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Artificial Intelligence, Deep Learning, and the Arms Race to Control Tech’s Future

The current state of artificial intelligence in 2016

Artificial Intelligence represents the next chapter of the Information Age, and Google, Microsoft, Amazon, IBM, and others are engaging in an arms race to control the platform that dictate tech’s future writes the New York Times. “The relationship between big companies and deep machine intelligence is just starting.”

So, what counts as artificially intelligent anyway? The Verge explains the difference between machine learning, deep learning, and neural networks, how they work, and why the future of AI is likely to be more subtle than you think. The next wave in technology isn’t about the technology, but rather the market that emerges from the technology.

Deep learning is “a killer technology,” Nvidia’s CEO says in a Fortune article that covers all things AI, data centers, autonomous vehicles, and more. While AI is still in its infancy, the road to super intelligent apps and machines is starting to come into focus.

When you’re ready to deeply learn more, this eBook will teach you how to use deep learning to solve problems related to image recognition, speech recognition, and natural language processing.

tl;dr A Googler explains deep learning in just one minute

Did you enjoy this? Consider joining Emergent Future, a weekly, hand-curated dispatch exploring technology through the lens of artificial intelligence, data science, and the shape of things to come. Emergent Future is powered by Algorithmia, an open marketplace for algorithms, enabling developers to create tomorrow’s smart applications today

Terminating Tay – A Microsoft AI Experiment Gone Wrong

Tay, the Microsoft AI Bot for Twitter

You Might Have Heard: The Microsoft AI experiment with Tay, their machine learning Twitter bot, ended after a mere 24-hours. The company pulled the plug when she almost immediately turned into a sexist, racist Nazi. Tay was suppose to learn how to communicate like a human by engaging in conversations with Twitter users.

“This gets to the underlying problem,” Vice argues. “Microsoft’s AI developers sent Tay to the internet to learn how to be human, but the internet is a terrible place to figure that out.”

The New Yorker writes that “Tay’s breakdown occurred at a moment of enormous promise for A.I.” Earlier in the week, an AI-written novel passed the first round of a literary competition in Japan, and last week AlphaGo, the AI from Google’s DeepMind,defeated the top-ranked Go player in the world.

As information destined for humans is increasingly handled by AI’s, the need for an open dialogue about the ethics grows. Google and DeepMind still haven’t revealed who sits on their AI ethics board.

+ A question of lesser importance: why are AI’s like Siri and Cortana so clever, but so bad at empathy anyway? A recent study might hold the key.

Did you enjoy this? Consider joining Emergent Future, a weekly, hand-curated dispatch exploring technology through the lens of artificial intelligence, data science, and the shape of things to come. Emergent Future is powered by Algorithmia, an open marketplace for algorithms, enabling developers to create tomorrow’s smart applications today

Why Algorithms as Microservices are Changing Software Development

We recently wrote about how the Algorithm Economy and containers have created a fundamental shift in software development. Today, we want to look at the 10 ways algorithms as microservices change the way we build and deploy software.

10 ways the algorithm economy and containers are changing how we build and deploy software today


Peter Sondergaard from Gartner has been the main thought leader of the Algorithm Economy, and how companies can use algorithms to extract value from their data.

Peter Sondergaard Senior Vice President, Gartner “Data is inherently dumb. Algorithms are where the real value lies.”


Google, Facebook, Amazon, Netflix and others are using algorithms to create value, and impact millions of people a day.

Algorithmic intelligence is at the core of today’s most important companies


The algorithm economy and containers allow developers to run algorithms as microservices, which means code can be written in any programming language, and then seamlessly united across a single API.

Three fundamental shifts in technology: ● The Algorithm Economy ● Containers ● Microservices


The algorithm economy enables a marketplace where easy-to-integrate algorithms can be made available and easily stacked together to manipulate data, extract key insights, and solve problems efficiently. 

The Algorithm Economy The next wave of innovation, where developers can produce, distribute, and commercialize their code


Containers wrap applications, services, and their dependencies into a lightweight package that runs like a virtual machine. 

Containers Lightweight virtualization that bundles all the application logic, dependencies, libraries, etc. into a single package running in the cloud


Microservices decouple modules from a monolithic codebase, reducing fragility in the codebase, and ensuring each service acts a smart endpoint.

Microservices An architecture where the various functions of an app are unbundled into a series of decentralized modules, each organized around a specific business capability


When algorithms run as microservices, we ensure code is dependency-free, interoperable, and composable.

