#process automation case study

[sanjida1]

AI HIGH TICKET COMMISSIONS

[itesservices]

😎 Take a Look at This Automated Data Processing Success Story

🚼 Embark on a transformative journey with our automated data processing success story. Discover seamless efficiency and unparalleled success as we share insights, strategies, and real-world results that showcase the power of automated data processing. Revolutionize your approach and join the ranks of those who have unlocked unprecedented productivity and triumph.

[essglobe]

Tailored Services: RPA Services for the Manufacturing Industry

There is a broad range of other RPA use cases in manufacturing apart from the above-mentioned ones in the vast manufacturing industry. If you feel like your business is not moving into the digital age quickly enough and existing systems are too complex or old to integrate and automate, then ESS RPA consultants can help you to move forward with your RPA goals faster.

Elevate your manufacturing with specialized RPA services. Unlock tailored solutions that optimize processes and drive efficiency in your industry.

[andrewleousa]

Automated Data Processing Case Study: Explore How a RegTech Firm Enhanced Its Business Agility 

Are you also struggling with inefficient workflows to collect, transform, process, and analyze ever-increasing volumes of data? Irrespective of the answer, you need to go through this automated data processing success story to discover the power of technology. Learn how cutting-edge technology streamlines workflows, eliminates errors, and boosts productivity. Unleash the potential of your business with efficient data processing solutions.

[covid-safer-hotties]

Also preserved on our archive

Whenever you hear someone trying to blame kid's poor test scores "post pandemic" on "lockdowns," show them this.

By Dr. Sushama R. Chaphalkar, PhD.

New research shows that mild COVID-19 alters brain structure and connectivity in key areas responsible for memory and cognition, emphasizing the lasting effects on young people’s brain health.

In a case-control study published in the journal Translational Psychiatry, researchers used magnetic resonance imaging (MRI) and cognitive tests to examine brain structure, function, and cognition in adolescents and young adults with mild coronavirus disease 2019 (COVID-19) compared to healthy controls in a pandemic hotspot in Italy. They identified significant changes in brain regions related to olfaction and cognition, with decreased brain volume and reduced functional connectivity in areas like the left hippocampus and amygdala, which were linked to impaired spatial working memory. Notably, no significant differences were observed in whole-brain connectivity, suggesting that these changes were localized rather than widespread.

Background COVID-19, primarily known for respiratory symptoms, also affects the central nervous system, leading to neurological issues like headaches, anosmia, and cognitive changes. MRI-based studies reveal anatomical brain changes in COVID-19 patients, such as reduced gray matter and decreased volume in regions like the hippocampus and amygdala, often linked to cognitive deficits.

While research mostly focuses on severe cases and older adults, a majority of infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, occur in adolescents and young adults who also experience long-lasting cognitive symptoms.

This age group, undergoing key brain development, is impacted by changes in spatial working memory and brain structure, which are crucial for cognitive functions shaped by social interactions, significantly disrupted by the pandemic.

Given that this is the largest and most understudied population affected by COVID-19, understanding the brain and cognitive impacts in adolescents and young adults is vital.

Therefore, researchers in the present study compared anatomical, functional, and cognitive outcomes, utilizing a longitudinal design that allowed them to assess both pre- and post-infection differences, in COVID-19-positive and negative adolescents and young adults from Lombardy, Italy, a global hotspot during the pandemic.

About the study The present study involved participants from the Public Health Impact of Metal Exposure (PHIME) cohort, a longitudinal investigation of adolescents and young adults in northern Italy. Between 2016 and 2021, 207 participants, aged 13 to 25 years, were included in a sub-study with MRI scans and cognitive tests. After COVID-19 restrictions were lifted, 40 participants (13 COVID+ and 27 COVID−) participated in a follow-up study, which replicated the MRI and cognitive assessments.

The mean age of participants was 20.44 years and 65% were female. COVID+ status was confirmed through positive reverse transcription polymerase chain reaction (RT-PCR) tests within 12 months of follow-up. Neuropsychological assessments used the Cambridge Neuropsychological Test Automated Battery (CANTAB) to evaluate spatial working memory.

MRI and functional MRI data were acquired using a 3-Tesla scanner, processed, and analyzed for structural and local functional connectivity using eigenvector centrality mapping (ECM) and functional connectivity (FC) metrics. Whole-brain functional connectivity metrics showed no significant differences between COVID+ and control groups, indicating that the observed changes were specific to key brain regions rather than generalized across the entire brain.

Statistical analysis involved the use of pairwise Student's t-tests, Kolmogorov–Smirnov test, linear regression, two-waves mediation analysis, negative binomial regression, and linear regression, all adjusted for covariates.

Results and discussion Significant differences were observed in the two groups regarding the time between assessments, COVID-19 symptoms, and vaccine status. The research identified five localized functional connectivity hubs with significant differences between the two groups, including the right intracalcarine cortex, right lingual gyrus, left frontal orbital cortex, left hippocampus and left amygdala, which is vital for cognitive functions. Only the left hippocampal volume showed a significant reduction in COVID+ participants (p = 0.034), while whole-brain connectivity remained unchanged, reinforcing the localized nature of the brain changes.

