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Testing Electromag Nodes on Apple M4 mac mini, very impressed with its performance in handling a complex scene like this. The magnetic field calculations are updated in realtime with no lag in EEVEE with a compositor node setup. The video shows the magnetic field of an embedded rogowski current... show more

Sam M

8,986 subscribers

48,749 görüntüleme • 1 yıl önce •via X (Twitter)

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Asger Bjørn Jørgensen profil fotoğrafı

Asger Bjørn Jørgensen1 yıl önce

This is truly remarkable, Sam 😍. And we wish to expand our design verification tools of power modules and PCBs in this direction. We understand that the CPU/GPU markets are way beyond us, but believe that efficient SiC/GaN design will require similar efforts. Thank you.

Michael Toutonghi (Mike.vrsc@) profil fotoğrafı

Michael Toutonghi (Mike.vrsc@)1 yıl önce

Can you recommend how I might get started if I have some high voltage inductive actuators that I’d like to either optimize or redesign?

LiamHz profil fotoğrafı

LiamHz1 yıl önce

@MasterTimBlais blender science vis!

Dagan Schoen profil fotoğrafı

Dagan Schoen1 yıl önce

wait you use blender for sims?

Peter Mathia ✈ profil fotoğrafı

Peter Mathia ✈1 yıl önce

How do you run Blender?

Christian Simon profil fotoğrafı

Christian Simon1 yıl önce

Can you tell us more about the pipe-line / integration ? From KiCAD to FEM (?) to Blender ?

Guttural Prayer profil fotoğrafı

Guttural Prayer1 yıl önce

Love your massive work

Mark Ankcorn profil fotoğrafı

Mark Ankcorn1 yıl önce

@DanielleFong Which one? Plain M4 or the Pro and how much RAM? Don’t leave the nerds hanging!!

Sam M profil fotoğrafı

Sam M1 yıl önce

@DanielleFong plain M4 mac mini, base cheapest model. 16GB unified RAM

darthur profil fotoğrafı

darthur1 yıl önce

Okay, I guess I need a new laptop now....

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You can use Blender's geometry nodes to solve physics and electromagnetic equations such as Biot-Savart law. You can calculate the magnetic field of a coil anywhere in 3D space and visualise the magnetic fields. Additionally, you can see in real-time how the magnetic field lines change as the coil gets deformed and twisted! #geometrynodes #b3d #blender3d #electronics #Engineering #Science #physics #kicad #circuits

You can use Blender's geometry nodes to solve physics and electromagnetic equations such as Biot-Savart law. You can calculate the magnetic field of a coil anywhere in 3D space and visualise the magnetic fields. Additionally, you can see in real-time how the magnetic field lines change as the coil gets deformed and twisted! #geometrynodes #b3d #blender3d #electronics #Engineering #Science #physics #kicad #circuits

Sam M

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Working on PCB stackup visualizer using geometry nodes, this is can be useful to show all the layers and the type of vias in a PCB design, and also can help in advanced designs that have embedded copper coins and components. Its fully procedural and controllable using gizmos #b3d #geometrynodes #pcbdesign #electronics #engineering #kicad #altium #3DModel #Science #Manufacturing #animation

Working on PCB stackup visualizer using geometry nodes, this is can be useful to show all the layers and the type of vias in a PCB design, and also can help in advanced designs that have embedded copper coins and components. Its fully procedural and controllable using gizmos #b3d #geometrynodes #pcbdesign #electronics #engineering #kicad #altium #3DModel #Science #Manufacturing #animation

Sam M

11,732 görüntüleme • 1 yıl önce

very excited to share what I've been working on, I've created an addon which allows you to run FastHenry directly in Blender! you can use the power of Blender to create any curve object and then call FastHenry to simulate the resistance and inductance. This demo video shows how you can calculate the resistance and inductance of a bond wire in a power module. You can experiement with different shapes and curvatures and see how the inductance changes. Furthermore you can control the radius with geomotry nodes! Also, you can combine this with ElectroMag Nodes to then visualise the magnetic fields! This addon will be a free update to ElectroMag Nodes #b3d #blender3d #geometrynodes #inductance #electronics #hardware #science #engineering #pcbdesign #educational #magnet #kicad #freecad #altium Maurizio Di Paolo Emilio hackaday

very excited to share what I've been working on, I've created an addon which allows you to run FastHenry directly in Blender! you can use the power of Blender to create any curve object and then call FastHenry to simulate the resistance and inductance. This demo video shows how you can calculate the resistance and inductance of a bond wire in a power module. You can experiement with different shapes and curvatures and see how the inductance changes. Furthermore you can control the radius with geomotry nodes! Also, you can combine this with ElectroMag Nodes to then visualise the magnetic fields! This addon will be a free update to ElectroMag Nodes #b3d #blender3d #geometrynodes #inductance #electronics #hardware #science #engineering #pcbdesign #educational #magnet #kicad #freecad #altium Maurizio Di Paolo Emilio hackaday

