Smarter Vending

 Has been happening,   more being done. 

Adding Smarts to Vending Machines Drives Convenience, Efficiency

Advanced feature sets and functionality are projected to drive the market for connected vending to nearly nine million units by 2024.

Keith Kirkpatrick

From Communications of the ACM | March 1, 2023

Adding Smarts to Vending Machines Drives Convenience, Efficiency

Communications of the ACM, March 2023, Vol. 66 No. 3, Pages 20-22 10.1145/3579651

Vending machines, which allow people to easily purchase items without interacting with a human worker, have been around since the 1st century, when a Greek engineer and mathematician named Hero Alexandria created a machine that accepted a coin before dispensing holy water at a temple, to prevent people from taking more than their share of holy water.

Two millennia later, a far greater number and variety of products can be purchased from vending machines, thanks in part to the advent of new technologies including always-on, Internet of Things (IoT) connectivity, advanced physical and digital controls that allow these machines to be placed in a wide variety of settings, and the use of artificial intelligence (AI)-based algorithms that can capture and analyze customer insights, improve stocking efficiency, and deliver greater levels of personalization to customers.

The global installed base of connected vending machines reached an estimated 2.4 million units in 2019, according to Berg Insight, a research firm that tracks the installed base of connected vending machines. Connected vending machines are equipped with an always-on Internet connection, which allows data to be sent between machines in the field and management software, enabling real-time payments, monitoring, and remote management of the machines.

Advanced feature sets and functionality are projected to drive the market to nearly nine million units by 2024, according to Berg Insight, helped along by the desire of organizations to better serve customers without needing to attract and retain relatively costly human workers.  ... '

A Trap for Efficient Light Use

 And thus using it more efficiently.  How well?

Creating a perfect trap for light

by Hebrew University of Jerusalem  and TU Wein    in TechExplore

Whether in photosynthesis or in a photovoltaic system: If you want to use light efficiently, you have to absorb it as completely as possible. However, this is difficult if the absorption is to take place in a thin layer of material that normally lets a large part of the light pass through.

Now, research teams from TU Wien and from The Hebrew University of Jerusalem (HU) have found a surprising trick that allows a beam of light to be completely absorbed even in the thinnest of layers: They built a "light trap" around the thin layer using mirrors and lenses, in which the light beam is steered in a circle and then superimposed on itself—exactly in such a way that the beam of light blocks itself and can no longer leave the system. Thus, the light has no choice but to be absorbed by the thin layer—there is no other way out.

This absorption-amplification method, which has now been presented in the scientific journal Science, is the result of a fruitful collaboration between the two teams: the approach was suggested by Prof. Ori Katz from The Hebrew University of Jerusalem and conceptualized with Prof. Stefan Rotter from TU Wien; the experiment was carried out in by the lab team in Jerusalem and the theoretical calculations came from the team in Vienna.

"Absorbing light is easy when it hits a solid object," shared Prof. Stefan Rotter from the Institute of Theoretical Physics at TU Wien. "A thick black wool jumper can easily absorb light. But in many technical applications, you only have a thin layer of material available and you want the light to be absorbed exactly in this layer."

There have already been attempts to improve the absorption of materials: For example, the material can be placed between two mirrors. The light is reflected back and forth between the two mirrors, passing through the material each time and thus having a greater chance of being absorbed. However, for this purpose, the mirrors must not be perfect—one of them must be partially transparent, otherwise the light cannot penetrate the area between the two mirrors at all. But this also means that whenever the light hits this partially transparent mirror, some of the light is lost.

To prevent this, it is possible to use the wave properties of light in a sophisticated way. "In our approach, we are able to cancel all back-reflections by wave interference", noted HU's Prof. Ori Katz. Helmut Hörner, from TU Wien, who dedicated his thesis to this topic explained, "in our method, too, the light first falls on a partially transparent mirror. If you simply send a laser beam onto this mirror, it is split into two parts: The larger part is reflected, a smaller part penetrates the mirror."  .... ' 

Visibility Can Ease the Pain of Long Chassis Return Times

Made me think the process again.

How Visibility Can Ease the Pain of Long Chassis Return Times

August 26, 2022

By William Sandoval, SCB Contributor, in SupplyChainBrain

After a year of steady increases in freight prices, the U.S. trucking industry is experiencing a cooldown in demand, with linehaul rates declining significantly from their highs at the start of 2022. Trucking capacity has loosened considerably, thanks to new space entering the system, and a plateauing of consumer demand across major geographic markets.

