Nota AI

  Jaehoon Lee Technical Content Manager, Nota AI   When enterprises adopt AI, the most common bottleneck is not model development. It is the deployment stage: getting a finished model to run reliably on the actual target device.T...

High signal Matched: inference, throughput, benchmark, performance, latency, cost, gpu, model, evaluation, quantization, int8, benchmarks, leaderboard

  Jaehoon Lee Technical Content Manager, Nota AI   NetsPresso® now embraces AI agents. An easy-to-use interface sits on top of the validated pipeline that handles everything from model compression to device deployment.When a user...

High signal Matched: inference, endpoint, kernel, verification, moe, benchmark, latency, cost, gpu, release, model, evaluation, quantization, quantized, int4, evaluate, benchmarks, swe-bench, mmlu, agent, agents, api

  Hancheol Park, Ph. D.AI Research Engineer, NetsPresso Tech, Nota AI Geonmin Kim, Ph. D.AI Research Engineer, NetsPresso Tech, Nota AI Geonho LeeEdge AI Engineer Intern, NetsPresso Tech, Nota AI Jaehoon Lee Technical Content Manager,...

High signal Matched: generation, moe, performance, model, weights, paper, research, evaluation, korea, korean, seoul, naver, training, fine-tuning, quantization, agent, agents, agentic

  Jaehoon Lee Technical Content Manager, Nota AI   Series Notice: NetsPresso® Technical Blog, Part 2In Part 1, we walked through a scenario of deploying Llama 3.2 1B on an edge device to illustrate the NetsPresso® workflow. The f...

High signal Matched: inference, kernel, cuda, matmul, benchmark, performance, latency, cost, npu, model, weights, paper, research, evaluation, furiosa, training, quantization, int8, int4, awq, gptq, sdk, open-source

  Jaehoon Lee Technical Content Manager, Nota AI   AI Model Optimization: Why Models Won't Run on HardwareThe Chip Is Ready, but the Model Won't DeployIf you have ever tried deploying an AI model onto your own chip, the following...

High signal Matched: inference, multi-gpu, kv cache, verification, performance, latency, gpu, model, research, evaluation, quantization, quantized, awq, gptq, evaluate

  Jaehoon Lee Technical Content Manager, Nota AI   In March, a single official announcement from Google Research rocked trillions of won in the market capitalization of U.S. infrastructure and semiconductor stocks. The catalyst:...

High signal Matched: inference, serving, generation, throughput, kv cache, benchmark, performance, cost, b200, blackwell, introducing, model, fp8, research, training, fine-tuning, quantization, quantized, agent, agentic, frontier model

  Jaehoon Lee Technical Content Manager, Nota AI   GTC has evolved far beyond a technology conference, drawing attention from global economies and financial markets alike. This year, CEO Jensen Huang took the stage in his tradema...

High signal Matched: inference, prefill, generation, throughput, cuda, kv cache, performance, latency, cost, gpu, npu, launch, model, research, cloud, training, long-context, context window, agent, agents, agentic, open-source

  NP Product Team, Nota AI   The role of Edge AI is rapidly expanding.Offline voice assistants now carry on conversations in our daily lives, vehicles infer routes in real time, and smartphones generate images without a network c...

High signal Matched: inference, kv cache, moe, benchmark, performance, latency, cost, model, research, seoul, quantization

  Hancheol Park, Ph. D. AI Research Engineer, Nota AI Tairen PiaoAI Research Engineer, Nota AI Tae-Ho KimCTO & Co-Founder, Nota AI ✔️ Resource : The official quantized model of Solar-Open-100B, which passed the first round of Sout...

High signal Matched: inference, serving, prefill, generation, throughput, moe, router, benchmark, performance, latency, ttft, tpot, blackwell, release, model, weights, open model, research, evaluation, korea, korean, upstage, training, post-training, quantization, quantized, int4, evaluate, benchmarks, mmlu, long-context

  Jewon Lee | Wooksu Shin | Seungmin Yang | Ki-Ung Song | Donguk Lim | Jaeyeon Kim | Tae-Ho Kim |  Bo-Kyeong KimEdgeFM Team, Nota AI ✔️ Resources for more information: GitHub, ArXiv, Project Page, Demo.✔️ Accepted at ICLR 2026. &...