The left amygdala mediated the relationship between COVID-19 and spatial working memory "between errors" (p = 0.028), a critical finding that highlights the indirect effect of amygdala connectivity on cognitive function in COVID+ individuals. This mediation analysis underscores the role of specific brain regions in influencing cognitive deficits, as only the indirect effect was statistically significant for spatial working memory errors. The orbitofrontal cortex, involved in sensory integration and cognitive functions, also showed decreased connectivity in COVID+ individuals, supporting previous findings of structural and functional changes in this region during COVID-19.

The study is limited by small sample size, lack of diversity, potential confounding factors due to the long interval between MRI scans, treatment of certain subjects as COVID-negative based on antibody testing beyond the 12-month threshold, and the possibility of non-significant findings in mediation analysis due to these factors.

Conclusion In conclusion, the findings indicate persistent structural and functional alterations in specific brain regions of COVID-19-positive adolescents and young adults, including changes in gray matter volume and localized functional connectivity, which correlate with diminished cognitive function, particularly in working memory.

Further research is necessary to evaluate the longevity and potential reversibility of these brain and cognitive changes post-infection, enhancing our understanding of post-COVID outcomes and informing future interventions and treatments. The longitudinal design of this study, with pre- and post-COVID data, strengthens these findings by allowing direct comparisons over time, offering robust insights into the impact of COVID-19 on adolescent brain development.

Journal reference: COVID-19 related cognitive, structural and functional brain changes among Italian adolescents and young adults: a multimodal longitudinal case-control study. Invernizzi, A. et al., Translational Psychiatry, 14, 402 (2024), DOI: 10.1038/s41398-024-03108-2, www.nature.com/articles/s41398-024-03108-2

[milk5]

On the Skidelsky/Fuller post I reblogged, I absolutely welcome automation given the following criteria:

1. The output is identical or, holistically, more positive than human labor output

2. This automation occurs within an economic system in which GDP growth (or similarly fraught metrics) is not the primary objective

3. The automation aids the sustainability of nature and humanity

The USA's agriculture industry is a wonderful example of modern automation failing all three of these criteria. Throughout the entire industrial revolution, agriculture has trended away from being a society-wide confederation of family/community-scale, labor-intensive smallholdings to our current reality of a small number of monolithic industrial farms that are maintained by astoundingly few people who operate increasingly complex and expensive equipment.

Our massive-scale industrial farms are fantastic at what they were designed for; they grow as much of a staple crop as possible without regard to human or environmental health, doing so using minimal labor. Fundamentally, it is an extractive industry. Fossil fuels are extracted to power the machinery, processing, and logistics systems. Nutrients are extracted from the soil to the point that crop growth can only be sustained with heavy amounts of industrial fertilizer input. Entire ecosystems are sacrificed when forests are cleared to be exploited and repeatedly battered with pesticides. This is all primarily to produce soybeans, feed corn, and cotton to then process into products like factory farm livestock feed-slurry, corn syrup, junk food, and sweatshop garments. Secondarily, it is to produce flavorless, nutrition-void produce that can be sold year-round. Consistency is the goal, although one may find that nature itself is curiously inconsistent.

This case study of automation's failings can be traced back to a few major factors:

1. Old-style agriculture work is disagreeable to the USA's perverted fascination for infinite GDP growth; each farm laborer that can be replaced by a machine is a potential worker that could move into a city (or suburb) and put in the same amount of hours at a higher-dollar job. It's just opportunity cost, and this is more-or-less what Skidelsky and Fuller find offensive about our current labor zeitgeist; instead of the now-jobless laborers being free to pursue their interests, they are instead shoehorned into some shitty desk job that produces a relatively greater amount of money to be leeched by executives and shareholders -- this is "more productive" to our economy on the basis of GDP growth and thus must be prioritized over agricultural labor.

2. Industrial approaches to large-scale agriculture are inherently reductive to an extreme extent. Nature is far more complex than Liebig or any other enlightenment thinker ever imagined. Industrialization is great at making cars or computer chips or Gucci jackets or whatever, as these are things that can be standardized with relative ease. Nature cannot be tamed and standardized in a similar way; ecosystems, particularly soil ecosystems, can vary massively even in small areas of the same climate type. Our agriculture systems cope with this simply by ignoring such factors and reducing crop growth to a formula. In X region, plant Y variety of Z crop on A date and apply a regimen of B-type fertilizer and C-type pesticide on D date etc etc. This is the most egregious reduction of something in all of history.

Liebig's reduction of agriculture to the NPK model, just three elements, is good for achieving the singular goal of making your plant of choice come out of the ground, but it ignores all the nuance of soil, climate, and evolution. The other factors don't matter. Modern lab-designed fertilizers often feature a plethora of additional micronutrients, but the goal is still to produce a healthy crop, not healthy soil. Soil itself is an organism, it is something that must be nurtured to be healthy; industrial pesticide/fertilizer regimens are to the soil as feed slurry/antibiotic regimens are to factory farm animals.

Natural processes are, itself, the greatest form of automation for agriculture. Plants and animals that are native to a region have evolved to grow there regardless of human intervention. It is our disruption of these processes that forces agriculture to be labor/resource-intensive. This isn't to say that everyone must immediately abandon all non-native foods and adopt a primarily undomesticated Ötzi diet, but instead, it's worth considering that the complexity of modern technology is not even close to being at parity with the complexity of nature; nature has a several billion year head start. There is no way to flawlessly "tame" it with technological solutions, but a comfortable middle ground can certainly be found.

