What Can Be Like a Bee? A Drone
March 11, 2021
Drones are mainly associated with aerial photography, eventual package deliveries, and unmanned attacks. None of these, however, drive drone scientists to improve the robot technology. What really moves them forward is the desire to replicate bees’ graceful movements and fully seeing flowers’ ultimate beauty says Science Daily in the article, “Appreciating A Flower’s Texture, Color, And Shapes Leads To Better Drone Landings.”
Technically it should be impossible for bees to fly, but reality proves that idea wrong. Bees are amazing navigators who use optical flow, perceiving an object’s speed in their view field. Robotics researchers designed an algorithm based off the optical view concept to allow robots to judge distances by visual cues (colors, shapes, and textures).
Drones will learn from the optical flow AI, but the concept has limitations:
“Optical flow has two fundamental limitations that have been widely described in the growing literature on bio-inspired robotics. The first is that optical flow only provides mixed information on distances and velocities — and not on distance or velocity separately. To illustrate, if there are two landing drones and one of them flies twice as high and twice as fast as the other drone, then they experience exactly the same optical flow. However, for good control these two drones should actually react differently to deviations in the optical flow divergence. If a drone does not adapt its reactions to the height when landing, it will never arrive and start to oscillate above the landing surface. Second, for obstacle avoidance it is very unfortunate that in the direction in which a robot is moving, the optical flow is very small. This means that in that direction, optical flow measurements are noisy and hence provide very little information on the presence of obstacles. Hence, the most important obstacles — the ones that the robot is moving towards — are actually the hardest ones to detect!
The limitations can be fixed if robots can interpret optical flow and visual appearances of objects in their field. Seeing some distance by visual appearances resulted in better landings for drones.
Learning how to land the drones leads to better understanding of insects’ intelligence. Biology and robotics do not often mesh outside of science fiction, but tiny bees could leads to advances in robotic navigation.
Whitney Grace, March 11, 2021
Quantum Computing: A Nasty Business
March 3, 2021
In a PhD program, successful candidates push the boundaries of knowledge and change the world for the better. Sometimes. One illustration of this happy outcome is the case of Zak Romaszko at the University of Sussex, who contributed to the school’s ion trap quantum computer project. Robaszko is now working at his professor’s spin-off company Universal Quantum on commercialization of the tech to create large-scale quantum computers. Bravo!
Unfortunately, not all PhD programs are crucibles of such success stories. One in particular appears to be just the opposite, as described in “A Dishonest, Indifferent, and Toxic Culture” posted at the Huixiang Voice. The blog is dedicated to covering the heartbreaking experience of PhD candidate Huixiang Chen, who was studying at the University of Florida’s department of Electrical and Computer Engineering when he took his own life. The note Chen left behind indicated the reason, at least in part, was the pressure put on him by his advisor to go along with a fraudulent peer-review process.
We learn:
“It has been 20 months since the tragedy that a Ph.D. candidate from the University of Florida committed suicide, accusing his advisor coerce him into academic misconduct. Our latest article dropped a bump into the academic world by exposing the evidence of those academic misconduct. The Nature Index followed up with an in-depth report with comments from scientists and academic organizations worldwide expressing their shock and deep concerns about this scandal that happened at the University of Florida.”
A joint committee of the academic publisher Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE) investigated the matter and found substance in the allegations. ACM has imposed a 15-year ban on participation in any ACM Conference or Publication on the offenders, the most severe penalty the organization has ever imposed. The post continues:
“The conclusion finally confirmed two important accusations listed in Huixiang Chen’s suicide note that:
1) The review process for his ISCA-2019 paper was broken, and most of the reviewers of the paper are ‘friends’ of his advisor Dr. Tao Li. The review process became organized and colluded academic fraud:
2)After recognizing that there are severe problems in his ISCA-2019 paper, Huixiang Chen was coerced by his advisor Dr. Tao Li to proceed with a submission despite that Huixiang Chen repeatedly expressed concerns about the correctness of the results reported in work, which led to a strong conscience condemnation and caused the suicide.
“Finally, the paper with academic misconduct got retracted by ACM as Huixiang’s last wish.”
Chen hoped the revelations he left behind would lead to a change in the world; perhaps they will. The problem, though, is much larger than the culture at one university. Peer reviewed publications have become home to punitive behavior, non-reproducible results, and bureaucratic pressure. Perhaps it is time to find another way to review and share academic findings? Google’s AI ethics department may have some thoughts on academic scope and research reviews.
