Getting quickly from none to done.

Writing is very different today compared to fifteen years ago.

To be published used to mean in print, which constrained space but was less hasty. There were more gatekeepers, and far less content competing for readers’ attention. It had only taken a few years, but technology completely overhauled the economics of the written word.

I didn’t think the process was over.

I like writing, and at the very least, it’s been central to my career so far. But with decades of work ahead of me, I felt it would be risky to ignore the progress being made in natural language…

And the data showing it works.

Maybe you’re after a new job, and despair at sending your CV into the void.

Maybe you own a business, but are struggling to strike a chord with your target buyers.

Either way, you’re facing the same problem: to your audience — either prospects or employers — you are a noise blip, indistinguishable from other noise blips, at a time when everyone’s attention is already so compromised.

Founding editor of Wired magazine, Kevin Kelly, wrote of how, in the creator economy, you only need 1000 true fans to make a living. …

Look! No math

Source: Wikipedia, ‘ABBA, The Definitive Collection’

For the life of me, I couldn’t understand how BERT or GPT-2 worked.

I read articles; followed diagrams; squinted at equations; watched recorded classes; read code documentation; and still struggled to make sense of it all.

It wasn’t the math that made it hard.

More like, that the big part you’d expect to precede the nitty-gritty was somehow missing.

This article bridges the gap, explaining in simple terms how these models are built. It’s the article I wish I could have read first; many of the details would have then slotted right into place.

With the generous help of ABBA…

Surveying the current state of play

Source: Pexels

The financial services industry is falling in love with text crunching — also known as Natural Language Processing (NLP).

This infatuation is brought about by necessity, since investment companies are drowning in text data: analysis, news, contracts, compliance reports…

And the finance sector does like in-house tech. Away from Silicon Valley, investment banks in particular have been embracing engineering talent with absolute zeal. Though this process was well underway even before the 2008 financial crisis, subsequent regulation sped it up, by creating demand for better data solutions.

There are also the incentives to consider. It’s an industry driven by the…

Explained with Internet cats.

You didn’t come here to hear it’s useful to have a strong professional network.

Your inner hunch, that it’s probably helpful, is backed by data. According to LinkedIn, more than 70% of professionals get hired where they already have a connection.

But what seems to work so well for others, somehow isn’t working for you:

Maybe you feel like you don’t know any of the right people; that your network’s too small; that it’s not helpful enough. Maybe you feel you’ve got tons to offer, but can’t get anyone to care. …

And showing your professional worth can be made easy

Tristan Harris was a cookie-cut Silicon Valley entrepreneur: He studied computer science at Stanford; He built a startup for quick content search; His startup was bought out by Google; At Google, he worked on improving their e-mail. Tristan Harris was not a writer.

But then he did decide to write.

He put together a 141-page presentation urging big-tech companies to take more responsibility for how their technology manipulates users’ attention. He sent the presentation to a few of his co-workers, who then forwarded it to some more people. …

Kids learn how to launch a new business within days.

Samia is 17, Bill is 15. They live in London and attend different schools. Together, within two weeks, they’ve created and launched a business with proven demand. How cool would it be to know exactly how they did it?

As part of a work experience scheme, Bill and Samia had a short internship. Their brief was to create a new product or service for the sneaker industry in less than 2 weeks, and then pitch it to adidas.

I know many people with ideas for new businesses. Their owners rarely…

What makes a skill useful to your long-term career?

My biggest fear growing up was that I would end up useless.

I couldn’t see why anyone would pay for doing things I considered fun. I didn’t feel like I knew anything particularly useful either. What if I wouldn’t be able to earn any money? What if I would end up a drifting outcast ?

I don’t know if anyone else felt like that as a child. But lots of people must have, because I see how many are worried of the very same things as adults. …

Useful for NLP. Not that complicated.

Although we read, write and speak in sequential order, in practice words are aligned in a hierarchy. As we master our native tongue, this hierarchy becomes second nature, to the point we rarely have to stop and think which words should go where to form a complete sentence.

Parse trees are a way of visualising this hierarchy explicitly, in a tree graph.

Until a few years ago, lots of natural language processing (NLP) involved parsing sentences into such graphs and fiddling with them. …

30% of financial headlines fit a specific pattern.

Over the past few years, financial-news sentiment analysis has taken off as a commercial natural language processing (NLP) application.

Like any other type of sentiment analysis, there are two main approaches: one, more traditional, is by using sentiment-labelled word lists (which we will also refer to as dictionaries). The other, is using sentiment classifiers based on language models trained on huge corpora (such as Amazon product reviews or IMDB film reviews).

For domain-specific sentiment analysis, these latter language models tend to perform poorly. Hardly a surprise: a medical article reads nothing like a film review. In this respect, transfer learning…

Vered Zimmerman

Paying attention.

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