The rise in trucking capacity also has to do with an improvement in efficiency across different nodes in the end-to-end supply chain, be it at ports, intermodal yards or warehouses. Transportation networks work in partnership, meaning that any tangible improvement in efficiency within one logistics segment has ripple effects on the efficiency of other segments.

As throughput across ports, intermodal yards and warehouses improved this year, the long truck queues outside their gates started dwindling, reducing idling times. This enabled drivers to keep their trucks moving for a longer duration within their allotted hours of service (HOS), directly increasing capacity availability without injecting fresh capacity into the system.

That said, the trucking industry is still far from solving some of its deepest challenges since the pandemic, such as the shortage of intermodal chassis in circulation. This bottleneck continues to tighten, threatening to set off a vicious cycle of delays throughout the logistics pipeline.

The industry isn’t suffering from an actual physical shortage of chassis. Instead, the current situation is a reflection of logjams that have persisted for a while, caused by a failure to optimize chassis usage. Chassis turnover days are a lynchpin metric that determines the health of the trucking economy, with higher numbers indicating a fall in efficiency.

TRAC Intermodal, the largest marine chassis provider in the U.S., reports a threefold increase in wait times for truckers to return chassis, compared with the pre-pandemic normal. This has an enormous impact on chassis availability. For fleets, increasing capital investment in procuring new chassis will also not be enough, considering the holdups in the system that will only continue to accumulate in the absence of serious optimization.

The headwinds to movement come from the railroad segment as well. The U.S. rail industry is seeing massive congestion across intermodal hubs such as Chicago and Joliet, with trains backed up for miles around their destinations. With the peak season approaching, shippers eager to front-load their inventories will cause an even greater surge in demand for capacity. 

This would add more burden to an already precarious situation. One common reason for delays in chassis returns is the truckers themselves. Stuck in long queues outside intermodal hubs and warehouses, they prefer to “drop and hook” their chassis, reducing the hassle of waiting for the containers to be off-loaded.

But with warehouses swimming in excess containers and struggling with historically low space availability, containers sit longer atop chassis, rendering the chassis non-operational for that duration. As warehouses continued to reel under space and labor shortage, container-bound chassis keep piling outside their gates, drastically increasing chassis turnover times. 

While fleets focus on leveraging drop-and-hook as a way to maximize their driver hours, it often comes at the expense of fleet utilization. With the industry being cyclical, the burden of delayed chassis inevitably comes back to hurt the fortunes of fleet businesses, as they scramble to find an empty chassis to haul the freight they signed up for.   .... ' 

On TAB Overloads in Chrome

 Well yes, will give this a try.

Overcoming Tab Overload   By Carnegie Mellon University School of Computer Science

In a study of Internet browser tab usage, computer scientists at Carnegie Mellon University (CMU) found that tab overload is an issue for many people.

The researchers assessed tab use via surveys and interviews, asking why people kept tabs open and why they closed them. They found that despite being overwhelmed by the number of open tabs, people did not want them hidden for fear they would not go back to them.

The researchers also created a Google Chrome browser extension, dubbed Skeema, to turn tabs into tasks. Skeema leverages machine learning to suggest how open tabs could be grouped into tasks and allows users to organize, prioritize, and switch between them.

CMU's Joseph Chee Chang said, "Our task-centric approach allowed users to manage their browser tabs more efficiently, enabling them to better switch between tasks, reduce tab clutter, and create task structures that better reflected their mental models."

From Carnegie Mellon University School of Computer Science

Accelerating the Speed of AI

Means of speeding p AI, decreasing energy use.

Accelerating AI computing to the speed of light   by University of Washington  in TechxPlore

Artificial intelligence and machine learning are already an integral part of our everyday lives online. For example, search engines such as Google use intelligent ranking algorithms, and video streaming services such as Netflix use machine learning to personalize movie recommendations.

As the demands for AI online continue to grow, so does the need to speed up AI performance and find ways to reduce its energy consumption

Now a University of Washington-led team has come up with a system that could help: an optical computing core prototype that uses phase-change material. This system is fast, energy efficient and capable of accelerating the neural networks used in AI and machine learning. The technology is also scalable and directly applicable to cloud computing.

The team published these findings Jan. 4 in Nature Communications.

"The hardware we developed is optimized to run algorithms of an artificial neural network, which is really a backbone algorithm for AI and machine learning," said senior author Mo Li, a UW associate professor of both electrical and computer engineering and physics. "This research advance will make AI centers and cloud computing more energy efficient and run much faster."

