Meta unveiled Brain2Qwerty v2, an AI system that converts... brain activity into text without requiring brain surgery. - Uses non invasive MEG recordings and end to end deep learning. - Achieved 61% word accuracy on average, with the best participant reaching 78%. - Trained on 22,000 sentences, significantly outperforming previous non invasive approaches. - Meta also open sourced the code to accelerate neuroscience research.show more

30 minutes of video. Robot learns the task. Open-source,... end-to-end. An open-source framework for training robot policies from only 30 minutes of human egocentric videos captured via Meta Aria glasses: Achieving zero-shot transfer to robots without any robot data collection. The method relies on Interaction-Centric Tokens that encode hand-object spatial relationships invariant to embodiment and viewpoint, supplemented by auxiliary objectives like object motion prediction and latent consistency to extract richer supervision signals from the same data. HumanEgo demonstrates strong cross-embodiment, cross-environment performance on bimanual tasks, outperforming baselines like ACT and teleop data while being trainable on a single RTX 4090 GPU. Thanks for sharing, Zhi (Leo) Wang. 📌 Website: Paper: Code: Video: ——- Weekly robotics and AI insights. Subscribe free:show more

Meta releases VGGSfM Visual Geometry Grounded Deep Structure From... Motion Structure-from-motion (SfM) is a long-standing problem in the computer vision community, which aims to reconstruct the camera poses and 3D structure of a scene from a set of unconstrained 2D images. Classical frameworks solve this problem in an incremental manner by detecting and matching keypoints, registering images, triangulating 3D points, and conducting bundle adjustment. Recent research efforts have predominantly revolved around harnessing the power of deep learning techniques to enhance specific elements (e.g., keypoint matching), but are still based on the original, non-differentiable pipeline. Instead, we propose a new deep SfM pipeline VGGSfM, where each component is fully differentiable and thus can be trained in an end-to-end manner. To this end, we introduce new mechanisms and simplifications. First, we build on recent advances in deep 2D point tracking to extract reliable pixel-accurate tracks, which eliminates the need for chaining pairwise matches. Furthermore, we recover all cameras simultaneously based on the image and track features instead of gradually registering cameras. Finally, we optimise the cameras and triangulate 3D points via a differentiable bundle adjustment layer. We attain state-of-the-art performance on three popular datasets, CO3D, IMC Phototourism, and ETH3D.show more

AN ANTHROPIC LEAD ENGINEER ACCIDENTALLY LEAKED HIS PERSONAL OBSIDIAN.... INSIDE - NOT CODE OR PROMPTS, BUT A DIAGRAM OF HIS OWN BRAIN, ORGANIZED AS A NEURAL NETWORK 8,893 nodes. 4,729 connections. A $10/month app opens Obsidian. 21 inputs, ReLU on every layer. The first hidden layer has 26 neurons, followed by 33, then 24, and so on all the way to the output. Thousands of connections flash in real time this isn’t a conceptual diagram from a blog, but a living brain that powers decision-making within the company. 9,000 documents, each with its own semantic space, all interconnected it earns about $2m a year for sorting Markdown files into the right folders. The company that builds the world’s best AI maintains its internal knowledge base in the same app that a freshman uses for class notes three years of discipline and a single open Obsidian tab you’re reading this on a device where, tonight, you can open that same Obsidian and start building your own vaultshow more

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

🦿Xpeng showed a humanoid robot called IRON whose movement... looked so human that the team literally cut it open on stage to prove it is a machine. IRON uses a bionic body with a flexible spine, synthetic muscles, and soft skin so joints and torso can twist smoothly like a person. The system has 82 degrees of freedom in total with 22 in each hand for fine finger control. Compute runs on 3 custom AI chips rated at 2,250 TOPS (Tera Operations Per Second), which is far above typical laptop neural accelerators, so it can handle vision and motion planning on the robot. The AI stack focuses on turning camera input directly into body movement without routing through text, which reduces lag and makes the gait look natural. Xpeng staged the cut-open demo at AI Day in Guangzhou this week, addressing rumors that a performer was inside by exposing internal actuators, wiring, and cooling. Company materials also mention a large physical-world model and a multi-brain control setup for dialogue, perception, and locomotion, hinting at a path from stage demos to service work. Production is targeted for 2026, so near-term tasks will be limited, but the hardware shows a serious step toward human-scale manipulation.show more

Bringing you all on the inside for a first-hand,... behind-the-scenes look at some of the latest and greatest recovery options the Broncos are providing their players in their new $175 million state-of-the-art facility. This allows their players to recover as hard as they train. Too many athletes miss the boat on this and only recover when they have an injury or do minimal amount. As hard as you train, recovery harder!!! You’ve got to outwork the world in all areas and that includes how you take care of your body. Check these out… Cryo-room — Not a cryochamber but a whole room. Dry float tank — I’ve only been in ones where you are immersed in water, have never seen a “dry” version until today. The Ammortal Chamber — a high-end, futuristic biohacking pod that combines five core non-invasive wellness technologies into a single 25-minute, zero-gravity session designed to accelerate muscle recovery, reduce stress, and promote deep nervous system reset. This absolutely calmed down my nervous system so my body could heal itself. Hyperbaric chamber — I do this couple times a week back home to try to repair damage done to my brain and overall recovery. Makes a huge difference in how I bounce back each week. Other amenities: Did 25 minute sauna at 185 degrees, their water area of their hot and cold plunge pools is fantastic! They also have sleep pods for quick recovery naps and a ton more. I cannot thank Beau Lowery and his incredible player health and performance staff enough for helping me out and showing me all the bells and whistles #broncos #recovery #training #nfltrainingcampshow more

