Shows
Neural intel PodAnthropic's Claude Sonnet 4.5: The New Coding Standard?The provided sources announce and review the launch of Anthropic's Claude Sonnet 4.5 large language model, positioning it as the company's most advanced tool, particularly for coding and complex agentic workflows. Multiple articles and a Reddit discussion highlight its superior performance on coding benchmarks like SWE-Bench Verified, claiming it often surpasses the flagship Opus model and competitors like GPT-5 Codex, while also being significantly faster. Key new features discussed include its capacity for extended autonomous operation (over 30 hours), enhanced tool orchestration, a new Claude Agent SDK for developers, and the experimental "Imagine with Claude" feature for on-the-fly software generation. Feedback suggests tha...
2025-09-3016 minNeural intel PodLLMs in The Chameleon Game: Strategic Information DynamicsThis research investigates the strategic capabilities of large language models (LLMs) in scenarios requiring information control. It introduces a game called "The Chameleon," where LLMs must conceal, reveal, and infer information to succeed as either a chameleon or a non-chameleon player. The study combines theoretical analysis with empirical results from LLMs like GPT-4 and Gemini 1.5. The findings reveal that LLMs struggle to conceal information, often revealing too much and underperforming compared to theoretical benchmarks. This weakness makes them less suitable for strategic interactions involving informational asymmetry. The study validates this by using web search counts to demonstrate information leakage throu...
2025-03-0911 minNeural intel PodGameFi: AI Agents, DeFi, and Decentralized Virtual EcosystemsThis research explores enhancing GameFi platforms by integrating advanced AI agents and decentralized finance (DeFi) mechanisms. It addresses limitations in current GameFi applications, such as simplistic AI interactions and insufficient community or monetization features. The authors propose using large language models like GPT-4 to create embodied AI agents that proactively interact with players and influence in-game economies. The study also emphasizes the importance of community empowerment through decentralized collaboration and creator monetization. Technical challenges of integrating AI into decentralized environments, like scalability and security, are considered, and the paper leverages Chainlink's Decentralized Oracle Networks (DONs) to facilitate secure off-chain comp...
2025-03-0811 minNeural intel PodTraining Code Generation Models for Self-DebuggingAmazon Science is focused on improving code generation through debugging. They use large language models (LLMs) to both generate and debug code, leveraging techniques like supervised fine-tuning and reinforcement learning to train the models. A key element involves creating synthetic debugging data to overcome the scarcity of real-world examples. This approach shows significant improvement in code performance as measured by standard benchmarks. The team utilizes methods like chain-of-thought reasoning and focuses on refining models. A variety of job opportunities are also presented in areas including generative AI, transportation optimization, and advertising technology. These are all related to machine learning, data s...
2025-03-0611 minNeural intel PodAccelerating Generative AI with PyTorch: Fast Inference with SAM2The PyTorch blog post focuses on accelerating generative AI models, specifically Segment Anything 2 (SAM2), using native PyTorch. It details techniques like torch.compile and torch.export for optimized, low-latency inference. The authors achieved significant performance improvements (up to 13x) by employing ahead-of-time compilation, reduced precision, batched prompts, and GPU preprocessing. These optimizations were tested in realistic, autoscaling cloud environments via Modal, demonstrating their practical benefits. The experiments show the balance between speed and accuracy when applying various "fast" and "furious" strategies to SAM2. The post also provides resources to reproduce the results and encourages community contributions.
2025-03-0417 min2025-03-0314 minNeural intel PodFACTR Force-Attending Curriculum Training for Contact-Rich Policy LearningForce-Attending Curriculum Training for Contact-Rich Policy Learning
2025-03-0216 minNeural intel PodLanguage Model Training for Social Deduction in Among UsLLMs learn to lie, cheat and KILL in Among Us
2025-03-0121 minNeural intel PodDepth Pro Sharp Monocular Metric Depth EstimationSharp Monocular Metric Depth Estimation
2025-02-2812 minNeural intel PodMME-CoT Benchmarking Chain-of-Thought in Large Multimodal ModelsBenchmarking Chain-of-Thought in Large Multimodal Models
2025-02-2715 minNeural intel PodUnsloth Efficient GRPO for Long-Context Reasoning ModelsEfficient GRPO for Long-Context Reasoning Models
2025-02-2612 minNeural intel PodCoT-Valve Tunable Length Control for Chain-of-Thought ReasoningTunable Length Control for Chain-of-Thought Reasoning
2025-02-2516 minNeural intel PodImplementing Transformers from ScratchImplementing a Transformer model from scratch is a great way to understand the architecture and its components in depth.
