Cloud Computing


Voices in AI – Episode 37: A Conversation with Carolina Galleguillos

Today’s leading minds talk AI with host Byron Reese

In this episode Byron and Carolina discuss computer vision, machine learning, biology and more.

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Today’s leading minds talk AI with host Byron Reese

Byron Reese: This is Voices in AI brought to you by Gigaom, I’m Byron Reese. Today our guest is Carolina Galleguillos. She’s an expert in machine learning and computer vision. She did her undergrad work in Chile and has a master’s and PhD in Computer Science from UC San Diego. She’s presently a machine learning engineer at Thumbtack. Welcome to the show.

Carolina Galleguillos: Thank you. Thank you for having me.

So, let’s start at the very beginning with definitions. What exactly is “artificial” about artificial intelligence?

Well, I read somewhere that artificial intelligence is basically trying to make machines think, which is very “sci-fi,” I think, but what I’m trying to say here is we’re trying to automate a lot of different tasks that humans do. We have done that before in the Industrial Revolution, but now we’re trying to do it with computers … Read More »


Voices in AI – Episode 37: A Conversation with Mike Tamir

Today’s leading minds talk AI with host Byron Reese

In this episode, Byron and Mike talk about AGI, Turing Test, machine learning, jobs, and Takt.

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Today’s leading minds talk AI with host Byron Reese

Byron Reese: This is Voices in AI, brought to you by Gigaom. I’m Byron Reese. I’m excited today, our guest is Mike Tamir. He is the Chief Data Science Officer at Takt, and he’s also a lecturer at UC Berkeley. If you look him up online and read what people have to say about him, you notice that some really, really smart people say Mike is the smartest person they know. Which implies one of two things: Either he really is that awesome, or he has dirt on people and is not above using it to get good accolades. Welcome to the show, Mike!

Mark … Read More »


Digital Transformation 101: What are we trying to transform, and why?

It’s pretty easy to be a digital transformation consultant these days. Here’s what you do.

First, you report on the amount of data growth, the increasing rate of change and other exponential factors; you flag up the massive growth of recent, tech-first companies such as Amazon and Alibaba (whilst carefully ignoring those who tried and failed to follow similar models); you list out conveniently acronymised manifestations of technological progress — Social, Mobile, Analytics and Cloud. Oh and IoT. And AI. You get the picture.

Having engendered a suitable level of fear and uncertainty among your target audience, namely executive decision makers (who happen to control consulting budgets), you go in with the scoop: that the only possible response is to transform. Not to tweak, nor encourage stepwise progress, but to make a ground-to-sky, soup-to-nuts matrix-style inversion of the entire organisation.

How should we … Read More »


Is enhanced reality an AR/VR cop-out?

Watch out, there’s a new term on the block. Even as the initial flurry of excitement over Oculus-primed virtual reality seems to be in a perpetual state of prototyping, and as other forms of augmentation are hanging about like costume options for Ready Player One, discussion is turning to enhanced reality. I know this not because of some online insight (Google Trends isn’t showing much), but because it has come up in conversation more than once with enterprise technology strategists.

So, what can we take from this? All forms of adjusted reality are predicated on a real-time feed of information that brings a direct effect to our senses:

At one end of the scale, we have fully immersive environments known as Virtual Reality (VR). These are showing themselves to be enormously powerful tools, with potential not just in gaming or architecture but … Read More »


How Machines Learn: The Top Four Approaches to ML in Business

Machine learning sits at the forefront of innovation across a growing number of industries in today’s business world. Still, it’s a mistake to think of machine learning as one monolithic business solution — there are many forms of machine learning and each is capable of solving different sets of problems. The most popular forms of ML used in business today are supervised, unsupervised, semi-supervised, and reinforcement learning. At Vidora, we’ve used these techniques to help Fortune 500 partners solve some of their most pressing problems in innovative ways. This article draws from our experiences to demystify these four common approaches to ML, introducing practical applications of each technique so that anyone in your organization can recognize how machine learning can enhance your business.

Machine Learning at a Glance

Machine learning is an approach to Artificial Intelligence which borrows principles from computer science … Read More »


Lambda is an AWS internal efficiency driver. So why no private serverless models?

I’ve been in a number of conversations recently about Functions as a Service (FaaS), and more specifically, AWS’ Lambda instantiation of the idea. For the lay person, this is where you don’t have to actually provide anything but program code — “everything else” is taken care of by the environment.

You upload and press play. Sounds great, doesn’t it? Unsurprisingly, some see application development moving inexorably towards a serverless, i.e. FaaS-only, future. As with all things technological however, there are plusses and minuses to any such model. FaaS implementations tend to be stateless and event-driven — that is, they react to whatever they are asked to do without remembering what position they were in.

This means you have to manage state within the application code. FaaS frameworks are vendor-specific by nature, and tend to add transactional latency, so a re good for … Read More »