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There is no one moment when SaaS Software as a Service was conceived, because SaaS as a concept has a host of components; all of which have had to come together in the right context in order to produce value for any sector or vertical market. Different sectors have moved towards SaaS models at different speeds.

In technical terms, SaaS relies on cloud delivery at scale, a minimum degree of widely available connectivity, and enterprise-grade security. If any of these are weak, SaaS drops off the agenda.

Artificial intelligence (AI) in gaming isn’t a recent innovation. As early as 1949, mathematician and cryptographer Claude Shannon pondered a one-player chess game, in which humans would compete against a computer. 

Indeed, gaming has been a key engine of AI, and a proving ground for the simulations, constructed environments and tests of realism that are the foundation of virtual experiences. 

At Unbabel we’re avid users of Slack, coordinating hundreds of overlapping workstreams, keeping the growing team of a multinational startup all on the same page, and generally living out our internal culture: one that values continuous learning about the areas we work in and on, and seeks to discover new and better ways to work.

As we’ve grown, more voices have been added to one of our channels, #worth_reading rebellious academics, failed philosophers, restless souls, frustrated artists, and all-round geeks— and we think the collective curation here has now become a resource worth sharing more widely. 

So let’s look at what we shared this month: 

Building the world’s translation layer is a fantastic mission. For us, that means becoming a transversal and pervasive service which can remove communication barriers anywhere, anytime, using a combination of artificial intelligence technologies (machine translation and an assortment of machine learning mechanisms) and a growing global community of bilinguals. 

This also means ingesting, processing and distributing a massive amount of data per second while guaranteeing that our customers’ standards for quality and speed are met. 

It’s easy to lose ground in e-commerce. In a crowded market where customers can buy from a competitor as simply as following a link, retailers have to work hard. Every search term, product description and user pathway matters.

Not surprisingly, smart players have come to depend on the abundance of data consumers make available at every step of the business process. They deploy predictive analytics, machine learning and other Artificial Intelligence techniques to redefining the rules of the game, helping some stay ahead of the competition, and improving the customer experience overall. 

Here are just a few examples of how.  

The robots are coming. And they’re scary. That’s one of the conclusions of a survey commissioned by the UK’s Royal Society, which assessed the public’s perception of the risks and benefits of machine learning.But machine learning and robotics are just two components of AI, not the whole thing. And our perceptions of associated risk are magnified by a Hollywood sensibility. For example, the survey shows that we have a particular fear of predictive policing – the idea that government organisations will be able to make judgements about our propensity towards all sorts of anti-social behaviour (Minority Report) and even retaliate (Robocop).Ordinary consumers don’t yet understand AI– their view is dystopian; particularly as the press focuses on the relentless story that AI steals jobs. That’s understandable: one in six US workers drives for a living, and these jobs will undoubtedly be razed in a driverless future...

Translation services have traditionally been offered on a cost-per-word basis; and there are good reasons why. It’s transparent: we all agree on what words are, and it’s clear that more words require more effort. But if we look a little deeper, it doesn’t align well with the changing world.

Charging by the word is not new. In fact, part of the reason that we think it’s outdated is that the best example of charging by the word comes from 100 years ago the telegram. Because customers hated being charged by the word, a pioneer named Nelson E Ross carefully put together a guide to all the sneaky ways to avoid word fees while still communicating effectively. 

What if you found yourself in the middle of a crisis – and the only information available to you was in a language you couldn’t understand?

It’s a desperate thought, and yet one which is all too common. Natural disasters don’t respect borders. And we live in a globalised world where we travel, trade and make our homes in many other countries. In fact, practically every crisis will be affected by a language barrier.

We have a huge vision for Unbabel to provide human-quality translations at the scale of machine translation. But how do we know we’re doing a good job? 

For us, quality is a blend of having a good initial text to work from, feeding it through our domain-adapted machine translation, and then intelligently distributing these outputs to a curated community of editors, who we support with tools and aids that allow them to review, post-edit and approve the content as fast as possible.

First, here are the multiple ways that we measure, control and optimise quality across our language pipeline.