Everyone is talking about GPT-3, so, we talked about GPT-3. This seems to be the paper that started it all, “Language Models are Few-Shot Learners.” The paper is long with 75 pages, but there are 31 authors, so there are ~2.42 pages per author. That should make it easy. Probably we will only have time …
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We began a new thread related to ethics in AI with papers focus on papers by Buolamwini and Gebru. AI is now used routinely to make decisions that once were made by people in areas ranging from hiring to policing to social matchmaking. It seems fair to scrutinize these applications for ethics and fairness. Particularly …
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Google Research recently open sourced TaPas, a system for doing natural language queries on tabular data. The model is fully differentiable and based on BERT. We read the paper, “TAPAS: Weakly Supervised Table Parsing via Pre-training.” We ran the code from google research repo on a virtual machine and saw both the power of the …
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For this first session of 2021, we did almost a pure tutorial session. We covered BERT again, but went through the experience using using TensorFlow 2.3 and Hub on a virtual machine. Along with the tutorial, we created a small repo with requirements and some instructions.
We are prepared to do a tutorial on setting up a C++ autotools project. Here is the autotools skeleton project with the resources to start.
On 14 January, we will begin with a tutorial on ML in a VM with GPU. I am pretty happy with the experience that i have had using TensorFlow 2.3 and Hub on a virtual machine. We have talked about the BERT paper and other language models, but I want to do a refresher with …
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This tutorial should be pretty short, and is contained in a repo. The README.md explains most of the necessary details. Additionally, this bibliography also documents the history of reading for our Reading Club.
We returned to a topic for which we had previously had many sessions, that of NLP and word embeddings. We discussed “Deep contextualized word representations” by Peters et alia. We discussed the historical context of ELMo being popular as a bidirectional language model having the advantage over Word2vec of taking word order into account. For …
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We looked at a classical quantum-inspired algorithm by Erwin Tang in “A quantum-inspired classical algorithm for recommendation systems” and an associated follow up paper by Arrazola et alia “Quantum-inspired algorithms in practice.” This algorithm uses clever sampling techniques to approximate solutions for linear equations of the form Ax = b where x is unknown, essentially …
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We had taken a break from regular meetings, and when we returned, we switched gears to topics in quantum computing applied to machine learning. We discussed a few sections from “Machine learning & artificial intelligence in the quantum domain” by Vedran Dunjko and Hans J. Briegel.