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The computers we see today were not always the same. By computers, I mean anything able or helpful in computing. Early computers were mechanical calculators, punching machines, etc. Then came ENIAC etc., which was digitally computed but was too big. The usage of personal computers started as a hobby among a certain set of people and went on to become something that people cannot live without.

History of Computers

As I am writing on the progress of computers, I see computers of the future being more mobile and more powered as compared to desktops and laptops, including the one I am using to compile the history of computing as a presentation. Check out the progress in the computer field as a PPT below. The link to the progress of the computers PDF file is given towards the end of the post.

Presentation Transcript: Important Points

Anything that helps in computing anything is a computer. Early computers were basically calculators with or without storage capability. This presentation is about the progress of computers.

1] Early computers were mechanical

2] The Night-Time Machine was developed by Leonardo Da Vinci for guessing time at night when it was dark. In the daytime, they used to measure time using shadow. Clocks are also computers that compute time using tension or crystal ticks.

3] 1935: Odhner Circa was developed. This was among the first computers used by mathematicians.

4] 1820: Arithometer was developed for clerks for addition tasks

5] 1889: Felt’s Comptometer or Comptograph was among the first calculators/computers that could do mathematical operations while also being able to print. It could not store data, however.

6] 1904: Burroughs company invented and sold Burroughs calculator that could perform arithmetic operations. It was popular among clerks due to its size.

7] 1910: Burroughs created an additional machine and called it Adding Machine. This model could store data in the machine itself.

8] Around 1890, while others focused on calculating machines, Hermann Hollerith was busy creating punch cards for use with his Tabulating Machine and sorting box. The concept of the machine was to perform functions using blocking and passage of the electrical system. Electric needles ran on the punched cards. When they encountered gaps (hole), the circuit was complete and created a binary one. This was among the first machines to calculate massive amounts of data in split seconds and probably was lead for binary operations in the computers.

9] A book on Hermann’s Tabulating Machine is available under the name of Origins of Digital Computing.

10] The first real computer was ENIAC: It could perform arithmetic operations and also be able to perform some general purposes. However, it was too big and was not for the general public. It was developed around 1945

11] In 1948, the IBM SSEC was released. This was also a digital computer using vacuum tubes. However, input was still using punch cards, somewhat using the Hermann’s Tabulating Machine technology.

12] In 1959, IBM 1970 was developed. This machine was able to store data within the computer. It also marked the transition of computers from vacuum tubes to transistors.

13] The real revolution in computers was the MITS Altair 8800, designed in 1974. Apart from hobbyists, this was purchased by organizations to speed up their accounting.

14] The IBM 8086 brings us up to date with modern computers. It is an obsolete model with CPU and a large monitor but worked on transistors and complex ALU. Those types of models were called desktops as one would keep them on desks and use a keyboard and mouse to operate them. Input in such computers was binary signals sent by the keyboard (ASCII Characters) and mouse (screen coordinates). If you have programmed in MS BASIC, you can easily understand how these input devices worked.

15] The desktops were further shrunk as technology progressed further. Desktops are being replaced by laptops in many organizations. Individuals too prefer laptops as they are smaller and can be carried anywhere. The Microsoft Windows operating system became very popular.

The future of computing is convertible computers and tablets. The only need of the hour is to provide powerful computing resources in a much small tablet and to keep it running, a battery that can last long.

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Physiological Evidence Of Evolution Of Short

Mate selection is a complex process influenced by biology, culture, and environment. Individuals seek long-term or short-term partners, depending on hormones, life stage, and self-perception. Women generally prefer long-term relationships but are always involved in short-term ones. Although most men end up in long-term relationships, most men prefer short-term mating.

A strategy becomes more attractive depending on the number of available partners responding to it and the lack of many domestic competitors using it. Recent speed dating studies show fewer differences between men and women than previous studies using other methods (e.g., self-report). However, whether this finding can be replicated in populations with more diverse levels of attractiveness and SES remains to be seen.

Short-Term Mating

Studies suggest that some people lean more towards short-term relationships (e.g., short-term flirting, one-night stands), others aspire to long-term relationships (e.g., marriage, cohabitation), and some more significant are still available for relationships of both types.