I've been editing this article about "brain mapping" and... connectomics, and I'm just stunned by how quickly the cost estimates to map, say, a mouse brain have plummeted in just the last couple years. It actually seems feasible that we could map the entire human brain -- all 86 billion neurons, and their connections -- in this lifetime. In the 1970s, Sydney Brenner started mapping all the connections between neurons in C. elegans. His team sliced the worm into thin pieces, took photos using an electron microscope, and manually traced and reconstructed each synapse for 302 neurons total. This project took more than a decade of work, and it cost about $16,500 to reconstruct each neuron. Scaling this up to a human brain boggles the mind. Electron microscopy remained the norm in connectomics for decades, because it was the only option available to see synapses at a resolution high enough to be able to trace their paths. Each electron microscope costs several hundreds of thousands of dollars, though, and you need lots of them to map even a mouse brain in a reasonable timeframe. In 2023, the Wellcome Trust released a report estimating how long, and how expensive, it would be to map the mouse connectome (~70M neurons). They estimated that imaging alone would cost $200-300M, and that proofreading (or ensuring that traces between neurons are correct) would cost $7-21 BILLION. (A human can only manually trace about 1 mm of neuron per hour.) Also, the images would occupy about 500 petabytes of data, and getting those data would require 20 electron microscopes running in parallel for about 5 years, continuously. They estimated the whole project would take about 17 years of work. This is, understandably, insane. But now it seems like there's an actual path toward mapping the full mouse brain in about five years for ~$100M dollars. There have been three major breakthroughs in the last year or so: 1/ Expansion microscopy, first developed in 2015, showed that it's possible to "enlarge" the brain by about 5x using a swellable polymer. But an improved method increases this number to >20x expansion, meaning we can now expand brains and image neurons much more easily using cheap light microscopes, rather than expensive electron ones. 2/ E11 Bio (a nonprofit research org) developed protein barcodes that get delivered into brain tissue; each neuron gets a unique combination of barcodes. These cells are then stained with colorful antibodies, which stick to a matching protein barcode, causing each neuron to light up in a distinct color. This makes tracing neurons so much easier. 3/ Google Research released PATHFINDER this May, an AI-based neuron tracing tool that can proofread about 67,200 cubic microns of brain tissue per hour, with very high accuracy. It works on electron micrographs, but something similar could be presumably be developed for the E11 / colorful tag approach. This is an extremely exciting time for neuroscience. (C. elegans connectome below.)show more

🚀 A better, faster co-folding-based binding affinity model. Predicting... how tightly a drug candidate binds to its target is critical in drug discovery. It also requires massive computational resources. State-of-the-art models can take 20 seconds to a minute per prediction, impractical for the demands of large scale early-stage programs . 💠 Today, Recursion’s Valence Labs is releasing Nesso-1: the fastest open-source co-folding-based binding affinity model available. At 1 second per prediction, it’s roughly 20x faster than our previous collaboration on Boltz-2 while matching or surpassing its accuracy across public and internal benchmarks. By leveraging NVIDIA Healthcare cuEquivariance, we’ve been able to further accelerate both training and inference by an additional 2-3x. We look forward to continuing to improve Nesso-1 in collaboration with NVIDIA. Weights and code are fully open-sourced. The core architectural ideas behind Nesso-1 build on the insight that coarse-grained co-folding representations can match full-atom models for affinity prediction at a fraction of the cost. Nesso-1 is the first open implementation of this approach with no proprietary dependencies, trained entirely on public data, built to be reproducible and extensible. We’re already using Nesso-1 internally in active drug discovery programs. Fast, reliable affinity prediction at scale is foundational to the kind of autonomous design loops that define our vision for Autonomous Precision Design and Nesso-1 is a meaningful step toward that. 👉 Report: 👉 Github: 👉 HF:show more

We’re excited to introduce ShinkaEvolve: An open-source framework that... evolves programs for scientific discovery with unprecedented sample-efficiency. Blog: Code: Like AlphaEvolve and its variants, our framework leverages LLMs to find state-of-the-art solutions to complex problems, but using orders of magnitude fewer resources! Many evolutionary AI systems are powerful but act like brute-force engines, burning thousands of samples to find good solutions. This makes discovery slow and expensive. We took inspiration from the efficiency of nature. ‘Shinka’ (進化) is Japanese for evolution, and we designed our system to be just as resourceful. On the classic circle packing optimization problem, ShinkaEvolve discovered a new state-of-the-art solution using only 150 samples. This is a big leap in efficiency compared to previous methods that required thousands of evaluations. We applied ShinkaEvolve to a diverse set of hard problems with real-world applications: 1/ AIME Math Reasoning: It evolved sophisticated agentic scaffolds that significantly outperform strong baselines, discovering an entire Pareto frontier of solutions trading performance for efficiency. 2/ Competitive Programming: On ALE-Bench (a benchmark for NP-Hard optimization problems), ShinkaEvolve took the best existing agent's solutions and improved them, turning a 5th place solution on one task into a 2nd place leaderboard rank in a competitive programming competition. 3/ LLM Training: We even turned ShinkaEvolve inward to improve LLMs themselves. It tackled the open challenge of designing load balancing losses for Mixture-of-Experts (MoE) models. It discovered a novel loss function that leads to better expert specialization and consistently improves model performance and perplexity. ShinkaEvolve achieves its remarkable sample-efficiency through three key innovations that work together: (1) an adaptive parent sampling strategy to balance exploration and exploitation, (2) novelty-based rejection filtering to avoid redundant work, and (3) a bandit-based LLM ensemble that dynamically picks the best model for the job. By making ShinkaEvolve open-source and highly sample-efficient, our goal is to democratize access to advanced, open-ended discovery tools. Our vision for ShinkaEvolve is to be an easy-to-use companion tool to help scientists and engineers with their daily work. We believe that building more efficient, nature-inspired systems is key to unlocking the future of AI-driven scientific research. We are excited to see what the community builds with it! Learn more in our technical report:show more