If sustainable, climate-friendly food production is the primary objective of agriculture, this is far more easily achieved by small, ecology-considerate farms than massive, largely automated industrial farms. A healthy soil ecosystem will aid in growth, flavor, nutrition, and, (quite importantly) carbon sequestration. Broadforking, shoveling, and wheelbarrow-pushing is absolutely more labor intensive than sitting back in a huge John Deere tractor with GPS-based autopiloting features, but the extra labor can turn a woefully extractive process into one that is instead highly regenerative.

[singularscissor]

Bright Crown is a highly experimental orbital iterator project. They were built in space in order to study and make use of conditions there.

A lot of words about their structure and how it works under the cut:

Their facility is consists of three main portions: the outer 'habitable' ring, a second concentric 'conduit' ring, and the central neural core.

Normally, the entire structure rotates along the outer/hab ring, in order to generate centrifugal artificial gravity (which is far more efficient than using gravity cores). This is particularly important, because the hab ring is home to an ecosystem of purposed organisms. These are designed to automate many processes, such as waste recycling, maintenance, handling of inbound supplies, etc. In times past, small research teams also lived in the hab ring.

Skipping the conduit ring for the moment, the neural core is where most of the stuff you'd normally expect to find in an iterator is located: neurons, processing strata, memory conflux, all those parts which actually form the brain of the iterator. And of course the focal puppet chamber.

Since the neural core is at the center of the spinning structure, it is not affected much by the centrifugal artificial gravity. Therefore, it can effectively utilize the natural low gravity environment as opposed to maintaining a constant antigravity field, as land-based iterators do. Additionally, heat sinks radiate heat directly into the vacuum of space, eliminating the need to use water as coolant.

However, water is still needed for use by the internal biological processors and neural tissue. Thus we arrive at the conduit ring, placed in between the hab ring and the neural core.

Without luxuries such as atmosphere and the ground, water on Bright Crown must operate on an artificial closed system. The conduit ring is a series of pipes, filters, and reservoirs intended to form a rough equivalent to the natural land-based water cycle.

Each section can pivot independently of the other sections and the overall spin of the station. While idle, the conduit ring spins slowly on its pivot (this helps it process water).

Bright Crown follows a similar cycle system as land iterators, where water is 'expelled' at regular intervals; only in this case the water is expelled into the conduit ring rather than the atmosphere. When enough water has been used, the conduit ring locks onto the neural core, and the entire station begins spinning along the conduit ring instead. The same method of artificial gravity is thus used to push the water out of the neural core, flooding the conduit ring.

But, keep in mind, the conduit ring could be at any point in its rotation when a flush cycle begins. Changing the spinning direction of the entire structure disrupts the hab ring's artificial gravity, and would generally not be great for anything living there (it would throw them around like they're in a giant washing machine). So there are shelter areas throughout the hab ring which are protected by antigravity cores, which suppress the spinning forces.

[ideas-on-paper]

Theories about Legion's "mini headlamps" (N7 special)

A very happy N7 Day to all of you Mass Effect fans!

Although I still haven't finished Mass Effect 3 (I just haven't been able to pick it up again after the Rannoch arc), I nevertheless wanted to do something special for this occasion, and I thought to myself that I might as well devote a quick study to a subject that's been on my mind for quite a long time: the purpose of Legion's three additional "mini headlamps".

You see, aside from the big, obvious flashlight in the middle, Legion also possesses three smaller lights at the side of their head. Ever since discovering these, I've been wondering what exactly those are for. I've observed that they glow red when Legion is under "stress" (an effect which is unfortunately not present in the Legendary Edition) - or rather, in situations that require a lot of processing power - but as far as their practical function goes, I could only guess. However, going through the ME3 dialogues again, I noticed a small detail which could potentially explain what exactly those small lights are - and in addition, give us a little insight into how Geth perceive the world visually.

Disclaimer: Before going into this, I should mention that I have no technical education in robotics, laser scanning, or any related areas of engineering. I based my conclusions solely on what information I could find on the internet, as well as my own reasoning and observations.

[Potential spoilers for ME3]

LADAR/LiDAR scanning and three-dimensional perception

To start off, what basically led me on this track was this comment by Tali in ME3:

Their AI lets them use extremely detailed ladar pings. Xen's countermeasure overwhelmed them with garbage data.

First off, we need to clarify what exactly ladar is. LADAR, more commonly known as LiDAR, stands for "Light amplification by Stimulated Emission of Radiation detection and ranging" - or, in case of LiDAR, "Light detection and ranging/Light imaging, detection and ranging. It's a method for measuring the distance, speed, and surface structure of objects by the means of laser scanning, usually with beams in the infrared spectrum (there are different wavelengths of light in use, however). Essentially, LiDAR is based on the same principle as the echolocation of bats, the only difference being the use of light instead of sound. Every LiDAR system consists of three integral components: a transmitter, a receiver, and a timer. The transmitter will send out a laser beam, which will be reflected by the object it hits; afterwards, the reflection will be registered by the receiver. Because the speed of light is a known constant, the distance of the object can be deduced by the timer, which will determine the delay between the light impulse being send out and the reflection being captured, also known as "time of flight".

