会社名ニュース
長年にわたるワイの技術のフロンティアに焦点を合わせ、データ産業の発展を見据えて
Frontline AI study 2026 — Medical Data Set Forward
大手医療専門家であるLANG HuitechとAIの科学者であるLANG Huitechは、11の主要な疾患データセットの最前線研究を発表しました。
骨の年齢 X線画像データセット:2026 フロンティア AI の研究開発の展望
In August 2026, a number of breakthrough AI research advances were made in the field of bone age film X-ray image datasets. Together with top medical experts, AI scientists and industry leaders, Langham Technology deeply analyzes the latest achievements of bone age tablet datasets in intelligent diagnosis, model training and clinical applications, and prospectively discusses industry trends and technology pathways.
全回転X線画像データセット:2026前線AI研究・業界有望
In August 2026, a number of breakthrough AI research advances were made in the field of whole spine X-ray image datasets. Together with top medical experts, AI scientists and industry leaders, Langham Technology deeply analyzes the latest achievements of the scoliosis dataset in intelligent diagnosis, model training and clinical applications, and prospectively discusses industry trends and technology pathways.
肢骨折X線画像データセット:2026 フロンティアAI研究と業界展望
In August 2026, a number of breakthrough AI research advances were made in the field of X-ray imaging datasets of fractured limbs. Together with top medical experts, AI scientists and industry leaders, Langham Technology deeply analyzes the latest achievements of limb fracture datasets in intelligent diagnosis, model training and clinical applications, and prospectively discusses industry trends and technology pathways.
チェストX線原膜イメージングデータセット:2026 フロンティアAI研究・産業見通し
In August 2026, a number of breakthrough AI research advances were made in the field of chest X-ray flat image datasets. Together with top medical experts, AI scientists and industry leaders, Langham Technology deeply analyzes the latest achievements of chest radiograph datasets in intelligent diagnosis, model training and clinical applications, and prospectively discusses industry trends and technology pathways.
病理学的全スライス画像(WSI)データセット:2026前線AI研究と業界予見
In August 2026, a number of breakthrough AI research advances were made in the field of pathological full-slice imaging (WSI) datasets. Together with top medical experts, AI scientists and industry leaders, Langham Technology deeply analyzes the latest achievements of pathological WSI datasets in intelligent diagnosis, model training and clinical applications, and prospectively discusses industry trends and technology pathways.
Gastroscopyの内視鏡検査のビデオ画像データセット:2026フロンティアAIの研究開発の企業の展望
In August 2026, a number of breakthrough AI research advances were made in the field of endoscopic video image datasets. Together with top medical experts, AI scientists and industry leaders, Langham Technology deeply analyzes the latest achievements of gastroscope datasets in intelligent diagnosis, model training and clinical applications, and prospectively discusses industry trends and technology pathways.
内視鏡検査ビデオ画像データセット:2026 フロンティアAI研究・産業見通し
In August 2026, a number of breakthrough AI research advances were made in the field of colonoscopic endoscopic video image datasets. Together with top medical experts, AI scientists and industry leaders, Langham Technology deeply analyzes the latest achievements of colonoscopy datasets in intelligent diagnosis, model training and clinical applications, and prospectively discusses industry trends and technology pathways.
空気レンズのビデオ画像データセット:2026の前部ラインAIの研究および企業の foresight
In August 2026, a number of breakthrough AI research advances were made in the field of bronchoscopic video image datasets. Together with top medical experts, AI scientists and industry leaders, Langham Technology deeply analyzes the latest achievements of bronchoscopy datasets in intelligent diagnosis, model training and clinical applications, and prospectively discusses industry trends and technology pathways.
Vaginaのミラーおよび頚部レンズのビデオ イメージ データ セット: 2026 前部ライン AI の研究および企業の foresight
In August 2026, a number of breakthrough AI research advances were made in the field of colposcopy and cervical endoscopy video image datasets. Together with top medical experts, AI scientists and industry leaders, Langham Technology deeply analyzes the latest achievements of colposcopy datasets in intelligent diagnosis, model training and clinical applications, and prospectively discusses industry trends and technology pathways.
インスリンミラービデオ画像データセット:2026 Frontline AIの研究と業界予測
In August 2026, a number of breakthrough AI research advances were made in the field of biliopancreatoscopic video image datasets. Together with top medical experts, AI scientists and industry leaders, Langham Technology deeply analyzes the latest achievements of the cholangiopancreatoscopy dataset in intelligent diagnosis, model training and clinical applications, and prospectively discusses industry trends and technology paths.
Dermoscopyの皮の漏出イメージ投射データセット:2026フロンティアAIの研究および企業の展望
In August 2026, a number of breakthrough AI research advances were made in the field of dermoscopic skin lesions image datasets. Together with top medical experts, AI scientists and industry leaders, Langham Technology deeply analyzes the latest achievements of dermoscopy datasets in intelligent diagnosis, model training and clinical applications, and prospectively discusses industry trends and technology pathways.
Langhui E6および同心的なコレクション装置の深さの評価:2.1 mmの正確さはスマートなデータ記入項目を再定義しました
In August 2026, six-eye camera body acquisition equipment became a key entry point for VLA model training. Langham E6 achieved zero divergence and a position error of 2.1mm in 26 atomic motion trajectory evaluations. This paper analyzes how E6 opens a new infrastructure of humanoid robots and intelligent data with high precision, lightweight and data compliance capabilities from the perspectives of product managers, chief scientists, algorithm experts, advertising and compliance.
