Series 2: What have we learned?

[Michael_Bird]

This series has been a wild ride! We've spoken to some of enterprise tech's brightest brains this season, and one thing they weren't short of was opinions! Innovation is coming thick and fast, and we've discussed 5G, supercomputers, AI, computer science, digital transformation, zero trust, blockchain, IOT, energy innovation, quantum computing, mixed reality, and everything in between. But there were a few topics that cropped up time and time again. So... what have learnt this season?

It today's episode, we draw insights from over 60 hours of interviews and discuss the big themes that our guests were keen to point out! Host Michael Bird discussing how artificial intelligence is making waves in every part of our society, what organisations can do to avoid using tech for tech's sake, and why education should be at the heart of any future-faced organisation.

Artificial Intelligence isn't going anywhere!

From deep learning AIs producing the human like text to swarm learning in industry, AI, machine learning, and automation are the words on everyone's lips. And for good reason! In regular organizations, AI is being used to make our jobs better by abstracting away the mundane tasks that we love to hate. However, the really exciting use cases are a little more out of this world!

We talk data centre automation with John Frey, telemedicine in space with Eng Lim Goh, supercomputers modelling cells with Jacob Balma, technology managing people with Mary Towers, AI and the jobs landscape with Matt Armstrong-Barnes... and more!

How can we innovate without using tech for tech's sake?

From high-cost 5G connectivity to frivolous use of IoT sensors and a whole lot of hoo-ha about blockchain, using tech for tech's sake should be avoided at all costs! Almost every new tech has its detractors and evangelists, but by getting overexcited by a potential solution, we risk creating answers to problems that don't really exist. Responsible and reasonable use of tech requires the ends fit the means. So, what are organisations to do?

We hear about the New York Times' 5G Lab's winning approach to R&D, stacking use cases with 5G Rural Dorset, building blockchain better with Bumble Bee Foods and Florian Buehr, and radical approaches to digital transformation with Dave Strong and Dan Broomham.

Masters of their own destiny: why education has never been more important

The tech world is moving at an incredible pace and that poses a challenge, no matter what the technology is. To effectively and successfully bring in new tech, we need specialists, but we also need generalists. Bridging the skills gap requires worker education, but a decline in computer scientists could spell trouble for the sector. Luckily, our guests had plenty to say on the topic!

We discuss skilling up the workforce with Dave Strong, Ray Beausoleil and Tony Stranack. Simon Peyton-Jones and Matt Armstrong-Barnes share their thoughts on computing education at school, and we hear inspiring words from quantum cryptographer Dr. Sarah McCarthy about how her mathematical ambitions found the perfect environment in quantum cryptography and computer science.

Key takeaways:

• Machine learning and artificial intelligence are part of almost every organisations reality or ambition.
• New technologies are coming thick and fast, but the most important skill we're going to need is the ability to start with a problem and find the appropriate solution, not the other way round
• Education requires collaboration - from computing in schools and engaging university students, to educating members of the workforce about the tech they're using and up-skilling and promoting specialists in emerging fields.

Links and Resources:

What is machine learning? | HPE

Revolutionising healthcare with Artificial Intelligence | HPE

Machines and AI Are Taking Over Jobs Lost to Covid | Alana Semuels, TIME

What is Digital Transformation? - Enterprise IT Definitions | HPE

The Trade Union Congress

Technology Managing People - The Worker Experience | TUC

The Ethical Institute for AI and Machine Learning

Why we should teach children to code | Simon Peyton-Jones

Computing At School

Get Involved | Teach Computing

Our Vision | Teach Computing

UK Computer Science National Curriculum