Monthly Archives: August 2023

Like a lot of other runners, I obsess over shoes. Compared with other sports, running doesn't require a lot in terms of equipment, but you can't cut corners when it comes to your feet.

For me, a good fit and comfort are most important, but I also don't want shoes that will slow me down. Super-cushioned sneakers might be great if you're doing a loop around the neighborhood with your friends, or if your job requires you to spend all day on your feet, but not when you're trying to cut a few minutes off a race time.

That search for the perfect combination has felt like a never-ending quest since I started running a couple years ago. Now, training for my very first marathon, the TCS New York City Marathon on Nov. 5, the stakes are higher than ever. So when I was offered the chance to try out Fleet Feet's new and improved shoe-fitting software that's powered by artificial intelligence, I went for it.

But that doesn't mean I wasn't skeptical about its capabilities. Up until recently, a lot of consumer-facing AI has been more hype than reality. Meanwhile, I've been shopping at Fleet Feet, a national chain of specialty running stores, since shortly after joining my neighborhood running group in March 2022.

For more than a year, the company's in-house shoe nerds, which Fleet Feet refers to as outfitters, have largely kept my feet happy. They've answered all of my nitpicky questions and their recommendations changed as my running needs and goals evolved over time.

How does AI play into that?

In this case, AI provides a way to let store employees quickly compare the specific dimensions of my feet with those of millions of others, along with the designs of the shoes in their inventory, to pick out which ones might fit me the best.

The AI isn't designed to replace expert employees, it just gives them a better starting point for finding shoes with the correct fit, says Michael McShane, the retail experience manager for the New York store I visited.

"It turns the data into something much more understandable for the consumer," McShane says. "I'm still here to give you an expert assessment, teach you what the data says and explain why it's better to come here than going to a kind of generic store."

Anyone who's ever set foot, so to speak, in a running store knows there are lots and lots of shoes out there, and everyone's feet are different. What could feel like a great shoe to one person, could be absolute torture to run in for another.

A look at some of the data collected by a Fleet Feet fit id scan.

Originally rolled out in 2018, Fleet Feet's Fit Engine software analyzes the shapes of both of a runner's feet (collected through a 3D scan process called Fit ID) taking precise measurements in four different areas. It looks at not just how long a person's feet are, but also how high their arches are, how wide their feet are across the toes and how much room they need at their heel.

Plates in the scanner also measure how a person stands and carries their weight. Importantly, the scanner looks at both feet. Runners especially put their feet through a lot of use and abuse, making it likely that their feet will be shaped differently,

Mine were no exception, One of my feet measured more than a half size bigger than the other. I can't say I was surprised. In addition to ramping my training up to an average of 20 miles a week over the past year, my feet have also suffered through 17 years on the mean streets of New York, two pregnancies and one foot injury that left me with a wonky right big toe.

What was a little surprising was both feet measured bigger than my usual size 9 or 9.5. I've always had big feet, especially for a woman that stands just over 5 feet tall, but I'll admit that it was still a little traumatizing to be trying on shoes a full size larger than that for the first time.

The software's AI capabilities allow the system to then quickly compare the data from a customer's scan to all of the shoes in the store's inventory, as well as the millions of other foot scans in the system. Each shoe is graded as to how its measurements matched up with the customer's. Color-coded graphics show how each shoe measures up in specific areas.

While store employees have used versions of the software including the AI over the years, Fleet Feet says the latest improvements make it consumer facing for the first time, instead of something that takes place completely behind the scenes. The ultimate goal is to add it to the company's website to make it easier to find shoes that fit online, something that's notoriously tricky even for the biggest running shoe enthusiasts.

In addition to telling McShane and me how well a shoe could potentially fit, the software gave me a specific starting size to try on, since sizing can vary depending on shoe brand and model.

And I sure did try on shoes. The AI gave McShane loads of suggestions to start with, but it was up to him to narrow it down for me, taking into account my training needs and preferences. Ultimately, I wanted something cushioned and comfortable enough to get me through a marathon, but still light and agile enough that I wouldn't feel clunky or weighed down.

I also wanted something new. After a year of almost religiously wearing Hoka Cliftons for everyday runs, they now felt too bulky and slow. I also liked the Brooks Ghost trainers, but more for walking around New York than racing.