NEW WORLD MODEL: Yann LeCun's team is back with... an efficient model! This project involves Yann LeCun, Lukas Kuhn, Lucas Maes, Quentin Le Lidec, and Randall Balestriero. A couple definitions first: - DINO: self-DIstillation with NO labels. A self-supervised image model (Meta, 2021) where a student network learns to match a teacher (an EMA copy of itself) across two crops of the same image, with no labels and no negatives. - SIGReg: a regularizer that prevents embedding collapse by forcing the embeddings to match an isotropic Gaussian, tested with a normality test (Epps–Pulley) on many random 1-D projections instead of in full dimension. LeVJEPA is a self-supervised video pretraining method, released with open code, weights, and checkpoints. It learns a video representation by pushing the embeddings of global and local crops of the same clip together (an invariance loss), while a regularizer called SIGReg forces the embeddings toward an isotropic Gaussian to provably prevent representation collapse. Unlike V-JEPA and V-JEPA 2 it uses a single shared encoder with a projector and no target network, no predictor and no stop-gradient. It drops 95% of tokens per view, uses block-causal attention (each frame attends only to past frames), and has a single loss weight. It is evaluated purely as a representation learner via frozen probing on ImageNet-1K, Something-Something-v2 and Kinetics-400, not on any robot. What I find interesting, is that V-JEPA and V-JEPA 2 need an EMA target encoder, stop-gradients and a capacity-limited predictor to avoid collapse; LeVJEPA drops all of it for one shared encoder plus projector, preventing collapse instead with the SIGReg regularizer under a provable guarantee and a single hyperparameter. The "P" (predictor) in JEPA is effectively gone. LeVJEPA is also less compute intensive: - 5.6x to 20.8x lower total pretraining compute than V-JEPA 2 - 7.6 points higher on ImageNet-1K at matched FLOPs - trains at batch size 128 within 8GB where V-JEPA 2 saturates at batch size 28 Also worth mentioning: ImageNet-1K accuracy rises monotonically with the token-drop rate, from 33.9% at rho = 0 to 47.6% at rho = 0.95. The aggressive dropping is actually doing regularization work. On the JEPA-versus-DINO debate: - it loses to DINOv2 by 3.1 points on ImageNet-1K (appearance, static) - but wins on Something-Something-v2 by nearly 2x (motion, temporal) - and beats V-JEPA 2 by 1.9 points on ViT-L at 5.6x lower cost. -> optimized for temporal and motion understanding per compute dollar.show more

Grok Summary of Neuralink’s “Two Years of Telepathy” Update... Neuralink’s Telepathy is their pioneering brain-computer interface (BCI) aimed at restoring independence for people with paralysis by translating neural signals into digital commands for controlling devices like computers, phones, and robotic limbs. The article reflects on two years of progress, highlighting clinical trials with 21 participants (Neuralnauts), technical breakthroughs, personal stories of transformation, challenges, and ambitious future goals. • Key Milestones: Enrolled 21 participants worldwide; achieved information transfer rates over 10 bits per second (surpassing able-bodied mouse control); developed a mental ten-finger keyboard for typing up to 40 words per minute; launched the VOICE trial for real-time speech restoration targeting 140 words per minute; expanded trials from three in 2024 to multiple per month in 2025, with no serious device-related adverse events. • Patient Experiences and Impacts: ◦ Noland (first recipient, spinal cord injury): Regained independence for studying, reading, and college (best grades ever); describes it as reclaiming lost life. ◦Nick (paralyzed four years): Controls robotic arm for tasks like feeding; feels natural gestures, restoring a sense of movement. ◦Sebastian (medical student, recent injury): Uses for 17 hours daily to annotate papers and multitask in lectures, boosting productivity. ◦Audrey (20-year injury): Creates abstract art, gains online fame, plans a gallery; feels her mind “a little free.” ◦Jake (ALS): Uses mental keyboard for tasks; sees himself as a “superhero” for his son. ◦Brad (ALS): Controls wheelchair camera to watch his son at events; views ALS as an opportunity for innovation. • Technical Advancements: Translates thoughts into intuitive cursor/robotic control; detects bilateral hand signals from single-sided implants; adapts to individual brain variations during surgery; upcoming upgrades include tripling electrodes to 3000 and exploring less invasive insertion methods. • Challenges: Variations in brain anatomy and disease stages affect performance; early thread retraction issues addressed; communication loss in ALS patients (up to 95% decline ventilation); need for faster, more natural control. • Future Plans: Enhance hardware and procedures for consistency; advance speech restoration; accelerate enrollments; invite quadriplegic individuals (from spinal cord injury, ALS, or stroke) to join the patient registry; seek talent to scale solutions.show more

