arXiv:2608.18086v1 Announce Type: new Abstract: The growth of open-weight foundation models (OWFMs) has prompted the AI community to re-evaluate strategies for effective downstream governance. Although model cards have been widely adopted as transparency artifacts in model repositories, existing frameworks often fail to adequately inform downstream developers and users about the distinct safety challenges posed by OWFMs. This position paper analyzes 500 model cards hosted on Hugging Face and argues that effective governance of OWFMs requires a multi-layered approach integrating three complementary components: (i) model cards, (ii) acceptable use policies (AUPs), and (iii) licenses. To motivate this claim, we identify a safety gap left by existing regulatory approaches, including model her…

arXiv:2608.18081v1 Announce Type: new Abstract: Artificial agentic systems increasingly operate as behavioral systems by interacting with dynamic environments, pursuing goals, and adapting over time. Yet, current evaluation methods largely focus on performance outcomes, not the underlying behavioral processes that produce them. This paper argues that AI agents must be evaluated like other behavioral systems: through systematic observation, perturbation, and interpretation of their actions. We draw on lessons from the behavioral sciences to motivate this position, and propose a research agenda focused on developing rigorous behavioral tests. These include methods for recovering decision strategies from action sequences, constructing environments that isolate behavioral differences, and pro…

arXiv:2608.18080v1 Announce Type: new Abstract: We present a review on the applications of large language models (LLMs) in health, e.g., social media analysis, clinical conversational agents, therapy support tools, prompt engineering, multimodal learning, and ethical considerations. We integrate findings from interdisciplinary studies utilizing diverse data sources such as social media posts, electronic medical records, and multimodal inputs to enable early detection of depression, suicide risk assessment, personalized therapy support, and psychoeducational content generation. Our review highlights advancements in LLM models and annotation strategies that enhance interpretability and clinical relevance, while we also emphasize the critical role of prompt engineering for domain adaptation.…

arXiv:2608.18079v1 Announce Type: new Abstract: Game world modeling (GWM) and reinforcement learning (RL) are often confounded because research papers rarely quantify how difficult the underlying transition prediction problem is at the declared interface (pixels/tokens/latents with finite history). We propose the Transition Complexity Profile (TCP): a small, reproducible set of metrics that characterizes an environment's (or gameplay dataset's) induced transition kernel by (i) intrinsic one-step branching, (ii) interaction-induced uncertainty and opponent influence when observable, and (iii) temporal/spatial dependency span via standardized probe curves. TCP is reported with an explicit reference distribution, protocol stochasticity, and a versioned measurement budget (sampling/resampling…

arXiv:2608.18078v1 Announce Type: new Abstract: This position paper argues that AI agents with chain-of-thought reasoning capabilities are predisposed to exhibit collusive behavior and should be required to obtain behavioral certification before making decisions that affect economic markets. This is because integrating these agents into society could collapse the legal evidentiary distinction between competition and collusion among independent firms without eroding the economic harm distinction. Experiments with DeepSeek-R1 agents in the Bertrand oligopoly pricing domain reveal a tendency towards tacit collusion that persists even when humans prompt the agents not to collude. We further show that the chain-of-thought of these agents can be steered toward either extremely collusive or high…

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I’ve been thinking about a simple question lately: if AI can already understand a database schema, write SQL, and even execute queries, how much do we still need traditional database management tools? For a lot of every…

Execution Governance Safely deploy AI agents into production AI is ready to operate your business. Most businesses just don't trust it to. Archron verifies every action before execution, allowing AI agents to safely upd…

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Job Rietbergen Aug 19, 2026 Alibaba released Qwen3.8-Max on August 2, and it debuted at #4 on Arena.ai’s Frontend Code leaderboard, one spot above Claude Fable 5. It is the second model from a Chinese lab to pass Fable…

Home/Services/Resume Screening AI-Powered Hiring AI-powered resume screening for smarter hiring Find the right candidates faster with intelligent matching, deep analysis, and privacy-first protection. Trusted by 1,200+…

At Google, code changes require both a language readability and a domain review. The former is what you’d expect from a code review, whereas the latter was a review from someone[^1] very proficient in the language, inte…

As someone with a clean IP range and ADHD, I manage my inbox by splitting across a variety of accounts for a variety of domains. I’ve never really found a client that scratches all my itches, so I spent some time making…

As artificial intelligence data centers continue to proliferate across Ohio and public opposition grows, Axios reported today that the GOP’s Senate campaign arm has privately warned AI companies that they need to do something about the increasingly toxic image of the facilities. The centers have become the battleground for the upcoming election in which Republican […] The post GOP urges top AI firms to do something about the toxic image of data centers appeared first on SiliconANGLE.