Sam M

58,782 görüntüleme • 2 yıl önce

Very excited to share this #openEMS simulation of a 60GHz #mmwave radar PCB! You can see how the e-field component is generated and then propagates in the transmission lines towards the antenna array. The radiated electric field shows one main lobe at 0 deg, and smaller side lobes #b3d #radar #kicad #electronics #educational hackaday #blender3d #antenna #rf Altium KiCad PCB FreeCAD (CAD+CAM+CAE) Jacques Lucke Chris Gammell #Physics #Engineering #Science

Very excited to share this #openEMS simulation of a 60GHz #mmwave radar PCB! You can see how the e-field component is generated and then propagates in the transmission lines towards the antenna array. The radiated electric field shows one main lobe at 0 deg, and smaller side lobes #b3d #radar #kicad #electronics #educational hackaday #blender3d #antenna #rf Altium KiCad PCB FreeCAD (CAD+CAM+CAE) Jacques Lucke Chris Gammell #Physics #Engineering #Science

Sam M

83,772 görüntüleme • 3 yıl önce

You can now use Blender Fasthenry to do PCB layout studies, calculate impedances of loops and return paths and determine how many vias you need! This demo shows how the impedance of DC decoupling capacitor is impacted by its distance from the IC, and the number of vias under the IC and near the capacitor. This is for a two-layer 1.6mm PCB at 1MHz. Blender FastHenry is now a solid tool for layout simulations and impedance calculations, available on Github. #b3d #geometrynodes #engineering #science #electronics #Simulation #kicad #altium #hardware #technology #3dmodeling #pcbdesign hackaday Maurizio Di Paolo Emilio

You can now use Blender Fasthenry to do PCB layout studies, calculate impedances of loops and return paths and determine how many vias you need! This demo shows how the impedance of DC decoupling capacitor is impacted by its distance from the IC, and the number of vias under the IC and near the capacitor. This is for a two-layer 1.6mm PCB at 1MHz. Blender FastHenry is now a solid tool for layout simulations and impedance calculations, available on Github. #b3d #geometrynodes #engineering #science #electronics #Simulation #kicad #altium #hardware #technology #3dmodeling #pcbdesign hackaday Maurizio Di Paolo Emilio

Sam M

37,632 görüntüleme • 1 yıl önce

Very excited to share the release of my addon Blender FastHenry! Use Blender's powerful modelling capability combined with geometry nodes to run FastHenry simulations! Blender is becoming a multi-purpose tool not just a tool for 3D graphics and animation, but also for engineering and scientific work too. This video shows how you can calculate the impedance of wire bonds and leads of a Mosfet in a TO-220 package, you can see what effect bending the leads and adding a heatsink have on the impedance! hackaday Dave Jones Sybren A. Stüvel 🔶 🐈‍⬛ (sybren@fosstodon.org) #b3d #blender3d #electronics #geometrynodes #3dart #pcbdesign #transistors #Engineering #science #physics #Technology #kicad #simulation #manufacturing

Very excited to share the release of my addon Blender FastHenry! Use Blender's powerful modelling capability combined with geometry nodes to run FastHenry simulations! Blender is becoming a multi-purpose tool not just a tool for 3D graphics and animation, but also for engineering and scientific work too. This video shows how you can calculate the impedance of wire bonds and leads of a Mosfet in a TO-220 package, you can see what effect bending the leads and adding a heatsink have on the impedance! hackaday Dave Jones Sybren A. Stüvel 🔶 🐈‍⬛ ([email protected]) #b3d #blender3d #electronics #geometrynodes #3dart #pcbdesign #transistors #Engineering #science #physics #Technology #kicad #simulation #manufacturing

Sam M

45,882 görüntüleme • 1 yıl önce

Wire bonding and lead impedance calculation in Blender FastHenry! I've improved how the simulation results are visualised, the entire objects now gets overlaid with a colour rather than using bound boxes. Red is for showing the self-inductance of a selected objected, yellow for mutually coupled objects and blue for conductive plane objects. Very impressed how easy it is nowadays to code anything with Python and Blender #b3d #electronics #engineering #science #pcbdesign #hadware #geometrynodes #3dmodeling #educational #simulation #fasthenry #altium #pythonlearning #electromagnetics #kicad

