Most A.I. companies reveal very little about their algorithms in the name of intellectual property protection. How much of A.I. is “artificial,” and how much is manual labor?

New laws were important victories for personal privacy in a year that was otherwise marred by tech industry scandals, blunders, and all kinds of reminders of innovation’s creepy side. Here are a few recent developments worth keeping an eye on this year.

Researchers borrowed equations from calculus to redesign the core machinery of deep learning so it can model continuous processes like changes in health

As I reflect on 2018, a thought keeps occurring to me. History will probably regard this as the age of the troll. Not just this year — maybe this whole decade. It was a time when the world got…

Algorithms now know that people who buy fresh fennel are less likely to make home insurance claims, but they’re not smart enough to stop showing baby-related ads to women who’ve miscarried.

For the last couple of decades, ETL (extract, transform, load) has been the traditional approach for data warehousing and analytics. The ELT (extract, load, transform) approach changes the old paradigm. But, what’s actually happening when the “T” and “L” are switched?

QC is humanity’s next big step forward, but can we be good stewards of such power?

Excerpted from the book Life 3.0: Being Human in the Age of Artificial Intelligence. The rest of the book is about another tale — one that’s not fictional and not yet written: the tale of our own future with AI. How would you like it to play out? 

Two million people under the age of 25 will stop using the social network this year, research firm eMarketer predicted. For the first time, the majority of US internet users between the ages of 12 and 17 won’t use Facebook once a month this year.

We have a problem just now, in that many governments around the world just see Blockchain, Distributed Ledgers, Tokenisation — call it what you want — as just another series of technology that they have to adopt, and set up mechanisms for their industry to integrate it into new products.

The search for artificial general intelligence has been focused on various ways to mimic the human brain. This works for certain aspects of intelligence, yet we have failed to replicate the right parts of brain-like behavior necessary for all the powers we find in ourselves.

Artificial intelligence was born of organisational decision-making and state power; it needs human ethics, says Jonnie Penn of the University of Cambridge.

“The development of full artificial intelligence could spell the end of the human race…It would take off on its own and redesign itself at an ever-increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete and would be superseded.” — Stephen Hawking

Over the past few years, the Facebook feed has become a reviled part of pop culture–a symbol of everything people complain about when they think of the company, from opaque algorithms to political…

After reading this post, you’ll walk away with a stronger grasp of the following:

• What a distributed system is
• The properties of a distributed system
• What it means to have consensus in a distributed system
• An understanding of foundational consensus algos (e.g. DLS & PBFT)
• Why Nakamoto Consensus is a big deal

The Byzantine Generals’ Problem is analogous to solving consensus issues on the blockchain. The nodes must all agree on a certain set of rules, and be able to move forward by agreeing on a particular assessment of transaction information before it is added onto the chain. This is not easy — thousands of people use the network and must ensure that they agree on the validity of new information that’s to be added, on top of preventing bad actors from sabotaging the ledger and rewriting history. So, a specific type of consensus mechanism/algorithm must be adopted. This protocol enables a coherent group of network entities to work together in order to update the ledger in a secure fashion.

blockchains have several major technical barriers that make them impractical for mainstream use today.

Machine learning is one of the most exciting new features used in technology today. However, it is undoubtedly controversial too. At the moment, this controversy does not really come from the prospect of ultra-intelligent robots dramatically taking over the human race; instead, it’s because powerful technology like this can be used just as negatively by criminals, as it can be used positively by those with good intention. In this piece, I would like to explore the darker side: how criminals use AI illegally.

I have now come to the realization that human compatible AI is a problem that is inextricably intertwined with human civilization. It cannot be solved because present human civilization isn’t structured in a manner that is aligned with the needs of humanity. 

It’s as if Big Tech has hacked the political system and the politicians themselves. Zuckerberg’s testimony shows how little American leaders even understand the new world of algorithms, Ad-platforms, and AI.