And I was more than happy to say goodbye to a pair of Nike Zoom Fly 5 shoes that I bought for the NYC Half Marathon. Their carbon-fiber plates and light construction made them super speedy, but their lack of heel cushioning gave me monster blisters that would explode and bleed. Sure I could have taken them back, but I liked their speed so much I just tapped my feet up every time I wore them to protect against the rubbing.

The MIzuno Wave Rider 26.

I spent well over an hour at Fleet Feet trying all kinds of shoes. Since the AI had pinpointed the appropriate size for each model, the sizes I tried on varied but they all pretty much fit. That in itself was a time saver. The main challenge was figuring out what felt the most comfortable when I took a jog around the store.

A pair of Brooks Glycerin felt cushy, but also a bit clunky. I loved a pair of Diadoras from Italy, but they ran small and the store didn't have my size, which probably would have been a monster 10.5, in stock. Conversely, a New Balance model I tried seemed too roomy to give me enough support.

For me, it was about finding the right level of cushioning and weight. Per McShane's advice, I tried my best to ignore colors. When it comes to running shoes, I'm a big fan of bright, fun colors, but looks don't help with comfort or cut seconds off your mile pace.

After many, many boxes, it came down to the Asics Gel-Cumulus and Mizuno Wave Rider (both $140). Both were light and springy and I took more than one jog around the store in both of them. I also tried them out with a new pair of insoles ($55), which also were fitted to me with the help of the AI.

I've never used insoles before, but I was told that they would give me greater support for the kind of double-digit mile training I had ahead of me, improving my endurance and reducing the chance of injury. Socks are also key to preventing dreaded blisters, so I grabbed a pair of my go-to Feetures Elite Ultra Lights ($18).

After much debate, I ended up walking out of the store with the Mizunos. While I've had Asics in the past, I've never tried Mizunos before. They seemed a bit faster and more tailored to my feet than the Asics were. It also turned out that they were on sale and I ended up getting them for $105.

That's because there's a new version rolling out that the store didn't have in stock yet, so they weren't in the system for the AI to find. While it was nice to save $35, had I known that I might have gone with the Asics just because they're more current.

After four runs totaliing about25 miles, I still like the shoes, though the insoles have taken a little getting used to, but I'm also thinking about picking up a pair of the Asics just to compare.

For most people, this use of AI will probably go unnoticed, at least until it's added to the website. While officially now geared to the consumer, it still seems more of a tool for store employees. Sure, data-crunching AI can be great, but it's the efforts and expert advice of the outfitters themselves that are going to ensure that I keep coming back to their stores.

After all, the TCS NYC Marathon isn't until Nov. 5 and I've got a long road of many miles and many, many pairs of shoes ahead of me before I reach the starting line.

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Can AI Help Me Find the Right Running Shoes? - CNET

Cell counting is extremely important in research, medicine, and even environmental monitoring where scientists use it to track cell growth, a persons health, or monitor plankton levels in oceans or bacteria in a water sources.

But scientists who have used a hemacytometer, a specialized laboratory device used for manual cell counting, might tell you how challenging it can be to accurately determine cell numbers. This is because the hemacytometer consists of a thick glass slide with a rectangular indentation that creates a counting chamber. The chamber is divided into grids or squares with known dimensions, allowing for accurate cell counting and concentration calculations. It can be quite a challenge to figure out the number of cells in those tiny spaces.

Manual cell counting is a tedious task, explained Yudong Zhang, professor of School of Computing and Mathematical Sciences,University of Leicester in an email. It requires operators to count cells in the small grids of a counting board under a microscope. The grids on the counting board are divided into tiny sections, making it easy to make counting errors. Moreover, performing such a concentration-demanding task for a prolonged period can also have an impact on the operators physical well-being.

Zhang, therefore, wondered whether in this age of AI and automation if something more could be done to alleviate the burden of manual counting methods, which are often time consuming, labor intensive, and susceptible to human error.

Last year, while tutoring my cousin for his high school assignment, I came across a question about using a blood cell counting board to count cells, said the studys co-author, Lijia Deng. It made me curious if there were AI technologies available for this purpose. After conducting a bit of research, I found that there were opportunities to improve existing cell counting methods.

Alongside colleagues, Shuihua Wang and Qinghua Zhou from the same university, the team set out to alleviate the burden of manual counting. To do this, they created an innovative automated detection method powered by AI.