Cynthia Murrell, March 3, 2021
Fixing the Innovation Economy?
February 19, 2021
I read “How to Fix What the Innovation Economy Broke about America.” I noted this sentence:
No initiative, no program, no development aid will, by itself, solve
the deepest problem of all: distrust of American institutions. Reagan
told Americans that government was not the solution, it was the
problem.
I asked myself, “Does MIT lack the institutional memory to recall that it accepted funds from Jeffrey Epstein?” The decision failure makes clear that the problems with the analysis in the article manifests itself in the actions of entities like MIT.
Social and intellectual failure cannot be attributed to a single factor. Its remediation begins with institutions and the individuals who comprise those entities. Innovation is one chemical in the exhaust generated by actions which are corrosive.
Pontification is okay. Bandying about words like “trust” is hand waving.
Stephen E Arnold, February 19, 2021
Intel: Outputting Horse Hooey (Translation for Thumbtypers: Nonsense)
February 16, 2021
I read “Intel Mocks Apple’s M1 MacBooks in Grudge-Bearing Ad Campaign.” Let’s assume that the information in the Tech Radar article is spot on. I learned:
Intel is back to mocking Apple, having posted a series of tweets highlighting the shortcomings of Apple’s M1 processors.
Yep, Intel and the tweeter thing.
The article points out that Apple divorced Intel from its M1 computers. But there are visitation writes for some Apple computers I think.
The write up points out:
Intel’s tweets link to a video from YouTuber Jon Rettinger, that compare laptops equipped with Intel chips to Apple’s ?M1? Macs. “If you’re looking for a good laptop in 2021, there are many things to consider, but processor choice might be more important than you think,” a description on Rettinger’s video reads. “You might be considering Apple’s new M1-based laptops, but before you hit the buy button, let me show you what Intel’s new Evo laptops can offer you!” Intel’s aggressive tweets come just days after the company posted a series of cherry-picked benchmarks designed to provide that its 11th-generation processors are better than Apple’s ARM-based M1 chips.
I have pointed out that Intel’s Horse Ridge announcement struck me as horse feathers. If Intel is using the tweeter to output negative vibes and fiddling benchmarks, is it possible that Intel has moved from horse ridge to horse feathers?
I prefer innovation, demonstrations of technical competence
Stephen E Arnold, February 16, 2021
Managing Engineers: Make High School Science Club Management Methods More High School-Like?
February 4, 2021
I read an interesting and thoughtful essay in Okay HQ. “Engineering Productivity Can Be Measured – Just Not How You’d Expect.” The “you” seems to be me. That’s okay. As a student of the brilliant HSSCMM encapsulated in decisions related to handling staff, I am fascinated by innovations.
The write up points out:
Since the advent of the software industry, most engineering teams have seen productivity as a black box. Only recently have people even begun to build internal tools that optimize performance. Unfortunately, most of these tools measure the wrong metrics and are shockingly similar across companies.
The idea is that MBA like measures are off the mark.
How does the HSSCMM get back on track? The write up states:
Productivity in engineering therefore naturally increases when you remove the blockers getting in the way of your team.
The idea of a “blocker” is a way to encapsulate the ineffective, inefficient, and clumsy management tactics touted by Peter Drucker and other management experts.
What does a member of the science club perceive as a blocker?
- Too many interruptions
- Slow code reviews
- Lousy development tools
- Too much context switching (seems like a variant of interruptions, doesn’t it?)
- Getting pinged to do work outside of business hours (yep, another variation of interrupting a science club member).
Let’s summarize my HSSCMM principles. The engineers — at least the ones in the elite of the science club — want to be managed by these precepts:
- Don’t interrupt the productive engineers/professionals
- Don’t give us tools the productive / engineers and professionals don’t find useful, helpful, good, or up to our standards
- Provide feedback, right now, you inefficient and unproductive human
- Don’t annoy productive engineers / professionals outside of “work” hours.
These seem perfectly reasonable if somewhat redundant. However, these productive engineers / professionals have created the systems, methods, apps, and conventions that destroy attention, yield lousy software and tools, and nourish the mind set which has delivered the joys of Twitter, Facebook, Robinhood, et al to the world.
Got that, Druckerites? If not, our innovations in artificial intelligence will predict your behaviors and our neuro morphic systems will make you follow the precepts of the science club.
That sound about right?
Stephen E Arnold, February 4, 2021
What Makes the Web Slow? Really Slow?