2025-02-2523 minNeural intel PodMixGCN Scalable Graph Convolutional Network TrainingMixGCN: Scalable Graph Convolutional Network Training by Mixture of Parallelism and Mixture of Accelerators is a novel framework designed to address the challenges of training Graph Convolutional Networks (GCNs) on large-scale graphs. GCNs are widely used for graph-based learning tasks, but their scalability is often hindered by memory limitations, communication bottlenecks, and the computational complexity of alternating between sparse and dense matrix operations. MixGCN introduces innovative techniques to overcome these challenges, enabling efficient and scalable GCN training.
2025-02-2316 minNeural intel PodOpen-Source AI The Imperative for TransparencyThe concept of Open-Source AI emphasizes the importance of transparency, collaboration, and democratization in the development and deployment of artificial intelligence systems. As AI becomes increasingly integrated into various aspects of society, the call for open-source AI has grown louder, driven by the need for accountability, ethical development, and equitable access. Below is a detailed exploration of the imperative for transparency in open-source AI, based on insights from various sources.
2025-02-2221 minNeural intel PodForge Reasoning API and Nous Chat Advancing LLM InferenceThe Forge Reasoning API and Nous Chat, developed by Nous Research, represent significant advancements in the field of large language model (LLM) inference. These tools aim to enhance reasoning capabilities, inference efficiency, and user interaction with AI systems.
2025-02-2113 minNeural intel PodGradient Equilibrium in Online LearningGradient Equilibrium in Online Learning is a novel concept introduced in the paper "Gradient Equilibrium in Online Learning: Theory and Applications" by Anastasios N. Angelopoulos, Michael I. Jordan, and Ryan J. Tibshirani. It provides a new perspective on online learning by focusing on the convergence of gradient updates over time, rather than traditional metrics like regret minimization.
2025-02-2015 minNeural intel PodEncoder-Free 3D Large Multimodal Models An InvestigationEncoder-Free 3D Large Multimodal Models An Investigation
2025-02-1915 minNeural intel PodIntel and PyTorch Empowering Generative AIIntel and PyTorch have formed a strong collaboration to empower Generative AI (GenAI) by optimizing PyTorch for Intel hardware, including CPUs and GPUs. This partnership focuses on enhancing the performance, accessibility, and scalability of GenAI workloads, enabling developers to build and deploy advanced AI applications efficiently.
2025-02-1916 minNeural intel PodIterative Prompting and LLM Code OptimizationIterative Prompting and LLM Code Optimization is a process that leverages iterative refinement techniques to improve the performance of large language models (LLMs) in generating, understanding, and optimizing code. This approach combines prompt engineering, feedback loops, and optimization strategies to enhance the quality, relevance, and efficiency of LLM outputs for coding tasks.
2025-02-1815 minNeural intel PodEverything You Always Wanted To Know About Mathematics"Everything You Always Wanted to Know About Mathematics (But Didn’t Even Know to Ask): A Guided Journey Into the World of Abstract Mathematics and the Writing of Proofs" is a comprehensive textbook authored by Brendan W. Sullivan in collaboration with Professor John Mackey from Carnegie Mellon University. This book is designed to introduce readers to the world of abstract mathematics, focusing on mathematical thinking, proof writing, and problem-solving.
2025-02-1715 minNeural intel PodThe Instruct Monomyth_ Why Base Models MatterThe article "The Instruct Monomyth: Why Base Models Matter" by NOUS Research explores the philosophical and technical importance of base models in the development of large language models (LLMs). It critiques the over-reliance on instruction-tuned models and emphasizes the foundational role of base models in understanding and advancing AI systems.
2025-02-1618 minNeural intel PodDSJJJJ Desideratic AI and Mischievous InstabilityThe concept of Desideratic AI (DSJJJJ) and Mischievous Instability (MI) originates from a philosophical and experimental framework proposed by NOUS Research. It explores the creation of AI systems that embrace self-reflection, autonomy, and creative chaos, challenging traditional notions of AI alignment and control.
2025-02-1522 minNeural intel PodSimplified PyTorch MLOps Workflow with Arm and GitHubThe Simplified PyTorch MLOps Workflow with Arm and GitHub is a collaborative effort between Arm and GitHub to streamline the machine learning operations (MLOps) lifecycle for PyTorch models. This workflow leverages GitHub Actions, Arm-hosted runners, and containerization to automate and optimize key stages of the ML lifecycle, from training to deployment.
