This blog continues from GPT3 and AGI: Beyond the dichotomy – part one

GPT3 and AGI

Let’s first clarify what AGI should look like

Consider the movie ‘Terminator’

When the…

Background

Earlier this week, I spoke at an interesting online event organized by Khaleej times in the UAE (UAE’s longest running daily English newspaper).

This two-part blog is based on the talk. I addressed a hard topic – and one which I hope sparks some…

I was asked this question: What is the connection between AI, Cloud-Native and Edge devices?

On first impressions, it sounds like an amalgamation of every conceivable buzzword around - but I think there is a coherent answer which points to a business need. 

Let us…

I like to approach algorithms from the perspective of problem solving. I created this list from a Mc Kinsey document (link below). It’s a good indicative approach. In practice,

Background

Last week, the UK witnessed chaos over exam results (GCSE and A-levels).

The fiasco also provided a textbook case on how to build a biased algorithm.

Sadly, this will be the shape of things to come.

These decisions were overturned because of the backlash – but many more…

In my previous blog what is driving the innovation in nlp and gpt3 , I talked about how GPT3 has evolved from the basic transformer architecture.

Based on that blog, a start-up approached me saying that they had an idea which they felt could only be implemented by GPT3.

They were eagerly waiting to be approved (isn’t everybody - he…

2019 and 2020 have seen rapid strides in NLP

What’s driving the rapid strides in NLP and will this trend continue?

Here is a simple way to explain the rise and rise of NLP

Today, GPT-3 is displaying some amazing results. Some call it more like AGI (Artificial General Intelligence). Created by OpenAI with a large investment from Microsoft, GPT stands for Generative Pretrained Transformer

The three words offer a clue to the success and future…

In this post, we explore a new python package for feature engineering

Feature engineering is the process of using domain knowledge of the data to transform existing features or to create new variables from existing ones, for use in machine learning. Using feature engineering, we can pre-process raw data and make it suitable…

Introduction

I had this conversation some time ago with an Engineer who came from a traditional background.

By that I mean, he had been in the same industry (heavy engineering) for 30 years.

Of these, he had been in the same company for 25 years (and this was his second job).

After understanding from me about data science, he said that as an engineer, he did…

Earlier this week, I was speaking at an event on AI for Real Estate where I showed an example from a BBC clip which said that “central London is now a ghost town” (due to COVID 19)

A few months ago, this headline would have been laughable

In London, central London and the London underground are a key fabric of daily…

I have been reading a book recently about algorithms in the wider sense

(40 algorithms every programmer should know -book and github link below)

I spend a lot of time with algorithms considering my teaching (AI at University of Oxford).

For Machine Learning and Deep Learning, we need to study a…

In the paper A survey on bias and fairness in machine learning.- the authors outline 23 types of bias in data for machinelearning. The source is good – so below is an actual representation because I found it useful as it is

full paper link below

1) Historical Bias. Historical bias is the already…

Background

Anomaly detection for IoT is one of the archetypal applications for IoT.

Anomaly detection techniques are also used outside of IoT.

In my teaching at the #universityofoxford - we use anomaly detection as a use case because it brings together many of…

Recently Springer made some good books on maths free to download.

Competitive programming strategies are useful for many data science interviews and they help to improve your maths foundations.  There are not many books on this subject (although there are many good websites and YouTube resources).

So, I hope you find this book…

I like this image from the twitter feed of the Paris based Venture Capitalist Michael Jackson

It shows that everyone wants to be an ‘AI start-up’ - but only when it suits them! 

So, how exactly do you build (and identify) an AI start-up

I always like to start off with a set of ground…

Last week,  we heard (from journalists!) that journalists at MSN are being replaced with AI.

I think this is shape of things to come

The announcement highlights a wider trend i.e. how every…

In various formats, one of the most frequent questions I am asked is the equivalent of:

“Can you recommend a free self-paced learning path for #machinelearning and #deeplearning?”

In this post, I attempt an answer

This is based on my work / teaching students primarily at Oxford University, but I…

Introduction

In this post, I argue that

• The idea of AI Superpowers could also apply to people and not only nations.
• Post COVID the biggest change will be the loss of the factory assembly line (the 1920s Henry Ford model and Frederic Taylor's division of labor ideas)
• A new class of ‘worker’ - if we may call them…

I am currently exploring this idea in a paper

Could your personality decide how you can collaborate with AI in future jobs?

I am a strong believer in a mode where humans and AI work together and collaborate 

I also believe that if we can master this skill, we can bring manufacturing jobs back from offshore destinations

In the book…

For the first time, I taught an AI for Cyber Security course at the University of Oxford.

I referred to this paper from Johns Hopkins which covered Deep Neural networks for Cyber Security (A Survey of Deep Learning Methods for Cyber Security) – references below where you can download the full…