Cover Girl!

Martha Stewart, at 81, is a cover girl, proving it\u27s never too late. So incredibly motivating! I, too, was contacted to do a two-page spread. However, it was one photo of me in a bikini, but it took two pages

Living A La Carte

It had been three long years, and I was dining with an ole beau. The menu had changed a bit and read like a situation comedy

Mothers

Why do mothers make the best parole officers? They\u27ll never let you finish a sentence

Lottery Sweeps By My House — Again

The Super Lottery Sweepstakes swept by my house yet again

Can\u27t Stop Dancing

If they don\u27t want me to tango in the market, why do they play music? And why do they think it\u27s necessary to call the authorities

Unemployed

Yup! I am about to be out of a job and technology is to blame. Self-driving cars are to become a reality

When Lightening Up Isn\u27t Easy

It\u27s a difficult week with painful memories of loss to our country and worldwide grief over losing a woman of regal stature, Queen Elizabeth

Understanding polysemanticity in neural networks through coding theory

Despite substantial efforts, neural network interpretability remains an elusive goal, with previous research failing to provide succinct explanations of most single neurons' impact on the network output. This limitation is due to the polysemantic nature of most neurons, whereby a given neuron is involved in multiple unrelated network states, complicating the interpretation of that neuron. In this paper, we apply tools developed in neuroscience and information theory to propose both a novel practical approach to network interpretability and theoretical insights into polysemanticity and the density of codes. We infer levels of redundancy in the network's code by inspecting the eigenspectrum of the activation's covariance matrix. Furthermore, we show how random projections can reveal whether a network exhibits a smooth or non-differentiable code and hence how interpretable the code is. This same framework explains the advantages of polysemantic neurons to learning performance and explains trends found in recent results by Elhage et al.~(2022). Our approach advances the pursuit of interpretability in neural networks, providing insights into their underlying structure and suggesting new avenues for circuit-level interpretability

Successful Therapy of Refractory Erythema Nodosum Associated with Crohn's Disease Using Potassium Iodide

Erythema nodosum is a common extraintestinal manifestation of Crohn's disease. While mild skin involvement often responds to conservative management, severe or refractory cases may require systemic corticosteroid or immunosuppressive therapy. This report describes successful treatment of severe, refractory erythema nodosum associated with Crohn's colitis using oral potassium iodide. While the mechanism of action of this agent is poorly understood, it appears to be an effective and nontoxic therapy for Crohn's-related erythema nodosum and warrants further evaluation in a placebo controlled trial