It's been a busy year, even if interrupted slightly by you know what... BUT, the support for our AI blog has not wavered.
Below we have rounded up our 15 most-read blogs of the year, including must-read papers suggestions from AI experts, advice for those starting out in AI, Netflix predictive algorithms and more. See a summary of each blog and link below!
Back in May we gathered a group of our industry friends and AI experts to ask them what they believe are 'must-read' papers. The experts from OpenAI, Uber, Gartner and more suggested a wide-variety of topics, including Gradient-based Hyperparameter Optimization through Reversible Learning, Modeling yield response to crop management using convolutional neural networks and more. See the full list of 13 papers here.
Released late in 2019, the list celebrating diversity in AI noted those who we believed have pushed boundaries in the industry over the past 12 months. This saw some great feedback, created connections between listed Women and acted as an educational tool for those looking to find new individuals to follow. See who made the list here.
Another blog which had over 10k views in the first week was our must-read AI book in 2020. We had many suggestions for inclusions & aimed to keep the list varied enough to appeal to all levels of AI understanding. See the whole list including literature of big data inequality, Emotion AI and more. See the full list of titles here.
One of the final expert-led blogs of 2020 saw us ask our community their greatest two pieces of advice for individuals starting out their career in AI. The contributors from MILA, DeepMind, Target and more offered their two cents for those interested in working in AI. See all of the advice and tips here.
After the success of the first 'must-read' papers blog earlier in the year, we asked 11 new experts for their recommendations. The contributors in this excerpt suggested papers from 'A Simple Framework for Contrastive Learning of Visual Representations' to 'f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization' and more.
Following on from the 2019 list, we gathered all of the statistics and markers for investments, venture capital, seeding rounds and more for AI startups. This resulted in our top 10 cities blog for 2020. Of course, there are some of the normal suspects in there, but some surprises included too. See the full list of cities here.
We were on the verge of our first lockdown in the UK and many were starting to work from home and stockpile, so we decided to stockpile the best AI resources including books, podcasts, videos, papers and more that could keep people busy in the early days of the pandemic. See our list here!
From new to old, we rounded up some of the most interesting AI conversations in podcast form. Whilst papers and blogs are an extremely useful means of finding out the latest AI news, sometimes it's a little easier to digest in audio form. The podcasts included in this list were chosen for not only being the best in regard to content, but also for making some of the more complex concepts in the industry digestible for all. See our list of top podcasts here.
We have put together lists of Women who we believe are pioneering the field of AI in the current day, but this blog was a twist. We decided to put together a list of pioneers in Computer Science that facilitated and shaped the work we do today. Included on the list are Mary Cartwright, Katherine Johnson and more. See our full list of pioneering women here.
Following the success of our first 'top AI books' reading list, we thought we should put ten more great books forward for our readers. The below books include a short summary & link to the place of free download or purchase. Start your AI, ML and GAN education here.
Of the many Women in AI lists we have done, we'd yet to see one focussed on the lone star state. Included in this list are 30 Women that we believe have spearheaded AI development in Texas. From academics to AI leads at fortune 100 companies, this list covers a wide range of industries and job roles. See the full list here.
We were delighted to have the chance to meet with Lex Fridman early in 2020 for a workshop on Reinforcement Learning. At the time of this workshop, the MIT researcher highlighted the standing of Reinforcement Learning and Deep Reinforcement Learning at the time as well as future predictions. You can see the full meeting notes from Lex here.
Wait, how did Netflix know I wanted to watch that? Spooky... right? Well, not exactly. Through the use of Machine Learning, Collaborative Filtering, NLP and more, Netflix undertake a 5 step process to not only enhance UX, but to create a tailored and personalised platform to maximise engagement, retention and enjoyment. Read our insider info on Netflix here.
We have seen that this year, anything is certainly possible. That said, we thought we would ask our community of AI expert friends what they thought on the topic, asking - 'Do you think we will see another AI Winter? If so, why? The answers vary from those are skeptical to those that think it's a real possibility. Read the experts opinions here.
Let's be honest, 2020 has been a bit of a mess, seemingly, on the surface at least, bringing the world to a halt. That said, behind the scenes, AI has been progressing as much as ever. Following on from our 2019 edition, we have highlighted 30 influential women in AI that have been working hard behind the scenes to keep the cogs turning. See the full list here.
Favourite Community Blogs
Alongside some of our most-read blog, we really liked the below AI blogs from some other community websites:
With so much to learn and so many advancements to follow in the field of data science, there are a core set of foundational concepts that remain essential. Twenty of these ideas are highlighted here that are key to review when preparing for a job interview or just to refresh your appreciation of the basics. Read more here.
The well-established technologies and tools around ETL (Extract, Transform, Load) are undergoing a potential paradigm shift with new approaches to data storage and expanding cloud-based compute. Decoupling the EL from T could reconcile analytics and operational data management use cases, in a new landscape where data warehouses and data lakes are merging. Read more here.
Exploring Scientific Literature on Online Violence Against Children Using Natural Language Processing
The following work is part of the Omdena AI Challenge on preventing online violence against children, implemented in collaboration with John Zoltner at Save the Children US. This article is written by Wen Qing Lim, Maria Guerra-Arias, Sijuade Oguntayo. Read more on this blog here.
This paper provides a categorization framework for assessing the safety posture of a system that consists of embedded machine learning components. It additionally ties that in with a safety assurance reasoning scheme that helps to provide justifiable and demonstrable mechanisms for proving the safety of the system. Read more on this paper here.
This edition of Your Guide to AI from Nathan Benaich brings you the State of AI Report 2020. For the third year running, Nathan and Ian Hogarth analyse the most interesting developments in AI over the last 12 months. See more on this report here.
Global spend on AI is predicted to be $98 Billion by 2023, up from 37.5 Billion in 2019. Maybe not unexpected for those witnessing it up close, but a whopping growth trajectory nonetheless. While machine learning models strive to mirror and predict real life as closely as possible, the people behind these models don't represent the real world. Despite this rapid forecasted growth, women still only make up a 12% of the ML workforce. Read more here.
AI is often framed as something that’ll change our future, but many people aren’t aware of quite the extent to which AI already used in society and everyday life. While it’s important to recognize that AI is still very much in its infancy in regard to large-scale change, there have been incremental advancements in recent years, which have somewhat gone under the radar for those not regularly perusing the latest AI news or working in said fields. To explore just how prevalent AI is in our everyday lives, we have collected five spaces in which AI is shaping consumer behavior and practices. Read more here.