However, because each laser beam only represents the coordinates of a single point, multiple laser beams are necessary to create a detailed 3D map of the environment. Some LiDAR lasers, like those used in automated vehicles, pinwheel to collect data in a 360° radius, generating a 3D image of all objects in the vicinity, including cars, pedestrians, and other obstacles. This results in multiple "points" forming a "point cloud" together, digitally depicting the surroundings on a 3D level. Because each laser emits hundreds of impulses per second, this technology enables you to take highly precise measurements in a very short period of time. LiDAR technology is not only utilized in autonomous driving, but also all kinds of other areas too, like archaeology, topographical mapping, and monitoring of vegetation growth.

Now, with this in mind, my theory is that Legion's small headlamps are the transmitter and receiver components of the LiDAR system - more specifically, I think the transmitters are located on the right, while the singular light on the left is the receiver. However, since we know that normal scanning LiDAR requires multiple laser beams for a detailed 3D image, the question is why Legion would only have two of them implemented. Personally, my suspicion is that the Geth might be using a flash LiDAR: Flash LiDAR is a different type of LiDar emitting a single wide, diverging beam, similar in shape to the beam of a flashlight. By projecting the reflected light onto a sensor array, a flash LiDAR can create a complete 3D environment without the use of multiple impulses. In addition to being very compact, flash LiDAR sensors have no moveable parts, making them extremely resistant to any kind of vibration - an undeniable advantage in all situations that require quick movement, such as combat.

Analysis of atmospheric composition with LiDAR

Still, that doesn't explain why Legion would have an additional transmitter on the right side of their head. We do know, however, that the laser scans with LiDAR are precise enough to not only measure the exact distance between objects, but also analyze the density of particles in the air: Because the molecules in the air cause the light from the laser beam to backscatter, LiDAR is also utilized in monitoring air quality and detecting fine dust, being able to determine traces of atmospheric gases such as ozone, nitrous gases, carbon dioxide, and methane. Depending on the wavelength of light used, the LiDAR system might be more or less precise in measuring molecular backscattering. For that reason, LiDAR systems using multiple wavelengths of light are most efficient in determining the exact size distribution of particles in the air.

With this in mind, let's take a look at Legion's opening line in ME2 upon entering the Heretic station:

Alert. This facility has little air or gravity. Geth require neither.

Going by what I explained above, the reason why Legion was able to tell there is no oxygen in the atmosphere isn't because they have some built-in chemical sensors to analyze the air's components - it's because they can literally "see" the particles in the air.

Thus, I think the second transmitter on the right side of Legion's head might use a different kind of wavelength specifically intended for the detection of atmospheric particles, perhaps in the UV-spectrum (the general rule is that the shorter the wavelength, the higher the resolution of the 3D image is, and since UV has a shorter wavelength than infrared, I imagine it might be used for this purpose). Meanwhile, the big flashlight in the middle might be a photoreceptor, being able to detect "normal" light visible to humans. In addition, the Geth are probably able to see��UV-light (since the Quarians are able to see it, it would be logical to assume the Geth are as well), and maybe even infrared and other wavelengths. To summarize the function of all of Legion's headlights, I imagine it works roughly like this:

The two lights on the right side of Legion's head (marked with a red and magenta line) might be LiDAR transmitters, using infrared and UV-light, respectively; the single small light on the left (circled with green) might be the LiDAR sensor/receiver, while the big light in the middle (circled with blue) might be a photoreceptor (Source)

The effect of Xen's countermeasure (and potential means to bypass it)

It might be difficult to imagine from a human point of view, but judging from the information that the Geth use LiDAR as their main method of depth perception, Tali describing Xen's invention as a "flash bang grenade" actually makes a lot of sense: If you're normally able to observe your surroundings down to a molecular level, it would probably feel very disorienting if you're suddenly not, not mention being unable to tell whether an object is far away or close by (which would be absolutely devastating if you suddenly come under attack).

Still, that doesn't mean there are no potential alternatives: Radar, which has been in use longer than LiDAR, is another method to determine the range, angle, and velocity of objects. Due to radar using long-waved micro- and radio waves, the measurements are generally a lot less precise than those with LiDAR; despite this, radar still has its use during inclement weather, when LiDAR systems are very prone to disturbances by dust, mist, and rainfall. Furthermore, LiDAR can only provide measurements up to 200 meters, while radar is more efficient at greater distances. In fact, most modern autonomous driving vehicles work both with LiDAR and radar, in addition to a conventional camera (the only vehicles that don't use LiDAR are those from Tesla, which have a reputation of being unsafe). So, it's only reasonable to assume that the Geth don't rely on LiDAR alone, but use various technologies in combination with it to compensate for each one's weaknesses.

Interestingly, a type of 4D radar is currently in development, intended to be used in autonomous driving. It provides 3D images with a similar resolution as LiDAR, at a potentially much cheaper cost. Still, whether LiDAR or 4D radar is the better choice for autonomous driving is still a heatedly debated question, and only time will tell which of both systems comes out on top. Nevertheless, assuming Xen's "flash bang grenade" only targets the Geth's LiDAR sensors, I wonder if they could've potentially found a way to adapt and bypass it, given enough time.