Algorithms as containerized microservices ensure interoperability


Code is always live, and available to use without ever having to manage or provision servers. 

Code is always “on,” and can auto-scale in the cloud without ever having to configure, manage, or maintain servers and infrastructure


By running algorithms as microservices, we also allow companies to focus on their data, while the algorithm economy supplies the algorithms needed.

The algorithm economy allows for the building blocks of algorithmic intelligence to be made accessible, and discoverable through marketplaces and communities


The fundamental shift of container technology, the algorithm economy, and algorithms packaged as microservices creates an environment where rapid prototyping has never been easier due to a reduction in the infrastructure needed to build and deploy apps.

Containerizing algorithms as microservices makes code accessible via an API, and hosted on scalable, serverless infrastructure in the cloud

Liked this? Get our Algorithms as Microservices deck here.

AlphaGo’s Historic Victory, The Brain vs Deep Learning, and more from the Department of Bots

You may have heard about AlphaGo: Go has officially fallen to machines, just like Jeopardy did before it to Watson, and chess before that to Deep Blue. Now that artificial intelligence has mastered Go, New Scientist asks what game should it take on next. Deep-Q is learning not only Pong with Tensorflow and PyGame, but also Flappy Bird. If that wasn’t enough, here’s a timeline of artificial intelligence victories from 1997-3041. You read that correctly.

Department of Bots
Motherboard argues that joke-telling robots represent the final frontier of A.I., since humor requires self-awareness, spontaneity, linguistic sophistication, and empathy. That’s not an easy task for a bot. Speaking of, why do developers love chatbots so much? Facebook’s Messenger Bot Store is coming, and it could be the most important launch since the App Store. We’re believers, but will robots take your job?

The Brain vs Deep Learning
Want to know why the singularity is anywhere but near? Read this great examination of the brain’s electrochemical and biological information processing pipeline as it relates to deep learning. There are a few problems with consciousness as it relates to superintelligence. The DeepMind founder has plans beyond just Go. He’s designing for healthcare, robots, and your phone. Use Neural Doodle to turn your two-bit doodles into fine artworks with deep neural networks. Very cool.

Point/Counterpoint
Harvard Business Review argues that you need an algorithm, not a data scientist. Not so fast, says Data Science Central. You need a data scientist, and then an algorithm. But, what you’re really looking for is the Algorithm Economy.

Debunking A.I. Myths
Thanks to the pioneering work of scientists, a clearer picture is emerging about A.I., and the most common misconceptions and myths. These are the 7 biggest myths about A.I., and 17 predictions about the future of big data.

The Internet of (Broken) Things
A security expert hacked a hotel’s Android-based light-switch tablet, and then gained control to the electronics in every single room. Oof. This is going to be a continual challenge for companies as they integrate digital technologies in meaningful ways to enhance homes and improve their lives. Here’s your chance to meet the 10 pigeons(!) live tweeting London’s air pollution. Oh, and by the way, they’re wearing tiny backpacks.


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The Emergent Future and the Shape of Things to Come

We’ve started a newsletter called the Emergent Future, which is a weekly, hand-curated dispatch exploring technology through the lens of artificial intelligence, data science, and the shape of things to come. EF is published every Tuesday and goes out to Algorithmia subscribers. Stay on top of emerging trends by subscribing to Emergent Future today. 


Google vs Go

Google's DeepMind defeats legendary Go player Lee Se-dol in historic victory.
You might have heard: Se-dol finally won his first match, after losing three in a row in a best-of-five competition. The two meet for the final time Today.
+ ‘I’m in shock!’ How an AI beat the world’s best human at Go


The Future of Computing

The Economist weighs in now that the era of predictable improvement in computer hardware is ending.
+ Chris Dixon: What’s Next in Computing?


How To Think About Bots

In order to better comprehend the possibilities, and perils, of social bots we must ask about their design, implementation, regulation, and ethics.
+ Motherboard presents In Our Image, a week of stories on AI


Minecraft Will Soon Be Able to Play Itself

Microsoft is using Minecraft to train artificial intelligence to play the hugely popular game.
+ Microsoft invites artificial intelligence developers to test their creations within Minecraft's virtual landscapes.

Is This Year the Internet Finally Learns to See?

Initially, the Internet was built for text, and technology has learned how to read at a pretty advanced level. However, the web has become increasingly visual, and tech has not fully kept up: the Internet can read, but it can’t see.
+ Using Neural Networks to Combine Random Images