Automated cell counting methods are not completely absent from these fields. However, mainstream instruments are based on the Coulter Principle, which is the detection and measurement of changes in electrical resistance produced by a particle or cell suspended in a conductive liquid, explained Zhang. These instruments do not provide visual feedback, and cell morphology often reflects important information, such as the differences between cancer cells and normal cells.

In a recent study published in Advanced Intelligent Systems, the team unveiled a revolutionary deep learning network they called Spatial-based Super-Resolution Reconstruction Network (SSRNet), which was spearheaded by Deng. This network predicts cell counts and segments cell distribution contours with remarkable precision, said Zhang.

Using this method, the cell sample is captured as an image which is then processed to enhance the clarity of the cells against the images background. The image is then fed to the AI counting system, which generates the cell count and distribution within the image.

This AI-based approach can quickly predict the number and distribution of cells with just a single image, said Zhang. The principle of this method lies in the convolutional neural networks focus on cell features, enabling the prediction of cell count and distribution.

Traditionally, AI uses artificial neural networks computational models inspired by the structure and function of the human brain to perform tasks and learn from encountered situations. Training any neural network model requires rich datasets, added Zhang. And there is a lack of sufficient, annotated datasets in the field of cell imaging.

The team therefore took a different approach to overcome the lack of data needed to train their model, instead using it to predict the overall quantity and distribution regions to accomplish the task of cell counting.

They did this by taking advantage of a concept called upsampling, which is a technique used to increase the resolution or sampling rate of digital data. It involves taking existing digital samples and adding extra samples in between them to create a higher-resolution version of the original data.

The traditional method is to use purely mathematical methods, which introduce new pixel values due to mathematical calculations, explained Deng. Although these new pixels make the image appear clearer, they can affect the prediction of quantity. Our method uses artificial intelligence to predict new pixels, reducing the potential system errors caused by mechanical calculations, improving counting accuracy, and also achieving the performance of traditional methods in clarity.

Its like rolling out the dough after fermentation our approach doesnt introduce new pixels out of thin air; each new pixel is inferred from existing ones, Deng continued. Compared to purely mathematical methods, our approach ensures better consistency between the upscaled image and the original image in terms of features. Additionally, the larger the scaling factor, the more apparent the advantages become.

There was also the added challenge of ensuring their AI system could be used anywhere, even in regions with limited computing resources. To help popularize our AI model and make it available to labs that may lack advanced computing resources, we made our neural network model extremely lightweight so that its running memory read and write consumption is only 1/10 of a traditional AI model.

The innovative features of their AI model will allow it to find application beyond just medicine and biology, promising to unlock new possibilities in various industries. As proof-of-concept, the team demonstrated how this model could be used to count the number of sesame seeds on a piece of bread.

Sesame counting was done just for fun, say the team, it has no practical significance but demonstrates the methods sophistication and speed, which could one day be applied to more advanced applications, including cell counting, among others. For example, we could eventually use aerial photography to remotely capture the breeding population of penguins to understand their population size, which avoids human interference with animals, explained Deng.

This method represents a significant leap forward in the field of cell counting, said Zhang. By leveraging the power of AI and innovative spatial-based super-resolution reconstruction techniques, this approach offers unprecedented precision and efficiency in predicting cell numbers and distributions, which can help fight against infectious diseases.

With its potential, this advancement promises to streamline processes, reduce human error,. As the research continues, further refinements and applications of this AI-powered method are expected to reshape the landscape of cell analysis, ultimately benefiting countless individuals and facilitating scientific progress.

Reference: Lijia Deng, Qinghua Zhou, Shuihua Wang, Yudong Zhang, Spatial-Based Super-resolution Reconstruction: A Deep Learning Network via Spatial-Based Super-resolution Reconstruction for Cell Counting and Segmentation, Advanced Intelligent Systems (2023). DOI: 10.1002/aisy.202300185

Feature image credit: Scott Webb on Unsplash

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AI is revolutionizing manual cell counting - Advanced Science News

Born in Omaha, Nebraska on Aug. 30, 1930, Warren Buffett has become one of the most successful investors in history. TheBerkshire Hathaway CEO has led his company on an incredible run of market-beating success and generated fantastic returns for long-term shareholders. He's also been an inspiration to millions of investors around the world and helped popularize wisdom, strategies, and individual investment opportunities that have put people on a path to financial freedom.