Anyway, that's the material for a different kind of analysis - for now, I hope you enjoyed this little deep dive into the science behind the Geth. Thank you all for reading and have a nice N7 Day! :-)

[wanderersrest]

Diabolos Est Machina Part 1: Defining Artificial Intelligence

Special thanks to my sister, who helped inspire me to do this series.

Welcome to the first part of Diabolos Est Machina, the series covering AI ethics in relation to the Devil Gundam! Today, we'll be covering the basics of artificial intelligence! Yes, that's right! This is actually a school lesson!

Something to also keep in mind is that artificial intelligence is a broad field, so we will have to do a lot of defining today. We're going to take a look at what artificial intelligence is, the different concepts that make up the field of artificial intelligence, and why we would create an artificial intelligence in the first place.

What Is Artificial Intelligence?

Artificial Intelligence (AI for short) is a field of study in computer science that focuses on allowing a computer to perceive the world around it as if it were a human. As we are all aware, computers are not sentient beings. The idea behind AI is to make it so that a computer can perform certain tasks where complex decision-making is concerned. At its most basic, an AI is practically a large nest of conditional statements (If X Then Y Else Z). In fact, calling it an AI is even a bit of a misnomer; a more apt name would be Complex Information Processing, but that doesn't roll off the tongue the way Artificial Intelligence does.

When created, the AI is like that of a baby. And like all babies do, the AI needs to learn. And the way most AI today can achieve this is through Machine Learning, since using just conditional statements would be exhausting and prevent the AI from being able to change its outputs dynamically. Machine Learning is a pretty broad and complicated subject itself, but the gist of it is that Machine Learning is the means by which an AI can learn how to do a given task. If you've ever heard of things like Neural Networks (NN) or Large Language Models (LLM), they are both applications of Machine Learning.

The AI has to be trained with a given data set in order for it to be able to accomplish a given task. To understand this a little bit better, lets take a quick look at a field I am actually pretty knowledgeable on: Computer Vision. Computer Vision, as its name suggests, is the field of AI where the general goal is to make a computer able to perceive visual data using cameras. So for something like facial recognition, we would need to train the system on a data set of some kind. So we train the AI on a data set consisting of two things: faces and not faces. The goal during the training phase is to reinforce the AI (in this case our facial recognition software) on what is or is not a face. We repeat this training process until the AI is able to differentiate faces from non-faces.

So, Why Make An AI? What's Its Purpose?

Like any form of automation, the purpose of AI is to perform tasks at a more efficient rate than what humans are capable of achieving. In a more positive light, AI is useful in its ability to remove the human element from dangerous, and in some cases outright impossible, tasks. On the other hand (and I'm willing to bet this is probably what you know AI for dear reader), AI is also used by major corporations to force people out of their jobs for the sake of the bottom line.

Another purpose for the existence of AI is in research, specifically when it comes to understanding how human consciousness works. The idea, like most constructed models in general, is to create a sort of simulacrum of how human intelligence works. There are, of course, a couple of issues with this.

The first is that we don't really know how human intelligence works, so how would we even be able to create something that models human intelligence if we barely understand human intelligence in the first place?

The second problem is that, as they currently stand, AI systems are not very smart.

Okay, IBM Watson is kind of smart, but that was almost ten years ago. Yes, I can feel myself aging rapidly...

But even Watson has the same problem as most AI systems, which is they are reliant on the data they are trained on. And because the data they are trained on is almost always a very specific type of data, it means that most AI systems are only good at doing one specific task and pretty much nothing else.

"But Kaien," you might ask, "What about Artificial General Intelligence? If we just made a system that could handle different tasks instead of just one then-"

NO. It's already enough of a pain in the ass to make an AI system that can handle one specific task really well. The idea that we are close to any kind of general AI that can do a multitude of tasks (let alone do them well) is, to be frank, something a snake oil salesman would tell you. Even when they handle tasks that they are supposed to be good at doing, AI systems can and do fail.

A prime example of a specific AI system failing is Amazon's Rekognition being used by the ACLU to highlight how a facial recognition system can incorrectly flag non-criminals as criminals due to systemic racial biases. It's surprising if this is your first time hearing about facial recognition in a major capacity; not so much if you know that computer vision software can and will occasionally label cats as dogs.

To put it bluntly before moving on: as they currently stand, AI systems in general are nowhere near ready to be used as a replacement for humans in pretty much every scenario where corporate ghouls try to sell them for.

Conclusion

As we wrap up this section of Diabolos Est Machina, you might be asking yourself "But why the Devil Gundam? Couldn't you cover something more iconic like HAL-9000 or Skynet?"

And to be frank, enough ink has been spilled over HAL-9000 (heck, there's an interesting paper you can read that focuses on AI ethics through the lens of HAL ), and Skynet isn't particularly interesting in my opinion due to it being more of a generic "AI overlord who is evil and wants to wipe out humanity." At least AM was an actual character...