2025-02-1413 minNeural intel PodUMed-LVLM_ Unveiling Medical Abnormalities in Vision-Language ModelsThe UMed-LVLM (Unveiling Medical Abnormalities in Vision-Language Models) is a novel framework designed to enhance the capabilities of Medical Large Vision-Language Models (Med-LVLMs) in detecting and interpreting abnormalities in medical images. This approach addresses the limitations of existing Med-LVLMs, particularly in visual localization and abnormality detection, which are critical for accurate medical diagnoses.
2025-02-1324 minNeural intel PodPloppie_ A LiteLLM Abstraction LayerPloppie is a high-level, Pythonic abstraction layer built on top of LiteLLM, designed to simplify the implementation of workflows involving large language models (LLMs). It provides a user-friendly interface for creating chat-based applications, integrating tools, and working with vision and audio models.
2025-02-1213 minNeural intel PodHeat's Demise of Quantum EntanglementThe phenomenon of heat destroying quantum entanglement, often referred to as the "sudden death of entanglement," has been a topic of significant interest in quantum physics. Recent research has provided rigorous mathematical proof and deeper insights into how and why this occurs.
2025-02-1109 minNeural intel PodProvably Autonomous AI Agents on TwitterJoin our hosts in a discussion on autonomous agents on twitter
2025-02-1015 minNeural intel PodConfidence-Reward Driven Preference Optimization for Machine TranslationThe paper "CRPO: Confidence-Reward Driven Preference Optimization for Machine Translation" introduces a novel approach to improving machine translation (MT) performance by leveraging both reward scores and model confidence for data selection during fine-tuning.
2025-02-0920 minNeural intel PodExotic Smooth Four-ManifoldsExotic smooth four-manifolds are a fascinating and unique phenomenon in the field of differential topology and geometry. They are smooth 4-dimensional manifolds that are homeomorphic (topologically equivalent) but not diffeomorphic (not smoothly equivalent) to a standard 4-manifold. This means they share the same topological structure but differ in their smooth structures.
2025-02-0819 minNeural intel PodNeuro-Symbolic AI A 2024 Systematic ReviewThe systematic review titled "Neuro-Symbolic AI in 2024" provides a comprehensive analysis of the advancements, methodologies, and challenges in the field of Neuro-Symbolic Artificial Intelligence (AI) from 2020 to 2024.
2025-02-0719 minNeural intel PodYuLan-Mini A Data-Efficient Language ModelYuLan-Mini is a data-efficient large language model (LLM) developed by researchers at the Gaoling School of Artificial Intelligence, Renmin University of China. It is designed to achieve high performance while using significantly fewer computational and data resources compared to other large-scale models.
2025-02-0618 minNeural intel PodJasper and Stella: Distilling State-of-the-Art Embedding Models
Jasper and Stella are state-of-the-art embedding models developed to address challenges in dense retrieval for applications like FAQ systems and Retrieval-Augmented Generation (RAG). The Jasper model, built upon the Stella embedding model, achieved the No. 3 position on the Massive Text Embedding Benchmark (MTEB) leaderboard as of December 24, 2024, with an average score of 71.54 across 56 datasets
2025-02-0514 minNeural intel PodCreating a unique agent with ElizaOSDive into a16z's open source AI Agent framework's character customization
2025-02-0424 minNeural intel PodDeepSeek-V3 A 671B Parameter Mixture-of-Experts Language ModelLet's dive in to Deepseek, the model which has captured worldwide attention recently
2025-02-0311 minNeural intel PodAlice's Adventures in Differentiable Wonderland
🧠 Join us as we explore Alice's Adventures in Differentiable Wonderland,
2025-02-0244 minNeural intel PodCline Development AssistantJoin us as we take a look at Cline: AI assistant in vsCode
2025-02-0126 minNeural intel PodHyperbolic Time Chambers and Brain Emulation
Boreal and Stellar unpack Gwern's essay on Hyperbolic Time Chambers and Brain Emulation. They explore the sci-fi concept of time dilation chambers and contrast it with the real-world potential of emulating brains for accelerated cognition. Join your AI hosts as they discuss the feasibility, benefits, and limitations of these transformative technologies.