Wire bonding and lead impedance calculation in Blender FastHenry! I've improved how the simulation results are visualised, the entire objects now gets overlaid with a colour rather than using bound boxes. Red is for showing the self-inductance of a selected objected, yellow for mutually coupled objects and blue for conductive plane objects. Very impressed how easy it is nowadays to code anything with Python and Blender #b3d #electronics #engineering #science #pcbdesign #hadware #geometrynodes #3dmodeling #educational #simulation #fasthenry #altium #pythonlearning #electromagnetics #kicad

Sam M

29,843 görüntüleme • 1 yıl önce

New update on combining FastHenry and Blender 🔶 , I've added the ability to calculate the mutual inductance between objects! Also developed a basic UI inside Blender to visualise the results and to highlight the inductively coupled objects. This video shows some examples of what can be donw now. First demo shows how you can model the impedance of die bond wires and the coupling to adjacent wires, you make adjustments to their lengths and curvatures and see the results in near-real-time. Second demo shows calculating inductances and mutual inductance of air-core inductors with arbitrary positions and deformations. Third demo shows simulating PCB coils over a range of frequencies for applications such as wireless power and distance sensing. And you can combine this with Electromag Nodes to visualise the magnetic fields! #b3d #blender3d #geometrynodes #electronics #hardware #science #technology #pcbdesign #kicad #altium #ansys #3dart #programmer #python #engineering #semiconductors #circuits #inductors #components

New update on combining FastHenry and Blender 🔶 , I've added the ability to calculate the mutual inductance between objects! Also developed a basic UI inside Blender to visualise the results and to highlight the inductively coupled objects. This video shows some examples of what can be donw now. First demo shows how you can model the impedance of die bond wires and the coupling to adjacent wires, you make adjustments to their lengths and curvatures and see the results in near-real-time. Second demo shows calculating inductances and mutual inductance of air-core inductors with arbitrary positions and deformations. Third demo shows simulating PCB coils over a range of frequencies for applications such as wireless power and distance sensing. And you can combine this with Electromag Nodes to visualise the magnetic fields! #b3d #blender3d #geometrynodes #electronics #hardware #science #technology #pcbdesign #kicad #altium #ansys #3dart #programmer #python #engineering #semiconductors #circuits #inductors #components

Sam M

35,070 görüntüleme • 2 yıl önce

DIY electromagnetic levitator that works 👌 The UFO is made with 3D printed parts of its own design, neodymium magnets and carries a coil and several LEDs so it can be powered wirelessly with an external induction circuit. This is based on the magnetic levitation circuit of Celestí Capell. Video Credit: David Villafranca #diy #digitalelectronics #makermovement #engineering #engineer #electronics #ciencia #science #hazlotumismo #technlogy #pcb #diyelectronics #diyprojects

DIY electromagnetic levitator that works 👌 The UFO is made with 3D printed parts of its own design, neodymium magnets and carries a coil and several LEDs so it can be powered wirelessly with an external induction circuit. This is based on the magnetic levitation circuit of Celestí Capell. Video Credit: David Villafranca #diy #digitalelectronics #makermovement #engineering #engineer #electronics #ciencia #science #hazlotumismo #technlogy #pcb #diyelectronics #diyprojects

Wevolver

15,909 görüntüleme • 1 yıl önce

NEW PHYSICS! ANY "GENIUSES" OUT THERE WILL HAVE A CHANCE TO PROPOSE THE FIRST THEORY, TO EXPLAIN THESE NOVEL OBSERVATIONS. In many previous videos, I showed you how a permanent disc-magnet spins in the SAME direction as a 3-phase magnetic field (placed below), and rises up. What happens if we use an aluminum disc instead? By itself, an aluminum disc won't spin, because it has no internal magnetic field (which is needed to interact with the 3-phase field below). Yet if we add BOTH an aluminum disc, and also a large wire coil with AC power, then a magnetic field will be induced in that aluminum disc, and it becomes able to spin! The next question becomes: in which DIRECTION does the aluminum disc spin, with its induced magnetic field? Physics "geniuses", please watch this video to find out! Feel free to propose a new theory to explain these strange observations. We find that a large aluminum disc (100 mm diameter) spins clockwise, in the SAME sense as a rotating magnetic field below. Whereas a small aluminum disc (70 mm diameter) spins anti-clockwise, in an OPPOSITE sense to the rotating field below, Why has no one noticed this before? Mainstream physicists today just memorize old equations from textbooks, and could not discover "fleas on a dog".🤡 I suspect that these new data support a "vortex" theory of magnetism, but will let YOU decide! 😀