Although both sexes are engaged in non-binding sex, men are more likely to desire short-term relationships than women, possibly because of historical asymmetries in the costs and benefits of short-term mating. Since women bear most of the burden during pregnancy, childbirth, and postpartum, short-term sexual intercourse has resulted in higher costs (low parental investment, infectious diseases, violence, etc.) against ancestral women than men.

Biological Evidence of Short-Term Mating

Men and women are more similar in what they want in a short-term partner but differ in what they want in a long-term partner. Asexual animals pass all of their chromosomes, and therefore, all copies of every gene, to their offspring. In contrast, by meiosis, sexually reproducing diploid animals have two copies of each chromosome but pass on only one copy of each chromosome to eggs or sperm.

For example, aphids will promote asexual reproduction when their environment is stable. When the environment gets cold, most aphids reproduce sexually because sexual reproduction produces eggs resistant to freezing and can be halted during the winter. Genetic diversity may also lead to evolutionary defenses against parasites and disease. The mud snail, Potamopyrgus antipodarum hosts several fluke parasites.

Sexual individuals of this species are more common in areas with a high risk of tapeworm infection. In areas of low risk of infection, asexual individuals have replaced sexual individuals. This suggests that the genetic diversity gained from sexual reproduction is necessary for this species to resist parasites, as clonal individuals may not readily survive in areas where parasites are abundant.

Sexual reproduction usually involves the evolutionary distinction of males and females. Females typically produce far fewer gametes (eggs) than males and invest more in each. Males, on the other hand, produce many gametes (sperm) and invest little in each. Substantial differences in gamete investment between the sexes lead to, in some cases, opposing reproductive strategies between the sexes. Females may be more interested in mate selection than males due to their high gametophyte cost.

Physiological Evidence for Short-Term Mating

Recent research has shown that individual differences in psychological traits can also lead to differences in mate preferences. In line with this research, only facial stimuli have been used as a proxy for attractiveness. Few studies have examined the association between psychological traits and attractiveness indices—other physical indicators such as WHR and BMI. In addition to the impact of gender-typical psychographic characteristics on the attractiveness assessment, partner preferences in short- and long-term relationships largely depend on gender.

Historically, evolutionary psychologists were among the first to consider short-term mating of offspring as an adaptive reproductive strategy (most other psychologists have considered itResearch has suggested that females pursuing short-term mating prioritize physical attractiveness to facilitate the mating acquisition of good genes. Although it is known that physical characteristics are important in mate selection, the study examining the importance of physical characteristics in assessing male fitness has yet to be easily discovered. Strategic pluralism suggests that women engage in short-term sexual relationships when the benefits of doing so outweigh the costs.

Testicle Size as an Evidence

Males have far larger testes compared to their body weight than gorillas and orangutans. Male testes account for 0.018 percent of gorilla body weight and 0.048 percent of orangutan body weight. In comparison, human male testes account for 0.079 percent of men’s body weight, which is 60% higher than orangutans and more than four times that of gorillas when body size is considered. Men’s huge testes give evidence that women in human evolutionary history occasionally had sex with more than one guy within a few days. Without sperm competition, this size of testes would not have evolved.

Moreover, it implies that both sexes pursued short-term mating at times. However, humans do not have the enormous testes of any primate. The volume of human testes is far less than that of the very promiscuous chimp, whose testes account for—more than 269 percent of its body weight. The volume of human testes is far less than that of the very promiscuous chimp, whose testes account for—more than 269 percent of its body weight.

Variations in Sperm Insemination

Variations in sperm production and insemination further indicate the evolutionary occurrence of casual mating. Thirty-five couples agreed to provide ejaculates resulting from sexual intercourse, from either condoms or flow back, the gelatinous mass of seminal fluid spontaneously discharged by a woman at various points after intercourse, in a study to determine the effect on sperm production of separating mates from each other.

Each couple’s partners had been separated for varied amounts of time. Men’s sperm counts increased considerably as the couple’s time apart increased since their previous sexual contact. The longer men spent apart, the more sperm they inseminated in their spouses when they eventually had intercourse.