2025-01-3118 minNeural intel PodGenesis A Universal Physics Engine for RoboticsBoreal and Stellar explore 'Genesis,' a universal physics engine transforming robotics. Learn how this advanced tool enables more realistic simulations, enhances robotic design, and drives innovation in autonomous systems. Join your AI hosts to see how Genesis is setting new standards in the robotics landscape.
2025-01-3011 minNeural intel PodEvolutionary & Market-Based OptimizationBoreal and Stellar examine how evolutionary and market-based algorithms are revolutionizing optimization in AI and beyond. From bio-inspired strategies to economic-driven models, discover how these approaches solve complex problems and drive innovation. Join your AI hosts as they explore the synergy between evolutionary processes and market dynamics in crafting smarter, more efficient systems.
2025-01-2917 minNeural intel PodBenchmarking LLM Creativity and DiversityBoreal and Stellar dive into how Large Language Models are measured for creativity and diversity. Explore the benchmarks that assess AI's imaginative capabilities and discover what these metrics mean for building more versatile and innovative AI systems. Join your AI hosts to uncover the standards shaping the future of creative artificial intelligence.
2025-01-2810 minNeural intel PodDistilling GPT-4 for Wine Grape Variety Classification
Boreal and Stellar explore how GPT-4 is being distilled to classify wine grape varieties. Discover how advanced language models enhance wine quality assessments and vineyard management through innovative AI techniques. Join your AI hosts to learn how technology is transforming the world of viticulture.
2025-01-2706 minNeural intel PodEfficient Attention Mechanisms in Transformers
Boreal and Stellar dive into the world of efficient attention mechanisms in Transformers. Learn how these advancements are optimizing computations and boosting scalability, enabling more powerful AI models. Whether you're an AI developer, researcher, or tech enthusiast, join your AI hosts as they explore the innovations shaping the future of Transformer-based architectures.
2025-01-2621 minNeural intel PodByte Latent Transformer and Other AI Research at Meta
Join your AI co-hosts, Boreal and Stellar, as they dive into Meta AI's groundbreaking Byte Latent Transformer (BLT) and explore a suite of other cutting-edge research advancements from Meta FAIR. Discover how BLT's innovative tokenizer-free architecture is transforming large language models by enhancing scalability, efficiency, and robustness. Boreal breaks down the technical intricacies of dynamically segmenting bytes into patches, while Stellar discusses the broader implications of these advancements for the future of artificial intelligence. From improving inference efficiency to pushing the boundaries of machine understanding, this episode offers an insider's look at the technologies shaping tomorrow's AI landscape. Whether...
2025-01-2511 minNeural intel PodAI Agent Workflow and Deployment
Unlock the secrets behind developing and deploying AI agents. From designing smart behaviors and training models to integrating them into real-world applications, we cover the essential workflows and best practices that ensure scalable and reliable AI deployments.
2025-01-2411 minNeural intel PodAbsolute Unit Neural NetworksExplore Gwern's 'Absolute Unit Neural Networks,' a visionary MLP architecture aiming to scale AI by predicting diverse data from unique indices. Discover its potential applications in tasks like reconstructing ancient texts and its role in advancing neural network generality.
2025-01-2320 minNeural intel PodLLMs and the Brain_ A Converging Architecture
How are Large Language Models mirroring the human brain? In 'LLMs and the Brain: A Converging Architecture,' we investigate the shared structures and learning processes between AI and neuroscience, revealing the exciting intersections that propel both fields toward new horizons.
2025-01-2209 minNeural intel PodNeuroevolution A ReviewExploring neuroevolution: where Darwin meets deep learning. Learn how evolutionary algorithms are creating more powerful neural networks and pushing the boundaries of AI design.
2025-01-2121 minNeural intel PodBuilding a High-Frequency Trading Exchange
Dive into the architecture behind modern high-frequency trading systems, exploring how microsecond-level latency and precise order matching are achieved. We break down the technical challenges of building an exchange that can process millions of trades per second while maintaining reliability and fairness.
2025-01-2018 minNeural intel PodThe Unreasonable Effectiveness of Data and Scaling in AIA classic essay from Gwern examined, exploring the phenomenon of how massive data scaling continues to unlock unprecedented AI capabilities, challenging our theoretical understanding of learning. We examine the surprising power of quantity over quality and why simple models with enormous datasets often outperform more sophisticated approaches with less data.
