#GSFC -164.50

Towards objective...

A thread on how absurd the UK is on transgender issues and how the UK got so transphobic

In 2015 Parliament held an inquiry looking into the state of Transgender equality. Trans people of all stripes outlined many different problems across many, many different areas.

As a result Parliament created a list of recommendations including legal recognition for non binary people, gender recognition act reform, allowing 16 year olds to change their legal gender and reform of NHS gender identity services.

The government under Theresa May ignored everything that was recommended except for Gender recognition act reform. This act came into law in 2003 and gave trans men and women (but not non-binary people) the ability to legally change their gender on their birth certificates.

The process at that time to change your birth certificate under the GRA was to make an application to a panel of cisgender people who would decide if you were sufficiently trans based on your payslips, photo ID and bank statements. You would not get the option to speak to them.

(Also this process cost £140 which is just a tax on being trans)

Important paper from Google on large batch optimization. They do impressively careful experiments measuring # iterations needed to achieve target validation error at various batch sizes. The main "surprise" is the lack of surprises. [thread]

https://t.co/7QIx5CFdfJ

The paper is a good example of lots of elements of good experimental design. They validate their metric by showing lots of variants give consistent results. They tune hyperparamters separately for each condition, check that optimum isn't at the endpoints, and measure sensitivity.

They have separate experiments where the hold fixed # iterations and # epochs, which (as they explain) measure very different things. They avoid confounds, such as batch norm's artificial dependence between batch size and regularization strength.

When the experiments are done carefully enough, the results are remarkably consistent between different datasets and architectures. Qualitatively, MNIST behaves just like ImageNet.

Importantly, they don't find any evidence for a "sharp/flat optima" effect whereby better optimization leads to worse final results. They have a good discussion of experimental artifacts/confounds in past papers where such effects were reported.

Best resort on the Ganga at Rishikesh

THREAD: What is Golden Crescent and Golden Triangle and how it impacts India?

Golden Crescent region of South Asia - comprises of Afghanistan, Iran, and Pakistan - which is a principal global site for opium production and distribution.

Golden Triangle is the area where the borders of Thailand, Laos and Myanmar meet at the confluence of the Ruak and Mekong rivers. The Golden Triangle is called so because of the triangular shape formed by the locations of New Delhi, Agra and Rajasthan on a map.

India is wedged bw world’s 2 largest areas of illicit opium production, Golden Crescent & Golden Triangle, that has made Indian borders vulnerable to drug trafficking. It flows from 2 fronts, NW & NE, that possesses dual concern - violation of border & threat to national security

- Golden Crescent is world’s leading opium and cannabis producing region since 1983.

- Its proximity to Indo-Pak border has worsened the trafficking of hashish and heroin into Indian soil

- Trafficking happens through the border states of J&K, Punjab, Rajasthan and Gujarat.

- Golden Triangle is leading opium producing region of the South-east Asia, also an ancient narcotics supply route to North America & Europe.

- Myanmar-Northeast nexus is recognized by NCB as the root of heroin & chemical drugs

- Myanmar produces 80% of heroin produced in world