データオイルからスマート燃料まで:高品質のアイ2026のパラダイム革命
The public text corpus will be exhausted in 2028, and high-quality corpus has jumped from basic production factors to strategic resources to determine the upper limit of model capacity. In August 2026, the national level for the first time positioned the data set as a "new oil" strategic resource in the AI era. The Guizhou corpus platform suddenly reached 700TB, and 10 + provinces and cities opened dataset subsidies. Longhui Technology is at the forefront of the AI corpus paradigm revolution with 80 + datasets, 10 industry coverage, and expert-level evidence closed-loop methodology.
多角的なワークスペース:AIのスマートな年齢のための訓練データのための新しい基礎
In 2026, AI Agent officially entered the L3 practical era, and the paradigm transition from Agent Loop to Graph Engineering is reshaping the demand structure of training data. Zhiyuan Emu3 is unified modeling on the cover of Nature, and Qwen3.8-Max defines a new multimodal benchmark with 2.4 trillion parameters. With a matrix of 13 industry scenarios, 6-step annotation process and executable environmental data design, Langham Technology has built a new infrastructure for training data in the era of AI agents.
ヒューマン・インテリジェンスの不透明性: エキスパート・ランゲージが大きなモデル能力の小型化ボードを破る方法
Terminal Bench 3.0 reveals a real gap of 29.5 percentage points, with SWE-bench Verified scores approaching the ceiling. Industry consensus 2026: Pure synthetic data is no substitute for real expert trajectories. From RLHF's "like and step" feedback to expert-level evidence closed loop, from 9: 1 rejection delivery ratio to three stages of progressive acceptance - Longhui Technology has transformed decades of tacit knowledge of industry experts into an explicit trajectory that can be learned by AI.
医療用多角的なデータのための中国プログラム:医療AIを再構築できる時間的垂直データ
MICCAI 2026 released the EchoRisk longitudinal follow-up dataset, and long-time sequence multimodal medical data has become an international research hotspot. With 5000 + cases of longitudinal diagnosis and treatment full-modal data, 7 types of image modalities, and ICD-10-CN code mapping, Langhui Technology has established a national tuberculosis AI evaluation center in conjunction with Hunan Thoracic Hospital. From 500,000 CT cases to 100 million + medical NLP corpus, LANGHUI is reshaping the data base of medical AI with Chinese solutions.
ターミナルベンチ3.0から IAgent機能ギャップ:29.5パーセントポイントの背後にあるデータ革命を訓練する
Taking GLM-5.2 as a public sample, Terminal Bench 3.0 reveals the true gap of 29.5 percentage points between the domestic model and Sota. The root of the gap is not coding power, but long-range diagnostics, tool execution, and validation in expert environments. From the perspective of Changsha Langhui Chief Scientist, this paper deeply disassembles eight types of failure clusters and training data solutions.
「対話メッセージ」から「実行可能な専門家の環境」へのトレーニングデータにおけるパラダイムシフト
Terminal Bench 3.0 proposes that the Training Data Count Unit should be upgraded from “Message” to “Executable Environment”. This paper deeply analyzes the data design of the four capacity factories, the quality access control of the 9: 1 rejection delivery ratio, and the delivery standards of the auditable best practice trajectory, and explores how the customization of training data can become a key path for the breakthrough of large model capabilities.
グローバルAIビッグモデル・フロンティア・インサイト:エージェントの能力、オープンソースのインターチェンジ、トレーニングデータ、新しいベース
In August 2026, the global AI big model industry bid farewell to the pure parameter competition and turned to the four main lines of deep reasoning, autonomous agents, physical world models and robotics. From the perspective of Changsha Langhui Chief Scientist, this paper systematically analyzes the latest model progresses such as Qwen3.8-Max, DeepSeek-V4-Flash, Claude Fable 5, and GPT-5.6, and insights into the three major trends of open source switching, cost warfare upgrading, and training data new infrastructure.
証拠のエキスパートレベルのクローズドリング:長いHuitechが高品質のプログラミング言語でAIを提供する方法
When Kimi K3's paper emphasizes evaluation-data-RL closed loop, the Ultra mode of GPT-5.6 Sol requires high-quality failure case-driven improvement-high-quality expert trajectory corpus has become the core fuel for the evolution of AI agents. With a complete closed-loop system of expert-level evidence, Langham Technology provides high-quality corpus for AI programming evaluation from expert real-world problem solving to three-stage progressive acceptance.
グローバルAIプログラミングパターン2026:ビッグモデルエージェントコンペティションと中国 'sブレイクアウトロード
In August 2026, Meta released Muse Code to challenge Anthropic and OpenAI; Kimi K3 became the world's first 3T-level open source model with 2.8 trillion parameters; Tsinghua VeriLoop Coder-E1 achieved 85.20 SWE-bench Verified with 27b. This paper provides a panoramic analysis of the global AI programming pattern, technical route division, and China's AI breakthrough path.
SWE-bench から FrontierSWE へのパラダイムの飛躍と違い:2026 AI プログラミングベースライン評価
When GPT-5.6 Sol reaches 88.8% in Terminal-Bench 2.1, Claude Fable 5 leads SWE-Bench Pro with 80.3%, and VeriLoop Coder-E1 achieves 85.20 SWE-bench Verified with 27b - the traditional programming evaluation differentiation is disappearing. This paper provides an in-depth analysis of the eight unique problem types, the determination of substantive differences, and the differentiated focus of each field.