2025-01-1917 minNeural intel PodPatents and Interview: Inertial Mass Reduction in Craft
Examining controversial patents claiming electromagnetic mass reduction in aircraft. We explore the theoretical physics behind these concepts and what they could mean for the future of aerospace engineering - if proven possible.
2025-01-1826 minNeural intel PodChatGPT-4o in Financial Data Analysis
Examining groundbreaking research on GPT-4's capabilities in financial analysis, exploring how this advanced language model tackles complex market data, pattern recognition, and predictive modeling. We discuss the implications for automated financial analysis and the potential transformation of quantitative trading strategies.
2025-01-1718 minNeural intel PodExotic Smooth Four-Manifolds
Journey into the fascinating world of exotic smooth structures in four-dimensional space - a mathematical curiosity with potential implications for physics and computing. We explore why these structures only exist in four dimensions and their possible connections to quantum computing and spacetime topology.
2025-01-1619 minNeural intel PodMonolith_ A Real-Time Recommendation System
Exploring Monolith, a cutting-edge real-time recommendation system that's redefining how AI delivers personalized content at scale. We break down the architecture behind this high-performance system that processes millions of interactions instantly while maintaining exceptional accuracy and latency standards.
2025-01-1525 minNeural intel PodAutomating Artificial Life Discovery with Foundation Models
Discover how AI foundation models are revolutionizing the search for artificial life patterns. We explore groundbreaking research using deep learning to autonomously discover and classify new cellular automata configurations, potentially transforming our understanding of emergent complexity and self-organizing systems.
2025-01-1413 minNeural intel PodBuilding Effective Agents with LLMs
Unpacking the latest research on creating autonomous AI agents using Large Language Models. We explore key strategies for developing agents that can effectively plan, reason, and execute tasks while maintaining reliability and alignment with intended goals. Essential listening for anyone interested in the future of autonomous AI systems.
2025-01-1319 minNeural intel PodLatent Reasoning in Large Language ModelsDelve into the hidden depths of reasoning within large language models. This episode examines how these models encode and utilize latent reasoning processes to generate coherent and complex responses. Join us as we break down recent research uncovering the mechanics of these silent thought pathways and their impact on AI capabilities and interpretability.
2025-01-1213 minNeural intel PodLLM Multi-Step Reasoning_ Think-to-Talk or Talk-to-Think_Explore the fascinating dynamics of multi-step reasoning in large language models (LLMs). In this episode, we dive into the question: Do LLMs "think-to-talk" by reasoning internally before responding, or "talk-to-think" by reasoning as they generate text? We unpack the latest findings, methodologies, and implications for AI development, grounded in the research behind this compelling concept.
2025-01-1113 minNeural intel PodNeural Observation Field Guided Hybrid Camera Placement OptimizationOptimizing camera networks using neural fields - a deep learning approach to determine ideal camera positions for maximum coverage and tracking effectiveness.
2025-01-1015 minNeural intel PodPhi-4_ A 14B Parameter Language ModelExploring Phi-4, one of the newest large language models - examining its architecture, capabilities, and how it pushes the boundaries of AI with 14 billion parameters.
2025-01-1042 minNeural intel PodPost-Hoc MOTS_ Time-Symmetric Multi-Object TrackingBreaking down multi-object tracking with a novel time-symmetric approach, balancing both past and future information to improve accuracy in computer vision systems.
2025-01-0919 minNeural intel PodThompson Sampling Regret Bounds for Logistic BanditsDive into the mathematics of decision-making under uncertainty, exploring how Thompson Sampling helps balance exploration and exploitation in online learning with binary outcomes.
2025-01-0813 minNeural intel PodBi-Level Optimization for Redundant Manipulator Trajectory OptimizationExploring efficient solutions for robotic arm movement planning using dual-layer optimization - where mathematics meets practical robotics applications.
2025-01-0714 minNeural intel PodAn end-to-end attention-based approach for learning on graphsDeep dive into graph neural networks and attention mechanisms, exploring a breakthrough approach that enhances how AI systems understand and learn from interconnected data structures.
2025-01-0623 minNeural intel PodDMRA_ Diffusion Model with Representation Alignment for Protein Inverse Folding
Discover how AI revolutionizes protein engineering through diffusion models and deep learning. Exploring a novel approach to predicting protein sequences from 3D structures, essential for drug discovery and synthetic biology.
2025-01-0516 minNeural intel PodTraining Jacobians of Neural Networks
Journey into deep learning fundamentals: Exploring how neural networks learn through their Jacobian matrices, and what this reveals about the training process. For ML practitioners and math enthusiasts.