And now to sound like a complete hypocrite, the Devil Gundam is interesting. Hear me out: a lot of this stems from the fact that a lot of the plot of G Gundam revolves around various superpowers (including THE UNDEFEATED OF THE EAST, MASTER ASIA) trying to get their hands on what is basically an AI-operated super weapon. Which is interesting, because the Devil Gundam's primary purpose was not to be used as a weapon. And next time, we will turn our focus onto the history of AI in fiction! Complete with HAL, AM, Atom, and even Skynet (without the flippant remarks this time, I swear). And most important to us: the JDG-00X Devil Gundam!

Also Hashmal might get a reference, as will the AV-0.

[sadik165]

Tips For Choosing The Right Cigarette Equipment Supplier

When it comes to cigarette manufacturing, choosing the right supplier for your equipment is crucial. The efficiency, reliability, and quality of your production, including processes involving cigarette wrapping machines, depend significantly on this decision. With numerous suppliers in the market, finding one that aligns with your needs can be overwhelming. This guide highlights key considerations to help you make an informed choice, ensuring that the supplier you select enhances your production capabilities and supports your business growth effectively.

1. Assess Your Business Needs

Before reaching out to suppliers, start by identifying your specific requirements. Do you need high-capacity machinery for large-scale production or smaller, versatile equipment for custom products? Consider the type of cigarettes you’ll produce, the speed you require, and any unique features like eco-friendly operations. Knowing your needs will narrow down your options and ensure you’re not paying for unnecessary capabilities.

2. Research Supplier Reputation

A supplier’s reputation reflects their reliability and product quality, especially for cigarette machinery spare parts. Seek reviews, testimonials, and case studies from similar businesses. Ensure they have experience in your industry. A well-established supplier with a proven track record is a safer and more dependable choice for long-term success.

3. Evaluate The Technology Offered

The cigarette manufacturing industry is evolving, with automation and digital technologies playing an increasingly significant role. Ensure the supplier offers modern, efficient, and technologically advanced equipment. Features like automated quality control, easy integration with existing systems, and user-friendly interfaces can boost productivity and reduce operational challenges.

4. Focus On After-Sales Support

Even the best machinery, like an automatic cigarette rolling machine, can face issues, making after-sales support essential. Opt for a supplier offering excellent customer service, quick response times, spare parts availability, and maintenance support. Also, inquire about warranties and staff training to ensure smooth operation and long-term equipment efficiency.

5. Consider Cost And Value

Although cost is a key factor, it should not be the sole consideration in your decision-making process. Analyze the long-term value of the equipment, including its durability, efficiency, and energy consumption. Sometimes, investing in slightly more expensive machinery can save you money in the long run through reduced downtime and maintenance costs.

6. Compliance With Industry Standards

Make sure the equipment adheres to industry regulations and meets all required safety standards. reliable supplier will have certifications to back up the quality and safety of their products. This ensures smoother operations and avoids potential legal or regulatory issues.

7. Seek Customization Options

Your business might have unique needs that off-the-shelf equipment cannot fulfill. Opt for a supplier who offers customization options, allowing you to tailor the machinery to your specifications.

Conclusion

Choosing the best supplier for cigarette manufacturing equipment involves assessing your needs, technology, and after-sales support. Today, companies like Budhan offer diverse equipment, including automatic cigarette-making machines and automatic box-packing machines, catering to modern manufacturing trends. Such suppliers provide comprehensive solutions that ensure efficient production and seamless packaging, making them valuable partners for business growth. Carefully evaluating such offerings helps establish a successful, long-term partnership with the right supplier.

[spacetimewithstuartgary]

New observations links comet water to Earth's oceans

Researchers have found that water on Comet 67P/Churyumov–Gerasimenko has a similar molecular signature to the water in Earth's oceans. Contradicting some recent results, this finding reopens the case that Jupiter-family comets like 67P could have helped deliver water to Earth.

Water was essential for life to form and flourish on Earth and it remains central for Earth life today. While some water likely existed in the gas and dust from which our planet materialized around 4.6 billion years ago, much of the water would have vaporized because Earth formed close to the sun's intense heat. How Earth ultimately became rich in liquid water has remained a source of debate for scientists.

Research has shown that some of Earth's water originated through vapor vented from volcanoes; that vapor condensed and rained down on the oceans. But scientists have found evidence that a substantial portion of our oceans came from the ice and minerals on asteroids, and possibly comets, that crashed into Earth. A wave of comet and asteroid collisions with the solar system's inner planets 4 billion years ago would have made this possible.

While the case connecting asteroid water to Earth's is strong, the role of comets has puzzled scientists. Several measurements of Jupiter-family comets—which contain primitive material from the early solar system and are thought to have formed beyond the orbit of Saturn—showed a strong link between their water and Earth's. This link was based on a key molecular signature scientists use to trace the origin of water across the solar system.

This signature is the ratio of deuterium (D) to regular hydrogen (H) in the water of any object, and it gives scientists clues about where that object formed. Deuterium is a rare, heavier type—or isotope—of hydrogen. When compared to Earth's water, this hydrogen ratio in comets and asteroids can reveal whether there's a connection.

Because water with deuterium is more likely to form in cold environments, there's a higher concentration of the isotope on objects that formed far from the sun, such as comets, than in objects that formed closer to the sun, like asteroids.

Measurements within the last couple of decades of deuterium in the water vapor of several other Jupiter-family comets showed similar levels to Earth's water.

