A new AI draws delightful and not-so-delightful images
OpenAI’s DALL-E 2 is incredible at turning text into images. It also highlights the problem of AI bias — and the need to change incentives in the industry.
Experiments I conducted with DALL·E 2 from @OpenAI replicating styles of well known portrait photographers using photo-realistic AI. 🧵1. Dorothea Lange pic.twitter.com/845AzE51xu— Michael Green (@triplux) June 30, 2022
WandB is a central dashboard to keep track of your hyperparameters, system metrics, and predictions so you can compare models live, and share your findings.
Reliance on metrics is a fundamental challenge for AI
Optimizing metrics is a central aspect of most current artificial intelligence (AI)
approaches, yet overemphasizing metrics leads to manipulation, short-termism, and
other negative consequences. This poses a fundamental challenge within AI. We review
how metrics can go wrong in practice, and we put forward an evidence-based framework
toward mitigating these harms.
Enterprise Data Analytics for a Connected Multi-Cloud World
Teradata Vantage is the connected multi-cloud data platform for enterprise analytics that delivers actionable answers and predictive intelligence. Learn more.
Training a collaborative filtering based recommendation system on a toy dataset is a sophomore year project in colleges these days. But where the rubber meets the road is building such a system at scale, deploying in production, and serving live requests within a few hundred milliseconds while the user is waiting for the page to load. To build a system like this, engineers have to make decisions spanning multiple moving layers like:
GitHub - dair-ai/ML-Notebooks: A series of code examples for all sorts of machine learning tasks and applications.
:fire: A series of code examples for all sorts of machine learning tasks and applications. - GitHub - dair-ai/ML-Notebooks: A series of code examples for all sorts of machine learning tasks and app...
TaxProf Blog: Will Machines Replace Us? Machine-Authored Texts And The Future Of Scholarship
Benjamin Alarie (Toronto; Google Scholar) & Arthur J. Cockfield (Queen's; Google Scholar), Will Machines Replace Us? Machine-Authored Texts and the Future of Scholarship, 3 L., Tech & Humans 5 (2021): We present here the first machine-generated law review article. Our self-interest motivates us to believe that knowledge workers who write...
AI and Drug Discovery: Attacking the Right Problems
I've been meaning to write some more about artificial intelligence, machine learning, and drug discovery, and this paper (open access) by Andreas Bender is an excellent starting point. I'm going to be talking in fairly general terms here, but for practitioners in the field, I can recommend this revi
Machine Learning with Python: from Linear Models to Deep Learning | edX
An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. -- Part of the MITx MicroMasters program in Statistics and Data Science.
Ryan Mac / BuzzFeed: In interview Kogan admits he broke Facebook's ToS but his app was within norms, says he worked on 10+ papers with Pete Fleming, now Instagram's head of research