NEW PHYSICS! ANY "GENIUSES" OUT THERE WILL HAVE A CHANCE TO PROPOSE THE FIRST THEORY, TO EXPLAIN THESE NOVEL OBSERVATIONS. In many previous videos, I showed you how a permanent disc-magnet spins in the SAME direction as a 3-phase magnetic field (placed below), and rises up. What happens if we use an aluminum disc instead? By itself, an aluminum disc won't spin, because it has no internal magnetic field (which is needed to interact with the 3-phase field below). Yet if we add BOTH an aluminum disc, and also a large wire coil with AC power, then a magnetic field will be induced in that aluminum disc, and it becomes able to spin! The next question becomes: in which DIRECTION does the aluminum disc spin, with its induced magnetic field? Physics "geniuses", please watch this video to find out! Feel free to propose a new theory to explain these strange observations. We find that a large aluminum disc (100 mm diameter) spins clockwise, in the SAME sense as a rotating magnetic field below. Whereas a small aluminum disc (70 mm diameter) spins anti-clockwise, in an OPPOSITE sense to the rotating field below, Why has no one noticed this before? Mainstream physicists today just memorize old equations from textbooks, and could not discover "fleas on a dog".🤡 I suspect that these new data support a "vortex" theory of magnetism, but will let YOU decide! 😀

Red Collie (Dr. Horace Drew) scientist/inventor

26,727 görüntüleme • 11 ay önce

What you're seeing here is a simulation of a solar-wind pressure interacting with Earth's magnetosphere. Computations are based on the equations of resistive magnetohydrodynamics (MHD). In the model, the plasma is treated as an electrically conducting fluid whose motion is coupled to the evolution of the magnetic field.

What you're seeing here is a simulation of a solar-wind pressure interacting with Earth's magnetosphere. Computations are based on the equations of resistive magnetohydrodynamics (MHD). In the model, the plasma is treated as an electrically conducting fluid whose motion is coupled to the evolution of the magnetic field.

Mathelirium

33,821 görüntüleme • 1 ay önce

It has finally happened - my first video guide on how to create electromagnetic openEMS simulations with Blender 🔶 is now available! This video guide will show you to first create geometries and specify ports in #blender3d , export them to openEMS, write a few python scripts, and then using geometry nodes to visualise and animate the results back in Blender. The video is based on the Rotman lens animation I did previously as the workflow for it covers a wide range of topics. I hope you find this video informative. Everything is done using open-source tools including #inkscape, #paraview and Octave! #b3d #electronics #hardware #science #educational #physics #engineering #geometrynodes hackaday #openEMS #electromagnetics #tutorial #mathematics #antenna #rf #kicad #altium

It has finally happened - my first video guide on how to create electromagnetic openEMS simulations with Blender 🔶 is now available! This video guide will show you to first create geometries and specify ports in #blender3d , export them to openEMS, write a few python scripts, and then using geometry nodes to visualise and animate the results back in Blender. The video is based on the Rotman lens animation I did previously as the workflow for it covers a wide range of topics. I hope you find this video informative. Everything is done using open-source tools including #inkscape, #paraview and Octave! #b3d #electronics #hardware #science #educational #physics #engineering #geometrynodes hackaday #openEMS #electromagnetics #tutorial #mathematics #antenna #rf #kicad #altium

Sam M

24,248 görüntüleme • 2 yıl önce

Progressively Optimized Local Radiance Fields for Robust View Synthesis paper page: present an algorithm for reconstructing the radiance field of a large-scale scene from a single casually captured video. The task poses two core challenges. First, most existing radiance field reconstruction approaches rely on accurate pre-estimated camera poses from Structure-from-Motion algorithms, which frequently fail on in-the-wild videos. Second, using a single, global radiance field with finite representational capacity does not scale to longer trajectories in an unbounded scene. For handling unknown poses, we jointly estimate the camera poses with radiance field in a progressive manner. We show that progressive optimization significantly improves the robustness of the reconstruction. For handling large unbounded scenes, we dynamically allocate new local radiance fields trained with frames within a temporal window. This further improves robustness (e.g., performs well even under moderate pose drifts) and allows us to scale to large scenes. Our extensive evaluation on the Tanks and Temples dataset and our collected outdoor dataset, Static Hikes, show that our approach compares favorably with the state-of-the-art.

