” On top of that, Iranian proxies in Iraq took responsibility last night for the joint operation they carried out together with the Houthis (Iranian proxies in Yemen), which launched these ballistic missiles and UAVs towards the Israeli cities of Ashdod and Haifa (third video). Iran is besieging Israel on all sides, and Israel is bending, not breaking. This situation is genuinely dire. It explains why Hamas will not sign a ceasefire deal, and why other non-Iran aligned Gulf states are meeting with IDF commanders. The entire region is teetering on the edge of a much more widespread conflict with Iran, and Israel is taking the brunt of it. If this situation deteriorates, our allies in the Gulf may call for aid. As a second front in the war against the Iran-Russia-China-Qatar axis of malign global actors, this could not be more serious or worrying. And all the while we see subversive Iranian proxy organisations organising protests about Gaza on Western streets. Hopefully the West is not defeated domestically before the war even starts in earnest.

Andrew Fox

1,310,702 Aufrufe • vor 2 Jahren

Full Fine-tuning vs. Freezing Layers. Interact 👉 and == Full Fine-tuning == A real network has many — three layers in this example, billions of parameters in a production model. What does fine-tuning look like when you update all of them? That’s full fine-tuning: continue training every weight in the pretrained network on your new task. Every layer’s W gets its own ΔW. Nothing is frozen — every parameter is in play. Think of an MLP as a chain of prerequisites leading to an advanced course. Layer 1 might be Linear Algebra, layer 2 Probability, layer 3 Advanced Machine Learning — each one building on what came before. Fine-tuning is what happens during graduate study: the foundations are already there from undergrad, so you’re not re-learning. Full fine-tuning is reviewing every prerequisite to see what new topics have appeared and what discoveries the field has made since the last time you sat through them. Effective — but exhausting. This diagram shows the same three-layer MLP twice, side by side. On the left, the pretrained network runs on input X: three weight matrices W₁, W₂, W₃, each followed by a ReLU activation. Full fine-tuning gives the model the most freedom to specialize. Every parameter can move — and every parameter that can move must be stored. But not every prerequisite needs revisiting. The further you go back in the chain, the less the material has changed since pretraining — the linear-algebra basics under your computer-vision course are largely the same as they ever were. The next page does exactly that: freeze the prerequisites that haven’t moved, and only refresh the advanced one closest to your specialization. == Freezing Layers == Full fine-tuning reviewed every prerequisite — Linear Algebra, Probability, Advanced ML — to refresh each subject with the latest topics. Effective, but exhausting. Then you realize something. The prerequisites haven’t actually changed that much. Linear Algebra is still Linear Algebra; the matrix decompositions you learned still hold. Probability is still Probability; the distributions and Bayes’ rule haven’t moved. Almost all the new material — the new ideas, the recent discoveries — lives in the advanced layer at the top. That’s freezing layers: keep the prerequisite layers fixed at their pretrained state, and only update the advanced one. In the diagram below, W1​ and W2​ — the foundational prerequisites — stay frozen. Only W3​ — the layer closest to your task-specific output — gets a ΔW.
0:16

Full Fine-tuning vs. Freezing Layers. Interact 👉 and == Full Fine-tuning == A real network has many — three layers in this example, billions of parameters in a production model. What does fine-tuning look like when you update all of them? That’s full fine-tuning: continue training every weight in the pretrained network on your new task. Every layer’s W gets its own ΔW. Nothing is frozen — every parameter is in play. Think of an MLP as a chain of prerequisites leading to an advanced course. Layer 1 might be Linear Algebra, layer 2 Probability, layer 3 Advanced Machine Learning — each one building on what came before. Fine-tuning is what happens during graduate study: the foundations are already there from undergrad, so you’re not re-learning. Full fine-tuning is reviewing every prerequisite to see what new topics have appeared and what discoveries the field has made since the last time you sat through them. Effective — but exhausting. This diagram shows the same three-layer MLP twice, side by side. On the left, the pretrained network runs on input X: three weight matrices W₁, W₂, W₃, each followed by a ReLU activation. Full fine-tuning gives the model the most freedom to specialize. Every parameter can move — and every parameter that can move must be stored. But not every prerequisite needs revisiting. The further you go back in the chain, the less the material has changed since pretraining — the linear-algebra basics under your computer-vision course are largely the same as they ever were. The next page does exactly that: freeze the prerequisites that haven’t moved, and only refresh the advanced one closest to your specialization. == Freezing Layers == Full fine-tuning reviewed every prerequisite — Linear Algebra, Probability, Advanced ML — to refresh each subject with the latest topics. Effective, but exhausting. Then you realize something. The prerequisites haven’t actually changed that much. Linear Algebra is still Linear Algebra; the matrix decompositions you learned still hold. Probability is still Probability; the distributions and Bayes’ rule haven’t moved. Almost all the new material — the new ideas, the recent discoveries — lives in the advanced layer at the top. That’s freezing layers: keep the prerequisite layers fixed at their pretrained state, and only update the advanced one. In the diagram below, W1​ and W2​ — the foundational prerequisites — stay frozen. Only W3​ — the layer closest to your task-specific output — gets a ΔW.