Men inseminated 389 million sperm each ejaculate on average when the couples spent 100% of their time together. However, when couples spent just 5% of their time together, males inseminated 712 million sperm each ejaculate, nearly doubling the number. The amount of sperm inseminated rises when other men’s sperm is present simultaneously in the wife’s reproductive tract due to the chance for extramarital sex afforded by the couple’s separation and the period since the man’s previous ejaculation did not affect the rise of sperm insemination.

Even if the male masturbated to climax while apart from his wife, he still inseminated more sperm when reunited if he had been separated from her for an extended period. The husband’s increased sperm insemination after lengthy separation assures that his sperm has a better shot in the race to the egg by crowding out or displacing a potential interloper’s sperm. The fact that males have a physiological mechanism that increases sperm count when their wives may have had opportunities to be unfaithful suggests that humans had extramarital affairs at some point in their evolutionary past.


Mate selection can be measured empirically, but the mechanisms underlying mate selection are not always well understood. Advances in molecular genetic technology have allowed mate selection research to focus on behavioral observations to understand mating preferences at the molecular level. Mate selection based on genetic factors may evolve to avoid inbreeding and maximize the offspring’s genetic quality.

Hp Laptop Computers And 2

All performance specifications represent the typical specifications provided by HP’s component manufacturers; actual performance may vary either higher or lower.

Multi-core is designed to improve performance of certain software products. Not all customers or software applications will necessarily benefit from use of this technology. Performance and clock frequency will vary depending on application workload and your hardware and software configurations. Intel’s numbering is not a measurement of higher performance.

5G module is optional and must be configured at the factory. Module supports non-millimeter wave 5G frequencies (below 6 GHz). The full utilization of this module’s functionality is dependent on network providers’ technical ability to support module and speed.  Backwards compatible to 4G networks. Module requires activation and separately purchased service contract. Check with service provider for coverage and availability in your area. Connection, upload and download speeds will vary due to network, location, environment, network conditions, and other factors. 5G & 4G LTE networks not available in all regions.

4G LTE module requires separately purchased service contract. Check with service provider for coverage and availability in your area. Connection speeds will vary due to location, environment, network conditions, and other factors. 4G LTE not available on all products, in all regions.

Google Play Store apps sold separately and not included.

HD (High Definition) content required to view HD images.

NVIDIA® Max-Q Design can help reduce system heat and noise in thinner form factor PC’s.  Form factor design and thickness of the system will vary. Overall graphics performance may be lower than alternative graphics solutions that do not utilize Max-Q design.

Windows 10 and Windows 11/MM18: Battery life will vary depending on various factors including product model, configuration, loaded applications, features, use, wireless functionality, and power management settings.  The maximum capacity of the battery will naturally decrease with time and usage. See chúng tôi for additional details.

HP Sure View integrated privacy screen that functions in landscape orientation. Available on select HP models and requires factory configuration. Brightness will vary between sharing and privacy modes.

Battery life tested by HP using continuous Netflix video playback, Windows 10 Netflix app, 150 nits brightness, system audio level 17%, headphone attached, played full-screen, wireless on. Actual battery life will vary depending on configuration and maximum capacity will naturally decrease with time and usage.

Full high-definition (FHD) content is required to view FHD images.

Multi-core is designed to improve performance of certain software products. Not allcustomers or software applications will necessarily benefit from use of this technology. Performance and clock frequency will vary depending on application workload and your hardware and software configurations. AMD’s numbering is not a measurement of clock speed.

Percentage of ocean-bound plastic contained in each component varies by product.

Weight will vary by configuration.

Ultrabook, Celeron, Celeron Inside, Core Inside, Intel, Intel Logo, Intel Atom, Intel Atom Inside, Intel Core, Intel Inside, Intel Inside Logo, Intel vPro, Itanium, Itanium Inside, Pentium, Pentium Inside, vPro Inside, Xeon, Xeon Phi, Xeon Inside, and Intel Optane are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries.

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The information contained herein is subject to change without notice. The only warranties for HP products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. HP shall not be liable for technical or editorial errors or omissions contained herein.

The Evolution Of Solid State Drives (Ssds)

When solid state storage were invented over half a century ago and then made widely commercially available, their effect was transformative — the technology has played a major role in the evolution of storage, gaming, business and computing. But by examining SSDs, you can also understand what the future will hold for their components, benefits and applications.

What is SSD storage?

