This week we cover the historic AI partnership, look at the newAWS P2 GPU instances, ponder humanities mission to Mars, check in on chatbots, catch up on recent news from the Google Research Team, and recap the thoughts, ideas, and opinions inNotes from the Frontier.
Plus, our top projects to try at home, and favorite articles from the past week.
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Historic AI Partnership 👾
You Might Have Heard: Amazon, Facebook, Google, IBM, and Microsoft have formed a partnership to advance the public understanding of artificial intelligence.
The five tech giants are tasked with establishing best practices for dealing with the challenges and opportunities that AI presents. They’ve released eight guiding principles, which evoke Isaac Asimov’s original “Three Laws of Robotics.”
TechCrunch points out that “Data is becoming an important currency for the modern world. The data’s value is rooted in its applications to artificial intelligence. Whichever company owns the data, effectively owns AI. Right now that means companies like Facebook, Amazon, Alphabet, IBM and Microsoft have a ton of power.”
This is why it’s important to democratize access to state-of-the-art algorithmic intelligence.
Oh, and Apple refused to join new AI club. Go figure.
AWS P2 GPUs 💃🎉
AWS officially launched P2 GPU-backed instances to give large-scale cloud-based machine learning a boost.
Researchers and data scientists can now use the instances to accelerate a wide range of compute-intensive applications, like deep learning, genomics, and computational fluid dynamics.
The new instances can use up to eight NVIDIA Tesla K80 GPUs, which contain two Nvidia GK210 GPUs – that’s 16 GPUs running in parallel, folks.
Mission to Mars 🚀📡
Elon Musk announced his plans to colonize Mars and save humanity…
As part of his plan to make humans a multiplanetary species, Musk unveiled his giant rocket, spaceship, and the critical infrastructure needed to support the project.
The Interplanetary Transport System consists of four parts: the rocket, the spaceship, a fueling tanker, and “propellant depots.”
SpaceX plans to fly an unmanned spacecraft to Mars as early 2018. The flights would continue about every two years and, if all goes according to plan, would culminate with the first human mission to Mars in 2025.
Ultimately, SpaceX is planning for a time when any person can go anywhere they want in our vast Solar System—a new golden age for exploration, with uncharted physical frontiers in every direction.
Bots, Baby 🤖
Amazon unveiled their new $2.5 million “Alexa Prize,” a university competition to advance conversational AI by building bots that can converse coherently for 20 minutes.
They’re calling these “socialbots,” a new Alexa skill for having engaging conversation.
Students will use the Alexa Skill Kit to build bots for Alexa-powered devices like the Echo and Echo Dot, where users can say “Alexa, let’s chat about,” and then pick a topic or news event.
Speaking of bots, 45,000 developers are using Microsoft Bot Framework for Skype and other chat platforms. Facebook’s Messenger platform has 34,000 developers.
From the Google Research Blog 📝
A collection of recent datasets and papers from the Google Research team.
- Image Compression with Neural Networks
- Introducing the Open Images Dataset (dataset here)
- How Robots Can Acquire New Skills from Their Shared Experience
- A Neural Network for Machine Translation, at Production Scale
- Announcing YouTube-8M: A Large and Diverse Labeled Video Dataset for Video Understanding Research (dataset here)
Notes From The Frontier 🔮
The thoughts, ideas, and opinions from the Emergent // Future community on Medium.
The Amazon Dash Button. Another automation device?
Home automation is at an all time high, with a reach into the market of even the least tech-savvy consumers. (link)
What Machine Learning Will Do For Design
Machine learning is ready to collaborate with designers. Are you willing to let it? (link)
Since the introduction of the smartphone there has been a relative lull in the popular adoption of new technology that radically alters the way we interact with information. (link)
Recognizing Beer with TensorFlow
One of the demonstrations we have showcases a screen, with a camera which you can show a beer. The screen then recognizes the beer and gives you information about it. (link)
Image recognition is not enough
As with language, photos need contextual intelligence. (link)
Contribute your take on frontier technologies and their impact on society on Medium. We’ll share the most insightful posts and comments each week with more than 2k like-minded subscribers.
What We’re Reading 📚
- Why Deep Learning is Suddenly Changing Your Life. Decades-old discoveries are now electrifying the computing industry and will soon transform corporate America. (Fortune)
- Deep Fried Data. My dream for the web is for it to feel like big city. A place where you rub elbows with people who are not like you. Somewhere a little bit scary, a little chaotic, full of everything you can imagine and a lot of things that you can’t. (Idle Words)
- In the age of the algorithm, the human gatekeeper is back.The rise of algorithms has been relentless, but we need human input in our world of technological innovations. (Guardian)
- The Simpsons by the Data. Analysis of 27 seasons of Simpsons data reveals the show’s most significant side characters, a pattern of patriarchy, declining TV ratings, and more. (Todd W. Schneider)
- How front-end development can improve Artificial Intelligence? What’s holding back Artificial Intelligence? While researchers rightly focus on better algorithms, there are a lot more things to be done. In this post I’ll discuss three ways in which front-end development can improve AI technology: by improving the collection of annotated data, communicating the capabilities of the technology to key stakeholders, and exploring the system’s behaviors and errors. (Ines)
Try This At Home 🛠
- How to Solve FizzBuzz Using Machine Learning
- A deep learning software that easily generates images with a few brushstrokes
- Generating Faces with Deconvolution Networks
- Learning Reinforcement Learning, with Code, Exercises, and Solutions
- Graph Convolutional Networks – Intro to neural networks on graphs
- Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Curious? An implementation of Texture Networks, coming soon to Algorithmia. Get in touch if you want to learn more.
Emergent Future is a weekly, hand-curated dispatch exploring technology through the lens of artificial intelligence, data science, and the shape of things to come. Subscribe here.