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95 posts · Last used 2h

Tarah Wheeler @Tarah@infosec.exchange
· 2h ago
Boosted by @trending@homestead.social
I have been (mostly secretly) pursuing my doctorate for more than six years at the University of Oxford. Yesterday, I successfully defended my thesis and passed my viva. This morning was the first time I got to say to someone "so sorry but it's not Miss Wheeler, it's Doctor Wheeler." My path here was beyond weird. Oxford rejected me three times between 2018 and 2020. Then a pandemic, Brexit, and a late third round of admissions at the Oxford Internet Institute, University of Oxford opened a door, and I matriculated over Zoom as a DPhil in Social Data Science from my little room in Seattle at 3 a.m in October of 2020. My thesis uses classic machine learning methods at scale, with full transparency, to detect potential influence in text over time. It started with a question about whether Ada Lovelace ever read Mary Shelley’s Frankenstein, and it ended up deep in Harold Bloom’s theory of influence. I presented the methods paper at Computational Models of Narrative in Madrid this year. I also rowed for my college’s boat club (come on Linacre College, Oxford!!), went to more bops than I’ll admit to, and finally got to really, really love academia. If school never fit you, and especially if you’re neuroatypical, you may just need to wait until you can do it on your own terms. I have failed out of or gotten kicked out of or dropped out of many more schools than I ever got a degree from. You can do it and just message me if you want to talk. There are more people than I could ever hope to thank in a single post, and I'll be writing more about them over the next weeks and months. I did it my way. The whole story is here: https://www.tarah.org/2026/11/10/i-got-a-doctorate-in-machine-learning-from-oxford-mostly-in-secret-over-the-last-six-years/ #Oxford #DPhil #MachineLearning #DigitalHumanities #DataScience
tarah.org

I got a doctorate in machine learning from Oxford (mostly) in secret over the last six years – Tarah Wheeler

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Metin Seven @metin@graphics.social
· 5d ago
Boosted by @trending@homestead.social
Read an interesting quote today, by Joseph Weizenbaum in 1976. He coded Eliza… "What I had not realized is that extremely short exposure to a relatively simple computer program could induce powerful delusional thinking in quite normal people." Eliza was a simple piece of software compared to today's AI. 😓 #tech #technology #BigTech #IT #AI #ArtificialIntelligence #LLM #LLMs #ML #MachineLearning #GenAI #generativeAI #AIAgent #AISlop #enshittification
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Claude M. Schrader @cschrader@hachyderm.io
· 1w ago
Boosted by @welcome@friends.deko.cloud
New server, so it’s time for a new #introduction I’m a #cloud engineer working with #esri #arcgis software in #aws. In the past, I’ve also done #devops, #networking, #sysadmin, and #machinelearning. I live in #philadelphia, I’m a dad, I’ve got a dog, and read or watch the #Sixers in the few minutes of spare time I find. I’m on a nonprofit working to protect and save green space in Philadelphia’s Kensington neighborhood. Go birds.
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Camille Roux @camilleroux@mastodon.social
· 1mo ago
Laya : moteur de décision non-autoregressif pour classer vos textes (choix, score, oui/non) en un seul forward pass, 33 ms, dans plus de 100 langues. Router qui sélectionne le bon checkpoint par requête. Open source, licence Apache 2.0. ⬇️ https://github.com/NandhaKishorM/laya #MachineLearning #AI 📬 Ma veille dev, chaque vendredi par email → https://l.camilleroux.com/sig-84n
github.com

GitHub - NandhaKishorM/laya: Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.

Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per re...

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Metin Seven @metin@graphics.social
· 1mo ago
🤭 The Copilot+ PC brand is dead: Microsoft and PC makers quietly pull back on tarnished Windows 11 AI PC branding https://www.windowscentral.com/microsoft/windows-11/the-copilot-pc-brand-is-dead-microsoft-and-pc-makers-quietly-pull-back-on-tarnished-windows-11-ai-pc-branding #tech #technology #BigTech #IT #AI #ArtificialIntelligence #LLM #LLMs #ML #MachineLearning #GenAI #generativeAI #AIAgent #AISlop #FuckAI #Fuck_AI #enshittification #microslop #microsoft
windowscentral.com
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Lobsters @lobsters@robot.villas
· 1mo ago
DeepSeek Elastic Compute (DSec): Sandbox Infrastructure for Effective Agentic Training at Scale https://arxiv.org/abs/2609.22978 #AI #MachineLearning #CloudComputing
DeepSeek Elastic Compute (DSec): A Sandbox Infrastructure for Effective Agentic Training at Scale
arxiv.org

DeepSeek Elastic Compute (DSec): A Sandbox Infrastructure for Effective Agentic Training at Scale

Large-scale agentic training and evaluation with large language models (LLMs) rely on isolated, stateful execution environments in which models inspect repositories, invoke tools, execute commands, and interact with task-specific services. These workloads create sandboxes in large bursts, span heterogeneous functionality and isolation requirements, retain state across long interactions, and draw from large image corpora with limited reuse. Supporting them therefore requires an elastic execution

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RakeshPalani @RakeshPalani@social.vivaldi.net
· 1mo ago

🚀 Building Stoic — an AI Search & Answer Platform

Stoic is an AI-powered search and answer platform I’m building to turn documents, web content, images, and other information into useful, grounded answers. It uses RAG, embeddings, semantic search, and vector databases to retrieve relevant context before generating an answer. The backend is built with Python and FastAPI, with Supabase + pgvector for vector storage and similarity search. I’m also experimenting with LLM model routing, streaming responses, multimodal processing, and LLM-as-a-judge evaluation. The goal is to make AI search more reliable by focusing not only on generation, but also on retrieval quality and evaluation. I’m building Stoic as a hands-on learning project and continuously improving the architecture, performance, and user experience. If you're interested in AI engineering, RAG, LLMs, semantic search, or building AI products, I’d love to connect and hear your thoughts. 🤝

🔗 Try Stoic: https://stoic-app.vercel.app 💻 GitHub: https://github.com/Rakesh051204/cloud9-frontend

#AI #GenerativeAI #LLM #RAG #MachineLearning #AIEngineering #Python #BuildInPublic

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stoic-app.vercel.app

Zehn

Vizual o'rganish · O'zbekiston

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freekmurze @freekmurze@phpc.social
· 2mo ago
🔗 Run AI in the Browser: A Practical Guide to Transformers.js https://tighten.com/insights/run-ai-in-the-browser-a-practical-guide-to-transformers-js/ #javascript #machinelearning #ai #browser
Run AI in the Browser: A Practical Guide to Transformers.js
tighten.com

Run AI in the Browser: A Practical Guide to Transformers.js

Imagine you need to integrate AI into your web app. Let's say you want to quickly translate text. Preferably, you'd like to use something free and open source (you don't want any surprise bills at the end of the month). One...

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Zoomers of the Sunshine Coast 🇨🇦 @SCZoomers@mstdn.ca
· 2mo ago
Replying to
Worth boosting: #FediScience and #MachineLearning communities, ISTA (Institute of Science and Technology Austria), Yandex Research, KAUST GenAI CoE, Neural Magic, and open-weights/local-LLM enthusiasts.
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