Progressively Optimized Local Radiance Fields for Robust View Synthesis paper page: present an algorithm for reconstructing the radiance field of a large-scale scene from a single casually captured video. The task poses two core challenges. First, most existing radiance field reconstruction approaches rely on accurate pre-estimated camera poses from Structure-from-Motion algorithms, which frequently fail on in-the-wild videos. Second, using a single, global radiance field with finite representational capacity does not scale to longer trajectories in an unbounded scene. For handling unknown poses, we jointly estimate the camera poses with radiance field in a progressive manner. We show that progressive optimization significantly improves the robustness of the reconstruction. For handling large unbounded scenes, we dynamically allocate new local radiance fields trained with frames within a temporal window. This further improves robustness (e.g., performs well even under moderate pose drifts) and allows us to scale to large scenes. Our extensive evaluation on the Tanks and Temples dataset and our collected outdoor dataset, Static Hikes, show that our approach compares favorably with the state-of-the-art.

AK

140,624 görüntüleme • 3 yıl önce

It is hard to understand "UFO physics", because many aspects of that technology disagree with what we know about magnetic physics, from previous experiments here on Earth! For example, when a spinning flywheel with 4 NNNN magnets reaches a spin frequency of 10 Hz (or 20 Hz for a flywheel with 8 NSNSNSNS magnets), it creates a non-magnetic STASIS FIELD in its center, where anti-clockwise spin and clockwise counter-spin forces seem to CANCEL or COLLIDE. This may be involved in some way with UFO physics, but since we have never seen it before, we find it hard to understand how it works, or what to do next! The 'Great Professors" in our Schools do not have a clue. Your A.I. devices do not have a clue either. Clowns to the left, jokers to the right. I will keep trying.

It is hard to understand "UFO physics", because many aspects of that technology disagree with what we know about magnetic physics, from previous experiments here on Earth! For example, when a spinning flywheel with 4 NNNN magnets reaches a spin frequency of 10 Hz (or 20 Hz for a flywheel with 8 NSNSNSNS magnets), it creates a non-magnetic STASIS FIELD in its center, where anti-clockwise spin and clockwise counter-spin forces seem to CANCEL or COLLIDE. This may be involved in some way with UFO physics, but since we have never seen it before, we find it hard to understand how it works, or what to do next! The 'Great Professors" in our Schools do not have a clue. Your A.I. devices do not have a clue either. Clowns to the left, jokers to the right. I will keep trying.

Red Collie (Dr. Horace Drew) scientist/inventor

14,654 görüntüleme • 27 gün önce

D-Wave announced a scientific breakthrough published in the esteemed journal Science Magazine, confirming that its annealing quantum computer outperformed one of the world’s most powerful classical supercomputers in solving a complex magnetic materials simulation problem with relevance to materials discovery. The new landmark peer-reviewed paper, “Beyond-Classical Computation in Quantum Simulation,” validates this achievement as the world’s first and only demonstration of quantum computational supremacy on a useful problem. An international collaboration of scientists led by D-Wave performed simulations of quantum dynamics in programmable spin glasses—a computationally hard magnetic materials simulation problem with known applications to business and science—on both D-Wave’s Advantage2™ prototype annealing quantum computer and the Frontier supercomputer at the Department of Energy’s Oak Ridge Lab. D-Wave’s quantum computer performed a complex simulation in minutes and with a level of accuracy that would take nearly a million years using the supercomputer. In addition, it would require more than the world’s annual electricity consumption to solve this problem using the supercomputer, which is built with graphics processing unit (GPU) clusters. For decades, scientists have aspired to build a quantum computer capable of solving complex materials simulation problems beyond the reach of classical computers. D-Wave's advancements in quantum hardware have made it possible for its annealing quantum computers to process these types of problems for the first time. Magnetic materials simulations, like those conducted in this work, use computer models to study how tiny particles not visible to the human eye react to external factors. Magnetic materials are widely used in medical imaging, electronics, superconductors, electrical networks, sensors, and motors. This is an incredibly important achievement. Please join us in congratulating the D-Wave team and our global collaborators on this remarkable milestone. It’s a significant moment for the quantum computing industry. Learn more about this monumental achievement: Read the press release here: #QuantumSupremacy #QuantumRealized #QuantumComputing #DWave #Technology #Innovation #Optimization #MaterialsDiscovery #ScientificBreakthrough $QBTS

