Computing Genius And WW2 Hero, Alan Turing, Will Be On U.K.’s 50-Pound Note

❝ Alan Turing, the father of computer science and artificial intelligence who broke Adolf Hitler’s Enigma code system in World War II — but who died an outcast because of his homosexuality — will be featured on the Bank of England’s new 50-pound note…

❝ Turing was just 41 when he died from poisoning in 1954, a death that was deemed a suicide. For decades, his status as a giant in mathematics was largely unknown, thanks to the secrecy around his computer research and the social taboos about his sexuality. His story became more widely known after the release of the 2014 movie The Imitation Game.

The Turing commemoration is the U.K. government’s latest public reevaluation of the genius who was convicted of homosexuality under “gross indecency” laws in 1952. By the time he died, Turing had been stripped of his security clearance and was forced to undergo a “chemical castration” regime of estrogen shots to avoid serving a two-year prison term.

The treatment of non-conformity by “polite” society over the centuries ranged from indecent to inhumane and cruel. Those who offended political pop culture and religion both – with their sexual preference – received the worst of it. Admitting narrow-minded stupidity of this sort is typically accompanied by “not on my watch” hand-wringing. And not much more. Still, the admission is part of the process of sorting out the dross remaining in our cultural brain.

McDonald’s trying out AI-powered menu boards

❝ Savory bacon, sweet Donut Sticks and a $5 value meal contributed to better-than-expected U.S. results for McDonald’s Corp. despite negative guest counts in the first quarter…

Going forward this year, McDonald’s said it is pivoting its focus to overall restaurant operations, especially at the drive-thru. McDonald’s said it has deployed menu boards with automated suggestive selling at 700 restaurants through Dynamic Yield. In late March, the Chicago-based chain purchased the decision logic technology company, which uses artificial intelligence to automate the upselling of menu items based on time of day, trending items and weather…

❝ When asked by an analyst where McDonald’s stands on adding a plant-based dish, CEO Steve Easterbrook said his culinary teams are “paying close attention to it.”

“The key for us is to identify the sustaining consumer trends,” he said.

I zeroed in on the plant-based consideration because of the dynamic IPO this past week for BEYOND MEAT. Their CEO emphasized that the simplest advantage they will offer consumers – beside a healthier planet and healthier consumers – is lower prices than meat. I haven’t any confidence in McDonald’s using lower wholesale commodity prices to reduce the tab for consumers. But, I look forward to taking advantage of the difference in the cut-throat world of supermarkets.

And – I wonder at the intelligence of fast food retailers who utilize the tastebud brain-switch of salty or sweet to bump their profits and don’t consider saving money for consumers to be equally compelling.

Elon Musk said what?

❝ In many ways, Tesla — Elon Musk’s lightning rod of a car company — is the perfect allegory for modern Silicon Valley. The ongoing psychodrama of personalities drowns out the amazing technical achievements that are happening all around us…

As usual, this has been a real “Dr. Jekyll and Mr. Hyde” kind of week for Tesla. It had a disastrous earnings report card, and Elon keeps creating all the wrong sorts of headlines. But in the middle of this maelstrom, the company announced a new chip that is going to eventually become the brain for their electric car. This chip is not just any chip — it will be able to make sense of a growing number of sensors that allow the car to become better and better at assisted (if not fully automated) driving…

❝ Tesla’s module is based on two AI chips — each one made of a CPU, a GPU, and deep learning accelerators. The module can deliver 144-trillion operations per second, making it capable of processing data from numerous sensors and other sources and running deep neural network algorithms. Ian Riches, an analyst with Strategy Analytics, told EE Times that this is “effectively the most powerful computer yet fitted to a production vehicle.” And Tesla is going to make a next-generation module that will be more powerful and will consume a lot less power.

As usual, Om Malik provides more depth, analysis and understanding than most of his peers. Please, RTFA, gather in another chunk of insight into Elon Musk’s apparently endless journey to reinvent the automobile along with any other software and hardware he bumps into in his young life.

An AI model showed Flint how to find lead pipes. What do you think they did after that?

❝ …Volunteer computer scientists, with some funding from Google, designed a machine-learning model to help predict which homes were likely to have lead pipes. The artificial intelligence was supposed to help the City dig only where pipes were likely to need replacement. Through 2017, the plan was working. Workers inspected 8,833 homes, and of those, 6,228 homes had their pipes replaced — a 70 percent rate of accuracy.

