NFTs are making a big splash in the tech world. Most of the hubbub has been about the sale of digital art. However, while researching an article I wrote on how NFTs work, I found loads of more ‘out-there’ uses for the tech.

Exchanged at a wedding

Two employees of the Cryptocurrency exchange platform Coinbase exchanged NFTs at their wedding ceremony. The couple minted two tokens called ‘Tabaat’, the Hebrew word for ‘ring’, and commissioned a symbolic animation to the NFT. Only two tokens have been minted and no more can be made. The exchange is immortalized on the blockchain for anyone to see.

The Software and Hardware I learned about during my degree is inside prison-sentence recommendation algorithms, self-guided missiles, and self-driving cars and yet very little time was devoted to discussing ethics. Instead, I explored right and wrong in my field through some extra-curricular reading. Here is a selection of books of some of the books I enjoyed:

Hello World by Hannah Fry

‘Hello World’ is an accessible introduction to the use of algorithms, AI, and Machine Learning in the real world. Fry shows how these powerful tools can be used for both good and evil, how they can replace humans, and, crucially, the situations where human…

Streamlit is a python library used to quickly build interactive dashboards for the web. The gallery of dashboards on the Streamlit website shows them being used for science communication, data analysis, and displaying machine learning models in action. I opted for a less serious topic to teach myself how to use the library. I found a dataset of all the dialogue in the original trilogy of Star Wars films and decided to build a dashboard exploring who says what and how.

If you want to jump ahead and see what the…

Tech and Art aren’t fields that intersect very often but a technology called NFTs have made a big splash in both recently. The auction of several pieces of digital art, as well as Twitter CEO Jack Dorsey’s first tweet, have been widely reported. Many see NFTs as a win-win for digital artists who struggle to get compensation for their work and wealthy millennials who want to collect a part of the digital milieu. However, there have also been concerns raised about how sensible all this money flying around is as well as the hidden impact on the climate caused by…

At the start of lockdown my boyfriend Blair asked me to help him build a website. He had one already on WordPress but wanted to make a new one from scratch so he had more control, and as an opportunity to learn some coding (he’s an Interior Designer). I’d built websites before and considered myself a good explainer (and a good boyfriend) so of course, I said yes.

The experience, however, had some bumps. Working remotely and with a non-techy person proven to be an unexpected challenge. …

When Ward Cunningham coined the phrase technical debt, evoking financial debt was intentional; we accrue technical debt when we take shortcuts that grant us some immediate benefit (ship-ability, development time, market competition) but incur interest payments that drain on our resources [1]. The early days of Facebook provide a good example: PHP was used as a framework for rapid development whilst Zuckerberg rapidly experimented with new features but eventually, this proved too great a drain on scalability and performance, and the debt was re-payed by switching to C++[2]. …

Like many gamers in 2021, I’m reeling from a disappointment. For those having lived under a rock, December 2020 saw the release of Cyberpunk 2077 by polish game studio CD Projekt Red. A leap in storytelling, gameplay, and immersion had been promised and, prior to release, Cyberpunk picked up a slew of ‘gamers choice’ and ‘most anticipated’ awards voted on by consumers who believed in that promise. Over 8 million people (me and my partner included) pre-ordered and went to bed at night dreaming of Night City.

The reality was more of a nightmare. The released game ran poorly on…

You’ll have probably heard of Neural Networks, you might have even used them. But how did this machine learning model come about? There were a series of inventions and incremental steps that led to the models we have today.

1847

Louis Augustin Cauchy outlined a process called Gradient Descent to find a minimum of a function with multiple variables.

1949

Psychologist Donald Hebb suggested that neural connections are strengthened when used and that new information permanently modifies the cellular structure of the brain. His ideas of a Hebbian Network would go on to be applied to artificial neural networks.

1954

Farley and Clark…