Search Results for author: Philip Feldman

Found 9 papers, 1 papers with code

Killer Apps: Low-Speed, Large-Scale AI Weapons

no code implementations14 Jan 2024 Philip Feldman, Aaron Dant, James R. Foulds

The accelerating advancements in Artificial Intelligence (AI) and Machine Learning (ML), highlighted by the development of cutting-edge Generative Pre-trained Transformer (GPT) models by organizations such as OpenAI, Meta, and Anthropic, present new challenges and opportunities in warfare and security.

Decision Making

Trapping LLM Hallucinations Using Tagged Context Prompts

no code implementations9 Jun 2023 Philip Feldman, James R. Foulds, SHimei Pan

Recent advances in large language models (LLMs), such as ChatGPT, have led to highly sophisticated conversation agents.

Hallucination

Polling Latent Opinions: A Method for Computational Sociolinguistics Using Transformer Language Models

1 code implementation15 Apr 2022 Philip Feldman, Aaron Dant, James R. Foulds, Shemei Pan

Text analysis of social media for sentiment, topic analysis, and other analysis depends initially on the selection of keywords and phrases that will be used to create the research corpora.

Memorization

Ethics, Rules of Engagement, and AI: Neural Narrative Mapping Using Large Transformer Language Models

no code implementations5 Feb 2022 Philip Feldman, Aaron Dant, David Rosenbluth

This paper discusses the problem of mapping information spaces in general, and then presents a concrete implementation of this concept in the context of OpenAI's GPT-3 language model for determining if a subordinate is following a commander's intent in a high-risk situation.

Ethics Language Modelling

Analyzing COVID-19 Tweets with Transformer-based Language Models

no code implementations20 Apr 2021 Philip Feldman, Sim Tiwari, Charissa S. L. Cheah, James R. Foulds, SHimei Pan

This paper describes a method for using Transformer-based Language Models (TLMs) to understand public opinion from social media posts.

Training robust anomaly detection using ML-Enhanced simulations

no code implementations27 Aug 2020 Philip Feldman

This paper describes the use of neural networks to enhance simulations for subsequent training of anomaly-detection systems.

Anomaly Detection

Navigating Human Language Models with Synthetic Agents

no code implementations10 Aug 2020 Philip Feldman, Antonio Bucchiarone

We compare the trajectories contained in the text generated by the agents/model and compare that to the known ground truth of the chess board, move legality, and historical patterns of play.

Integrating Artificial Intelligence into Weapon Systems

no code implementations10 May 2019 Philip Feldman, Aaron Dant, Aaron Massey

The integration of Artificial Intelligence (AI) into weapon systems is one of the most consequential tactical and strategic decisions in the history of warfare.

Ethics

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