2023 – Page 2 – Andrew Fairless, Ph.D.

What I Read: Problems of AI Consciousness

By Andrew Fairless on December 4, 2023October 5, 2023

https://thegradient.pub/an-introduction-to-the-problems-of-ai-consciousness/ An Introduction to the Problems of AI ConsciousnessNick Alonso9/30/23 “This brief introduction is aimed at those working within the AI community who are interested in AI consciousness, but mayContinue readingWhat I Read: Problems of AI Consciousness

What I Read: Visualizing Matrix Multiplication

By Andrew Fairless on November 30, 2023October 5, 2023

https://pytorch.org/blog/inside-the-matrix/ Inside the Matrix: Visualizing Matrix Multiplication, Attention and Beyondby Team PyTorchSeptember 25, 2023 “Matrix multiplications (matmuls) are the building blocks of today’s ML models. This note presents mm, aContinue readingWhat I Read: Visualizing Matrix Multiplication

What I Read: Data, The Land DevOps Forgot

By Andrew Fairless on November 28, 2023October 5, 2023

Data – The Land DevOps Forgot • Michael Nygard • YOW! 2023GOTO ConferencesSep 30, 2023Michael Nygard – General Manager of Data at Nubank & Author of “Release It!” “We willContinue readingWhat I Read: Data, The Land DevOps Forgot

What I Read: Privacy side channels in ML

By Andrew Fairless on November 27, 2023October 5, 2023

https://spylab.ai/blog/side-channels-machine-learning/ Privacy side channels in machine learning systemsEdoardo Debenedetti, Florian TramèrSep 12, 2023 “An additional application of our membership inference attack is to test whether specific data sources were partContinue readingWhat I Read: Privacy side channels in ML

What I Read: Estimate Token Importance in LLM Prompts

By Andrew Fairless on November 16, 2023October 5, 2023

https://www.watchful.io/blog/a-surprisingly-effective-way-to-estimate-token-importance-in-llm-prompts A Surprisingly Effective Way to Estimate Token Importance in LLM PromptsShayan Mohanty “Prompting is our primary means of instructing these AIs, yet the process of crafting effective prompts hasContinue readingWhat I Read: Estimate Token Importance in LLM Prompts

What I Read: Auditing AI, How Much Access

By Andrew Fairless on November 14, 2023October 5, 2023

https://aipolicy.substack.com/p/ai-accountability-transparency-2 Auditing AI: How Much Access Is Needed to Audit an AI System?Chapter 2 in our AI Accountability & Transparency series(By Sarah H. Cen, Cosimo L. Fabrizio, James Siderius, AleksanderContinue readingWhat I Read: Auditing AI, How Much Access

What I Read: Overton Paradox

By Andrew Fairless on November 9, 2023October 5, 2023

https://brilliant.org/lesson/the-overton-paradox/ The Overton Paradox “This apparent contradiction is what we’re calling the Overton Paradox: People become more liberal as they get older, but they are more likely to say theyContinue readingWhat I Read: Overton Paradox

What I Read: How make history with LLMs

By Andrew Fairless on November 8, 2023October 5, 2023

https://leighmariebraswell.substack.com/p/how-to-make-history-with-llms-and How to make history with LLMs & other generative modelsLeigh Marie BraswellSep 21, 2023 “Over the past year I’ve talked to many founders, operators, and investors, and I’ve encounteredContinue readingWhat I Read: How make history with LLMs

What I Read: Optimizing LLM in production

By Andrew Fairless on November 6, 2023October 5, 2023

https://huggingface.co/blog/optimize-llm Optimizing your LLM in productionSeptember 15, 2023Patrick von Platen “…efficient LLM deployment…. pros and cons of adopting lower precision, provide a comprehensive exploration of the latest attention algorithms, andContinue readingWhat I Read: Optimizing LLM in production

Year: 2023