Big Data and Predictive Math: Some Doubters

January 19, 2018

I love Big Data. I love fancy math. I spotted two articles this morning which offer a contrarian view about two popular buzzwords: Big Data and Predictive Analytics.

The first write up is from the capitalist’s tool, Forbes Magazine. I can not tell what’s an ad or what’s a “real” journalistic endeavor. But in today’s world? Maybe the distinction is like arguing with St. Thomas Aquinas about the cause of evil.

Forbes’ story is “Big Data Is Overrated Compared To Human Ingenuity.” The main point is that humans with intelligence are more ingenious than software. No software, as far as I can tell, was consulted when formulating the thesis. The main point for me was:

an algorithm may be able to cover sports, you cannot clone or generate whimsy or humor or the essence of what makes writing enjoyable to read. We are not (at least not yet) at a point where computers are able to have full conversations, let alone exude the creativity to come up with ideas. The creative geniuses of the future may, in fact, be aided by big data, but they will simply use it (as one would use Google to search the giant database known as the internet) to ask the right questions to solve the world’s problems.

My thought is, “What about robot wars?” Does that TV show presage the NFL of the future?

The second write up is from a British online publication. The article’s title is “Software That Predicts Whether Crims Will Break the Law Again Is No Better Than You or Me.”

The main idea strikes me as:

…if you took someone with no legal, psychological or criminal justice system training – perhaps you, dear reader – and showed them a few bits of information about a given defendant, they’d be able to guess as well as this software as to whether the criminal would break the law again.

Interesting point; however, software might be able to chop through a backlog of cases, thus reducing costs. Sure a few good apples will be tossed into the for profit prisons, but that’s just a statistical error.

What I find amusing is the point made by a TV pundit in “How to Stop ‘Extremely Disruptive’ AI from Harming Society: Robert Shiller.” I don’t know about you but knowing unintended consequences before they occur might be difficult. Facebook has been around for years, and people are just now figuring out that the system can do more than help grandmother keep track of the grandchildren.

Exciting stuff. Predictive law enforcement is important. Big Data are getting bigger and being used to sell ads to people who don’t recognize the message as an ad. Regulating technology is like standing on the pier after the Queen Mary set sail and shouting, “Hey, come back.”

Stephen E Arnold, January 19, 2018

Neural Net Machine Translation May Increase Acceptance by Human Translators

January 2, 2018

Apparently, not all professional translators are fond of machine translation technology, with many feeling that it just gets in their way. A post from Trusted Translations’ blog examines, “Rage Against the Machine Translation: What’s All the Fuzz About?” Writer Cesarm thinks the big developers of MT tech, like Google and Amazon, have a blind spot—the emotional impact on all the humans involved in the process. From clients to linguists to end users, each has a stake in the results. Especially the linguists, who, after all, could theoretically lose their jobs altogether to the technology. We’re told, however, that (unspecified) studies indicate translators are more comfortable with software that incorporates neural networking/ deep learning technology. I seem such tools produce a better linguistic flow, even if some accuracy is sacrificed. Cesarm writes:

That’s why I mention emotional investment in machine translation as a key element to reinventing the concept for users.  Understanding the latest changes that have been implemented in the process can help MT-using linguists get over their fears. It seems the classic, more standardized way of MT, (based solely on statistical comparison rather than artificial intelligence) is much better perceived by heavy users, considering the latter to be more efficient and easier to ‘fix’ whenever a Post-Editing task is being conducted, while Post Editing pre-translated text, with more classical technology has proven to be much more problematic, erratic, and what has probably nurtured the anger against MT in the first place, giving it a bad name. Most users (if not all of them) will take on pre-translated material processed with statistical MT rather that rule based MT any day. It seems Neural MT could be the best tool to bridge the way to an increased degree of acceptance by heavy users.

Perhaps. I suppose we will see whether linguists’ prejudice against MT technology ultimately hinders the process.

Cynthia Murrell, January 2, 2018

Humans Living Longer but Life Quality Suffers

December 28, 2017

Here is an article that offers some thoughts worth pondering.  The Daily Herald published, “Study: Americans Are Retiring Later, Dying Sooner And Sicker In Between”.  It takes a look at how Americans are forced to retire at later ages than their parents because the retirement age keeps getting pushed up.  Since retirement is being put off, it allows people to ideally store away more finances for their eventual retirement.  The problem, however, is that retirees are not able to enjoy themselves in their golden years, instead, they are forced to continue working in some capacity or deal with health problems.