As we prepare to launch several projects, we're eager... to provide a general update to our community. We are steadily approaching our end goal, thanks to the daily progress we're making toward our vision. Achieving our objectives will bring about a significant transformation in cross-chain interoperability and the flow of liquidity within protocols. This will address crucial challenges and drive mass adoption. Our future-focused approach and effective team collaboration keep us moving forward in an organized manner. Let’s delve deeper into the state of development of our current products and upcoming projects. Tao Bridge Starting with the Tao Bridge, which enables the #Bittensor community to unlock DeFi opportunities with their $TAO via a highly efficient blockchain like #MultiversX, known for its security, speed, and affordability. We deeply admire #Bittensor and believe a project like that is crucial for the future of not just the crypto space but also humanity, as it addresses the major challenges AI faces today: centralization, siloed and isolated work, which pose risks and hinder the technology's potential. We are committed to the vision of subnets and dynamic $TAO, convinced that this ecosystem is as groundbreaking as #Ethereum or #Bitcoin. We will continue to support #Bittensor wherever possible, and our bridge will also expand to other chains with Hatom V2. The TAO Bridge, deployed on and accessible through will launch on the Mainnet in 14 days, on March 27th. You can follow the countdown on the lending page at Given that our main priorities are security and stability, this period will be primarily focused on quality assurance to ensure a flawless Mainnet launch. The launch will also introduce TAO Liquid Staking at along with the integration of both $wTAO and $swTAO on the lending page. This allows #Bittensor users to leverage liquid stake, employ short or long strategies, among other DeFi strategies, or simply access stablecoin liquidity while maintaining exposure to their $TAO. Up to $1M will be distributed as additional incentives on top of the supply APYs at the launch of the $wTAO and $swTAO money markets, with $200K allocated for the first month specifically for bootstrapping. Initially, 70% of rewards will go to liquidity providers, and 30% to those using $HTM to boost their lending positions. This changes to a 50-50 split in the second month, and by the third month, all incentives are directed through the Booster. This approach encourages early participation and sustained engagement with $HTM. Introducing $TAO to #MultiversX will result in the creation of Liquidity Pools (LPs) on both AshSwap 🔥 and xExchange ⚡. These LPs will be incentivized by both entities, and Hatom will distribute extra rewards at launch. The goal is to make #MultiversX a one-stop hub for $TAO holders. Upon stabilizing the volumes, there will also be plans to integrate it on AshPerp 🔥. Furthermore, with the release of $USH, users will have the ability to mint it while retaining exposure to their $TAO. The TAO Bridge and TAO Liquid Staking smart contracts have been audited by Runtime Vеrification and @arda_project, while penetration testing and DevSecOps have been performed on our infrastructure by CertiK. We're excited to announce our exclusive partnership with TAONEW one of the top 5 validators on #Bittensor. TAONEW has been extremely helpful and supportive from day one. By sharing 50% of its service fee with its stakers, TAONEW enables Hatom to offer an optimized Staking APY to its users. Since our initial reference, #Bittensor has grown sevenfold, becoming the largest AI project in the crypto sphere. We reiterate our commitment to contribute to such technology and hope to address some of its current DeFi challenges. Syfy Moving forward, today marks a significant milestone, not only for our decentralized protocols but also for our development companies, which currently stand as the sole and primary contributors to the Hatom Labs and Soul Labs. We’re excited to unveil Syfy, the evolved identity of Hatom Labs and Soul Labs, now serving as the parent entity for our burgeoning development companies. Organization is crucial for scalability, which is why Syfy was established to cultivate an environment where our teams can collaborate more seamlessly, enhancing our effectiveness and efficiency. At the same time, we remain committed to upholding the financial independence of each project, supported by its own community of funding contributors. Feel free to explore our website at for more information! Additionally, don't forget to follow Syfy and explore their Genesis article highlighted in their initial post: Booster V2 The Booster V2 will introduce a range of new features and opportunities for $HTM holders: Optimized Position Boosting: Previously, boosting was done individually for each money market, necessitating $HTM token distribution and periodic rebalancing due to price fluctuations. With Booster V2, the system now considers the overall position, eliminating the need for manual rebalancing. Gas Fee Reduction: Booster V2 implements optimizations that result in reduced gas fees, making transactions more cost-effective for users. Incorporation of Governance: Users staking $HTM tokens gain voting rights directly within the Booster, allowing them to participate in governance decisions while maintaining their staked positions. (Note: Only $HTM tokens are considered for governance; LP tokens are not included.) Enhanced Boosting Mechanism: The Booster V2 enables LP Tokens to boost positions within the Booster, leveraging trading fees from swaps and farm incentives while boosting lending positions. Smart Contract Completion: The Booster smart contract has been completed and audited by @arda_project, ensuring security and reliability. Frontend Implementation: The frontend design for Booster V2 has been successfully implemented, providing users with an intuitive interface. Collaboration with xExchange: Exploration is ongoing for collaboration with xExchange ⚡ to enable LP creation, farming, and meta-staking within the Booster. Upon finalization of testing, we will launch the Booster V2 on the devnet to gather community feedback and begin preparations for the mainnet release. Soul Before delving into Soul Labs's developments, it's essential to summarize its core functionality briefly: Soul Labs seamlessly connects different lending protocols and blockchains, facilitating lending and borrowing across platforms like Aave, Compound Labs, and Hatom Labs, consolidating liquidity and users' borrowing capabilities. Utilizing LayerZero Labs and other messaging layers for cross-chain communication, Soul Labs bypasses asset bridging or synthetics, unlocking novel DeFi strategies and solidifying its position as the ultimate solution for cross-lending dilemmas. Soul V1 will be permissionless, holding censorship-resistant features, incorporating multiple redundancy mechanisms, and providing support for various DApps. We're thrilled to announce that, following the launch of the Tao Bridge in 2-3 weeks, we will introduce the Soul Labs website. This platform has been meticulously crafted over 250 days to not only provide a comprehensive overview of our vision but also to offer an engaging and captivating experience that promises to be memorable. Regarding the app, significant progress has been made on the V1 protocol, including: Smart Contract Development and Testing: • Completion of the initial phase of smart contract development. • Conducting advanced testing to ensure the system's robustness. • Establishment of a fully functional proof of concept. Successful deployment and testing on the #Goerli (#Ethereum Testnet) and #Mumbai (#Polygon Testnet), leveraging LayerZero Labs for seamless operation. Feature Enhancement and Protocol Optimization: • Enhanced testing procedures to bolster system resilience. • Integration of advanced features and significant code refactoring for optimization. • Incorporation of various communication methods, including LayerZero Labs, Formerly Axelar, now at @axelar, Chainlink CCIP), and wormholecrypto, into Soul Labs framework, enhancing its resilience and flexibility. This allows Soul Labs to maintain operation through alternative protocols if the primary one is temporarily paused. Website Development and Documentation: • Nearing the completion of the v1 app, with final touches being applied. • The preparation of comprehensive V1 documentation and the Yellow Paper, available upon Soul Labs's public launch, offering detailed insights into the platform's infrastructure and capabilities. USH Recognizing the critical need for stable liquidity within the ecosystem, we have positioned ourselves at the forefront of providing a solution by introducing $USH, the first native, decentralized, and over-collateralized stablecoin on #MultiversX. As market conditions have improved, we have observed a growing demand for stablecoins in the ecosystem, evidenced by the utilization rate in the Lending Protocol spiking to over 90% several times in recent months. Therefore, our goal is to tackle the current challenges faced by users by creating a robust product that will not only help them hedge against market volatility but also open up better opportunities to trade the markets and generate yield. We're happy to unveil the $USH website, now live with a sleek and intuitive user interface, designed for ease of use, which ensures that interacting with the protocol is straightforward and accessible for all. You can access it now through this link: For the technical side, we’re advancing steadily and we’ve accomplished the following milestones: Lending Protocol Facilitator: • Coded the first version to support multiple discount factors for different collaterals. • Implemented tracking of borrowing effectiveness to enable earnings forecasting for the module and support minting processes. Isolated Pools Facilitator: • Coded the first version of Isolated Pools Facilitator. • Use of $EGLD or $sEGLD as collateral, with positions stored always in $EGLD to benefit the protocol through Liquid Staking and lending interest. • Virtual account implementation for converting $sEGLD earnings into $USH, functioning like liquidation where users deposit $USH for a higher amount of $HsELGD. Staking Module • Coded the first version of the Staking Module that allows users to stake and unstake without any restrictions. We're currently focusing our efforts on the following tasks: • Implementation of HTM Booster in the discount model in the Lending Protocol. • Implementation of different depeg strategies and brainstorming further potential “soft” depeg mechanisms. • Research and implementation of rewards model for Staking Module. • Research and implementation of Boosted Vaults Facilitator. • Review and stress-test the first version of the code. Upon launch, $USH will be integrated into various protocols and AMMs across the ecosystem, further increasing both its utility and liquidity. The opportunities will be vast, enabling users to engage in a wide range of activities such as yield farming, staking, and arbitrage, all while leveraging a stable and reliable asset. Regarding the USH Airdrop campaign, it will continue until the official launch of $USH planned for late Q2-early Q3, rewarding all users who have actively participated in the initiative. Hatom V2 It is clear by now that we are driven to build a more robust, interoperable, and secure DeFi space, removing the current barriers that hinder users' capabilities to seamlessly interact with different blockchains. Through Hatom V2, we will introduce Hatom's cross-chain architecture, designed from the ground up for interoperability. This approach will elevate the protocol to unprecedented levels, enabling its deployment across various blockchains and facilitating seamless connections between them through Soul. By enhancing interoperability, Hatom V2 aims to foster a more inclusive and accessible ecosystem. This expansion will not only broaden the protocol's reach but also significantly increase its flexibility and utility, allowing users to interact with a diverse range of assets and products across different chains. We’re thrilled to share that we are currently crafting the V2 redesign of the Hatom webpage. Anticipate a jaw-dropping transformation that will truly astonish, blending cutting-edge design with an unparalleled user experience, elevating it to a dynamic, interactive hub, and making every interaction more engaging. Good things take time, but we are confident that the release of V2 website will take place in the second quarter of this year and will officially mark the start of our journey into the cross-chain landscape. We are excited about the future and we truly believe that this will mark the beginning of a new era for Hatom. It's crucial for us to develop rapidly without sacrificing the quality or the security of each product. We're strategically allocating resources to ensure smooth progress in every area of our work. As we push forward, we believe that the launch of Soul Labs will be the most important milestone due to its massive potential and disruptive technology. We would like to thank you all for the unwavering support you've shown over the past few months; it truly fuels our passion to push daily and make strides toward achieving our ambitious goals.show more