"It was really starting to look like these comets played a major role in delivering water to Earth," said Kathleen Mandt, planetary scientist at NASA's Goddard Space Flight Center in Greenbelt, Maryland. Mandt led the research, published in Science Advances on Nov. 13, that revises the abundance of deuterium in 67P.

But in 2014, ESA's (European Space Agency) Rosetta mission to 67P challenged the idea that Jupiter-family comets helped fill Earth's water reservoir. Scientists who analyzed Rosetta's water measurements found the highest concentration of deuterium of any comet, and about three times more deuterium than there is in Earth's oceans, which have about 1 deuterium atom for every 6,420 hydrogen atoms.

"It was a big surprise and it made us rethink everything," Mandt said.

Mandt's team decided to use an advanced statistical-computation technique to automate the laborious process of isolating deuterium-rich water in more than 16,000 Rosetta measurements. Rosetta made these measurements in the "coma" of gas and dust surrounding 67P. Mandt's team, which included Rosetta scientists, was the first to analyze all of the European mission's water measurements spanning the entire mission.

The researchers wanted to understand what physical processes caused the variability in the hydrogen isotope ratios measured at comets. Lab studies and comet observations showed that cometary dust could affect the readings of the hydrogen ratio that scientists detect in comet vapor, which could change our understanding of where comet water comes from and how it compares to Earth's water.

"So I was just curious if we could find evidence for that happening at 67P," Mandt said. "And this is just one of those very rare cases where you propose a hypothesis and actually find it happening."

Indeed, Mandt's team found a clear connection between deuterium measurements in the coma of 67P and the amount of dust around the Rosetta spacecraft, showing that the measurements taken near the spacecraft in some parts of the coma may not be representative of the composition of a comet's body.

As a comet moves in its orbit closer to the sun, its surface warms up, causing gas to release from the surface, including dust with bits of water ice on it. Water with deuterium sticks to dust grains more readily than regular water does, research suggests. When the ice on these dust grains is released into the coma, this effect could make the comet appear to have more deuterium than it has.

Mandt and her team reported that by the time dust gets to the outer part of the coma, at least 75 miles from the comet body, it is dried out. With the deuterium-rich water gone, a spacecraft can accurately measure the amount of deuterium coming from the comet body.

This finding, the paper authors say, has big implications not only for understanding comets' role in delivering Earth's water, but also for understanding comet observations that provide insight into the formation of the early solar system.

"This means there is a great opportunity to revisit our past observations and prepare for future ones so we can better account for the dust effects," Mandt said.

IMAGE: This image, taken by ESA’s Rosetta navigation camera, was taken from a about 53 miles from the center of Comet 67P/Churyumov-Gerasimenko on March 14, 2015. The image resolution is 24 feet per pixel and is cropped and processed to bring out the details of the comet's activity. Credit: ESA/Rosetta/NAVCAM

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Mastering B2B Sales: Your Essential Guide to 20 Proven Strategies and Tactics for 2025

The B2B sales landscape is transforming rapidly, driven by advancements in technology, changing buyer behavior, and heightened competition. As businesses gear up for 2025, the focus must shift to a more strategic, data-driven, and customer-centric approach to achieve sustainable growth. Below, we delve into 20 essential strategies and tactics that every B2B company should adopt to refine their sales processes and thrive in the ever-evolving market.

1. Personalized Customer Engagement

In today’s competitive environment, personalization is no longer optional—it’s essential. Tailor your messaging to address specific customer pain points and needs. Use CRM platforms to track interactions, preferences, and behavioral data, ensuring every touchpoint feels meaningful and relevant.

2. Adopt AI and Automation

Artificial intelligence and automation tools are transforming how B2B sales teams operate. From chatbots handling initial inquiries to AI-driven analytics predicting customer needs, these technologies streamline workflows, improve efficiency, and help prioritize leads for better conversion rates.

3. Focus on B2B Lead Generation in India

With India’s growing economy and increasing demand for B2B services, it’s a hotspot for lead generation. Companies like The Global Associates specialize in capturing high-quality leads in this region, enabling businesses to tap into one of the world’s fastest-growing markets. Invest in localized marketing campaigns, and utilize platforms like LinkedIn and Google Ads to target decision-makers effectively.

4. Implement Account-Based Marketing (ABM)

ABM is a powerful strategy where marketing and sales teams work collaboratively to target high-value accounts. Instead of casting a wide net, focus your resources on a select group of prospects, delivering customized campaigns that directly address their specific needs.

5. Enhance Your Digital Presence

Your online presence is often the first impression potential clients have of your business. Ensure your website is optimized for SEO, mobile-friendly, and offers a seamless user experience. Regularly update blogs, whitepapers, and case studies that demonstrate your expertise and add value to your audience.

6. Develop Multi-Channel Outreach

Gone are the days when email alone could drive sales. Today’s B2B buyers expect communication across multiple channels, including email, phone, social media, and even in-person meetings. A well-coordinated outreach strategy ensures you’re reaching prospects wherever they are most active.

7. Invest in Value-Driven Content

Content is the backbone of B2B marketing. Create in-depth whitepapers, blogs, videos, and case studies that address the challenges your prospects face. Use content as a tool to educate and build trust, positioning your business as a thought leader in your industry.

