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AI Industry
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- Generative AI has the potential to transform the finance function. By taking on some of the more mundane tasks that can occupy a lot of time, generative AI tools can help free up capacity for more high-value strategic work. For chief financial officers, this could mean spending more time and energy on proactively advising the…
- Earlier this year, when my colleague Casey Crownhart and I spent six months researching the climate and energy burden of AI, we came to see one number in particular as our white whale: how much energy the leading AI models, like ChatGPT or Gemini, use up when generating a single response. This fundamental number remained…
- In Silicon Valley’s imagined future, AI models are so empathetic that we’ll use them as therapists. They’ll provide mental-health care for millions, unimpeded by the pesky requirements for human counselors, like the need for graduate degrees, malpractice insurance, and sleep. Down here on Earth, something very different has been happening. Last week, we published a…
- Yichao “Peak” Ji is one of MIT Technology Review’s 2025 Innovators Under 35. Meet the rest of this year’s honorees. When Yichao Ji—also known as “Peak”—appeared in a launch video for Manus in March, he didn’t expect it to go viral. Speaking in fluent English, the 32-year-old introduced the AI agent built by Chinese startup Butterfly…
- Agentic AI is coming of age. And with it comes new opportunities in the financial services sector. Banks are increasingly employing agentic AI to optimize processes, navigate complex systems, and sift through vast quantities of unstructured data to make decisions and take actions—with or without human involvement. “With the maturing of agentic AI, it is…
- Earlier this summer, I walked through the glassy lobby of a fancy office in London, into an elevator, and then along a corridor into a clean, carpeted room. Natural light flooded in through its windows, and a large pair of umbrella-like lighting rigs made the room even brighter. I tried not to squint as I…
AI Research
- arXiv:2502.12669v2 Announce Type: replace Abstract: The rapid advancement of perovskite solar cells (PSCs) has led to an exponential growth in research publications, creating an urgent need for efficient knowledge management and reasoning systems in this domain. We present a comprehensive knowledge-enhanced system for PSCs that integrates three key components. First, we develop Perovskite-KG, a domain-specific […]
- arXiv:2509.05381v2 Announce Type: replace Abstract: We prove a formal impossibility result for reinforcement learning from human feedback (RLHF). In misspecified environments with bounded query budgets, any RLHF-style learner suffers an irreducible performance gap Omega(gamma) unless it has access to a calibration oracle. We give tight lower bounds via an information-theoretic proof and show that a […]
- arXiv:2509.08729v1 Announce Type: cross Abstract: Multi-turn-to-single-turn (M2S) compresses iterative red-teaming into one structured prompt, but prior work relied on a handful of manually written templates. We present X-Teaming Evolutionary M2S, an automated framework that discovers and optimizes M2S templates through language-model-guided evolution. The system pairs smart sampling from 12 sources with an LLM-as-judge inspired by […]
- arXiv:2509.08803v1 Announce Type: cross Abstract: The rise of misinformation underscores the need for scalable and reliable fact-checking solutions. Large language models (LLMs) hold promise in automating fact verification, yet their effectiveness across global contexts remains uncertain. We systematically evaluate nine established LLMs across multiple categories (open/closed-source, multiple sizes, diverse architectures, reasoning-based) using 5,000 claims previously […]
- arXiv:2506.23629v2 Announce Type: replace-cross Abstract: The integrity of Water Quality Data (WQD) is critical in environmental monitoring for scientific decision-making and ecological protection. However, water quality monitoring systems are often challenged by large amounts of missing data due to unavoidable problems such as sensor failures and communication delays, which further lead to water quality data […]
- arXiv:2509.06218v2 Announce Type: replace-cross Abstract: Interfacing quantum and classical processors is an important subroutine in full-stack quantum algorithms. The so-called "classical shadow" method efficiently extracts essential classical information from quantum states, enabling the prediction of many properties of a quantum system from only a few measurements. However, for a small number of highly non-local observables, […]
- arXiv:2509.08500v1 Announce Type: new Abstract: Using effective generalization capabilities of vision language models (VLMs) in context-specific dynamic tasks for embodied artificial intelligence remains a significant challenge. Although supervised fine-tuned models can better align with the real physical world, they still exhibit sluggish responses and hallucination issues in dynamically changing environments, necessitating further alignment. Existing post-SFT […]
- arXiv:2503.15108v3 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) excel at reasoning on text and Vision-Language Models (VLMs) are highly effective for visual perception, applying those models for visual instruction-based planning remains a widely open problem. In this paper, we introduce VIPER, a novel framework for multimodal instruction-based planning that integrates VLM-based perception with […]
- arXiv:2509.08312v1 Announce Type: new Abstract: The evolution toward Level 4 (L4) Autonomous Networks (AN) represents a strategic inflection point in telecommunications, where networks must transcend reactive automation to achieve genuine cognitive capabilities–fulfilling TM Forum's vision of self-configuring, self-healing, and self-optimizing systems that deliver zero-wait, zero-touch, and zero-fault services. This work bridges the gap between architectural […]
- arXiv:2509.08380v1 Announce Type: new Abstract: Generating regulatorily compliant Suspicious Activity Report (SAR) remains a high-cost, low-scalability bottleneck in Anti-Money Laundering (AML) workflows. While large language models (LLMs) offer promising fluency, they suffer from factual hallucination, limited crime typology alignment, and poor explainability — posing unacceptable risks in compliance-critical domains. This paper introduces Co-Investigator AI, an […]
Official Blogs
- Discover how SafetyKit leverages OpenAI GPT-5 to enhance content moderation, enforce compliance, and outpace legacy safety systems with greater accuracy .
- Applications are now open for OpenAI’s People-First AI Fund, a $50M initiative supporting U.S. nonprofits advancing education, community innovation, and economic opportunity. Apply by October 8, 2025, for unrestricted grants that help communities shape AI for the public good.
- OpenAI’s new research explains why language models hallucinate. The findings show how improved evaluations can enhance AI reliability, honesty, and safety.
- OpenAI invites researchers to its Bio Bug Bounty. Test GPT-5’s safety with a universal jailbreak prompt and win up to $25,000.
- OpenAI and the Greek Government have launched “OpenAI for Greece” to bring ChatGPT Edu into secondary schools and support responsible AI learning. This partnership aims to boost AI literacy, fuel local start-ups, and drive national economic growth.
- OpenAI is launching a Jobs Platform and new Certifications to connect workers with jobs, training, and certifications. Learn how we’re expanding economic opportunity and making AI skills more accessible.