Tom Yeh

27,587 Aufrufe • vor 4 Monaten

A very good morning. Welcome to The Council Benji This marks the third Skull in a little run. The first went to a fund I've never met. The second: through Eli Scheinman to a new collector/foundation who has been quietly entering the space in a very significant way across a number of collections whom I’ve never spoken to. Their new entrance enabled a wedding and start of a new married life for Conviction. In my very first conversation with him, we spoke about curses and commitments to the people we love. Since meeting got to talk through each step on that path, from letting go, what is imbued in the ring and ceremony of it all, a proposal, and on the way to the most important of the steps in pursuit of a blessed life. It is easy to get a little cynical on the over-leveraged exit stories that spring up from time to time, so it is a treat to watch one go towards a celebration that’s been building up in his life since the Skull was first acquired. And now: this. The third Skull and the first I can really write about as a shared story across both source and destination. An exit and an entrance. The exit: The Skulls of Luci were awarded as gifts 4 years ago. But before I'd minted Birth of Luci or painted the other 49, the first person in this space I showed the sketch of The Blueprint Skull to was actually Casey💎, when he was working at SuperRare . Casey was the very first person who onboarded me to NFTs, helping me navigate the early days of whatever it meant to even mint something. I explained the idea of gifting one to each person who bid in my first auctions. Though most of the Skulls went to the bidders, Casey's didn't. He didn't ask for one. I didn't tell him I'd give him one. But he helped me take my first steps here, and it's hard to imagine any of this making sense, or unfolding the way it has, without him. Since then, we've broken bread across continents, seen quite a lot of chortling margarita consumption, watched the rise and fall of a lot around us, weathered inter-Council dramas. He brought Laura El into The Monument Game, played as a Player, wore a Mask. Most of the vibe that started all of this, the wild west of it, feels faded in the broader space at times. But every Skull has a story and a person who helped us get here. Casey will always be the one who was there before any metric muddled the reason to care. The entrance: Last fall, Benji came over for a studio visit. We walked through Luci, the works, structure, and dream, as anyone who visits does. But we mostly talked about being a father and having a father. We discussed the very idea of "collection" stripped of accumulation, value, or signal, located more in the act or ceremony of it. What it was to grow up with a curious father who studied the edges of each thing he saw to know the next layer beneath why anyone might look or ignore it. That to pass this on is to pass on questioning, more than it is to pass on any kind of answer. The process of collecting can be perceived as an individual act of hoarding. For some it is maybe. But at its best, it's a way to bind through shared questioning, to bond in cooperation and competition with friends and family, it is the swapped story and meme of it all, and each object gathered along the way carries some shared memory that can, often does, and with intent: should; drift out of the object entirely. All in the psalm, always has been. The studio visit came and went. Soon after, a package arrived in the mail with two of the softest stuffed animals added to my daughter's own collection, now among her favorites. The Skull is a bonus to that, in the scheme of shared memory. For Rachel and I, while we are heads down making a body of work that unsettles us and excites us but demands unknown time to accomplish, it means a great deal to have this kind of support from long term people in the quiet process of making work we want to leave behind ourselves. Enormously grateful to Casey for the many years of support and friendship, to Benny for being a true patron, and to Benji for entering the arena for what I'm working on next. Welcome.
0:11

