The global shortage of electronic components is a result of global Pandemic that lasts for over a year now. With closure of borders, more strict controls and hundreds of thousands of people losing their jobs it is hard to maintain pre-pandemic numbers up and running.
What is more, recent Suez Canal blockage caused by big container carrier Evergreen’s Ever Given is not going to make it any easier on electronics shortages. The full blockade lasted six days, from 23rd to 29th of March 2021 and created massive “traffic jam” on both entries to canal.
“The [supply in the] first two months of this quarter was still ok, as our clients are all very big, but we started to see changes happening this month,” Liu reportedly told investors during the company’s latest earnings call.
The biggest client of Foxconn is a well known american behemoth Apple. This is going to complicate things taking into consideration that the newest Iphone 12 Pro Max is the best selling 5G device on American soil. Apple would most considerably, like to keep that trend and plans to sell even more devices from new series, most probably, labeled “13”.
Not only foxconn is having shortages, earlier same month Samsung warned about serious imbalance in semiconductor industry as a result of preparing for worldwide chip shortage.
From automotive industry, Toyota, Ford, Volkswagen and Nissan had to slow down their production lines due to shortage of sillicon, an important part of every car nowadays.
What is more, it is almost April and it is still near to impossible to buy newest PS5 or Xbox Series X consoles that had premiere last year! It is mainly because of many reselling groups as well as part shortages from Sony’s and Microsoft’s assemblies.
It is the same stroy with PC graphic cards and infamous RTX3000x line which is not available for months now. Rest of graphic cards prices skyrocketed because of shortages and growing number of crypto mines which requires huge GPU power.
Not only drivers have a harder time driving during rainfall. It turns out that artificial intelligence also has problems with driving in such conditions.
The fact that road incidents occur less frequently in the autumn and winter months, which are characterized by an increased amount of rain or snow, results from the fact that we drive slower. Limited visibility, fogged windows, problems with traction and braking on a flooded or snow-covered road make drivers take their feet off the gas. Interestingly, the research on autonomous systems shows that self-driving vehicles also have a problem with the “comfort” of driving in bad weather conditions.
On the one hand, this may seem surprising, but on the other hand, it is symptomatic. Surprisingly, intelligent vehicles are intended to be more perfect and safer, as they will be devoid of human weaknesses. And symptomatic, because every pioneering technology faces certain limitations or barriers, and this is the case with autonomous vehicles and the aforementioned rain, argues Prof. Marcin Ślęzak, director of the Motor Transport Institute.
ITS research carried out under the project “AV-PL-ROAD – Polish road to road transport automation” (in consortium with the Ministry of Infrastructure and the Warsaw University of Technology) indicates a number of factors that currently constitute an obstacle to the dynamic development of self-propelled vehicle technology. Apart from a number of legal issues, organizational and technological shortcomings remain to be solved, such as the construction of the necessary digital infrastructure in the 5G standard, the development of smart cities, data security, electromagnetic interference, calibration of systems for smooth and safe driving at the same time or the mentioned problem of driving in difficult conditions weather.
The artificial intelligence of an autonomous car uses a number of sensors to steer, including radars, LIDARs, ultrasound sensors and cameras. Thanks to them, it detects other nearby objects and makes independent decisions about all aspects of driving. The artificial intelligence system tries to track and predict what other cars will do, whether they are computer-driven or human-driven. This does not mean, however, that in rain or snow, self-propelled vehicles, despite the extensive electronics, will cope better than the proverbial Kowalski. Difficult weather conditions present an additional challenge for intelligent vehicles, as well as for humans. This is because disruptions in the functioning of LIDAR (the most accurate laser sensor onboard a self-driving car), e.g. due to bad weather conditions, are levelled with less accurate radar and cameras. It is not without reason that most road tests of such vehicles are carried out in places where it is sunny most of the time, such as California, Arizona or Texas, notes Prof. Ślęzak.
Of course, this does not mean that the intelligent vehicle will not move in the rain or stop in the middle of the road during heavy snowfall. It will start and keep going, but slower than cars driven by drivers. The factor that will further slow it down will be other road users – people and their conservative and even unpredictable driving. Therefore, it should be expected that self-propelled vehicles (although safer in principle, because they should reduce the number of accidents by about 30%) will generate traffic jams at least in the initial phase of their popularization.