If you're looking to follow in Buffett's footsteps, read on to see why two Motley Fool contributors believe that investing in these Berkshire Hathaway portfolio components would be a smart move this month.

Keith Noonan: If you're looking to replicate Buffett's investing moves, it makes sense to own Apple (AAPL 0.06%) in your portfolio. In a stunning vote of confidence, the Oracle of Omaha has made the tech stock Berkshire Hathaway's largest portfolio holding by far. Apple currently accounts for 46.9% of the company's stock portfolio. For comparison, Bank of America is Berkshire's second-largest stock position and makes up 8.9% of its total portfolio.

In recent years, Apple has often ranked as the world's most profitable company or taken second place behind oil giant Saudi Aramco. The tech giant stands as the world's largest company and currently has a market capitalization of nearly $3.1 trillion. Buffett loves companies with strong brands that are capable of serving up consistent profits, and Apple's world-beating business performance has made the stock a big winner for Berkshire Hathaway.

Berkshire first bought Apple shares in the first quarter of 2016, and investing in the tech giant has played a huge role in powering the tech conglomerate to beating the S&P 500 index since then. Berkshire's share price has climbed 171% since the beginning of 2016, handily topping the S&P 500 index's total return of 158% across the stretch.

Meanwhile, Apple stock has delivered a dividend-adjusted total return of 718% across the stretch.

AAPL Total Return Level data by YCharts

In addition to claiming more than 85% of global operating profits from smartphone sales, Apple has been gaining ground in the computers market, growing its software-and-services segment and scoring wins in emerging categories like wearable hardware. With one of the strongest brands in the tech space and a proven penchant for design excellence, the company could also go on to be a big winner in categories like augmented reality, smart cars, and artificial-intelligence-powered personal assistants.

Apple's brand and ecosystem strengths are unmatched in the consumer hardware space, and the company will likely continue to be a technology leader for decades to come.

ParkevTatevosian: One of my favorite Warren Buffett stocks to buy right now is Visa. The financial processing company has spent decades building a network of merchants that accept its cards as a payment method. On the other side of the transaction, there are over 4 billion Visa cards in consumer wallets today. Arguably, the most challenging part of its business plan is behind it.

That can certainly be observed in Visa's financial figures. Revenue grew from $11.8 billion in 2013 to $29.3 billion in 2022. The company benefits from moderate inflation since Visa primarily generates revenue as a percentage of transaction value using a Visa card.

More importantly, Visa has built an extremely profitable business. Its operating income rose from $7.2 billion to $19.7 billion in the abovementioned years. For 2023, Visa earned an astounding 67.1% operating profit margin. That figure is among the highest of any companies in Buffett's Berkshire Hathaway portfolio. It's also the highest of any of the businesses I follow.

V PE Ratio (Forward 1y) data by YCharts

Fortunately, investors don't have to pay an arm and a leg for this incredible stock. Visa is trading at a forward price-to-earnings multiple of under 24.5. Paying a fair price for an excellent business is a reasonable recipe for investment success. I'm not surprised that one of the greatest investors of all time has Visa stock in his portfolio.

When it comes to picking stocks, Warren Buffett famously prefers to keep it simple and avoid companies and situations that are overly complex. Within that mold, Apple and Visa are large, well-known companies that can be counted on to reliably generate significant profits. They might not be the most explosive stocks on the market, but they offer well-balanced risk-reward profiles, and it's not hard to see why Buffett's company has invested in them.

Bank of America is an advertising partner of The Ascent, a Motley Fool company. Keith Noonan has no position in any of the stocks mentioned. Parkev Tatevosian, CFA has positions in Apple and Visa. The Motley Fool has positions in and recommends Apple, Bank of America, Berkshire Hathaway, and Visa. The Motley Fool has a disclosure policy.

Originally posted here:

2 Warren Buffett Super Stocks to Buy Hand Over Fist in August - The Motley Fool

MQ-9B SeaGuardian on patrol above the North Sea during the 2021 European Maritime Demos.

Unmanned aircraft have been revolutionizing intelligence, military, and so many other applications for years. Now their impact extends to the way navies operate at sea.

Leading the way is the MQ-9B SeaGuardian, which enables the most advanced navies, coast guard agencies, and other maritime authorities to patrol longer, detect more, and make existing units much more effective.

