Fake faces, cheap product clips, and rule-skirting story ads are pouring into short-video commerce. Platforms are answering with automated review systems. Honest advertisers are stuck paying for the cleanup.
Enterprise artificial intelligence context startup Jedify Inc. today formally launched Data Agents, a product that lets business teams set up autonomous AI analysts by describing the work they want done in plain language. Data Agents takes on a longstanding limit of business intelligence software, where analysts have to build dashboards ahead of time around the […] The post Jedify formally launches Data Agents for building AI analysts in plain language appeared first on SiliconANGLE.
arXiv:2610.36432v1 公表タイプ：新規 要旨：ホモグリフおよび非表示文字による透かしは、編集ベースの透かしです。モデルがテキストを生成する方法を変更するのではなく、テキストが生成された後にその中に信号を隠す手法です。同形異義文字（見た目は同じか非常に似ているがUnicodeコードポイントが異なる文字）に置き換えたり、表示されない文字を挿入したりすることで、テキストを生成したモデルへのアクセスなしに実現します。生成時透かしは、トークナイザーがテキストを分割する方式のため、リソースが限られた言語では効果が低下します。これらの透かしは個々の文字単位で動作するため、トークナイザーには一切影響を与えません。そこで、こうした透かしがこのギャップを回避できるのかという疑問が生じます。24種類の文字体系に属する40の言語バリエーションを対象に、各文字が持つ隠蔽ビット数（容量）と、そのうちどれだけが
Information technology observability company Virtana today added Agentic Observability Enterprise Management to its platform so its artificial intelligence agents can pull agents from other vendors into an IT incident. The release goes after a gap left by the way enterprises have adopted AI agents so far. Most enterprise agents have come built into a single […] The post Virtana lets its AI agents pull in agents from other vendors to work IT incidents appeared first on SiliconANGLE.
Agents should understand more than your codebase—they should understand how your team works. Your preferences, repository conventions, skills, and custom instructions guide how changes should be made, while code in… The post GitHub intelligence puts your code, context, and history to work appeared first on The GitHub Blog.
In breathless press releases and posts, the company has touted its models’ ability to deliver scientific breakthroughs. But its IPO filing taps the brakes on just how fast its AI will lead to big discoveries.
arXiv:2610.36360v1 Announce Type: new Abstract: We present AK_QMUL's submissions to the ArGuard-2026 shared tasks on Arabic harmful-prompt detection: a binary safe/unsafe task (B1) and a seven-way harm-domain task (B2). Both submissions use one backbone -- JAIS-6.7B fine-tuned with 4-bit QLoRA and a linear classification head over its last-token representation. For B1 we train a four-way head that factors the label by dialect register {safe, unsafe} x {MSA, other}, we augment the training fold with MSA prompts from AraSafe, and decode with a plain argmax to score safe/unsafe. For B2 we fine-tune the same backbone as a seven-way classifier and average the softmax outputs of five random seeds. Both submissions ranked first on their track, with macro-F1 0.984 on B1 and 0.790 on B2. We report
チームが信頼の問題を解決できるなら、AIエージェントはなぜセマンティックレイヤーを定着させられるのか。
KOHO explains why AI self-serve analytics needs a strong data culture and a governed dbt foundation first.
Enterprises working with a GitHub or Microsoft account team can now get Copilot included with GitHub Enterprise for every licensed user. Previously, you had to manage two things: how many… The post GitHub Enterprise now includes access to GitHub Copilot appeared first on The GitHub Blog.