D-Wave announced a scientific breakthrough published in the esteemed journal Science Magazine, confirming that its annealing quantum computer outperformed one of the world’s most powerful classical supercomputers in solving a complex magnetic materials simulation problem with relevance to materials discovery. The new landmark peer-reviewed paper, “Beyond-Classical Computation in Quantum Simulation,” validates this achievement as the world’s first and only demonstration of quantum computational supremacy on a useful problem. An international collaboration of scientists led by D-Wave performed simulations of quantum dynamics in programmable spin glasses—a computationally hard magnetic materials simulation problem with known applications to business and science—on both D-Wave’s Advantage2™ prototype annealing quantum computer and the Frontier supercomputer at the Department of Energy’s Oak Ridge Lab. D-Wave’s quantum computer performed a complex simulation in minutes and with a level of accuracy that would take nearly a million years using the supercomputer. In addition, it would require more than the world’s annual electricity consumption to solve this problem using the supercomputer, which is built with graphics processing unit (GPU) clusters. For decades, scientists have aspired to build a quantum computer capable of solving complex materials simulation problems beyond the reach of classical computers. D-Wave's advancements in quantum hardware have made it possible for its annealing quantum computers to process these types of problems for the first time. Magnetic materials simulations, like those conducted in this work, use computer models to study how tiny particles not visible to the human eye react to external factors. Magnetic materials are widely used in medical imaging, electronics, superconductors, electrical networks, sensors, and motors. This is an incredibly important achievement. Please join us in congratulating the D-Wave team and our global collaborators on this remarkable milestone. It’s a significant moment for the quantum computing industry. Learn more about this monumental achievement: Read the press release here: #QuantumSupremacy #QuantumRealized #QuantumComputing #DWave #Technology #Innovation #Optimization #MaterialsDiscovery #ScientificBreakthrough $QBTS

D-Wave

65,039 görüntüleme • 1 yıl önce

HAO WANG BUILT AN AI SERVER FARM OUT OF 100 MAC MINIS. ONE $599 BOX KILLS A $200/MONTH CLAUDE CODE BILL FOR $3 IN ELECTRICITY a developer posted his $170 claude code bill from 10 days on reddit. someone replied "i bought a mac mini m4. haven't paid anthropic since" the m4 chip has 120 gb/s memory bandwidth and unified memory. a $599 mac mini runs ai faster than a $1,500 windows pc with a discrete gpu ollama now supports the anthropic messages api. claude code connects to your local mac mini with one environment variable. zero api costs, same interface a heavy developer pays $459 a month across claude code, chatgpt pro, gemini, cursor and copilot. the mac mini pays off in 3 months and runs on $3 after that uber rolled out claude code to 5,000 engineers and burned $3.4 billion in 4 months. the people who own the hardware in 2026 will look very far ahead in 2028 bookmark this and read the article below

HAO WANG BUILT AN AI SERVER FARM OUT OF 100 MAC MINIS. ONE $599 BOX KILLS A $200/MONTH CLAUDE CODE BILL FOR $3 IN ELECTRICITY a developer posted his $170 claude code bill from 10 days on reddit. someone replied "i bought a mac mini m4. haven't paid anthropic since" the m4 chip has 120 gb/s memory bandwidth and unified memory. a $599 mac mini runs ai faster than a $1,500 windows pc with a discrete gpu ollama now supports the anthropic messages api. claude code connects to your local mac mini with one environment variable. zero api costs, same interface a heavy developer pays $459 a month across claude code, chatgpt pro, gemini, cursor and copilot. the mac mini pays off in 3 months and runs on $3 after that uber rolled out claude code to 5,000 engineers and burned $3.4 billion in 4 months. the people who own the hardware in 2026 will look very far ahead in 2028 bookmark this and read the article below

starmex

50,756 görüntüleme • 3 ay önce

🚨 ASTRONOMERS JUST OBSERVED A BLACK HOLE’S MAGNETIC FIELD FLIP Scientists just watched the magnetic field around the famous black hole M87* completely reverse direction, like it suddenly decided it wanted to be the opposite kind of black hole. The flip didn’t happen last week, though. It happened 55 million years ago; we’re just now seeing it because light takes that long to travel from M87 to Earth. Over a few years of observations using the Event Horizon Telescope, researchers noticed that the magnetic field around the black hole’s glowing plasma disk didn’t just wobble. It vanished, then came back, pointing the other way. This kind of behavior was not in the script. For something this massive, scientists expected the magnetic field to stay stable. Like, rock-solid stable. But nope. It flipped, and none of the current physics models saw it coming. Now researchers are wondering if black holes are more unpredictable than they thought, or if something else nudged it into chaos. Source: Science News