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✌️📷show more

The Chinese are flying 4 sixth-generation prototypes, but what... does that mean? While the West keeps debating wars that seem never-ending, huh, China is flying low – or rather, high! – improving their 6th generation fighter prototypes, like the J-36/J-50, with total focus on advanced integration. This gives a huge strategic advantage, with emphasis on long-range missiles and multiple guidance to dominate global scenarios. China already has about 4 6th generation prototypes and plans to reach 8, selecting the most adapted one. All this under the General Concept: Indestructible Flying Brain: 6th generation fighters go way beyond just a slightly improved stealth; they are central platforms that command a global war web via AI, drones, and varied weapons, making previous fighters obsolete in connectivity and limiting them to very local operations. This omnipresence redefines air superiority, with the fighter surviving as a resilient node in the first hours of conflicts and being able to operate with speed. Kill Web: The Global War Web: The fighter acts as the central node of a real-time network, connecting submarines, satellites, ships, drones, and troops worldwide. It allows omnipresence, receiving data from a destroyer thousands of km away and attacking as if it were right nearby, with AI assisting the pilot in analysis and target acquisition. That's why the Chinese focus on missiles with ranges of thousands of km, with multiple guidance, turning the 6th generation pilot into a tactical manager very different from today's. Being a 6th generation fighter pilot is going to demand a lot. Command of Drone Swarms (CCA/Loyal Wingman) The fighter controls 6-20 drones simultaneously for reconnaissance, jamming, or suicide attacks. It transforms the pilot (or AI) into a "maestro" of a robotic orchestra, or quarterback of Collaborative Combat Aircraft (CCAs), which carry extra weapons, expanding offensive power without exposing the main fighter. Like, a controlled symphony of destruction! Superior Multi-Spectral Stealth (Stealth++) Not limited to radar, it covers infrared, acoustic, visual, and electromagnetic. It uses advanced materials, tailless designs, and minimal thermal signature to penetrate dense A2/AD defenses, making it extremely hard to detect and essential for operations in contested environments. Extreme Range, Autonomy, and New Generation Weapons Combat radius of 1,800-2,500 km without refueling, with sustained supercruise (Mach 1.5-2.0) without afterburner, thanks to adaptive cycle engines and huge internal tanks. There's talk of including lasers, but so far, what's really there are internal hypersonic missiles and 2-3x greater armament capacity than the F-35, all while maintaining total stealth. Artificial Intelligence, Integrated Sensors, Resilience, and Open Architecture AI as co-pilot or main, processing data in real time and making tactical decisions to reduce human load; optionally manned mode: piloted, remote, or autonomous flight; virtual cockpit via helmet visor. Multifunctional sensors combine radar, electronic warfare, communications, and non-kinetic effects, with total data fusion transforming the fighter into a flying data center. Network resistant to jamming and GPS loss via quantum-resistant communications, mesh networks, and inertial/computer vision navigation. Modular architecture allows quick upgrades (90% by software), avoiding high costs like in the F-35; in "Decision Centric Warfare," AI decides in milliseconds, with the human as an optional bottleneck, including cyber warfare and active defense. In another article, I'll talk about what I think of this in terms of costs and demand and if such an investment is really worth it.show more

