This is just the beginning: Telegraph’s Fabio Colasanti on AI in the media industryThis is just the beginning: Telegraph’s Fabio Colasanti on AI in the media industry
This is just the beginning: Telegraph’s Fabio Colasanti on AI in the media industry
June 30, 2016
Following The AI Summit in London in May, AI Business has interviewed attendees from a number of different industry sectors – from finance and professional services through to retail, utilities and several more.
The media industry is a key sector for AI application as well as its public perception, so we were very excited to catch up with Fabio Colasanti, Knowledge Architect and hands-on technical lead at Telegraph Media Group.
At TMG, Fabio specialises in semantic technologies and big data analytics as foundational pillars to enterprise-grade knowledge platforms. He also has a keen interest in evolutionary architecture, domain driven design and agile methodologies as key risk management techniques in software delivery.
We begin by looking at the bigger picture, as Fabio shares his thoughts on the broad impact of AI on the enterprise.
“Let's be clear on one important point: AI is not going to put anyone out of work. It is not a replacement for people and we should not see it as a threat. Ultimately, AI is about using machines for what they are best at: computation, evidence-based prediction, automation of tasks, correlation of facts, accumulation and exploitation of data to the algebraic maximum.”
Fabio sees the adoption of AI in our machines inevitable, and their influence on a business’s future undeniable: “Any business that deals with any of these tasks is bound to adopt AI in one form or another, sooner or later”, he explains. “The quality of the solution and the commitment to it are very likely to shape the evolutionary curve of the business, even in the short/medium term.”
In terms of the challenges faced by the enterprise in adopting AI, Fabio finds that many of the technicalities behind AI are problems largely solved – while accepting that they are still very much in evolution.
But he points out “one key gap”, and explains it in depth:
“On the data acquisition front, alongside more matured practices (NLP, text analytics, Information Retrieval) new ones have emerged thanks to the boost from Big Data and distributed computing: continuous streaming from near-ubiquitous sensors, image and voice recognition, open data.
“Similarly, at the other end of the spectrum, neural networks and cognitive modelling are established techniques that add to well-understood prediction and behavioural models, sentiment analysis and quantitative forecast.
“Right in the middle there is Knowledge Representation theory, and that's where we must now turn our focus to. Given the right input, the ability for a machine to behave ‘intelligently’ is a function of its inferencing capability and the quality of its reasoning engine – which in turn depends on highly expressive data models. Seems trivial, right? Well, that's what most business don't do enough of.
“We are good at harvesting data, we're good at analysing it, and we know how to predict outcomes from it. Now we must get better at injecting meaning into our data, transforming raw data into semantically-linked information that intelligent agents can reason upon. Once we do that, once we make explicit the nature of information within a context of meaning, then AI will really blossom.”
Using AI to inject meaning into data is a function that could prove invaluable across the enterprise. But how will the media industry specifically change by adopting AI? Rather than simply looking ahead to the future, Fabio points out the impact AI is already having in the present:
“The media industry has already adopted AI. Think text analytics and auto-annotation for semantic mark-up of content; think highly personalised recommender systems that search, package and deliver relevant content to the relevant audience based on personal interests, past behaviour and content features.”
And this is just the beginning, he continues: “As more and more structured meaning is injected into content metadata, machines will thrive in a space of rich context, reasoning their way through networks of knowledge to enable the next generation of AI-driven content delivery.”
The Telegraph is making its own advancements, of course, as Fabio explains that “The Telegraph itself has its own incredibly talented data modellers, knowledge architects and data scientists for delivering and researching innovative data-driven solutions.”
The impact of artificial intelligence on business, and the challenges that lie ahead in its implementation, were two of the key factors addressed at The AI Summit in London. Fabio summarises his thoughts from the event and closes with his overall perspective:
“There is an exciting vibe of opportunity pervading the scientific community. The AI Summit was a fantastic forum for decision makers and business execs to see some AI in action, and to witness some very real challenges being solved by very real AI implementations, and ultimately be inspired in their business strategy.
“AI is here, it's very real, and – to put it in Game Theory terms – is very much a ‘strictly dominant strategy’ for all those who believe intelligent agents to be a key competitive advantage for their business strategy.”
We spoke to Fabio after he attended the inaugural AI Summit in London on 5 May together with over 400 other influential AI and business leaders. The second, larger AI Summit takes place in San Francisco on 28-29 September. To find out more, and to join us at the Fort Mason Center in September, visit: theaisummit.com
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