Before bashing out emails and text messages by thumb became an accepted form of communication, typing was a fully manual skill. In the 80s, "the office" was an exclusive preserve for freaks who could type 40 words per minute at least. Those too modest or miserly to sign up for brick-and-mortar classes could pick up a software program called Mavis Beacon Teaches Typing for 50. At my Catholic high school, the application was the typing class. The priests just switched on the computers.

Artificial Intelligence (AI) and Machine Learning (ML) are two types of intelligent software solutions that aim to design futuristic technology with human-like qualities. At its crux, AI is a technology system whose objective is to emulate human faculties and perform a task while simultaneously justifying its actions based on factual information. On the contrary, ML is a subset of AI. It revolves around building software programs that facilitate more'sentient' or'sound' data-backed decision-making for computers. The history of AI can be traced back to the 1950s when computational techniques and abilities began to be infused in machines. The goal was simple: to transcend the current usage of computers and condition them for feasible decision-making.

Here at rRipple we have created the breakthroughs necessary to build the first'General AI', or Artificial Intelligence that will be smarter across the board than a human being. It's been a long road to create such a sophisticated, nuanced, capable technology and test it endlessly… But in that process we have learned some incredibly fascinating incites, ones we believe you will find truly captivating, about what the true nature of intelligence actually is. When we solve a problem. When we are creative… What's actually happening? Is it some partially supernatural process?

NPR's Rob Schmitz talks to Ethan Mollick of the University of Pennsylvania about an artificial intelligence program that uses AI to compose college essays, news stories, poems and even sitcoms.

Intel Drop #24 - The Threat Of A.I. Is Already Here A quick reminder, every link you need for our materials and articles is right here. Please share this article, so we can keep spreading the word. Join Bill's Twitter here, his Gab here, and our official We Are Sovereign Twitter here. Check the bottom of this post for important notes. The following was collated from a few wide-ranging conversations covering many topics. Bill: I few months ago you told me we need to keep an eye on A.I., but you didn't get much into it. Then this week you brought it up a lot more. Can you give everyone an update on that? The cabal has moved up the timeline on the use of A.I. in a way I did not expect at all." Bill: What are they doing? Gideon: "Introducing it to the public for the first time, which I did not think was something they had ready yet." Bill: But we already have A.I. surrounding us in some form or another, so what do you mean? Bill: So this is a different type of A.I. they are introducing? It is first important to understand there are two different things we must address. First, there are software-based A.I. programs. They mainly serve as automation technologies, like self-driving cars, or even simple customer support chat bots. In some cases, it is utilized to process data. None of that is a threat at all. It will never become sentient or fully replace human ingenuity, but this is where we see the concern focused. We see people talking about it, but not talking about what is the true threat. The true threat is that something is being brought into this world that the cabal will call'A.I.' but it is not."

Artificial intelligence software programs are becoming shockingly adept at carrying on conversations, winning board games and generating artwork -- but what about creating software programs? In a newly published paper, researchers at Google DeepMind say their AlphaCode program can keep up with the average human coder in standardized programming contests. "This result marks the first time an artificial intelligence system has performed competitively in programming contests," the researchers report in this week's issue of the journal Science. There's no need to sound the alarm about Skynet just yet: DeepMind's code-generating system earned an average ranking in the top 54.3% in simulated evaluations on recent programming competitions on the Codeforces platform -- which is a very "average" average. "Competitive programming is an extremely difficult challenge, and there's a massive gap between where we are now (solving around 30% of problems in 10 submissions) and top programmers (solving 90% of problems in a single submission)," DeepMind research scientist Yujia Li, one of the Science paper's principal authors, told GeekWire in an email.

A personal, guided tour to the best scoops and stories every day in The Wall Street Journal. Dr. Frederick P. Brooks Jr. liked building things, first laying foundations for modern computer systems at International Business Machines Corp. and later at the University of North Carolina, where he started the computer-science department. Dr. Brooks managed the development of IBM's System/360 family of compatible mainframe computers and then the software system that went with them during the 1960s. The computers became some of IBM's most popular models of the era, offering customers a choice of big or small computers with different processing speeds that could be used for both business and scientific tasks. The system was easy to expand since all the hardware ran off the same software, a departure from other systems that required software reprogramming when computers were added.

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Despite the remarkable technological advances that fill our lives today, the ways we work with the metals that underlie these developments haven't changed significantly in thousands of years. This is true of everything from the metal rods, tubes, and cubes that provide cars and trucks with their shape, strength, and fuel economy, to wires that move electrical energy in everything from motors to undersea cables. But things are changing rapidly: The materials manufacturing industry is using new and innovative technologies, processes, and methods to improve existing products and create new ones. Pacific Northwest National Laboratory (PNNL) is a leader in this space, known as advanced manufacturing. For example, scientists working in PNNL's Mathematics for Artificial Reasoning in Science initiative are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.