 More information: Changming Wu et al, Programmable phase-change metasurfaces on waveguides for multimode photonic convolutional neural network, Nature Communications (2021). DOI: 10.1038/s41467-020-20365-z

Journal information: Nature Communications 

OpenAI Monitors Machine Learning Efficiency

For now,  the most measurable and definable kind of AI is machine learning,   It uses much data and compute cycles.   Useful to measure the advances in efficiency.  That has been improving. according to OpenAI.  Notably that ' ... algorithmic progress has yielded more gains than classical hardware efficiency ...'.    At least for recent investments.  That is notable for future understanding of where to address our efforts.

AI and Efficiency  by OpenAI

We’re releasing an analysis showing that since 2012 the amount of compute needed to train a neural net to the same performance on ImageNet1 classification has been decreasing by a factor of 2 every 16 months. Compared to 2012, it now takes 44 times less compute to train a neural network to the level of AlexNet2 (by contrast, Moore’s Law3 would yield an 11x cost improvement over this period). Our results suggest that for AI tasks with high levels of recent investment, algorithmic progress has yielded more gains than classical hardware efficiency.

READ PAPER:  https://arxiv.org/abs/2005.04305  (technical)

Algorithmic improvement is a key factor driving the advance of AI. It’s important to search for measures that shed light on overall algorithmic progress, even though it’s harder than measuring such trends in compute ... '

Smart Meters not Influencing Electric Usage

Have always been interested in the influence of measurements, and the presentation of those measurements to influence behavior.   Many of our smart home experiments have tried to include that aspect of delivery.   Our home is fitted with a 'smart meter'.  Yet in this case Smart Meters are not doing the job:

Smart meters have little impact on people's energy usage habits, research finds  by Keele University in TechExplore

When the Smart Meter Rollout Programme launched a decade ago, it was touted as a way of helping consumers cut down on their energy usage, but new research has found that environmental concerns have little impact on reducing energy consumption.


Smart meters were introduced to allow customers to manage their energy use and it was hoped they would save money on bills and lessen their environmental impact by reducing energy demand, as well as changing their attitudes towards their energy use.

But new research by Keele University using focus groups has found that 10 years after the programme was rolled out, people's awareness around strategies for improving our energy efficiency is still only limited.

The findings also showed that environmental concerns are not a key driver in promoting energy reduction behaviours, not because participants don't care about the environment but because they felt a reduction in their energy consumption would have very little impact on the environment.  ... "

AI and Efficiency

Fairly obvious,  you can that most analytical and computing system have the same effect.  Consistency, speed, some level of autonomy,

How AI is Helping Efficiency Improve  By Kevin Gardner

AI is a wonder of modern science that has made a lot of things possible that were unthinkable before. Now thanks to AI many things can be done more quickly and more effectively. AI has increased the efficiency and productivity of many things in the industry. In this article, some of the examples of how AI has been helping in improving efficiency has been discussed.  ... " 

Learning More Efficient Allocation

Consider other possibilities for real time efficiency

Artificial intelligence could help data centers run far more efficiently
MIT system “learns” how to optimally allocate workloads across thousands of servers to cut costs, save energy.

Rob Matheson | MIT News Office

A novel system developed by MIT researchers automatically “learns” how to schedule data-processing operations across thousands of servers — a task traditionally reserved for imprecise, human-designed algorithms. Doing so could help today’s power-hungry data centers run far more efficiently.

Data centers can contain tens of thousands of servers, which constantly run data-processing tasks from developers and users. Cluster scheduling algorithms allocate the incoming tasks across the servers, in real-time, to efficiently utilize all available computing resources and get jobs done fast.   .... "  
                                                      

The Value of Inefficiency

I like the general thought.     Pure efficiency can make us miss things.   Its why  had second thoughts about optimization methods,  they could rarely be implemented directly, and their methods where often   did not give you enough hints at creative alternatives in context.  Podcast and transcript in K@W:

Edward Tenner discusses his new book about how too much efficiency kills creativity, innovation and problem-solving.

Technology is the undisputed champion of efficiency. Tasks that were once complex and time-consuming are now completed in the blink of an eye. But there is a downside to an abundance of technology. In his new book, scholar Edward Tenner explains how too much efficiency can kill creativity, which can turn off avant-garde thinking, innovation and problem-solving. He believes there is a better way to improve our lives through a combination of technology and intuition, and by exploring the random and unexpected.

Tenner, a distinguished scholar at the Lemelson Center for the Study of Invention and Innovation at the Smithsonian, spoke about his book, The Efficiency Paradox: What Big Data Can’t Do, on the Knowledge@Wharton radio show on SiriusXM. (Listen to the podcast at the top of this page.)

