Context is critical. As what was once mere data evolves into actionable intelligence, the context that binds that data becomes ever more essential.
Consider the word “java.” With no context around those four letters, you might not understand the reference or make any sort of connection. But if you add just one word to “java,” such as “development,” “island,” or “coffee,” the reference changes completely—and that’s with just a single word of context.
This is the type of active context and connection that the Brainspace engine provides. Read More
Daily Archives: July 12, 2019
Augmented Intelligence: A Collaboration of Humans and Machines
Catalytic: ‘RPA is the gateway drug for AI’
The immediate benefit of RPA is that it can eliminate a lot of repetitive manual labor and free up humans for what they are better at. But there’s also a side effect. RPA helps enterprises create a standardize framework for capturing data about how they execute processes as well as data about how processes can get delayed or stalled.
“If you set up RPA the right way by instrumenting the process, it’s possible to gather data to use as the training set for machine learning,” said Ted Shelton, Chief Revenue Officer at Catalytic, in an interview at Transform 2019. “RPA is the gateway drug for AI.” Read More
Has humanity reached "peak" intelligence?
You may not have noticed, but we are living in an intellectual golden age.
Since the intelligence test was invented more than 100 years ago, our IQ scores have been steadily increasing. Even the average person today would have been considered a genius compared to someone born in 1919 – a phenomenon known as the Flynn effect.
We may have to enjoy it while we can. The most recent evidence suggests that this trend may now be slowing. It may even be reversing, meaning that we have already passed the summit of human intellectual potential. Read More
How U.S. Tech Giants Are Helping to Build China’s Surveillance State
An American organization founded by tech giants Google and IBM is working with a company that is helping China’s authoritarian government conduct mass surveillance against its citizens, The Intercept can reveal.
The OpenPower Foundation — a nonprofit led by Google and IBM executives with the aim of trying to “drive innovation” — has set up a collaboration between IBM, Chinese company Semptian, and U.S. chip manufacturer Xilinx. Together, they have worked to advance a breed of microprocessors that enable computers to analyze vast amounts of data more efficiently.
Shenzhen-based Semptian is using the devices to enhance the capabilities of internet surveillance and censorship technology it provides to human rights-abusing security agencies in China, according to sources and documents. A company employee said that its technology is being used to covertly monitor the internet activity of 200 million people. Read More
Superhuman AI for multiplayer poker
In recent years there have been great strides in artificial intelligence (AI), with games often serving as challenge problems, benchmarks, and milestones for progress. Poker has served for decades as such a challenge problem. Past successes in such benchmarks, including poker, have been limited to two-player games. However, poker in particular is traditionally played with more than two players. Multiplayer games present fundamental additional issues beyond those in two-player games, and multiplayer poker is a recognized AI milestone. In this paper we present Pluribus, an AI that we show is stronger than top human professionals in six-player no-limit Texas hold’em poker, the most popular form of poker played by humans. Read More
A Benchmark for Machine Learning from an Academic/Industry Cooperative
MLPerf is a consortium involving more than 40 leading companies and university researchers, which has released several rounds of results. MLPerf’s goals are:
Accelerate progress in ML via fair and useful measurement
Encourage innovation across state-of-the-art ML systems
Serve both industrial and research communities
Enforce replicability to ensure reliable results
Keep benchmark effort affordable so all can play Read More
The Vision Behind MLPerf
A broad ML benchmark suite for measuring the performance of ML software frameworks, ML hardware accelerators, and ML cloud and edge platforms.
… since 2012 the amount of compute used in the largest AI training runs has been increasing exponentially with a 3.5 month-doubling time (by comparison, Moore’s Law had an 18-month doubling period). Since 2012, this metric has grown by more than 300,000x (an 18-month doubling period would yield only a 12x increase). Improvements in compute have been a key component of AI progress, so as long as this trend continues, it’s worth preparing for the implications of systems far outside today’s capabilities.” Read More
Rick's Cafe AI 