January 28, 2021
I read “We Rendered a Million Web Pages to Find Out What Makes the Web Slow.” My first reaction was the East Coast Internet outage which ruined some Type A workers’ day. I can hear the howls, “Mommy, I can’t attend class, our Internet is broken again.”
Here’s a passage from the “Rendered a Million Web Pages” which I found interesting:
Internet commentators are fond of saying that correlation does not equal causation, and indeed we can’t get at causality directly with these models. Great caution should be exercised when interpreting the coefficients, particularly because a lot confounding factors may be involved. However, there’s certainly enough there to make you go “hmm”.
Yep, I went “hmm.” But for these reasons:
- Ad load times slow down my Web experiences. Don’t you love those white page hung ads on the YouTube or the wonky baloney on the Daily Mail?
- How about crappy Internet service providers?
- Are you thrilled with cache misses?
- Pages stuffed full of trackers, bugs, codes, and spammy SEO stuff.
Hmm, indeed.
Stephen E Arnold, January 28, 2021
The Silicon Valley Way: Working 16 Hour Days in Four Hours?
January 26, 2021
Years ago I worked at a couple of outfits which expected professionals to work more than eight hours a day. At the nuclear outfit, those with an office, a helper (that used to be called a “secretary”), and ill-defined but generally complicated tasks were to arrive about 8 am and head out about six pm. At the blue chip consulting firm, most people were out of the office during “regular” working hours; that is, 9 am to 5 pm. Client visits, meetings, and travel were day work. Then after 5 pm or whenever before the next day began professionals had to write proposals, review proposals, develop time and cost estimates, go to meetings with superiors, and field odd ball phone calls (no mobiles, thumb typers. These phones had buttons, lights, and spectacular weird interfaces). During the interview process at the consulting outfit, sleek recruiters in face-to-face meetings would reference 60 hour work weeks. That was a clue, but one often had to show up early Saturday morning to perform work. The hardy would show up on Sunday afternoon to catch up.
Imagine my reaction when I read “Report: One Third of Tech Workers Admit to Working Only 3 to 4 Hours a Day.” I learned:
- 31% of professionals from 42 tech companies…said they’re only putting in between three and four hours a day
- 27% of tech professionals said they work five to six hours a day
- 11% reported only working one to two hours per day
- 30% said they work between seven and 10 hours per day.
The data come from an anonymous survey and the statistical procedures were not revealed. Hence, the data may be wonky.
One point is highly suggestive. The 30 percent who do more are the high performers. With the outstanding management talent at high technology companies, why aren’t these firms terminating the under performing 70 percent? (Oh, right some outfits did try the GE way. Outstanding.)
My question is, “For the 30 percent who are high performers, why are you working for a company. Become a contractor or an expert consultant. You can use that old school Type A behavior for yourself?”
Economic incentives? The thrill of super spreader events on Friday afternoon when beer is provided? Student loans to repay? Work is life?
I interpret the data another way. Technology businesses have a management challenge. Measuring code productivity, the value of a technology insight, and the honing of an algorithm require providing digital toys, truisms about pushing decisions down, and ignoring the craziness resulting from an engineer acting without oversight.
Need examples? Insider security threats, a failure to manage in a responsible manner, and a heads down effort to extract maximum revenue from customers.
In short, the work ethic quantified.
Stephen E Arnold, January 26, 2021
Computing: Things Go Better with Light
January 22, 2021
Electricity is too slow at matrix math for IBM. Now, announces ZDNet, “IBM Is Using Light, Instead of Electricity, to Create Ultra-Fast Computing.” The shift could be especially important to the future of self-driving automobiles, where ultra-fast processing is needed to avoid collisions at high travel speeds. Reporter Daphne Leprince-Ringuet writes:
“Although the device has only been tested at a small scale, the report suggests that as the processor develops, it could achieve one thousand trillion multiply-accumulate (MAC) operations per second and per square-millimeter – according to the scientists, that is two to three orders more than ‘state-of-the-art AI processors’ that rely on electrical signals.”