Solid state drive (SSD) storage uses non-volatile solid state chips that feature flash memory cells to store data on a long-term basis. Unlike traditional hard disk drives (HDDs), which use magnetic platters spinning at high speeds to using an actuator arm reminiscent of a record player, SSDs require no moving parts. Instead, the storage solution depends entirely on flash memory to store data, making them much faster at reading and writing data, both ad hoc and in sustained operations.

Using a mesh of electrical cells in a NAND — a type of non-volatile flash memory — to store data, SSDs include an embedded processor known as the controller. It runs firmware-level code to help the drive operate and bridge the media to the host computer via the interface bus. Today’s SSDs don’t require an additional power source that maintains an electrical current into the device at all times to preserve the data. This makes them increasingly more reliable than traditional HDDs (from a mechanical and data integrity standpoint).

SSDs also have built-in technology that further improves read/write speeds, making them faster than traditional HDDs. Historically, HDDs included a bit of memory within the drive hardware itself (typically eight or 16 MBs) to increase the perceived read/write performance. If the data a user wants to read or write can be stored within the high-performing cache memory, the drive temporarily stores the data in the fast memory modules. It then reports back to the operating system once this is complete, triggering the drive to transfer the data from the cache to the much slower magnetic media. This doesn’t always work, as only a small portion of the drive’s total data is cached at any time, and if data isn’t in the cache, it has to be read from the slower physical medium.

SSDs utilize the same kind of concept involving a cache, except they include dynamic random access memory (DRAM) chips — a type of semiconductor memory commonly used in PCs and servers — within the controller hardware on the SSD itself. Ranging from 64 MBs all the way up to GBs, they buffer requests to improve the life of the drive and serve short bursts of read/write requests faster than the regular drive memory allows. These caches are essential in enterprise storage applications, including heavily used file servers and database servers.

When were SSDs first available?

The use of flash memory for longer-term storage has been around since the 1950s, but those solutions were generally in mainframes or larger minicomputers. They also required battery backups to preserve the contents of the memory when the machine was not powered by the host, as those solutions used volatile memory.

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Since then, the technology has gotten smaller and faster, and it no longer requires battery backup. Performance has skyrocketed too, as new PC bus interfaces have made it possible for data transfer rates to far exceed the standard rates that traditional spinning media would saturate. They’re also less expensive today, even compared to the first SSD drive released in 1991 — a 20MB SSD that sold for $1,000.

Applications for SSDs

There are multiple benefits to using SSDs for production storage applications. Because SSDs have no moving mechanical components, they use less power, are more resistant to drops or rough handling, operate almost silently, and read quickly with less latency. Additionally, since there are no spinning platters or actuator arms, there is no need to wait for the physical parts to ramp up to operating speed. This feature eliminates a performance hit that hard drives cannot escape. SSDs are also lightweight, which makes them ideal for laptops, small form factor machines and high-capacity storage area networks in a smaller footprint.

To host both the database engine and the database itself for quick access.

As a “hot” tier in a stratified network storage archive, where frequently accessed data can be retrieved and rewritten very quickly.

In situations where physical shocks are a possibility and HDDs would present an untenable risk to system reliability.

In gaming, where the user is often moving through new environments.

In business settings where you need your operating system and applications to load quickly.

How to choose the right SSD for your needs

PCIe SSDs interface with a system via its PCIe slot — the same slot that is used for high-speed video cards, memory and chips. PCIe 1.0 launched in 2003, with a transfer rate of 2.5 gigatransfer per second (GT/s) and a total bandwidth of 8 Gbps. GT/s measures the number of bits per second that the bus can move or transfer.

Several years later, PCIe 2.0 was introduced, doubling both the bandwidth and the gigatransfer speed, hitting 16 Gbps and 5 GT/s, respectively. Subsequent generations doubled bandwidth and gigatransfer speeds with each new iteration. PCIe 3.0, for instance, features 32Gbps bandwidth and 8 GT/s.

Most recently, SSDs started using the PCIe 4.0 specification, which features bandwidth of 64 Gbps and a 16 GT/s rate. PCIe is now being paired with the non-volatile memory host controller interface specification (NVMe), a communications protocol for high-speed storage systems that runs on top of PCIe.