A single E. coli cell, placed on a dish,... will become 70 billion cells in just 12 hours. That’s exponential growth. But a new preprint shows that it's possible to engineer E. coli to grow linearly instead, where only one daughter cell continues dividing and the other stops. First, some context. In nature, there is a bacterium called Mycobacterium smegmatis (initially discovered in 1884 in ulcers scraped from syphilis patients.) M. smegmatis is weird because it divides asymmetrically. These cells grow only from one end, and all their cell wall biosynthesis machinery is located on that one end. So when the cell divides, one daughter gets this machinery and the other gets nothing. The daughter that gets the machinery can keep dividing immediately, but the other daughter has to remake all that machinery from scratch, so its growth is delayed. E. coli doesn’t grow like this. When it divides, it pinches in the middle and splits everything evenly. Enzymes, metabolites, and proteins get partitioned more or less randomly between the two daughters. For the new preprint, though, researchers engineered E. coli to behave more like M. smegmatis. Here is how they did it: First, they deleted a gene called cyaA, which encodes an enzyme (adenylate cyclase) that makes a molecule called cAMP. cAMP is SUPER IMPORTANT! It is a nutrient sensor that instructs E. coli to switch on genes that help it digest non-glucose carbon sources when glucose is scarce. Without cAMP, E. coli cells growing on alternative carbon sources will starve; they won’t know how to eat the food. Next, they added back a “split” version of the cyaA gene into the cells. In other words, they split the gene in two so that each half of the enzyme is made separately. Cells can only make cAMP, and thus eat non-glucose carbon sources, if these two halves come together. To facilitate that “coming together,” the researchers also fused the split cyaA proteins to sticky proteins that clump together, and to a fluorescent protein (to make it easy to track these molecules in the cell.) So now some interesting things start to happen if you grow E. coli on a growth medium lacking glucose. As the cell grows, its cyaA “halves” start clumping together into a giant ball. Inside the aggregate, the two enzyme halves come together and make cAMP. And when the cell gets big enough and divides, the clump of cyaA RANDOMLY goes to either daughter cell #1 or #2. The daughter that gets the aggregate (called PA+ in this paper) can keep dividing. The daughter that doesn’t (PA–) cannot. It still grows a few times — about four divisions — because it inherits some leftover cAMP from its mother. But after that, the metabolite is diluted away, and the cell stops growing. PA+ cells went through about 23 divisions on average before their aggregate decayed. And the population of cells, as a whole, grew linearly. This paper is cool because there are many applications where exponential growth is too unpredictable and, perhaps, unsafe. If you want to engineer bacteria to deliver drugs, clean up waste, or live in the gut, you don’t want them to double uncontrollably. This paper shows you can make them expand in a controlled, linear way. Alas, mutations could break this whole engineered system. A mutation that restores cyaA, for example, would give cells a new way to make cAMP. Mutations that make the aggregates split between daughters would break the asymmetry, too. But still, I really enjoy proof-of-concept engineering papers like this.show more

I have said this before and I shall say... it again: the attacks on Sam 'Dzata' George 🦁🇬🇭 are not organic. They are coordinated, laced with rage-baiting from some quarters on X. An X influencer once confessed to me that he actually enjoys dragging Sam George. To him, it’s just fun and cruise, yet he holds no real grudge. SMH. Honestly, I’m yet to meet anyone who has a genuine, solid reason to dislike him. Back when the NDC was in opposition, Sam George was one of the strongest, most fearless voices; on traditional media, social media, and right there on the grounds. His energy, bravery, and relentless fight played a huge part in the NDC’s victory. The damage he inflicted on the NPP is something they will never forget… and that, we all know, is the real source behind some of these attacks. Yet, amidst all the noise, he remains resolute and absolute in the execution of his duty. He holds himself to the highest standards. The previous government left behind such a massive mess that if we don’t fix it quickly, our country could be doomed. He fully understands the reset agenda and has thrown himself into it with total seriousness. Lest we forget, 1. He fought hard to increase our data volumes, pushing MTN’s popular bundle from 92GB to 214GB and Telecel’s from around 90GB to 250GB. Ghanaians are now getting far more value for their money. The irony? The haters now have even more data to come online and insult him. Lol. I made my first purchase in October 2025, and it actually lasted until February 2026! 2. He also put pressure on MultiChoice/DStv to improve their offerings and ease the burden on subscribers. Users have admitted that without his intervention, subscriptions could have hit GH¢600, but for the past 8 months, it has stayed at GH¢375. That means each DStv user has saved around GH¢1,800 so far. 3. To seriously tackle mobile money (MoMo) fraud, he is pushing for a proper, comprehensive SIM re-registration exercise. 4. He has reintroduced the anti-LGBTQ+ bill and remains firm, consistent, and unapologetic. To him, it is a serious aberration of the mind, and he has vowed to fight it with all his might. 5. Two weeks ago, he distributed laptops to all 130 learning centres to kick-start the ambitious One Million Coders programme. The registration website is now open and live. 6. Last Friday, he launched the National AI Strategy, a bold move that sets the tone for a major transformation of artificial intelligence not just in Ghana, but across Africa. 7. He is currently leading serious efforts to fully integrate Ghana into the PayPal ecosystem, opening new doors for digital payments and the economy. 8. He has issued a strong policy directive to telcos to fix network challenges and boost connectivity nationwide. He demanded 800 new cell sites from MTN alone this year and they have agreed. This is a massive win. In the last 8 years, the average annual rollout was around 200 sites, with some years as low as 30–50. Now in 2026, MTN alone is rolling out 800. Network coverage and speed across the country are about to improve significantly. You may not like Sam George personally, but that doesn’t change the facts: he is generous, humble, and an arduous workaholic. The truth remains one and it is gradually taking over. Today, people call him the “Prampram Messiah”. Dzata4AReason❤️show more