High signal Matched: inference, generation, verification, benchmark, performance, latency, cost, model, arxiv, evaluation, training, post-training, benchmarks

  Seungmin YangEdgeFM Lead, Nota AI On this page ▾ SummaryWith the introduction of NVFP4—a new 4-bit floating point data type in NVIDIA’s Blackwell GPU architecture—LLM inference achieves markedly improved efficiency.Blackwell’s NVFP4...

High signal Matched: inference, serving, decoding, prefill, generation, token generation, throughput, kernel, gemm, cutlass, distributed, benchmark, performance, latency, ttft, tpot, tokens/sec, cost, gpu, blackwell, launch, model, weights, fp8, research, training, post-training, quantization, quantized, awq, benchmarks, mmlu, retrieval

  Marcel Simon, Ph. D.ML Researcher, Nota AI GmbH Tae-Ho KimCTO & Co-Founder, Nota AI Seul-Ki Yeom, Ph. D.Research Lead, Nota AI GmbH   SummaryProposes a simple next-frame prediction task using unlabeled video to enhance sing...

High signal Matched: inference, performance, model, paper, research, training, fine-tuning, benchmarks

  Jaewoo SongSoftware Engineer, Nota AI   SummaryThis study proposes an AI model preprocessing method for improved quantization accuracies on edge AI devices which do not support advanced quantization methods due to their limitat...

High signal Matched: performance, model, weights, research, quantization, int8, int4

  Jewon Lee | Ki-Ung Song | Seungmin Yang | Donguk Lim | Jaeyeon Kim | Wooksu Shin | Bo-Kyeong Kim | Tae-Ho KimEdgeFM Team, Nota AI Yong Jae Lee, Ph. D.Associate Professor, UW-Madison   SummaryOur method, Trimmed-Llama, reduces t...

High signal Matched: inference, generation, kv cache, benchmark, performance, latency, model, weights, research, training, benchmarks, open-source

  Seul-Ki Yeom, Ph. D. Research Lead, Nota AI GmbH Tae-Ho KimCTO & Co-Founder, Nota AI   SummaryDelivers real-time AI performance on edge devices such as smartphones, IoT devices, and embedded systems.Introduces a novel "Reus...

High signal Matched: inference, kernel, benchmark, performance, cost, introducing, model, paper, research, benchmarks

  Hancheol Park, Ph. D.AI Research Engineer, Nota AI Geonmin Kim, Ph. D.AI Research Engineer, Nota AI Jaeyeon KimAI Research Engineer, Nota AI   SummaryIn this study, we propose a method for determining whether given multilingual...

High signal Matched: generation, performance, model, paper, research, training, fine-tuning

  Hancheol Park, Ph. D.AI Research Engineer, Nota AI Geonmin Kim, Ph. D.AI Research Engineer, Nota AI   SummaryIn this study, we present a method for detecting ambiguous samples in natural language understanding (NLU) tasks using...

High signal Matched: performance, paper, research, evaluation, training, evaluate

  Jaeyeon KimResearch Engineer, Nota AI Geonmin KimResearch Engineer, Nota AI Hancheol ParkTeam Lead of NetsPresso Application, Nota AI   IntroductionRecent large language models (LLMs) have demonstrated unprecedented performance...

High signal Matched: decoding, benchmark, performance, latency, tokens/sec, model, arxiv, research, technical report, evaluation, cloud, training, lora, benchmarks, leaderboard, open-source

  Jeongho KimResearch Engineer, Nota AI   SummaryOnline multi-camera system for efficient individual trackingAccurate ID management with Cluster Self-Refinement (CSR)Improved performance with enhanced pose estimation   Intro...

High signal Matched: performance, model, paper, research, evaluation, leaderboard