IBM researchers have been working toward this goal for some time. Last year, the company demonstrated the tech’s potential through in-memory computing with devices that performed computational tasks using light. Now they have created what they call a photonic tensor core they say is particularly suited for deep-learning applications. The article continues:
“The most significant advantage that light-based circuits have over their electronic counterparts is never-before-seen speed. Leveraging optical physics, the technology developed by IBM can run complex operations in parallel in a single core, using different optical wavelengths for each calculation. Combined with in-memory computing, IBM’s scientists achieved ultra-low latency that is yet to be matched by electrical circuits. For applications that require very low latency, therefore, the speed of photonic processing could make a big difference. … With its ability to perform several operations simultaneously, the light-based processor developed by IBM also requires much less compute density.”
That is another consideration for self-driving vehicles—the smaller the hardware the better. But this technology is far from ready for the road. IBM still must evaluate how it can be integrated for end-to-end performance. The potential to trade electricity for light is an interesting development; we are curious to see how this unfolds.
Cynthia Murrell, January 22, 2021
Technology and Exponential Costs: MBAs Confront a Painful Online Reality
January 20, 2021
The article “When Costs Are Nonlinear, Keep It Small” addresses exponential costs in terms of technology in general. A business uses software; costs can grow exponentially. I completely agree. The author, one Jessitron, states:
When costs increase nonlinearly with delay or batch size, larger batches are not more efficient…. The changes interact, and so batching them up increases the cost of the batch by more than the cost of the change you’re adding. Batching is less efficient.
I want to use this observation to explain why online information services find themselves in a cost swamp. The consequence of the exponential demand for resources are:
- Management needs cash and must put more pressure on sales professionals to close deals. Pressure leads to overstatement and clever workarounds. Once the deal is closed an an invoice sent, the sales professional moves on either to another company or to another customer.
- Marketing gets the message that sales are number one, so the art history majors and former hospitality workers crank out hyperbole-stuffed messages. (Post SolarWinds check out the tone deaf pitching of security systems which failed to notice the breach. Sales are needed, and marketing is the cheerful servant of the organization.)
- Fancy dancing with the books. The number of online companies booking business before cash arrives is probably infinitesimal, right? But there are other ways of producing money; for example, the public information about the activities of Fast Search & Transfer provide and example. Other examples are available.
- Go back to the funders. An enthusiastic group of clear eyed, good school, sincere individuals explain to an equally clear eyed, good school, sincere individuals why money should be invested. The recipients pray for a big sale or other financial home run because repaying the money is what might be called a long shot.
These activities are often a result of the truths that Jessitron explains and illustrates with annotated drawings.
In the online world, when something goes wrong, money must be spent. The amount required is unknown until the wrong is righted. How much is a new product? Same deal. The amount of cash required is unknown, yet cash must be spent.
Exponential costs are part of the deal. The article suggests that changes be kept small; that is, changing many things increases the likelihood of problems. Problems require cash. A cycle, just not so virtuous.
Online services live with exponential costs. Thus, the online vendors have zero choice but to do the type of thinking which has created some of the more fascinating ethical, financial, political, and technical tactical minefields dotting the datasphere.
Useful paper, Jessitron. Keep it small.
Stephen E Arnold, January 20, 2021
Intel Reminds Apple That It Is a Horse Around Company
January 19, 2021
I read “Intel Suggests It Will Wait for New CEO to Make Critical Decisions to Fix Manufacturing Crisis.” The headline suggests that Intel cannot manufacture chips as it did in the glory days of Silicon Valley. Wow, who knew?
There are a couple of other gems in this “real” news story too; to wit:
Intel allegedly embraces this view of Apple, another small outfit in the computing business:
“We have to deliver better products to the PC ecosystem than anypossible thing that a lifestyle company in Cupertino” makes,Gelsinger told employees Thursday. That’s a derisive, ifgood-natured, reference to Apple and the location of its corporateheadquarters.
Yep, lifestyle. Apple, I would remind Intel, has managed to enter the chip business without any of the quantum computing lynchpin baloney like the Horse Ridge innovation. That’s a technical achievement which strikes me as a combination of marketing, jargon, and horse feathers. Maybe a horse collar or a saddle blanket?
Another interesting passage asserts:
In a note to clients after Gelsinger’s hiring [the new CEO], Raymond James analystChris Caso said Intel doesn’t have time to deliberate.
Okay, time. There’s the ever chipper AMD, the Qualcomm outfit, a couple of eager beavers in lands which favor zesty spices. Oh, yes, and there’s the Apple operation, which sells products from pushcarts.
The article details the failures and fantasies of a company which has created Horse Ridge. Unfortunately instead of a stallion, the computational cowboys are riding Norwegian Fjord horses in the chip derbies.
Stephen E Arnold, January 19, 2021
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