Manufactured by San Diego-based General Atomics Aeronautical Systems, Inc., MQ-9B SeaGuardian has recorded a number of recent first-ever achievements in a range of operational and test environments around the world. Even as users prove out what the system can do as it begins to enter widespread service, theyre only scratching the surface of the ways MQ-9B will help rewrite the practice of sea power.

SeaGuardian has shown it can hunt for and help prosecute submarines. It escorts naval surface task groups. It provides sensing, targeting, and communications for the battle force. It self-deploys from its home station and integrates seamlessly into normal aviation traffic. When the mission is over, it flies back to its home station to get ready for the next assignment.

A substantial track record already is coming into focus.

In just two years time, the aircraft has recorded more than 12,000 operational hours in the service of the Indian Navy.

MQ-9B provided security and surveillance for the recent G7 2023 summit at its island location in Hiroshima, Japan.

And SeaGuardian has joined the U.S. Navy for some of its most complex and challenging integrated exercises including a major anti-submarine warfare exercise this past May in which the aircraft, flown by its crew from a ground control station and operated via satellite, joined with U.S. Navy helicopter squadrons to search for submarines in a range off the coast of Southern California. Helicopter crews flew out from San Diego, dropped their sonobuoys, and then SeaGuardian took over monitoring them. Shortly thereafter, its sensors detected a simulated submarine. This meant other helicopters could deploy to the scene armed with precise data about the targets location and course and then attack.

This U.S. Navy sub-hunting exercise was one of only several such exploits for SeaGuardian. In April, another, known as Group Sail, involved the aircraft partnering with Navy carrier strike groups off the coast of Hawaii, working with warships, aircraft, and other units to ensure the safe passage of the groups surface ships.

Strike Group Integration

As part of Group Sail, carriers, cruisers, and destroyers, as well as F-35 Lightning II fighters, F/A-18E/F Super Hornets, EA-18G Growlers, E-2D Advanced Hawkeyes, MH-60 Seahawks, and P-8 Poseidons worked alongside MQ-9B SeaGuardian, which provided the Navy with maritime domain awareness, information dominance, targeting capability, and more. What the aircraft did, in effect, was serve as the distant eyes and ears for naval commanders.

Its onboard sensors can see all through the visual and infrared spectrum, including with its onboard multi-mode radar through clouds, fog, mist, or smoke. Other onboard systems can hear throughout the radio frequency spectrum, collecting intelligence of all kinds that contributes to the most complete common operating picture possible.

No other large medium-altitude, long-endurance aircraft can contribute to sea power like this and there are even more ways that SeaGuardian contributes. The aircrafts proprietary Detect and Avoid System, invented by GA-ASI, means that it can operate in civil airspace just like any other aircraft. This eliminates the need for special arrangements or human-flown escort aircraft like those that remotely piloted aircraft might have needed in the past.

Also new: SeaGuardian self-deploys to far-flung operating areas. In each of the U.S. Navy maritime exercises described here, the aircraft took off from its home station in California and flew to the base where it was needed. Compare the convenience and simplicity of that kind of operation to the way some unmanned aircraft might have worked in the past being disassembled, packed into a crate, flown in another aircraft, and then reassembled for use on station. SeaGuardian makes all that unnecessary, with a great savings of time, money, and personnel.

Advanced onboard and supporting systems help make all this possible, including automatic takeoff and landing, artificial intelligence and machine learning, and cutting-edge networks. Satellite operations mean that MQ-9Bs pilots and crews can be located anywhere. During a May 2023 Northern Edge exercise around Alaska, for example, the crews flew SeaGuardian from the Pacific Northwest area of the United States at Naval Air Station Whidbey Island.

Such remote operation not only removes human crews from harms way at sea. It means MQ-9B can cover other inhospitable areas, such as the Earths cold ice-covered polar regions, without burdensome hardship deployments for crews or the necessity of also deploying search and rescue teams in case of a mishap. Taking the people off the aircraft protects them and their support units all while reducing cost and complexity.

The big challenges of the 21st century to seafaring nations and the responsible use of the oceans arent simple or easy to tackle. But the good news is that navies, coast guards, and others charged with sea power, maritime domain awareness, search and rescue, and other missions have a tool ready to meet those challenges head-on in the MQ-9B SeaGuardian.

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MQ-9B - A Growing Track Record of Performance in the Maritime ... - General Atomics Aeronautical Systems