保存済みツールを推薦
FOXAI SEARCH

サイト内検索

ニュース記事 511

funding

Circuit Mind lands $25M and puts AI agents to work checking circuit board schematics

British circuit board design startup Circuit Mind Ltd. today announced it has raised $25 million in new funding to extend its artificial intelligence platform across more of the hardware design process. A verification tool that puts AI agents to work hunting for errors in schematics launched at the same time. Circuit Mind offers software that […] The post Circuit Mind lands $25M and puts AI agents to work checking circuit board schematics appeared first on SiliconANGLE.

翻訳サービスが停止中のため原文を表示しています。
SiliconANGLE AI
研究の進展

Beyond IceBERT: Open-Data ModernBERT Encoders for Icelandic from 12M to 1B Parameters

arXiv:2610.36230v1 Announce Type: new Abstract: IceBERT, the reference encoder for Icelandic, found that a cleaned web crawl is enough to train a strong model and that starting from a multilingual model can help on some tasks. We revisit both findings with the ModernBERT architecture. We train Icelandic encoders from 12M to 1B parameters on 9B tokens of open data, and rerun IceBERT's benchmarks and five newer tasks for 30 encoders under one protocol with confidence intervals. Our 1B model trained from scratch, to our knowledge the first monolingual Icelandic encoder of that size, is significantly better than IceBERT on all eleven tasks; warm-started from the English Ettin encoder of the same shape, it has the best score of all encoders on every task we rank. Because our model shapes match

翻訳サービスが停止中のため原文を表示しています。
arXiv cs.CL
業界ニュース

Dell sees AI agent guardrails as a path to greater autonomy

As enterprises put AI agents to work, they face a challenge: How can they give those systems more autonomy while keeping AI agent guardrails in place? Security and resilience are becoming central considerations as enterprises decide which tasks to delegate to AI agents. Those decisions extend beyond individual actions to the data protection and cyber […] The post Dell sees AI agent guardrails as a path to greater autonomy appeared first on SiliconANGLE.

翻訳サービスが停止中のため原文を表示しています。
SiliconANGLE AI
model-evals

Fix evaluation bias to unlock better models on Amazon Bedrock

Property Finder found that 96.8% of their vision-AI evaluation labels were inherited from the incumbent model, hiding its true accuracy. See how they built unbiased ground truth, applied evolutionary prompt optimization, and selected a more accurate, cost-effective model on Amazon Bedrock, cutting cost by 86% across 11 image-quality attributes.

翻訳サービスが停止中のため原文を表示しています。
AWS Machine Learningブログ
研究の進展

どの方針に対して校正されるのか？介入下における固定世界モデルに対するコンフォーマル不確実性

arXiv:2610.35877v1 発表タイプ：新規 要旨：デプロイメント方針を変更すると、物理的な遷移メカニズムや予測器はそのままでも、世界モデルの不確実性が無効化される可能性がある。一歩先の予測において、源と対象の法則が条件付きメカニズム $P(Y|X)=Q(Y|X)$ を共有している場合、介入は事前結果の測度変化 $w(X)=dQ_X/dP_X$ によって特定される。方針制御された動的系では、この比は状態占有と行動傾向の項に分解される。重み付けされたコンフォーマル校正は、マージナルカバレッジを対象の法則へと移行させる；推定された比 $\hat w$ を用いれば、$P_Q\{Y \in C_{\hat w}(X)\} \ge 1-\alpha-TV(Q,\hat Q) \ge 1-\alpha-E_P|w-\hat w|$ が成立する。ソース対ターゲットのドメイン分類器に対する集団ロスレグレットは、同様の比の誤差を上限付ける。もし $h$ がそのクリッピング

arXiv cs.LG