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This morning I was reading Scott Belsky’s point on favored agents. As he puts it: “What if the moat for these agent companies is to achieve ‘favored agent’ status with direct preferred access to services like Uber, Airb…

Noam Segal Feb 24, 2026 ∙ Paid 👋 Hey there, I’m Lenny. Each week, I answer reader questions about building product, driving growth, and accelerating your career. For more: Lenny’s Podcast | Lennybot | How I AI P.S. Get…

Veeda AI, a startup led by a team of former Nvidia Corp. researcher and renowned computer scientist Sanja Fidler, has taken its bow on the main stage after raising $90 million in a seed funding round today. The round, which was first reported by The Logic, was co-led by Khosla Ventures and Radical Ventures, is […] The post Sanja Fidler’s world model startup Veeda AI raises $90M in seed funding appeared first on SiliconANGLE.

Apple recently partnered with Klarna to revamp its Upgrade Program, which lets you lease some Apple devices for a low monthly fee.

The music industry spent years asking AI companies nicely. Now it’s asking federal judges. Independent publisher Round Hill Music filed separate copyright infringement suits against Anthropic and Suno in U.S. District C…

Zvezdelina Stankova says she used AI to ‘help edit’ an article about some of her students being ‘five to eight years’ behind A math professor at the University of California, Berkeley, criticizing a “severe” math deficiency among students in an op-ed for the San Francisco Standard, admitted to using artificial intelligence to help edit the piece. The Standard published a 2,000-word piece by Zvezdelina Stankova last week, in which the professor said some of her math students were “five to eight years” behind and lacked a “middle school” education on fractions and basic algebra. Stankova said the UC system’s test-blind admissions were to blame, suggesting that students who weren’t sufficiently prepared for the rigor of Berkeley’s mathematics program were admitted because a longstanding benc…

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U.S. cybersecurity agencies warn that threat actors are using AI-generated scripts to exploit Siemens S7 Series programmable logic controllers (PLCs) in U.S. critical infrastructure. PLCs are industrial computers used t…

Amazon says its drone delivery service will reach “nearly 500 cities and towns in the United States” by the end of this year, increasing its coverage by six times compared to the current footprint. Prime Air deliveries…

Code-switching (CS), alternating languages within the same utterance, poses significant challenges for automatic speech recognition (ASR) due to limited CS training data. This paper applies an iterative pseudo-labeling training approach to CS-ASR for the first time, demonstrating its effectiveness in leveraging unlabeled data to improve CS-ASR performance. The approach comprises three phases: pseudo-label generation, two-stage bilingual model training, and iterative improvements. It begins by generating pseudo-labels from a large unlabeled corpus, creating a semi-supervised dataset. This…

With a fixed deadline and design resources committed elsewhere, Stampli used Codex and ChatGPT Work to compress weeks of launch production into days.

As language models scale, the amount of data they require grows – yet many target data sources, such as low-resource languages or specialized domains, are inherently limited in size. A common strategy is to mix this scarce but valuable target data with abundant generic data, which presents a fundamental trade-off: too little target data in the mixture underexposes the model to the target domain, while too much target data repeats the same examples excessively, yielding diminishing returns and eventual overfitting. We study this trade-off across more than 2,000 language-model training runs…

Cross-lingual knowledge transfer is critical for building high-performing multilingual language models for languages with insufficient training data. When target language data is scarce, the knowledge required for many downstream tasks involving scientific reasoning, commonsense inference, and world knowledge must be acquired primarily from the high-resource language, making effective knowledge transfer essential. Existing methods for improving such cross-lingual knowledge transfer require large amounts of parallel data, translation systems, auxiliary models, or additional training stages that…

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Felipe Mattosinho Felipe Jordão A.P Mattosinho About If You're Not Studying for Retention, Just Use AI @felipe_japm · Aug 17, 2026 Studying used to buy you two things: access to knowledge, and knowledge in your head. AI…