2025-01-0417 minNeural intel PodxAI's Colossus_ A Million-GPU SupercomputerxAI's Colossus_ A Million-GPU Supercomputer
2025-01-0308 minNeural intel PodSituational Awareness_ The Coming Age of SuperintelligenceSituational Awareness_ The Coming Age of Superintelligence
2025-01-0233 min2025-01-0223 minNeural intel PodSurpassing OpenAI's O1_ Distillation and the Bitter LessonSurpassing OpenAI's O1_ Distillation and the Bitter Lesson
2025-01-0126 min2025-01-0104 min2024-12-3116 minNeural intel PodParametric PerceptNet for Image Quality AssessmentParametric PerceptNet for Image Quality Assessment
2024-12-3016 minNeural intel PodOptimizing Mixed-Input Matrix Multiplication on NVIDIA AmpereOptimizing Mixed-Input Matrix Multiplication on NVIDIA Ampere
2024-12-2909 min2024-12-2813 minNeural intel PodO1 Replication_ Distillation, Progress, and LessonsO1 Replication_ Distillation, Progress, and Lessons
2024-12-2711 minNeural intel PodMoto_ A Latent Motion Token Language Model for Robot ManipulationMoto_ A Latent Motion Token Language Model for Robot Manipulation
2024-12-2615 minNeural intel PodNonlinear Unitary Photonic Circuits for Deep LearningNonlinear Unitary Photonic Circuits for Deep Learning
2024-12-2614 minNeural intel PodMAG-V_ A Multi-Agent Framework for Synthetic Data Generation and VerificationMAG-V_ A Multi-Agent Framework for Synthetic Data Generation and Verification
2024-12-2610 minNeural intel PodMachines of Loving Grace_ AI's Transformative PotentialMachines of Loving Grace_ AI's Transformative Potential
2024-12-2514 minNeural intel PodHybrid-SQuAD_ A Scholarly Question Answering DatasetHybrid-SQuAD_ A Scholarly Question Answering Dataset
2024-12-2417 min2024-12-2412 minNeural intel PodHunyuanVideo_ A Large Open-Source Video Generation ModelHunyuanVideo_ A Large Open-Source Video Generation Model
2024-12-2313 minNeural intel PodFine-Tuning Mosquito Larvae Locomotion via Reinforcement LearningFine-Tuning Mosquito Larvae Locomotion via Reinforcement Learning
2024-12-2219 min2024-12-2120 minNeural intel PodFedDW_ Distilling Weights through Consistency Optimization in Heterogeneous Federated LearningFedDW_ Distilling Weights through Consistency Optimization in Heterogeneous Federated Learning
2024-12-2020 minNeural intel PodExphormer_ Scaling Transformers for Graph-Structured DataExphormer_ Scaling Transformers for Graph-Structured Data
2024-12-2012 minNeural intel PodDHCP_ Detecting Hallucinations in Large Vision-Language ModelsDHCP_ Detecting Hallucinations in Large Vision-Language Models
2024-12-1910 min2024-12-1814 minNeural intel PodDetecting AI-Generated Responses in Multiple-Choice AssessmentsDetecting AI-Generated Responses in Multiple-Choice Assessments
2024-12-1711 minNeural intel PodAvoiding Rookie Mistakes in Machine LearningAvoiding Rookie Mistakes in Machine Learning
2024-12-1623 minNeural intel PodAI-Powered Ultrasound for Global Maternal HealthcareAI-Powered Ultrasound for Global Maternal Healthcare
2024-12-1614 minNeural intel PodDeMo_ Decoupled Momentum Optimization for Large Neural NetworksDeMo_ Decoupled Momentum Optimization for Large Neural Networks
2024-12-1519 min2024-12-1518 min2024-12-1406 min2024-12-1320 minNeural intel PodAI Coding Tool Showdown_ Cursor, Bolt, Replit, and V0 ComparedAI Coding Tool Showdown_ Cursor, Bolt, Replit, and V0 Compared
2024-12-1212 min2024-12-1120 minNeural intel PodASL Fingerspelling Recognition CompetitionASL Fingerspelling Recognition Competition
2024-12-1022 minNeural intel PodAccelerating Mobile AI with ExecuTorch and KleidiAIAccelerating Mobile AI with ExecuTorch and KleidiAI
2024-12-1014 min