Algorithmia Blog

Emergent // Future: AI Goes All-In On Humans, Apple Partners on AI Ethics, Cancer-Classifying Neural Network

Issue 39
This week we look at how he world’s best
poker players are getting crushed by AI, why Apple joined the Partnership on AI, and how an algorithm is diagnosing skin cancer as accurate as dermatologists.

Plus! What we’re reading this week and things to try at home!

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AI Goes All-In On Humans ♥️♣️♦️♠️

The world’s best poker players are getting crushed by AI in a Pittsburgh casino.

Four poker players are playing against DeepStack, an artificial intelligence algorithm running on a supercomputer located 15 miles away.

With just one day left in the 20-day tournament, the algorithm is up more than $1.6 million over the humans.

While a crushing defeat for humanity, it’s a major milestone for AI.

Machines have already become smart enough to beat humans at other games such as chess and Go, but poker is more difficult because it’s a game with imperfect information. With chess and Go, each player can see the entire board, but with poker, players don’t get to see each other’s hands.


Apple Partners on AI Ethics 🙌

Apple joined Google, Amazon, Microsoft, Facebook, and IBM to keep an open dialogue about the ethics of AI.

The Partnership on AI was formed in September 2016 with the goal of establishing best practices on the challenges and opportunities within the field.

Think of this group as a United Nations-like forum for companies developing AI  – a place for self-interested parties to seek common ground on issues that could do great good or great harm to all of humanity.

This is the second signal we’ve seen from about Apple becoming less secretive with their research. The big news to spill out of NIPS 2016 was Apple allowing its artificial intelligence teams to publish research papers for the first time.


Cancer-Classifying Neural Network 👨‍⚕️👩‍⚕️🏥

Stanford researchers have trained a single convolutional neural network to diagnose skin cancer as accurately as dermatologists.

The algorithm was trained from images directly, using only pixels and disease labels as inputs.

It was fed a dataset of nearly 130,000 images of skin disease labeled with 2,032 different diseases.

In three tests, the algorithm matched the performance of dermatologists, demonstrating an artificial intelligence capable of classifying skin cancer with a level of competence comparable to dermatologists.

This single CNN is capable of running on smartphones, potentially providing low-cost universal access to diagnostic skin care.


What We’re Reading 📚


Things To Try At Home 🛠


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. 

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