Despite being one of the world’s richest countries and having some of the best healthcare, Americans’ health has deteriorated in the past decade.  Here are some neighbors to make you cringe:

University of Michigan economists HwaJung Choi and Robert Schoeni used survey data to compare middle-age Americans’ health. A key measure is whether people have trouble with an “activity of daily living,” or ADL, such as walking across a room, dressing and bathing themselves, eating, or getting in or out of bed. The study showed the number of middle-age Americans with ADL limitations has jumped: 12.5 percent of Americans at the current retirement age of 66 had an ADL limitation in their late 50s, up from 8.8 percent for people with a retirement age of 65.

Also, Americans’ brains are rotting with an 11 percent increase in dementia and other cognitive declines in people from 58-60 years old.  Researchers are not quite sure what is causing the decline in health, but they, of course, have a lot of speculation.  These include alcohol abuse, suicide, drug overdoses, and, the current favorite, increased obesity.

The real answer is multiple factors, such as genes, lifestyle, stress, environment, and diet.  All of these things come into play.  Despite poor health quality, we can count on more medical technological advances in the future.  The aging population maybe the test grounds and improve the golden years of their grandchildren.

Whitney Grace, December 28, 2017

Silicon Valley Has the Secret to Eternal Life

December 27, 2017

Walt Disney envisioned his namesake park, Walt Disney World, to be a blueprint for the city of the future.  Disney was a keen futurist and was interested in new technology that could improve his studios and theme parks.  His futuristic tendencies led to the urban legend that he was cryogenically frozen and will one day be revived.  Disney wasn’t put on the ice, but his futuristic visions are carried out by Silicon Valley technologists seeking immortality.  Quartz reports on the key to eternal life in the article, “Seeking Eternal Life, Silicon Valley Is Solving For Death.”

Death is the ultimate problem that has yet to be solved.  Many in Silicon Valley, including Oracle’s Larry Ellison, are searching for a solution to prolong life with anti-aging research.  Bill Maris convinced Alphabet’s Larry Page and Sergey Brin to start Calico, Google’s billion-dollar effort to cure aging.  Also, cryogenics remains popular:

Other denizens of the valley pursue cryogenics or cryonics, which is the process of freezing oneself in a vat of liquid nitrogen soon after death. They do this in the hope that it will suspend them in time, preserving them for a future when science can bring them back to life. There are about 350 people already frozen worldwide with another 2,000 signed up—but yet to die.

Medical breakthroughs have already extended the US lifespan and that of other developed nations.  Developing nations still have short lifespans and it draws the conclusion that wealthier people will live forever, while the poor ie quicker.  It is questionable that the extra years tacked onto people’s lives are really worth it because many people spend them unable to care for themselves or in pain.

The article spins into current anti-aging research, then into philosophy about humans vs. machines and what makes a person a person.  Throw in some science-fiction and that is the article in short.

Whitney Grace, December 27, 2017

There Is on Obscure Search Engine Beating Google (a Little)

December 22, 2017

Is there life out there beyond Google? Sure, there’s Bing and Yahoo, but are there any people could actually fall into a routine of using? If that’s your question, things could be looking up for your search, according to a recent Search Engine Watch story, “6 Innovative New Search Engines To Keep an Eye On.”

According to the story,

Believe it or not, there are a number of other search engines out there, still crawling the web and making their mark. Since Google has so completely dominated the “all-purpose” search engine space, many of them have moved to occupy more niche areas, like academia, or sought to distinguish themselves in other ways.

 

As technology continues to have a hand in most everything that we do, it’s important to be aware of the other contenders in the industry. While they aren’t likely to revolutionize SEO overnight, they’re indicative of the trends and technology currently making their way through search, which could show up on a much larger scale later on.

To those on the list, we wish you good luck. You’re gonna need it. Google has had a stranglehold on the search world for longer than anyone can remember. The only one of the engines recommended here that even stand a chance is Semantic Scholar. As Wired pointed out, this scholarly engine actually stands a great chance of succeeding somewhere Google can’t because it helps users bypass pesky paywalls for scientific journals. Wow. Keep an eye on this.

Patrick Roland, December 22, 2017

IBM Thinks It Can Crack Pharmaceutical Code with AI

December 20, 2017

Artificial intelligence has been tasked with solving every problem from famine to climate change to helping you pick a new favorite song. So, it should come as no surprise that IBM thinks it can revolutionize another industry with AI. We learned exactly what from a Digital Trends story, “IBM’s New AI Predicts Chemical Reactions, Could Revolutionize Drug Development.”

According to the story,

As described in a new research paper, the A.I. chemist is able to predict chemical reactions in a way that could be incredibly important for fields like drug discovery. To do this, it uses a highly detailed data set of knowledge on 395,496 different reactions taken from thousands of research papers published over the years.

Teo Laino, one of the researchers on the project from IBM Research in Zurich, told Digital Trends that it is a great example of how A.I. can draw upon large quantities of knowledge that would be astonishingly difficult for a human to master — particularly when it needs to be updated all the time.

