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I trained models across MacBooks using Apple's AirDrop protocol. grove is a distributed training library for Apple Silicon. Devices discover each other over AWDL, a direct radio link. If there's a shared WiFi network it upgrades to that for speed, otherwise everything goes over the direct link. No router,...

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Swarnim Jain

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667,214 görüntüleme • 3 ay önce •via X (Twitter)

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built an payment app on Solana that discovers people near you over AWDL - the radio protocol behind apple's airdrop. basically two phones find each other over direct radio link. tap a face, enter an amount, send sol.
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built an payment app on Solana that discovers people near you over AWDL - the radio protocol behind apple's airdrop. basically two phones find each other over direct radio link. tap a face, enter an amount, send sol.

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Speed running my home AI cluster running distributed inference across 2 MacBooks and 2 Mac Minis. exo intern displays a real-time network topology as devices discover each other over the local network. Code is open source 👇
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Speed running my home AI cluster running distributed inference across 2 MacBooks and 2 Mac Minis. exo intern displays a real-time network topology as devices discover each other over the local network. Code is open source 👇

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The Grove Points Program is Live🦜 Grove Points opens Grove to the wider community, with 10M points available daily. There's only one way to Enter the Grove: supply USDS or USDC through Grove Savings and accrue points. Credit where credit is due.
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The Grove Points Program is Live🦜 Grove Points opens Grove to the wider community, with 10M points available daily. There's only one way to Enter the Grove: supply USDS or USDC through Grove Savings and accrue points. Credit where credit is due.

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OAK 4 CS now supports PTP synchronization. Sync multi-camera exposures over standard Ethernet. No FSYNC wiring, no daisy chains, no trigger cables across long distances. Just a shared clock distributed over the network. For multi-camera perception, distributed AI vision, and sensor fusion at scale.

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Brooks Koepka is sporting a Grove XXIII logo on his golf bag this week. MJ’s club is maybe the funnest place in golf. If I could take 7 normal golf buddies to any club in America other than Augusta for a stay and play, it would be Grove XXIII.

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Me and the homies at Brohemian Grove. Link to join us in the comments.
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Me and the homies at Brohemian Grove. Link to join us in the comments.

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BIG SAUCE WALK OFF GAME WINNING EXTRA INNING HOMER! Trevor Shinall goes yard to give Pine Grove a 4-3 win over West Union.

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1️⃣4️⃣ bombs for Bennett Van Cleve! 💣 Watch: Join the Grove Collective: Ole Miss Baseball x The Grove Collective

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Grove is an app for collaborative experimentation and creative work with AI agents grove - a place to grow your ideas closed beta starts next week, hit my DMs if u are interested in trying it out!

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This week on The Lineup, we discuss the turning point of Walnut Grove HS Girls Soccer's semifinal win over Burleson Centennial, an incredible save by Finley Pike on a PK attempt that led to the game-winning goal for Walnut Grove just 27 seconds later. Walnut Grove takes on Smithson Valley for the State Championship this weekend. Presented by Soulman's Bar-B-Que
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This week on The Lineup, we discuss the turning point of Walnut Grove HS Girls Soccer's semifinal win over Burleson Centennial, an incredible save by Finley Pike on a PK attempt that led to the game-winning goal for Walnut Grove just 27 seconds later. Walnut Grove takes on Smithson Valley for the State Championship this weekend. Presented by Soulman's Bar-B-Que

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FINAL | Pleasant Grove 2, Calallen 1 Pleasant Grove with two runs in the seventh and walks it off on a wild pitch to win the 4A D1 state title. The celebration is on for the Hawks.
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The Grove is the other way, buddy! 🐿
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The Grove is the other way, buddy! 🐿

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This is from Apple's State of the Union The local model is a 3B parameter SLM that uses adapters trained for each specific feature. Diffusion model does the same thing, adapter for each style. Anything running locally or Apple's Secure Cloud is an Apple model, not OpenAI.
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This is from Apple's State of the Union The local model is a 3B parameter SLM that uses adapters trained for each specific feature. Diffusion model does the same thing, adapter for each style. Anything running locally or Apple's Secure Cloud is an Apple model, not OpenAI.

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TIMBERRR!!!🌲 Look out for April Grove! April Grove - a cozy, casual lumberjack experience - is hitting Steam with a store page today!🪵🪓 Wishlist it on Steam so you know EXACTLY when it releases in June!

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Democrat Mayor in Lemon Grove, California Alysson Snow for Lemon Grove City Council orders the arrest of her political opponent for speaking up at a city council meeting.
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Democrat Mayor in Lemon Grove, California Alysson Snow for Lemon Grove City Council orders the arrest of her political opponent for speaking up at a city council meeting.