The ills of psychology and psychotherapy have been the same for years – poorly structured data, a multitude of schools and therapeutic methods, the effectiveness of which is poorly or almost completely unverifiable.
Will the algorithms be able to help the man who created the imperfect, flawed system?
According to a 2016 meta-analysis published in the Psychological Bulletin, which was conducted over the past 50 years, psychology has made no progress in predicting acts of suicide. Subsequent cross-sectional studies laboriously try to sift the grain from the chaff and at the same time show how much pseudoscience is in psychology. As an introduction, it is worth mentioning the famous psychologist who almost has the status of a star – Philipha Zimbardo, whose experiment also did not survive the test of time and turned out to be an ordinary fraud, which was discovered by a French documentary filmmaker.
Despite the crises that psychology is going through, there are also areas where attempts are made to apply algorithms and solutions bordering on the use of artificial intelligence and machine learning. Let’s take a look at the most interesting solutions that scientists have managed to create so far. We will omit historical algorithms, such as ELIZA, which is one of the first intelligent interlocutors-therapists, and focus on the subjective, more advanced three.
Say hi to Ellie, avatar therapist.
Despite the fact that this is an algorithm that is already old, despite the poor graphic interpretation of the therapist, it still makes a big impression. The algorithm analyzes our facial expressions, gestures, voice timbre or eye movement and conducts the conversation as in classical therapy. Studies have shown that veterans (who participated in the pilot) suffering from post-traumatic stress disorder were more likely to answer questions to a digital “human” than to a real therapist. The results achieved by the algorithm were appreciated by clinicians who were impressed by the effectiveness of the algorithm and the openness of patients during the conversation with the avatar.
A much more specialized approach is proposed by Spring Health, which creates algorithms that monitor only mental illnesses.
We are able to predict whether the condition of a given patient will improve after the selected therapy – says Adam Chekroud, co-founder of Spring Health
The Spring Health algorithms are used, for example, by employees of Amazon and Gap Inc. For now, however, this diagnosis consists in selecting appropriate drugs based on questionnaires filled in by the patients themselves.
This process is, of course, largely automated and can boast very high treatment effectiveness, but we are still a little short of artificial intelligence, which would be a full-fledged and effective therapist. For now, the effectiveness of the algorithms depends on the analysis of a sufficiently large set of data. The algorithm analyzes data on several hundred thousand patients, taking into account all their medical data, and on this basis creates a whole network of relationships between the type of patient and the therapy that turned out to be the most effective.
On the basis of such a network of dependencies, algorithms are already able to identify people with mental disorders long before their diagnosis by any human doctor.
So we can risk a statement that in the future machines will be responsible for healing not only our body, but also our mind. The only question is how distant this future is.
Sources: – American Psychological Association, After Decades of Research Science Is No Better Able to Predict Suicidal Behaviors. – https://bit.ly/3cszETI – https://bit.ly/3sy9ogi – https://on.mktw.net/3w64GIN
How do you treat yourself today affects how you will feel in 30 years. Nothing to say that most people have a short-term perspective on their health conditions. Even though the lifestyle of many individuals has changed, the overall pattern in human behavior remains the same: People do not respect their health when being young and pay the price as they age. The anomaly that is present today is the growing efficiency of medicine. As a result, people who would die because of the sins of the past are living longer, however, with a lower quality of life.
Factors called civilizational are those related to the daily routine of people in western civilization. Means of transport, house heating, eating habits, etc. it all is made in a certain way and leaves some traces which are affecting the quality of air, amount of physical activity or bones condition. This in turn brings new susceptibilities to diseases
The 21st century is a time of changes provoked by the 4th industrial revolution along with changes in US world hegemony. We can see that the old scheme where the value-chains ended in the western world and started somewhere in Asia is just ending. Globalization was the reason for flourishing decades for western economies where companies like Apple revolutionized the whole world. Globalization is also the reason for decreasing power of the USA. As the factories have been moved outside the US and Europe with all their know-how and organizational intelligence Asia started to gain potential. Moreover, social media shown people all around the world, how it is to live in rich countries, the new limits have been surpassed. The global economy based on old solutions and hard exploitation of raw materials ran in not environmentally friendly ways, compiled with rising social aspirations of people all around the world was just too much for our planet.