Heading into 2018, the City signed a big, national engineering firm, AECOM, to a $5 million contract to “accelerate” the program, holding a buoyant community meeting to herald the arrival of the cavalry in Flint…

❝ As more and more people had their pipes evaluated in 2018, fewer and fewer inspections were finding lead pipes…The new contractor hasn’t been efficiently locating those pipes: As of mid-December 2018, 10,531 properties had been explored and only 1,567 of those digs found lead pipes to replace. That’s a lead-pipe hit rate of just 15 percent, far below the 2017 mark…

❝ There are reasons for the slowdown. AECOM discarded the machine-learning model’s predictions, which had guided excavations. And facing political pressure from some residents, Mayor Weaver demanded that the firm dig across the city’s wards and in every house on selected blocks, rather than picking out the homes likely to have lead because of age, property type, or other characteristics that could be correlated with the pipes.

After a multimillion-dollar investment in project management, thousands of people in Flint still have homes with lead pipes, when the previous program would likely have already found and replaced them.

Life in America seems about as predictable as ever. Doesn’t have to be. Still, don’t get smug about analyzing the causes. Just fix it!

Autonomous robots can be bigots. Short-term payoffs work on machines, too.

❝ Showing prejudice towards others does not require a high level of cognitive ability and could easily be exhibited by artificially intelligent machines, new research has suggested.

Computer science and psychology experts from Cardiff University and MIT have shown that groups of autonomous machines could demonstrate prejudice by simply identifying, copying and learning this behaviour from one another…

❝ Though some types of computer algorithms have already exhibited prejudice, such as racism and sexism, based on learning from public records and other data generated by humans, this new work demonstrates the possibility of AI evolving prejudicial groups on their own…

❝ The findings involve individuals updating their prejudice levels by preferentially copying those that gain a higher short term payoff, meaning that these decisions do not necessarily require advanced cognitive abilities.

Your new self-driving car might not take you to the polls if it thinks you won’t vote for Trump or one of his lackeys.

Human Bankers Are Losing to Robots

❝ Something interesting happened in Swedish finance last quarter. The only big bank that managed to cut costs also happens to be behind one of the industry’s boldest plans to replace humans with automation.

❝ Nordea Bank AB, whose Chief Executive Officer Casper von Koskull says his industry might only have half its current human workforce a decade from now, is cutting 6,000 of those jobs. Von Koskull says the adjustment is the only way to stay competitive in the future, with automation and robots taking over from people in everything from asset management to answering calls from retail clients.

I imagine that Sweden’s labor culture will require, enable, a fair amount of retraining and education as required to meet this critical change in professional employment. Do I think anything comparable will be the response in the United States when similar job cuts take place?

That’s a rhetorical question, right?

Staying in touch with Atlas

Atlas is the latest in a line of advanced humanoid robots we are developing. Atlas’ control system coordinates motions of the arms, torso and legs to achieve whole-body mobile manipulation, greatly expanding its reach and workspace. Atlas’ ability to balance while performing tasks allows it to work in a large volume while occupying only a small footprint.

The Atlas hardware takes advantage of 3D printing to save weight and space, resulting in a remarkable compact robot with high strength-to-weight ratio and a dramatically large workspace. Stereo vision, range sensing and other sensors give Atlas the ability to manipulate objects in its environment and to travel on rough terrain. Atlas keeps its balance when jostled or pushed and can get up if it tips over.

Boston Dynamics rocks. I almost went to work for a precursor, a firm that ended up merged or “blended” into Boston Dynamics – before I left Boston in 1986. The chance to come to the Southwest and the Rockies was too tempting to walk away from. Surely might have been an interesting road to follow if I’d stayed.

AI System learned to master Rubik’s Cube in 44 hours

Meet DeepCube, an artificially intelligent system that’s as good at playing the Rubik’s Cube as the best human master solvers. Incredibly, the system learned to dominate the classic 3D puzzle in just 44 hours and without any human intervention.

“A generally intelligent agent must be able to teach itself how to solve problems in complex domains with minimal human supervision,” write the authors of the new paper, published online at the arXiv preprint server. Indeed, if we’re ever going to achieve a general, human-like machine intelligence, we’ll have to develop systems that can learn and then apply those learnings to real-world applications…

On the surface, the Rubik’s Cube may seem simple, but it offers a staggering number of possibilities. A 3x3x3 cube features a total “state space” of 43,252,003,274,489,856,000 combinations (that’s 43 quintillion), but only one state space matters — that magic moment when all six sides of the cube are the same color. Many different strategies, or algorithms, exist for solving the cube. It took its inventor, Erno Rubik, an entire month to devise the first of these algorithms…

RTFA. Interesting stuff – and you may as well get used to the topic whether you’re ready or not. Your next job interview might be with an entity built on systems like this. 🙂