Amy Reichert

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Cloud GPU training is a scam. A single M4 MacBook does 2.9 TFLOPS. Seven friends with MacBooks match an NVIDIA A100. Alexander Hayes just open-sourced a tool that makes this work over Wi-Fi. It's called AirTrain. Here's how it works: Traditional distributed training (DDP) syncs gradients after every single step. For a 124M parameter model, that's ~500MB exchanged per step. You need 50 GB/s of sustained bandwidth. Impossible over Wi-Fi. AirTrain uses the DiLoCo algorithm. Each Mac trains independently for 500 steps, then syncs only the difference. One sync per 500 steps instead of one per step. 500x less network communication. Wi-Fi actually works. The entire sync takes ~2 seconds. Here's what makes it wild: → Zero-config discovery. Devices find each other automatically via mDNS/Bonjour. Same protocol as AirDrop. → Fault tolerant. Nodes can join and leave mid-training without killing the run. → Checkpoint relay. Train for a few hours, export a checkpoint, hand it off to someone else to continue. Like a relay race for ML training. → Built on Apple's MLX framework. Native to M1/M2/M3/M4/M5 unified memory. No host-to-device copy overhead. → Local dashboard. Real-time loss curves, peer monitoring, throughput metrics in your browser. Here's the wildest part: An M4 Max with 128GB unified memory can train a 70B parameter model without offloading. An NVIDIA RTX 4090 has 24GB VRAM. Apple Silicon gets ~245-460 GFLOPS per watt. Training on MacBooks costs almost nothing in electricity compared to cloud GPUs. And there are hundreds of millions of Apple Silicon Macs in the world. The math: Traditional DDP: 1 sync per step = 50 GB/s required AirTrain (DiLoCo): 1 sync per 500 steps = 0.1 GB/s required Wi-Fi handles 0.1 GB/s. That's it. That's the breakthrough. They even built a community platform at with live session browsing, checkpoint sharing, and a contributor leaderboard. Training a 124M parameter GPT-2? Instead of renting cloud GPUs at $3/hr, pool three MacBooks in a coffee shop and train for free. MIT licensed. Built in Python. 1 contributor. Early stage but the idea is insane. 100% Open Source. (Link in the comments)
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Cloud GPU training is a scam. A single M4 MacBook does 2.9 TFLOPS. Seven friends with MacBooks match an NVIDIA A100. Alexander Hayes just open-sourced a tool that makes this work over Wi-Fi. It's called AirTrain. Here's how it works: Traditional distributed training (DDP) syncs gradients after every single step. For a 124M parameter model, that's ~500MB exchanged per step. You need 50 GB/s of sustained bandwidth. Impossible over Wi-Fi. AirTrain uses the DiLoCo algorithm. Each Mac trains independently for 500 steps, then syncs only the difference. One sync per 500 steps instead of one per step. 500x less network communication. Wi-Fi actually works. The entire sync takes ~2 seconds. Here's what makes it wild: → Zero-config discovery. Devices find each other automatically via mDNS/Bonjour. Same protocol as AirDrop. → Fault tolerant. Nodes can join and leave mid-training without killing the run. → Checkpoint relay. Train for a few hours, export a checkpoint, hand it off to someone else to continue. Like a relay race for ML training. → Built on Apple's MLX framework. Native to M1/M2/M3/M4/M5 unified memory. No host-to-device copy overhead. → Local dashboard. Real-time loss curves, peer monitoring, throughput metrics in your browser. Here's the wildest part: An M4 Max with 128GB unified memory can train a 70B parameter model without offloading. An NVIDIA RTX 4090 has 24GB VRAM. Apple Silicon gets ~245-460 GFLOPS per watt. Training on MacBooks costs almost nothing in electricity compared to cloud GPUs. And there are hundreds of millions of Apple Silicon Macs in the world. The math: Traditional DDP: 1 sync per step = 50 GB/s required AirTrain (DiLoCo): 1 sync per 500 steps = 0.1 GB/s required Wi-Fi handles 0.1 GB/s. That's it. That's the breakthrough. They even built a community platform at with live session browsing, checkpoint sharing, and a contributor leaderboard. Training a 124M parameter GPT-2? Instead of renting cloud GPUs at $3/hr, pool three MacBooks in a coffee shop and train for free. MIT licensed. Built in Python. 1 contributor. Early stage but the idea is insane. 100% Open Source. (Link in the comments)

Guri Singh

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I told y’all I wouldn’t stand for the cheating and The Grove would pay for this. A week later:
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I told y’all I wouldn’t stand for the cheating and The Grove would pay for this. A week later:

Right Field Renegades (Tait’s Army)

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