🚨 ASTRONOMERS JUST OBSERVED A BLACK HOLE’S MAGNETIC FIELD FLIP Scientists just watched the magnetic field around the famous black hole M87* completely reverse direction, like it suddenly decided it wanted to be the opposite kind of black hole. The flip didn’t happen last week, though. It happened 55 million years ago; we’re just now seeing it because light takes that long to travel from M87 to Earth. Over a few years of observations using the Event Horizon Telescope, researchers noticed that the magnetic field around the black hole’s glowing plasma disk didn’t just wobble. It vanished, then came back, pointing the other way. This kind of behavior was not in the script. For something this massive, scientists expected the magnetic field to stay stable. Like, rock-solid stable. But nope. It flipped, and none of the current physics models saw it coming. Now researchers are wondering if black holes are more unpredictable than they thought, or if something else nudged it into chaos. Source: Science News

Mario Nawfal

1,047,809 görüntüleme • 11 ay önce

$For decades, biologists argued that birds migrate using magnetic fields, and that cryptochrome proteins in their eyes help them figure out where to fly. But the evidence for this has always been flimsy. In 1972, Wolfgang and Roswitha Wiltschko captured migratory European robins, put them in cages, covered the cages with a blanket, and wrapped electric coils around them. Once the birds lost their view of the sky, they still tried to move, or "hop," in the direction of their normal migration route. But when the Wiltschkos flipped the magnetic field around, the robins started hopping in random directions. They took this as evidence that, somehow, birds migrate using a magnetic sense. (Not bad!) In 2000, three theoretical biophysicists in Illinois, Ritz, Adem, and Schulten, proposed a mechanism for that magnetic sense. They argued that when blue light hits a receptor in the eye, it might create something called a "radical pair," locking two electrons into a spin state that a magnetic field could then nudge. They suggested that cryptochromes, light-sensitive proteins in the retina, might be responsible. (Speculative!) And then, in 2021, researchers apparently confirmed this! They took cryptochrome proteins from a type of migratory robin and put them in a test tube. They shone blue light at the proteins and found that this light induced them to form that transient "radical pair" state. And finally, they showed that magnetic fields could change this photochemistry where, in the presence of a magnetic field, the proteins formed fewer of these radical pairs, because the field forced a larger fraction of the excited molecules to ‘collapse’ back to their resting state. The experiment they used to measure this, though, has almost nothing to do with biology. You literally isolate the proteins, bombard them with a blue laser and, after each pulse, measure how much light the proteins absorb. For the robin cryptochrome protein, adding a magnetic field changed the absorbance *slightly.* But here’s the caveat: All of this was done in vitro, in a test tube, in a water-based buffer (rather than a cell). And, even worse, the experiment was done at 5 degrees Celsius (waaaay colder than the bird’s normal temperature) and at a low pH. And even after all this tinkering, they still *barely* saw a magnetic response! The news media didn't report many of these caveats. I randomly pulled one story from Science News and another from the University of Oxford, and neither even mentioned that the researchers ran the experiment at low temperature. The Oxford writeup actually hyped the result up more than the paper itself; that author wrote: “…the authors think the proteins involved could be significantly more sensitive in their native environment. In cells in the retina, the proteins are probably fixed and aligned, increasing their sensitivity to the direction of the magnetic field. Moreover, they are also likely to be associated with other proteins that could amplify the sensory signals." (Wow!) When Andrew York and Maria Ingaramo, two scientist working at Calico, heard about these results, they grew skeptical and decided to search for magnetically-responsive proteins — that actually work under physiological conditions — on their own. And that search, in turn, gave rise to Nonfiction Laboratories, a company that not only has created such proteins, but is now trying to commercialize them to make magnetically controlled cancer therapies that are only active near a tumor. The clip below is from my podcast.$