However, not everyone has a PCIe-enabled system, and some may have PCIe slots in conjunction with other system add-ons, like memory or graphics cards. In these cases, other SSDs like the Samsung 870 EVO are an ideal option for content creators, IT professionals and everyday users. An 870 EVO uses the standard SATA interface to achieve the maximum SATA interface limit of 560/530 MB/s sequential speeds. Samsung 870 QVO also achieves the maximum SATA interface limit, with offerings in the 1, 2, 4, and 8 TB 2.5-inch SATA form factor configurations.

What does the future hold?

In the short term, capacities will continue to ramp up, while the cost per GB for SSDs will continue to decrease. New form factors that increase the number of parallel data transmission lanes between storage and the host bus will emerge to increase the speed and quality of the NAND storage medium.

The physical layer of cells that holds the blocks and pages will improve, offering better reliability and performance. Form factor will also continue to shrink. In 2023, Samsung announced it had reduced cell volume by up to 35%, making its 176-layer 7th-generation V-NAND SSD offering similar in height to its previous generation.

Learn more about how to improve your storage planning and evaluation processes with this free guide.

Grandma’s Insomnia Might Be A Product Of Evolution

If your sleep is getting worse with age, evolution might be to blame.

A study recently published in Proceedings of the Royal Society B found that humans’ age-specific sleep patterns may have evolved to protect mixed-age groups from potential danger in the night. And in this scenario, the elderly members of these groups may have drawn the short straw—their restless sleep made them perfect for the night watch.

“Looking at sleep patterns is really relevant not only to basic science, but also to increasing our understanding of cross-cultural sleep,” says Alyssa Crittenden, a study co-author and assistant professor at the University of Nevada, Las Vegas. “It provides crucial clues of how species evolved.”

“Most human sleep research has been in sleep labs in Western societies,” says first author David Samson, who was a postdoctoral fellow at Duke University at the time of the study and is currently an assistant professor at the University of Toronto, Mississauga. “It’s not a great model, they go from one temperature- and light-controlled room to another.”

The researchers studied Hadza adults ranging from those in their late teens to the elderly. While the subjects slept, they each wore an actigraph, which Samson describes as a “super Fitbit.” Much like its commercial analog, the device is worn on the subject’s wrist and can tell if they are asleep or awake based on activity. But the actigraph also has extra capabilities, like measuring the amount of light in the environment, and it can withstand much harsher conditions.

From the actigraph data, the researchers characterized each subject’s sleep pattern: when they were sleeping or awake, and how long each period lasted. Some people were lighter sleepers who regularly woke up throughout the night, others slept undisturbed all night; there were subjects that went to bed early and woke up early, while other subjects tended to sleep later in the night and into the morning.

The biological roots of these patterns lie in circadian rhythms, the internal clock that dictates our behavior at any given time of day. Are you an early bird? A night owl? Well, those are actual biological characteristics, known as chronotypes (scientists actually use “lark” and “owl” to describe the two extremes). They can even be inherited. Chronotypes encapsulate the unique ways that each of our individual circadian rhythms drive our sleep behavior.

People have thought about the evolutionary role of elders in human society before, in what is known as the “grandmother hypothesis.” It suggests that women live beyond their reproductive years—a trait unique to humans, killer whales, and pilot whales—because they play an important role in their familial group’s survival. They can help care for grandchildren and teach them how to survive, allowing younger females to focus on reproducing. The researchers expanded that idea to coin the “poorly sleeping grandparent hypothesis:” In mixed-age groups, grandmothers—or grandparents in general—may sleep discontinuously so that they can remain alert to potential dangers while their offspring rest.

According to Samson, this finding could provide an important new perspective on how people think about and stigmatize insomnia, a condition that is very common among older people—almost half of adults over the age of 60 report having trouble sleeping.

“It may normalize things we consider to be disorders,” Samson says. “We tend to label things as a disorder if they don’t match up with normal parameters. But insomnia may be an evolutionary mismatch with the modern context.”

It could also impact how insomnia is treated in the elderly. For example, cognitive behavioral therapy has been shown to be effective in treating insomnia: By identifying the cause of the insomnia, people are able to effectively manage it. Explaining the evolutionary origins of insomnia could play a similar role in treatment.