8. Strengthen Sales Enablement

Empower your sales team with the tools, resources, and training they need to succeed. This includes access to up-to-date product information, buyer personas, and data-driven insights that can help them tailor their pitch to individual prospects.

9. Leverage Data Analytics

Incorporate data-driven insights into every stage of your sales funnel. Use analytics tools to track customer behavior, identify trends, and refine your strategies. This approach ensures you’re always making informed decisions that drive results.

10. Collaborate with Strategic Partners

Partnering with complementary businesses can open doors to new opportunities. For instance, a software provider could partner with a consulting firm to offer bundled services, creating value for both companies and their customers.

11. Focus on Customer Retention

It’s often said that retaining a customer is more cost-effective than acquiring a new one. Implement loyalty programs, provide excellent post-sale support, and continuously engage with your existing customers to ensure they remain loyal advocates for your brand.

12. Harness the Power of Video Marketing

Video content is increasingly becoming a preferred medium for B2B buyers. Use explainer videos, product demos, and client testimonials to engage prospects and communicate your value proposition effectively.

13. Encourage Referrals

Happy customers can become your best brand ambassadors. Develop a referral program that incentivizes your existing clients to recommend your services to their network.

14. Monitor Competitors

Keeping a close eye on your competitors can provide valuable insights. Identify what’s working for them and where they might be falling short. Use this information to refine your strategies and gain a competitive edge.

15. Expand Internationally

If your business hasn’t explored international markets yet, 2025 might be the year to do so. Develop localized strategies to address the specific needs and cultural preferences of global audiences.

16. Use Social Proof to Build Credibility

Social proof, such as client testimonials, success stories, and case studies, plays a crucial role in establishing trust. Showcase these prominently on your website and marketing materials to demonstrate your capabilities.

17. Align Sales and Marketing Teams

Silos between sales and marketing teams can hinder your growth. Align their goals and encourage collaboration to create a seamless journey from lead generation to conversion.

18. Host Webinars and Events

Webinars and events are excellent ways to educate your audience, showcase your expertise, and generate new leads. Offer valuable insights during these sessions to leave a lasting impression on your prospects.

19. Optimize Pricing Strategies

Your pricing strategy should cater to different customer segments. Offer tiered packages, volume discounts, or subscription models to accommodate varying budgets and requirements.

20. Partner with Industry Experts

Collaborate with B2B sales and lead generation experts like The Global Associates. With a proven track record of delivering high-quality leads and helping businesses achieve their sales goals, partnering with such firms ensures your strategy is backed by experience and expertise.

Final Thoughts

The future of B2B sales lies in leveraging technology, focusing on customer-centric strategies, and optimizing lead generation efforts in emerging markets like India. By adopting these 20 essential tactics, businesses can stay ahead of the curve, driving both growth and profitability in 2025.

Would you like a tailored approach to integrate these strategies into your business? Collaborate with The Global Associates to unlock the full potential of your B2B sales strategy.

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Innovate with Confidence: RPA Solutions Tailored for Retail Success

Implementing RPA in inventory management benefits retailers with accurate inventory level tracing, demand and supply forecasting, as well as by streamlining communication, between all suppliers.

RPA software technology can benefit any retail organization with proper discovery, mapping, and deployment. The bots can be used for more than just tracking inventories, sending out notifications, and transferring data across systems.

Embrace innovation with RPA solutions designed for retail. Optimize inventory management, enhance efficiency, and stay ahead in the competitive landscape.

[rthidden]

Boost Your Agency’s Success with These Simple Strategies

Every small professional service agency owner wants to thrive, but chaos can lurk around every corner. Here’s how to navigate smoothly!

1. Claim Your Niche

Identify what sets you apart from others in the market. Are you the wizard of _______? Your unique niche can be your greatest asset.

Once pinpointed, focus your marketing efforts on that niche. A well-crafted message can attract the right clients faster than a clickbait cat video!

2. Build Strong Relationships

Networking isn’t just a buzzword; it’s a business lifeline. Attend events and don’t forget to follow up! People love to feel remembered.

Consider creating a referral program. Everyone likes a good deal—incentivizing referrals can turn your current clients into our best salespeople.

3. Streamline Your Processes

Evaluate your internal workflows. Are you drowning in paperwork? Use tools like project management software to simplify and automate where possible.

Regularly review your processes to identify bottlenecks. A leaner operation saves time, money, and a few gray hairs along the way!

4. Embrace Continuous Learning

The professional landscape is constantly changing. Invest in online courses or workshops relevant to your field. Knowledge is power—especially when it can help you serve clients better.

Encourage your team to share what they learn. A culture of learning fosters innovation and boosts morale!

5. Leverage Social Proof

Showcase client testimonials and case studies on your website. Prospective clients trust the opinions of others like their favorite barista!

Maintain an active presence on social media platforms where your audience hangs out. Share success stories, behind-the-scenes content, and engage with followers to build a community.

Conclusion and call to action.

Embrace these strategies to steer your professional service agency toward greater success. Start small, pick one point to implement this week, and watch the impact unfold. I’d love to hear your stories or any additional tips you might have—let’s keep the conversation going!