For decades, biologists argued that birds migrate using magnetic fields, and that cryptochrome proteins in their eyes help them figure out where to fly. But the evidence for this has always been flimsy. In 1972, Wolfgang and Roswitha Wiltschko captured migratory European robins, put them in cages, covered the cages with a blanket, and wrapped electric coils around them. Once the birds lost their view of the sky, they still tried to move, or "hop," in the direction of their normal migration route. But when the Wiltschkos flipped the magnetic field around, the robins started hopping in random directions. They took this as evidence that, somehow, birds migrate using a magnetic sense. (Not bad!) In 2000, three theoretical biophysicists in Illinois, Ritz, Adem, and Schulten, proposed a mechanism for that magnetic sense. They argued that when blue light hits a receptor in the eye, it might create something called a "radical pair," locking two electrons into a spin state that a magnetic field could then nudge. They suggested that cryptochromes, light-sensitive proteins in the retina, might be responsible. (Speculative!) And then, in 2021, researchers apparently confirmed this! They took cryptochrome proteins from a type of migratory robin and put them in a test tube. They shone blue light at the proteins and found that this light induced them to form that transient "radical pair" state. And finally, they showed that magnetic fields could change this photochemistry where, in the presence of a magnetic field, the proteins formed fewer of these radical pairs, because the field forced a larger fraction of the excited molecules to ‘collapse’ back to their resting state. The experiment they used to measure this, though, has almost nothing to do with biology. You literally isolate the proteins, bombard them with a blue laser and, after each pulse, measure how much light the proteins absorb. For the robin cryptochrome protein, adding a magnetic field changed the absorbance slightly. But here’s the caveat: All of this was done in vitro, in a test tube, in a water-based buffer (rather than a cell). And, even worse, the experiment was done at 5 degrees Celsius (waaaay colder than the bird’s normal temperature) and at a low pH. And even after all this tinkering, they still barely saw a magnetic response! The news media didn't report many of these caveats. I randomly pulled one story from Science News and another from the University of Oxford, and neither even mentioned that the researchers ran the experiment at low temperature. The Oxford writeup actually hyped the result up more than the paper itself; that author wrote: “…the authors think the proteins involved could be significantly more sensitive in their native environment. In cells in the retina, the proteins are probably fixed and aligned, increasing their sensitivity to the direction of the magnetic field. Moreover, they are also likely to be associated with other proteins that could amplify the sensory signals." (Wow!) When Andrew York and Maria Ingaramo, two scientist working at Calico, heard about these results, they grew skeptical and decided to search for magnetically-responsive proteins — that actually work under physiological conditions — on their own. And that search, in turn, gave rise to Nonfiction Laboratories, a company that not only has created such proteins, but is now trying to commercialize them to make magnetically controlled cancer therapies that are only active near a tumor. The clip below is from my podcast.

Niko McCarty.

21,405 görüntüleme • 18 gün önce

"Mac Minis for example are a very good fit" - Andrej Karpathy Andrej Karpathy shouted out my work on EXO Labs in his keynote at Y Combinator AI SUS! Here's the breakdown: Right now most AI workloads run in the cloud where requests from different users are continuously batched together. These workloads are FLOPS-bound and favors hardware with the best unit economics of $ per FLOP, i.e. enterprise GPUs. The personal computing revolution will shift these workloads to personal devices with lower batch sizes (mostly batch_size=1). batch_size=1 inference is memory-bound, because all of the model parameters need to be loaded into the GPU every time a token is generated. Apple Silicon with its Unified Memory architecture has a lot of memory and memory bandwidth per $ compared to other hardware: - M4 Pro Mac Mini, 24GB @ 273GB/s, $58.33/GB, $5.13/GB/s - H100, 80GB @ 3350GB/s, $625/GB, $14.93/GB/s The unit economics of Apple Silicon are becoming more compelling with every release of the Mac. The future of AI inference looks more like open weights models (OpenAI open weights model soonTM) run at low batch_size on personal devices.

"Mac Minis for example are a very good fit" - Andrej Karpathy Andrej Karpathy shouted out my work on EXO Labs in his keynote at Y Combinator AI SUS! Here's the breakdown: Right now most AI workloads run in the cloud where requests from different users are continuously batched together. These workloads are FLOPS-bound and favors hardware with the best unit economics of $ per FLOP, i.e. enterprise GPUs. The personal computing revolution will shift these workloads to personal devices with lower batch sizes (mostly batch_size=1). batch_size=1 inference is memory-bound, because all of the model parameters need to be loaded into the GPU every time a token is generated. Apple Silicon with its Unified Memory architecture has a lot of memory and memory bandwidth per $ compared to other hardware: - M4 Pro Mac Mini, 24GB @ 273GB/s, $58.33/GB, $5.13/GB/s - H100, 80GB @ 3350GB/s, $625/GB, $14.93/GB/s The unit economics of Apple Silicon are becoming more compelling with every release of the Mac. The future of AI inference looks more like open weights models (OpenAI open weights model soonTM) run at low batch_size on personal devices.

Alex Cheema

103,604 görüntüleme • 1 yıl önce