The Gradient
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The GradientResearchAfter Orthogonality: Virtue-Ethical Agency and AI Alignment Preface This essay argues that rational people don’t have goals, and that rational AIs shouldn’t have goals. Human actions are rational not because we direct them at some final ‘goals,’ but because we align actions to pr
The GradientResearchAGI Is Not Multimodal "In projecting language back as the model for thought, we lose sight of the tacit embodied understanding that undergirds our intelligence." –Terry Winograd The recent successes of generative AI models have convinced some
The GradientResearchShape, Symmetries, and Structure: The Changing Role of Mathematics in Machine Learning Research What is the Role of Mathematics in Modern Machine Learning? The past decade has witnessed a shift in how progress is made in machine learning. Research involving carefully designed and mathematically principled architect
The GradientResearchWhat's Missing From LLM Chatbots: A Sense of Purpose LLM-based chatbots’ capabilities have been advancing every month. These improvements are mostly measured by benchmarks like MMLU, HumanEval, and MATH (e.g. sonnet 3.5, gpt-4o). However, as these measures get more and mor
The GradientResearchWe Need Positive Visions for AI Grounded in Wellbeing Introduction Imagine yourself a decade ago, jumping directly into the present shock of conversing naturally with an encyclopedic AI that crafts images, writes code, and debates philosophy. Won’t this technology almost ce
The GradientResearchFinancial Market Applications of LLMs The AI revolution drove frenzied investment in both private and public companies and captured the public’s imagination in 2023. Transformational consumer products like ChatGPT are powered by Large Language Models (LLMs)
The GradientResearchA Brief Overview of Gender Bias in AI A brief overview and discussion on gender bias in AI
The GradientResearchMamba Explained Is Attention all you need? Mamba, a novel AI model based on State Space Models (SSMs), emerges as a formidable alternative to the widely used Transformer models, addressing their inefficiency in processing long sequences
The GradientResearchCar-GPT: Could LLMs finally make self-driving cars happen? Exploring the utility of large language models in autonomous driving: Can they be trusted for self-driving cars, and what are the key challenges?
The GradientResearchDo text embeddings perfectly encode text? 'Vec2text' can serve as a solution for accurately reverting embeddings back into text, thus highlighting the urgent need for revisiting security protocols around embedded data.
The GradientResearchWhy Doesn’t My Model Work? Have you ever trained a model you thought was good, but then it failed miserably when applied to real world data? If so, you’re in good company.
The GradientResearchDeep learning for single-cell sequencing: a microscope to see the diversity of cells On the the pivotal role that Deep Learning has played as a key enabler for advancing single-cell sequencing technologies.
The GradientResearchSalmon in the Loop On fish counting – a complex sociotechnical problem in a field that is going through the process of digital transformation.
The GradientResearchNeural algorithmic reasoning In this article, we will talk about classical computation : the kind of computation typically found in an undergraduate Computer Science course on Algorithms and Data Structures [1]. Think shortest path-finding, sorting,
The GradientResearchThe Artificiality of Alignment This essay first appeared in Reboot . Credulous, breathless coverage of “AI existential risk” (abbreviated “x-risk”) has reached the mainstream. Who could have foreseen that the smallcaps onomatopoeia “ꜰᴏᴏᴍ” — both evoca
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