today was the first time i was genuinely impressed... with what AI can do i recently decided to buy a whole FPV drone setup knowing basically nothing about the hardware side of it there's a pretty steep learning curve even just to set everything up properly: radios, RF protocols, flight controllers, ESCs, firmware, batteries, goggles, betaflight configs etc as someone that spends essentially 12h a day prompting agents to build software, it's actually pretty rare that i interact with AI on something where i have zero idea what's going on under the hood, and i never really used it for debugging a bunch of physical devices that all have to talk to each other i had codex + voice mode open for basically the entire setup. told it everything i bought, sent it some pics and then just started talking to it >what order do i set all this up in >how do i change this setting on the radio >which of these cables do i use >the drone is flashing pink wat mean >can you make this thing less insane to fly in my apartment and it was surprisingly seamless it would go find the manual for whatever specific thing i was holding, tell me exactly which buttons to press, what port to plug something into, what i should see if it worked etc then when i got to configuring the actual drone i had codex running on the computer it was plugged into, so it could inspect the config, back everything up, change settings, send usb reboot signals and check what happened the insane thing about voice mode is that youre literally hands on with the hardware and just telling codex what it should do, i literally never touched a thing on the computer besides starting voice mode if something doesn't work you tell it what happened and keep going a few hours of this and i had the radio, goggles, charger, batteries, drone firmware and betaflight all set up and had actually flown the thing the part that stuck with me is that i also understood what most of it was doing by the end, every time there was a term or tech i didnt understand id just ask to explain there is something absolutely magical about having proper real time personalized assistance, being able to dump a pile of unfamiliar hardware on your desk and have something figure out exactly what you own and walk through it with you in real time you become the missing physical link pressing the buttons i think spending all day using coding agents has actually made me pretty numb to AI progress. every new model is a bit better at some benchmark or can oneshot some task that the previous one couldn't and you just kinda adjust to it this felt different mostly because i had no existing knowledge to fall back on for the first time the jarvis comparison didn't feel cringe ai for coding and general computer tasks is cool and all but this feels a lot closer to the endgame anyone should be able to just ask any question about whats going on in their life and have realtime support i wonder if more hardware products will actually start exposing some sort of MCP or interface for agents to plug into thinking for example of how elevators in china are increasingly built with interfaces that let delivery robots call them directly instead of having to physically press a button we might actually start seeing hardware design shift from being purely human-interface-first to also being agent-interface-first buttons, screens and menus exist because humans need some way to tell machines what to do. agents don't necessarily need any of that if the hardware exposes an interface directly very curious which side closes the physical world gap first: humanoid robots that can operate hardware designed for humans, or hardware adapting so agents can operate it directlyshow more

Muse Glimmer, A 30B parameter dense model swallowing a... 130,000 token context window using only 19.3 GB of VRAM (extreme efficiency). No KV cache quantization required. I just benched the new Muse Glimmer 30B (dense) on a single RTX 4090. We are pulling 3,100+ t/s prefill and 75 tokens/second decode. The throughput is violent. Meta superintelligence lab just open sourced this agentic beast, explicitly engineered to dominate 24GB consumer cards. I pulled the latest llama.cpp source on Ubuntu 22 (CUDA 13) to see if the specs were real. Fed it a 28k token prompt. Here is the exact llama.cpp God Stack and benchmarking breakdown: # 1. The Deep Context Run (No Speculative Decoding) The architecture uses a massive 16:1 GQA (Grouped Query Attention) ratio. This means the KV cache footprint is practically non existent. ./build/bin/llama-server -m Muse-Glimmer-30B-UD-Q4_K_XL.gguf -c 130000 -b 4096 -ub 4096 -ngl 99 --port 8080 Prefill: 3134.95 t/s Decode: 50.00 t/s VRAM: 19.34 GB (I hit 130k context on pristine, unquantized f16 cache and still had 4.5 GB of VRAM left over. Absolute witchcraft). # 2. The DFlash Speculative Overdrive Meta shipped this with a DFlash block diffusion drafter. Let's trade that extra VRAM for pure speed. ./build/bin/llama-server -m Muse-Glimmer-30B-UD-Q4_K_XL.gguf -md dflash-kquant.gguf --spec-type draft-dflash --spec-draft-n-max 3 -c 80000 -b 4096 -ub 4096 -ngl 99 --port 8080 Prefill: 1293.69 t/s Decode: 75.00 t/s VRAM: 23.93 GB (Maxed out on card) the dflash gguf is additional 1.6 GBs # The Architecture Insight (Muse Glimmer vs. Gemma 4 31B) If you look at my Gemma 4 31B tests from last week, getting 140k context required heavily degrading the memory with Q4 KV quantization (gemma 31b q4 can do only about 40k context with unquantized kv on a 24gb card). That "unzipping" overhead bottlenecked Gemma's MTP decode speeds down to 65 t/s. Muse Glimmer completely sidesteps this bottleneck. By using aggressive 16:1 GQA, it keeps the KV cache in native f16 format at massive context lengths. Flash Attention gets to run at maximum uncompressed speed, letting the DFlash drafter push decode safely to 75 t/s without compute lag. With a 76% on SWE Bench Verified and seamless local tool calling, this model looks promising. Unsloth's Hugging Face GGUF links, intelligence/agentic benchmark details, and inference throughput performance graphs are posted in the replies. For 24GB rig, what’s your current go to model?show more

