Why 90% Accuracy in Text-to-SQL is 100% UselessTowards Data Science The eternal promise of self-service analytics
The post Why 90% Accuracy in Text-to-SQL is 100% Useless appeared first on Towards Data Science.
The eternal promise of self-service analytics
The post Why 90% Accuracy in Text-to-SQL is 100% Useless appeared first on Towards Data Science. Read More
How to Self-Host n8n on Docker in 5 Simple StepsKDnuggets This tutorial will guide you through the complete process of self-hosting n8n on Docker in just 5 simple steps, with detailed explanations and code samples, regardless of your technical background.
This tutorial will guide you through the complete process of self-hosting n8n on Docker in just 5 simple steps, with detailed explanations and code samples, regardless of your technical background. Read More
How Omada Health scaled patient care by fine-tuning Llama models on Amazon SageMaker AIArtificial Intelligence This post is co-written with Sunaina Kavi, AI/ML Product Manager at Omada Health. Omada Health, a longtime innovator in virtual healthcare delivery, launched a new nutrition experience in 2025, featuring OmadaSpark, an AI agent trained with robust clinical input that delivers real-time motivational interviewing and nutrition education. It was built on AWS. OmadaSpark was designed
This post is co-written with Sunaina Kavi, AI/ML Product Manager at Omada Health. Omada Health, a longtime innovator in virtual healthcare delivery, launched a new nutrition experience in 2025, featuring OmadaSpark, an AI agent trained with robust clinical input that delivers real-time motivational interviewing and nutrition education. It was built on AWS. OmadaSpark was designed Read More
We Tried 5 Missing Data Imputation Methods: The Simplest Method Won (Sort Of)KDnuggets We tested five imputation methods with proper cross-validation and statistical testing. Mean imputation won for prediction but destroyed feature relationships.
We tested five imputation methods with proper cross-validation and statistical testing. Mean imputation won for prediction but destroyed feature relationships. Read More
How This Agentic Memory Research Unifies Long Term and Short Term Memory for LLM Agents MarkTechPost
How This Agentic Memory Research Unifies Long Term and Short Term Memory for LLM AgentsMarkTechPost How do you design an LLM agent that decides for itself what to store in long term memory, what to keep in short term context and what to discard, without hand tuned heuristics or extra controllers? Can a single policy learn to manage both memory types through the same action space as text generation? Researchers
The post How This Agentic Memory Research Unifies Long Term and Short Term Memory for LLM Agents appeared first on MarkTechPost.
How do you design an LLM agent that decides for itself what to store in long term memory, what to keep in short term context and what to discard, without hand tuned heuristics or extra controllers? Can a single policy learn to manage both memory types through the same action space as text generation? Researchers
The post How This Agentic Memory Research Unifies Long Term and Short Term Memory for LLM Agents appeared first on MarkTechPost. Read More
How AI Can Become Your Personal Language TutorTowards Data Science How I used n8n to build AI study partners for learning Mandarin: vocabulary, listening, and pronunciation correction.
The post How AI Can Become Your Personal Language Tutor appeared first on Towards Data Science.
How I used n8n to build AI study partners for learning Mandarin: vocabulary, listening, and pronunciation correction.
The post How AI Can Become Your Personal Language Tutor appeared first on Towards Data Science. Read More
CISA has ordered government agencies to secure their systems against a high-severity Gogs vulnerability that was exploited in zero-day attacks. […] Read More
The Amsterdam Court of Appeal sentenced a 44-year-old Dutch national to seven years in prison for multiple crimes, including computer hacking and attempted extortion. […] Read More
Massive data dump reveals real identities and details of administrators and members of the notorious hacker forum. Read More
LLMs as verification oracles for Soliditycs.AI updates on arXiv.org arXiv:2509.19153v2 Announce Type: replace-cross
Abstract: Ensuring the correctness of smart contracts is critical, as even subtle flaws can lead to severe financial losses. While bug detection tools able to spot common vulnerability patterns can serve as a first line of defense, most real-world exploits and losses stem from errors in the contract business logic. Formal verification tools such as SolCMC and the Certora Prover address this challenge, but their impact remains limited by steep learning curves and restricted specification languages. Recent works have begun to explore the use of large language models (LLMs) for security-related tasks such as vulnerability detection and test generation. Yet, a fundamental question remains open: can LLMs aid in assessing the validity of arbitrary contract-specific properties? In this paper, we provide the first systematic empirical evaluation of GPT-5, a state-of-the-art reasoning LLM, in this role. We benchmark its performance on a large dataset of verification tasks, compare its outputs against those of established formal verification tools, and assess its practical effectiveness in real-world auditing scenarios. Our study combines quantitative metrics with qualitative analysis, and shows that recent reasoning-oriented LLMs – although lacking soundness guarantees – can be surprisingly effective at predicting the (in)validity of complex properties, suggesting a new frontier in the convergence of AI and formal methods for secure smart contract development and auditing.
arXiv:2509.19153v2 Announce Type: replace-cross
Abstract: Ensuring the correctness of smart contracts is critical, as even subtle flaws can lead to severe financial losses. While bug detection tools able to spot common vulnerability patterns can serve as a first line of defense, most real-world exploits and losses stem from errors in the contract business logic. Formal verification tools such as SolCMC and the Certora Prover address this challenge, but their impact remains limited by steep learning curves and restricted specification languages. Recent works have begun to explore the use of large language models (LLMs) for security-related tasks such as vulnerability detection and test generation. Yet, a fundamental question remains open: can LLMs aid in assessing the validity of arbitrary contract-specific properties? In this paper, we provide the first systematic empirical evaluation of GPT-5, a state-of-the-art reasoning LLM, in this role. We benchmark its performance on a large dataset of verification tasks, compare its outputs against those of established formal verification tools, and assess its practical effectiveness in real-world auditing scenarios. Our study combines quantitative metrics with qualitative analysis, and shows that recent reasoning-oriented LLMs – although lacking soundness guarantees – can be surprisingly effective at predicting the (in)validity of complex properties, suggesting a new frontier in the convergence of AI and formal methods for secure smart contract development and auditing. Read More
