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LLM inference in C/C++. Contribute to ggml-org/llama.cpp development by creating an account on GitHub.
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After 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 practices[1]: networks of actions, action-dispositions, action-evaluation…
The Gradient40 min readAGI 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 WinogradThe recent successes of generative AI models have convinced some that AGI is imminent. While these models appear to capture the essence of human
The Gradient18 min readShape, 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 architectures result in only marginal improvements while compute-intensive and…
The Gradient33 min readWhat'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 more saturated, is user experience increasing in proportion to these scores?
The Gradient13 min readWe Need Positive Visions for AI Grounded in Wellbeing
IntroductionImagine 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 certainly transform society — and hasn’t AI’s impact on us so far been
The Gradient30 min readFinancial 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) that excel at modeling sequences of tokens that represent words or parts of…
The Gradient8 min readA Brief Overview of Gender Bias in AI
AI models reflect, and often exaggerate, existing gender biases from the real world. It is important to quantify such biases present in models in order to properly address and mitigate them.
The Gradient15 min readMamba 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.
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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 Gradient12 min readDo 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 Gradient9 min readWhy 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.
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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].
The Gradient28 min readThe 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 evocative of and directly derived from children’s cartoons —
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