 An edited transcript of the conversation follows. ... 

Knowlege@Wharton: What’s so terrible about efficiency?

Edward Tenner: The problem with efficiency is that algorithms let us really learn from experience, they let us codify experience, they let us benefit, they recognize patterns. They are really tremendous at that. For example, I use the Google navigation program Waze. I first started out as a critic of it, but then I got into it more and more. However, the problem with Waze is that every once in a while, it will make a terrific blunder. If somebody relies completely on a system like that, no matter how brilliantly engineered, sooner or later some glitch is going to bite back. However, if they keep their awareness of where they are, if they keep their common sense, and if they keep trust in their common sense, then they can get the most of the program while avoiding those little disasters.

Knowlege@Wharton: Because we are so reliant on technology, are we losing something as a society, as a culture?    .... " 

Automation Making Retail Teams Less Efficient?

 An unexpected view.  Pointers to Wharton researcher work and expert comment in Retailwire.  Perhaps only until we learn to collaborate with advanced, initiative taking automation?

Will automation make retail teams less efficient?
Knowledge@Wharton staff

Presented here for discussion is an excerpt of a current article published with permission from Knowledge@Wharton, the online research and business analysis journal of the Wharton School of the University of Pennsylvania.

While the arrival of AI-supported automation in the workplace has led to concern about the potential loss of jobs, a new paper by a Wharton marketing professor explores the fate of those who keep their jobs but count robots instead of humans among their co-workers.

In “Men and Machine: When Should a Firm Adopt Automation?,” Wharton’s Pinar Yildirim and co-author Mustafa Dogan, a postdoctoral researcher at Carnegie Mellon University, show that in some cases, automation can actually lead to increased costs and inefficiencies because of its dysfunctional impact on human teams. ..... " 

Versustech

Recently looked at efficiency delivery in healthcare systems.  Here is one company that links location to efficiency.   Versustech.    Real time location system  (RTLS)  a part of Midmark.

Smarter Manufacturing Robotics with Watson

Interesting play, had never thought of Watson in terms of Robotics.  Note the wide variety of things ABB manufactures, which could lead to efficiency considerations, regarding scheduling and supply chain interactions.

Watson could be the key to smarter manufacturing robots
But will better bots take more jobs?
Rob LeFebvre, @roblef

Some reports predict that robots will replace 5 million jobs in the next couple of years. Bill Gates thinks we need a "robot tax" to compensate for those losses. A new partnership announced today between Swiss automation firm ABB and IBM's Watson initiative could hasten that future while it seeks to improve efficiency in on the manufacturing floor.

Swiss company ABB makes a ton of things, including electric vehicle power, industrial automation systems and manufacturing robots. It's biggest sales, though, come from software that enables communication between machinery and centralized control centers. It's looking to further this growth (and boost its sales) via this new partnership with Watson, IBM's artificial intelligence technology. ... " 

Coding Tips for Speeding up Python

Technical in CWorld: This came up in a recent effort.  Python is an interpreted language, thus slower than codes like C or Java. But there are ways to improve the comparison.  Though today we have much faster machines,  we are often working with much larger and complex data sets.

Internet of Things Shaking up Jobs

Some interesting examples of business IOT.  My electric meter was recently turned into an IOT device.

" ... After the town of Cary, N.C., installed a water meter system that automatically radios water usage to the public works department, it eliminated 10 meter-reading positions. The water resources group operates today with a smaller staff, thanks to the Internet of Things.

Workers used to check some 60,000 water meters once a month. Now the new meters record water usage each hour and transmit that usage data by radio four times per day. ... " 

Beyond Technology Efficiency

Efficiency should give you more time to do the things that you want.   But in practice humans and their managers and organizations often see this as a means to fit more things in.  The measures used and the rewards included are often ill defined and well integrated into our own heads.  So how can we make sure that technology helps us, rather than ensnare us?

Technology Should Be About More than Efficiency
by John Hagel III
" ... The very same technology that is generating this mounting performance pressure also provides us with the platforms and tools to re-awaken our imagination and overcome the cognitive biases that keep us confined within the practices of the past.  ... "

Improving Application Development

Creating reliable systems is still quite inefficient.  McKinsey reports on enhancing efficiency and effectiveness. " ... Software has become critical for most large enterprises. They should adopt a reliable output metric that is integrated with the process for gathering application requirements. ... "

CSX Efficiency Statement

In a CSX advertising piece, they point out that one of their trains can move a ton of freight nearly 500 miles on a gallon of fuel.  Nice going.   More from CSX.