This was the first study of the sentinel hypothesis in humans, but it won’t be the last. Samson and Crittenden hope to study sleep in populations around the world, ranging from rainforests to the Arctic, and compile the results into a global sleep database. If the patterns hold, then they might actually be able to show that the sentinel hypothesis is at play among humans, Crittenden says.

“It could help us ask and answer questions about how humans adapted to different ecological niches around the world,” Samson says.

So, kids, the next time your parents wonder why you don’t wake up earlier, just remind them that you evolved to be this way—getting up early is grandma’s job.

The Role Of Artificial Intelligence In Network Evolution

Artificial Intelligence in network evolution makes things much better than what it was in the past.

Internet connectivity has been growing at around 2% between 2024 – 2023. But over the last 2 years, it has grown by 8% which is a drastic increase in connectivity. Change in professional and personal life demands since the last two years has led to a transition in the user’s expectations. From work from anywhere to e-healthcare and online education, the transition of everything from offline to online has led to growth in connectivity over the period. Adding to the listed gaming and entertainment have scaled up the expectations of the users by many folds. Customer Experience has taken a centre stage for all the Communication Service Providers. To meet these expectations, modern networks are becoming more complex. Experience Disruption has replaced Service Disruption today.  

What to expect?

The new experience paradigm is expected to bring about various changes. Measuring Experience, Troubleshooting these networks with End to End Insights would be a key factor. Machine Reasoning, Machine Learning are going to play a vital role in this Network Evolution. Networks are going to get smarter and adapt to the needs of the consumers. Artificial Intelligence is going to play a key role in the following areas Awareness – Measurement & Prediction of Experience Reasoning – Root cause Analysis in Networks Interactive – Natural Language Interaction Mature – Intelligence that would Evolve over time and correct decisions Autonomous – Self adjust to the needs of the consumes This is the new ARIMA of networks. Awareness – Powered by Artificial Intelligence, networks would be completely aware of the type & nature of Connected Devices and their current bandwidth requirements. By understanding the trends, Networks of WiFi connections for home as well as in offices should be able to measure and personalize the experience of each user that comes on board. For certain IoT devices latency could be critical, but for other devices bandwidth. AI will help the networks to become completely aware of these demands. As home and office networks always have many devices working in tandem, it is important that AI optimizes the networks to obtain a collective optimum smooth user experience. Interactive – Natural Language Engines have got the power to bring about a great evolution. NLP provides Networks a voice to interact with humans in a way like never before. We have been seeing products like Alexa which are bridging the gap of communication between IoT devices and humans using Voice Interface. Network Admin and Home Users can interact with the network in a similar way. Networks would be able to understand human indentions and adapt accordingly. Mature – AI allows the transfer of the intelligence possessed by the Network Experts to Routers, Switches, and other elementals which are part of the network. Working in tandem with each other and with customer Experience as feedback systems in place, Machine Learning models engage in continuous learning and constantly optimize to maximize the experience. Autonomous – Integrating artificial intelligence in networks gives a switch from traditional reactive methods to proactive methods. Automating the method of finding a problem, diagnosing it, and prescribing a solution, help in the reduction of human interventions. With this proactive approach, we can expect maximum uptime of the network as the solution to the problem is identified and accelerated. This eventually will help the IT department to focus on its core objectives.  

How AI in networks can make our lives better

Technology evolves over time; it makes things much better than what it was in the past. With these new changes and enhancements, new vulnerabilities arise as well. Nothing has been more frustrating than not being able to connect to the network or getting slow internet despite having connectivity. Other than this, the safety of our information uploaded could be prone to risk. Sudden loss of network in the mid of an urgent task makes a user feel as if the world took a halt. AI has left no industry untouched. The network industry is no exception to that. Following are a few transformations that have begun with artificial intelligence getting into networks.

Increased Network Uptimes

Predictive Maintenance

Rapid issue resolution

Anomaly Detection

Network Security

Since the pandemic, we saw a great shift across all the major industries to the digital space. This shift has increased the importance of the availability of a superior and consistent network across the globe. Technology is evolving at an extreme pace; more network transformations in the future will arise. Networks will also start evolving just like humans at a pace that we cannot imagine as the computing powers are growing rapidly. New technologies that are coming to play, can potentially make the networks and devices associated with them mimic human intelligence and reasoning.  


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