Data science, artificial intelligence and pay-for-performance advertising.
Raytheon Artificial Intelligence Tools
Raytheon is developing AI to help manage battlefield data, as well as predict when planes need maintenance and to aid responses to humanitarian crises.
What is Quantum Computing?
A brief discussion about quantum computing and artificial intelligence.
The Coming Software Apocalypse

The problem is that programmers are having a hard time keeping up with their own creations. Since the 1980s, the way programmers work and the tools they use have changed remarkably little. There is a small but growing chorus that worries the status quo is unsustainable. “Even very good programmers are struggling to make sense of the systems that they are working with,” says Chris Granger, a software developer who worked as a lead at Microsoft on Visual Studio, an IDE that costs $1,199 a year and is used by nearly a third of all professional programmers. He told me that while he was at Microsoft, he arranged an end-to-end study of Visual Studio, the only one that had ever been done. For a month and a half, he watched behind a one-way mirror as people wrote code. “How do they use tools? How do they think?” he said. “How do they sit at the computer, do they touch the mouse, do they not touch the mouse? All these things that we have dogma around that we haven’t actually tested empirically.”
The findings surprised him. “Visual Studio is one of the single largest pieces of software in the world,” he said. “It’s over 55 million lines of code. And one of the things that I found out in this study is more than 98 percent of it is completely irrelevant. All this work had been put into this thing, but it missed the fundamental problems that people faced. And the biggest one that I took away from it was that basically people are playing computer inside their head.” Programmers were like chess players trying to play with a blindfold on—so much of their mental energy is spent just trying to picture where the pieces are that there’s hardly any left over to think about the game itself.
TLA+
TLA+, which stands for “Temporal Logic of Actions,” is similar in spirit to model-based design: It’s a language for writing down the requirements—TLA+ calls them “specifications”—of computer programs. These specifications can then be completely verified by a computer. That is, before you write any code, you write a concise outline of your program’s logic, along with the constraints you need it to satisfy (say, if you were programming an ATM, a constraint might be that you can never withdraw the same money twice from your checking account). TLA+ then exhaustively checks that your logic does, in fact, satisfy those constraints. If not, it will show you exactly how they could be violated.
The language was invented by Leslie Lamport, a Turing Award–winning computer scientist. With a big white beard and scruffy white hair, and kind eyes behind large glasses, Lamport looks like he might be one of the friendlier professors at the American Hogwarts. Now at Microsoft Research, he is known as one of the pioneers of the theory of “distributed systems,” which describes any computer system made of multiple parts that communicate with each other. Lamport’s work laid the foundation for many of the systems that power the modern web.
For Lamport, a major reason today’s software is so full of bugs is that programmers jump straight into writing code. “Architects draw detailed plans before a brick is laid or a nail is hammered,” he wrote in an article. “But few programmers write even a rough sketch of what their programs will do before they start coding.” Programmers are drawn to the nitty-gritty of coding because code is what makes programs go; spending time on anything else can seem like a distraction. And there is a patient joy, a meditative kind of satisfaction, to be had from puzzling out the micro-mechanics of code. But code, Lamport argues, was never meant to be a medium for thought. “It really does constrain your ability to think when you’re thinking in terms of a programming language,” he says. Code makes you miss the forest for the trees: It draws your attention to the working of individual pieces, rather than to the bigger picture of how your program fits together, or what it’s supposed to do—and whether it actually does what you think. This is why Lamport created TLA+. As with model-based design, TLA+ draws your focus to the high-level structure of a system, its essential logic, rather than to the code that implements it.
The Explainer: The Truth About Blockchain
True blockchain-led transformation of business and government is still many years away. That’s because blockchain is not a “disruptive” technology, which can attack a traditional business model with a lower-cost solution and overtake incumbent firms quickly. Blockchain is a foundational technology: It has the potential to create new foundations for our economic and social systems. But while the impact will be enormous, it will take decades for blockchain to seep into our economic and social infrastructure. The process of adoption will be gradual and steady, not sudden, as waves of technological and institutional change gain momentum.
You’ve Been Training AI For Free
Modern AI needs tons of data for training and quality control — and a lot of it is coming from human beings, whether it’s contract workers recruited from Amazon’s Mechanical Turk or regular users filling out a CAPTCHA.
What are the Ethical Concerns of Artificial Intelligence in Marketing?
The exchange of our personal data with marketing companies for services that makes our lives easier opens up ethical concerns. For AI to achieve its promise of true personalization and prediction, it needs a massive amount of data. You give up privacy for the power of AI.
Will Artificial Intelligence Take My Marketing Job? (Ep 3)
Artificial intelligence is intended to make lives better and more efficient, but it can replace tasks that can be automated. So there is a reality that companies will want to become more efficient by eliminating humans where they can, because if they don’t, their competitors will.
Some examples of jobs that may go away are telemarketing and writing earnings reports and media buyers and anything that a machine can do better.
How Can Marketers Use Artificial Intelligence? (Ep2)
AI needs to be solving a business problem or helping to achieve a goal more efficiently for it to make sense as a business application. Some examples touched upon in this video include using AI for recommendations, optimization and categorizations.
Machine learning can be defined as making predictions on future outcomes based on historical data. The key to machine learnings is that the machines are getting smarter and their predictions are getting better without any human intervention.
What is artificial intelligence in marketing? (Ep1)
In this 5-episode series, Paul Roetzer, Founder & CEO of PR 20/20, sits down with HubSpot Product Manager of Machine Learning, Kevin Walsh, to discuss the applications of artificial intelligence in digital marketing.
What is AI? To Paul, it is the umbrella term to encompass technologies and algorithms designed to make machines smart, with machine learning being the primary subset.
Machine learning can be defined as making predictions on future outcomes based on historical data. The key to machine learning is that the machines are getting smarter and their predictions are getting better without any human intervention.