It’s an absolutely valid plan, but we aren’t sure if IBM is the one to really pull off this trick. IBM trying to work in big pharma seems kind of like your uncle tinkering on his “inventions” out in the shed. We’d rather see someone whose primary focus is AI and medicine, like Certara, PhinC, and Chem Abstracts.

Patrick Roland, December 20, 2017

Quick Question: Why Not Loon Balloons, Google?

December 16, 2017

I read “Google Is Using Light Beam Tech to Connect Rural India to the Internet.” I understand. But the question just hangs there like a hot air balloon on a still day:

Why not use the vaunted Loon balloons?

I have an idea or two. What do you think about cost, complexity, and the weather? Yep, weather. As in weather balloons.

Does this pop the loon balloon big idea or just shine light on a loon balloon?

Stephen E Arnold, December 16, 2017

Bye-Bye Silicon Valley Monopoly

December 14, 2017

Silicon Valley is a technology epicenter and used to be synonymous with modern innovation, but that is no longer the case.  CNBC reports that, “Billionaire Investor Peter Thiel: Silicon Valley’s Monopoly On Big Growth Tech Companies Is Over.”   Peter Thiel is a famous Silicon Valley investor.  He helped launch PayPal, was an early investor in Facebook and Airbnb, and he also launched Palantir Technologies.  As one of the top Silicon Valley insiders, he said that:

‘I have been investing in the technology space — entrepreneur and investor over the past 20 years in Silicon Valley — and within the area of IT, it has for the last 10, 15 years in the US and the world been extremely centered on Silicon Valley,’ Thiel says, speaking at the Future Investment Initiative in Riyadh, Saudi Arabia, Thursday.  ‘I think there are a lot of reasons for that, but the question is, ‘Where is the growth going to happen the next 10 years?’ And what I would tend to think is that it will be more diversified from just Silicon Valley.’

Thiel continued that technology startups can be built anywhere, you just need the right people, money, and the right governance structures.  He was surprised that so many technology businesses popped up in Silicon Valley, but that happened because of the number of mentors and entrepreneurship concentrated in one area.  Innovators went where the action was happening.  It is similar to how actors go to Hollywood and writers head to New York City.

Thanks to Silicon Valley, technology has changed the world, so the next venture company can be located anywhere.  Take a guess about where the next big technology might be or if it will be spread out along the grid.

Whitney Grace, December 14, 2017

China Has an AI Police Station and That Is Not a Good Thing

December 12, 2017

The wave of things artificial intelligence can do is amazing. In China, they are even handling law enforcement with intelligent machines. While this might be a boon for efficiency, people like Stephen Hawking are not happy. We learned more from the Sanvada article, “Check Out The Artificial Intelligence-Powered Police Station in China.”

According to the story:

Recently China announced the opening of an AI-powered police station in Wuhan illustrating its plans to fully incorporate artificial intelligence as a functional part of its systems.

But the most interesting turn comes later, stating:

Artificial intelligence may not yet be up to the task. After all, not every case in the designated area will relate to car or driving related issues. Artificial intelligence has yet to be proven to have the capability of solving complex disputes. It may not use of all of the facts or comprehend the intricate dynamics of human relationships or the damage which can be caused to people whether it is in the case of molestation or rape and hence, may not have the sensitivity to deal with such scenarios.

We love the multitude of uses for AI but have to agree with the skepticism of Sanvada. One of the smartest people on the planet also agrees. Stephen Hawking recently commented that “AI could be the worst event in human history.” Let’s hope he’s not right and let’s hope wise guidance proves that AI police stations stay a novelty in the world of AI.

Patrick Roland, December 12, 2017

Big Data and Search Solving Massive Language Processing Headaches

December 4, 2017

Written language can be a massive headache for those needing search strength. Different spoken languages can complicate things when you need to harness a massive amount of data. Thankfully, language processing is the answer, as software architect Federico Thomasetti wrote in his essay, “A Guide to Natural Language Processing.”

According to the story:

…the relationship between elements can be used to understand the importance of each individual element. TextRank actually uses a more complex formula than the original PageRank algorithm, because a link can be only present or not, while textual connections might be partially present. For instance, you might calculate that two sentences containing different words with the same stem (e.g., cat and cats both have cat as their stem) are only partially related.

 

The original paper describes a generic approach, rather than a specific method. In fact, it also describes two applications: keyword extraction and summarization. The key differences are:

  • the units you choose as a foundation of the relationship
  • the way you calculate the connection and its strength

Natural language processing is a tricky concept to wrap your head around. But it is becoming a thing that people have to recognize. Currently, millions of dollars are being funneled into perfecting this platform. Those who can really lead the pack here will undoubtedly have a place at the international tech table and possibly take over. This is a big deal.

Patrick Roland, December 4, 2017

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