Has been a while since I've given an update... so here's a breakdown of where Sappy is at right now and what we're focusing on going into this year. Pre-amble: With altcoins & NFTs the market is definitely not the same as it was before. I think this is obvious to everyone but I've noticed there are still japanese soldiers that are convinced old tricks and mechanics work. They don't. Liquidity is thin; people want to bid assets that feel like "real companies" not vacuous memecoins. There's still room for memecoins, social currencies, and "utility tokens" (I would say without these functions, tokens are hard to justify versus equities). I'm not part of the camp that thinks there will never be hyperspeculation in crypto again, because there will be; we all love ponzis and PvPing each other onchain. Just not with solved games -- people need something new and fresh. So the overarching plan is to continue building for users, sustainable revenues that aren't tied to directly to crypto, and doubling down on the areas that we've already found PMF / Brand Market Fit. Then leaning into crypto during cyclical periods where liquidity is sloshing around at an accelerated rate. Where we've found early PMF / what we're leaning into: Roblox: we're going to continue to go hard and accelerate here. It's our main objective to ship more seal/brainrot focused games across most genres to cast as wide of a net as we can for the brand, and to also iterate and see what works and stays sticky. Our initial incursion into Roblox was very successful peaking at 2M+ MAU and still sustaining a large portion of that player base... for all of its success, that was a relatively amateur first attempt; we've been setting up better AI pipelines for Roblox development that makes it reasonable to ship many more games and 10x those player counts in totality. It's my belief that Roblox is the sandbox whose audience will be the most valuable on the internet once they are grown up. That intense feeling you get when you see a TikTok referencing an old game you enjoyed on the PS2 or the Gamecube, or when you see a Pokemon card is the exact same feeling the youth of today will get when reminiscing on the things they enjoyed engaging with when they were younger. Fortnite and Roblox are functional equivalents to the old school consoles and exactly where that is taking place. Which is why as much as I care about scaling revenues through Roblox, the long term brand equity gained purely through being popular on the platform is totally invaluable. It also can heavily convert to merchandise sales today if all touchpoints for the brand are dialed in (which is why brands get overcharged so much by Roblox dev shops for the same ROI that only cost us a few thousand $). We have the playbook, it's just about iterating new concepts and then aggressively scaling. Brand Expansion & Merchandising: I've started to create a content pipeline that is easily repeatable, cost efficient (costs next to nothing through either AI or smart reusable concepts), while still being very tasteful and meeting our quality standards for the brand. We are mostly focusing here on reaching people where they're at through nostalgic/emotional content, or just being visually stimulating through carefully curated aesthetics. Content that isn't superficial and touches people in a memorable way. I've attached some examples to the post so you can see what I mean rather than just read it. I don't think it's long until larger brands start doing this at scale, but it's always good to be ahead of the curve and most importantly winning on taste -- knowing what will resonate with people and what won't has always been our edge. The purpose for these accounts is not only to rack up attention but also to begin converting those into sales of both of physicals (plushies & gacha collectibles) and digital avenues like our games, and any other apps we produce. Because they're offshoot accounts it's also a lot easier to be aggressive/experimental with said conversion strategies. Sappy Studio: I'm wrapping everything like Omnia, and everything else into this category because they're all tangentially related. Beginning with Omnia, our current focus is gearing up for Season 0 which involves players competing in the ranked ladder for a prize pool that has rewards through Monad Momentum as well as a player-funded prize pool. This season will be fairly simple with us mostly logging retention, deck building habits, as well as qualitatively observing how aggressively players push the combat system. Deeper monetization wont exist yet outside of the player buy-in (to be eligible for P2E rewards). Beyond that our overarching principle this year is to focus heavily on risk-to-earn mechanics where a portion of that excess value is circular i.e. revenues flow back to prize pools or other parts of the economy, treating the game almost like a protocol where the objective is to amass TVL or player liquidity. Social is also a big focus, and that means implementing the Open World hub which from an infrastructure perspective has already been built out and tested by all of you previously. Right now we are scaffolding the environment in 3D and working through how that hub should look and feel, so players are excited to hang out & idle together while they're queuing. For sappydotlol, what I'm about to say is still early days from a design perspective so a lot can change, but I'm pushing the site in the direction of being a virtual game console. An intersection between Nintendo & Myspace where users can play, trade, and socially interact in a way that's deeply personalised; a breathe of fresh air from the hostility of the current internet. If you go back to my thesis on Roblox above and the game console references, you can kind of see how this will all sequentially tie together. In essence, the strategy is to acquire a critical mass of players through traditional platforms like Roblox, and use that attention and trust to provide an onboarding funnel for web2 users into our own sandbox filled with a mixture of our own browser-based experiences as well as an aggregation of others. The aim is to make the platform a breath of fresh air & bunker from the enshittified platforms like TikTok/IG/X where users are actually served in ways that delight rather than agitate, and where self-expression is incentivised. Closing: As always everything here is subject to change but I've never felt more conviction in our direction until now; I know exactly what we need to do and how, with everything aligning with our team's strengths. Very excited and grinding through things to the point where I'm getting headaches and can't sleep from being hyperfocused for long periods of time lol. There probably has never been a better time to join the ecosystem from a price to fuck around and find out perspective.show more