Building from the V shaped physique concept, you need to also have depth from the side view. This is achieved by building the ‘rear delts’, and here’s the most efficient exercise for quickly doing that.

Robust 3D shoulders. Photo by GorillaFreak

The rear delts are often ignored in many workout routines — and they are hard to target in general. The result is people have over-developed front delts, but more of a hunched forward and skinny look from the side view as the front delts get worked easily, while the side and rear delts lag. …

Exercising your side delts can add impressive width, but one exercise gives you the best bang for the buck.

side delts in focus — (Photo by Damir Spanic on Unsplash)

Based on studies, women are most attracted to men with a V shaped physique, meaning the shoulders are wider than the waist, creating a V taper from the front view.

Given the above, the question becomes how to optimally improve your V taper since the typical case is shoulders are not as wide as desired.

While you can’t readily change your bone structure, you can add mass to your shoulders and thus increase the width. …

Genetically modified mice with ‘humanized lungs’ were apparently created to test the infectiousness of coronaviruses in Summer, 2019 and not Spring 2020 as portrayed. Unlike other zoonotic jumps ala SARS, Covid-19 was surprisingly ‘pre-adapted’ to thrive and transmit in the human respiratory system from the start. …

Combining intermittent fasting days with cardio = Double the fat loss, retain muscle mass, improve cholesterol…

A study that compared the effects of intermittent fasting by itself, cardio by itself, or the combination of both may have found the optimal setup for rapid fat loss whilst maintaining muscle mass (and as a bonus, had the best improvement in LDL cholesterol levels).

Losing fat while not losing muscle is hard to do, so this study may have found an optimal combination for those interested in losing fat and improving their physiques.

Let’s review the study itself and breakout the results, and…

Four tips from scientific studies point the way to maximizing your gains if you are interested in increasing your arm size as efficiently as possible!

Photo by Karsten Winegeart on Unsplash

1 — Train your arms first.
While conventional workouts typically follow the larger muscles first, then smaller muscles, multiple studies have shown that muscles worked first get worked harder.
In particular, a study in Brazil compared having men train with arms first (biceps, triceps) vs arms last (bench press etc. first).

The results were quite clear. …

Short summary of how the US approved mRNA Covid vaccines work (Pfizer, Moderna)

With my work in Covid-19 related AI, I frequently get asked about the various covid vaccines, both approved and pending. Thus, I’m writing this article to provide a useful summary of the current mRNA vaccines, and will likely add another one on what’s pending — how they work, how and why they have been shown to be safe, and what’s potentially coming for vaccines in 2021.

US approved vaccines — Pfizer and Moderna — mRNA platform:

The basic path from mRNA to immune response (original image JMarchn, wikimedia) with my crude path additions. mRNA introduced to the bloodstream via injection (purple circle at top), picked up by dendritic cells that read the message and produce Covid-19 spikes on their surface. Immune cells then learn about the spike (light blue boxes) generating a prepared memory for future (actual) Covid-19 challenges.

The only two approved vaccines at the time of this writing…

AdaMod is a new deep learning optimizer that builds on Adam, but provides an automatic warmup heuristic and long term learning rate buffering. From initial testing, AdaMod is a top 5 optimizer and readily beats or exceeds vanilla Adam, while being much less sensitive to the learning rate hyperparameter, smoother training curve, and requires no warmup mode.

AdaMod converges to same point even using up to 2 order magnitude different learning rates vs SGDM and Adam end up with different results.

AdaMod is proposed in the paper “An Adaptive and Momental Bound Method for Stochastic Learning” by Ding, Ren, Lou and Sun.

How AdaMod works: AdaMod maintains an exponential, long term average of the adaptive learning rates themselves, and uses that to clip any…

Example of short term gradient changes on the way to the global optimum (center). Image from paper.

DiffGrad, a new optimizer introduced in the paper “diffGrad: An optimizer for CNN’s” by Dubey, et al, builds on the proven Adam optimizer by developing an adaptive ‘friction clamp’ and monitoring the local change in gradients in order to automatically lock in optimal parameter values that Adam can skip over.

CPC 2.0 in action — with only 1% of labeled data, achieves 74% accuracy (from the paper)

Current Deep Learning for vision, audio, etc. requires vast amounts of human labeled data, with many examples of each category, to properly train a classifier to acceptable accuracy.

By contrast, humans only need to see a few examples of a class to begin properly and accurately recognizing and classifying future examples of that class.

The difference is that humans are able to quickly generate accurate mental ‘representations’ of things, and then use those representations to flexibly account for future variations. After seeing a few images of bluejays for example, we can make a mental model or representation of a bluejay…

Summary: By replacing single convolutional kernels with a mixed grouping of 3x3–9x9 kernels, and a neural search ‘MixNet’ architecture, a new state of the art 78.9% accuracy on ImageNet top 1% is achieved under standard mobile metrics. MixNet-L outperforms ResNet-153 with 8x fewer params, and MixNet-M matches it exactly but with 12x fewer params and 31x fewer FLOPS.

Tan and Le of Google Brain recently show-cased a new depthwise convolutional kernel arrangement (MixConv) and a new NN architecture optimized for efficiency and accuracy using MixConvs in their paper: Mixed depthwise convolutional kernels.

This article will summarize the architecture of MixConv’s…

Less Wright

PyTorch, Deep Learning, Object detection, Stock Index investing and long term compounding.

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