A very good morning. Welcome to The Council Benji This marks the third Skull in a little run. The first went to a fund I've never met. The second: through Eli Scheinman to a new collector/foundation who has been quietly entering the space in a very significant way across a number of collections whom I’ve never spoken to. Their new entrance enabled a wedding and start of a new married life for Conviction. In my very first conversation with him, we spoke about curses and commitments to the people we love. Since meeting got to talk through each step on that path, from letting go, what is imbued in the ring and ceremony of it all, a proposal, and on the way to the most important of the steps in pursuit of a blessed life. It is easy to get a little cynical on the over-leveraged exit stories that spring up from time to time, so it is a treat to watch one go towards a celebration that’s been building up in his life since the Skull was first acquired. And now: this. The third Skull and the first I can really write about as a shared story across both source and destination. An exit and an entrance. The exit: The Skulls of Luci were awarded as gifts 4 years ago. But before I'd minted Birth of Luci or painted the other 49, the first person in this space I showed the sketch of The Blueprint Skull to was actually Casey💎, when he was working at SuperRare . Casey was the very first person who onboarded me to NFTs, helping me navigate the early days of whatever it meant to even mint something. I explained the idea of gifting one to each person who bid in my first auctions. Though most of the Skulls went to the bidders, Casey's didn't. He didn't ask for one. I didn't tell him I'd give him one. But he helped me take my first steps here, and it's hard to imagine any of this making sense, or unfolding the way it has, without him. Since then, we've broken bread across continents, seen quite a lot of chortling margarita consumption, watched the rise and fall of a lot around us, weathered inter-Council dramas. He brought Laura El into The Monument Game, played as a Player, wore a Mask. Most of the vibe that started all of this, the wild west of it, feels faded in the broader space at times. But every Skull has a story and a person who helped us get here. Casey will always be the one who was there before any metric muddled the reason to care. The entrance: Last fall, Benji came over for a studio visit. We walked through Luci, the works, structure, and dream, as anyone who visits does. But we mostly talked about being a father and having a father. We discussed the very idea of "collection" stripped of accumulation, value, or signal, located more in the act or ceremony of it. What it was to grow up with a curious father who studied the edges of each thing he saw to know the next layer beneath why anyone might look or ignore it. That to pass this on is to pass on questioning, more than it is to pass on any kind of answer. The process of collecting can be perceived as an individual act of hoarding. For some it is maybe. But at its best, it's a way to bind through shared questioning, to bond in cooperation and competition with friends and family, it is the swapped story and meme of it all, and each object gathered along the way carries some shared memory that can, often does, and with intent: should; drift out of the object entirely. All in the psalm, always has been. The studio visit came and went. Soon after, a package arrived in the mail with two of the softest stuffed animals added to my daughter's own collection, now among her favorites. The Skull is a bonus to that, in the scheme of shared memory. For Rachel and I, while we are heads down making a body of work that unsettles us and excites us but demands unknown time to accomplish, it means a great deal to have this kind of support from long term people in the quiet process of making work we want to leave behind ourselves. Enormously grateful to Casey for the many years of support and friendship, to Benny for being a true patron, and to Benji for entering the arena for what I'm working on next. Welcome.

Sam Spratt

20,786 Aufrufe • vor 4 Monaten

The three-body problem is a classic and notoriously difficult question in physics and mathematics. It asks: How do three objects, such as stars, planets, or moons, move under the influence of each other’s gravity? Unlike the simpler two-body problem, which has precise and predictable analytical solutions (like the Earth orbiting the Sun in an ellipse), the three-body problem quickly becomes chaotic and unpredictable. This complexity arises because each object's motion constantly affects, and is affected by, the other two. These gravitational interactions form a tangled and unstable system. In fact, there's no general formula that can solve all three-body scenarios exactly. This was first demonstrated in the 19th century by Henri Poincaré, whose work laid the foundations for chaos theory. While exact solutions remain elusive, scientists have discovered certain special cases where the motion is stable or periodic. One well-known example is the Lagrange points, where three bodies can maintain a stable triangular configuration. However, such neat solutions are rare. Today, thanks to powerful computers, researchers can simulate three-body systems with remarkable accuracy, helping us study triple-star systems, exoplanets, and asteroid dynamics. Yet even small changes in the starting conditions can lead to dramatically different outcomes, highlighting the sensitive dependence on initial conditions that defines chaotic systems. The three-body problem is actually a specific case of the broader n-body problem, where n can be any number of interacting bodies. As n increases, the complexity and unpredictability rise even further. The three-body problem serves as a vivid example of how simple laws of nature, like Newton’s law of gravity, can produce behavior that is intricate, unexpected, and profoundly difficult to predict.
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The three-body problem is a classic and notoriously difficult question in physics and mathematics. It asks: How do three objects, such as stars, planets, or moons, move under the influence of each other’s gravity? Unlike the simpler two-body problem, which has precise and predictable analytical solutions (like the Earth orbiting the Sun in an ellipse), the three-body problem quickly becomes chaotic and unpredictable. This complexity arises because each object's motion constantly affects, and is affected by, the other two. These gravitational interactions form a tangled and unstable system. In fact, there's no general formula that can solve all three-body scenarios exactly. This was first demonstrated in the 19th century by Henri Poincaré, whose work laid the foundations for chaos theory. While exact solutions remain elusive, scientists have discovered certain special cases where the motion is stable or periodic. One well-known example is the Lagrange points, where three bodies can maintain a stable triangular configuration. However, such neat solutions are rare. Today, thanks to powerful computers, researchers can simulate three-body systems with remarkable accuracy, helping us study triple-star systems, exoplanets, and asteroid dynamics. Yet even small changes in the starting conditions can lead to dramatically different outcomes, highlighting the sensitive dependence on initial conditions that defines chaotic systems. The three-body problem is actually a specific case of the broader n-body problem, where n can be any number of interacting bodies. As n increases, the complexity and unpredictability rise even further. The three-body problem serves as a vivid example of how simple laws of nature, like Newton’s law of gravity, can produce behavior that is intricate, unexpected, and profoundly difficult to predict.

Erika 

215,611 Aufrufe • vor 1 Jahr