Changes in economy and society are interrelated, henceforth, social tension rises significantly. For decades social structures were fluctuating, however, recently we can see a peaking moment where all around the world, everybody feels somehow unfair. The reason for that is huge gaps between past, present, and future.
On the one hand, there are philosophical tendencies that are focused on the future and believe in constant progress. This helps build new technologies, pushes the world forward, and gives unlimited opportunities. However, it raises more questions than it answers. People who are living by the promise of the future are struggling to appreciate the present, which results in e.g. mindfulness movements being only ad hoc solutions to the problem. Lack of deepness causes many existential problems and the rise of societal nihilism -> mental problems.
On the other hand, we have religions. To understand the catholic’s church attitude towards science and technology, we have to read Saint Thomas Aquinas from the 13th century (more than 700 years ago!). Even if the text is actual it is written in an old-fashioned manner and reaches a narrow audience. This in turn causes a deep conflict between faith in God (the mystery of existence) and Science.
It must be pointed that it is not only about religion which is a civilizational development just like science, however younger. Instead, it is about the deepness (the meaning of existence) that comes from being aware of The Mystery, that comes with religion.
This situation causes a conflict where well-educated people yet without an intellectual ethos are being denied by their religiosity and are not being offered anything in turn. This contradiction causes struggling with fundamentals like self-appreciation, fulfillment, or setting up a family.
How is healthcare changing?
Ancient Chinese doctors were equipped with an incredible skill of telling peoples’ medical conditions just by looking at their faces. Such a fast diagnosis system was a very efficient way to increase treatment capacities.
Today, instead of Chinese doctors we have phones with cameras and AI algorithms allowing facial recognition. An app called Face2Gene is not helping with the instant diagnosis of common health problems, instead, the solution is helping healthcare professionals detect the phenotype to diagnose patients faster and more accurately. It allows for the detection and classification of genetic diseases which otherwise would not be possible.
One of the major concepts of the medicine of the 21st century is the decentralization of health care and the decompression of the Physician role. It means that everybody will need to take care of themselves and will be responsible for observing any alarming symptoms just like they remember to brush the teeth every day.
However, as brushing teeth is a relatively simple activity identifying alarming symptoms requires academic knowledge and can’t be done so easily. Or it can?
The concept is being partially used in real life by the company called healthy.io which provides users with remote testing. For now, there are available:
Kidney testing solutions
Wound management solution
The growing amount of chronically ill people is a challenge, but also an opportunity for rare diseases to be identified and medical recommendations to be more accurate. In order for that to happen there are 2 components needed:
1. Collecting patients’ data
2. Sharing and processing of this data
Today’s internet is partially solving the second problem, however, the process of collecting data remains relatively untouched.
Dexcom is a company that has created a glucose monitoring system for diabetes. The tool is equipped with advanced analytics processing the data, smartphone integration, and glucose rising trends.
Since the glucometer is connected to the smartphone and unique for each user it gives tremendous opportunities for identifying certain symptoms with a concrete characteristic of the user. This in turn gives an opportunity for bigger precision of medical recommendations for future patients.
With the increasing popularity of 5G and Medical IoT solutions that will track human performance on many verticals, the amount of data obtained in such a way will be increasing.
Since this is a topic of a very sensitive nature and needs to be implemented very carefully, a lot of research still needs to be done. The initiative that is bringing the world closer to high-quality health care is Novartis’s grant program for startups and research institutes focusing on increasing the quality of patient-doctor relationships.
The American military agency DARPA intends to integrate artificial intelligence algorithms in fighter battles. A simulation was carried out with the participation of F-16 aircraft.
DARPA recently tested the possibilities of integrating artificial intelligence in air combat. Last month, the agency conducted tests in which two simulated F-16 fighters took part – their task was to defeat the enemy plane together. The test is part of the so-called ACE (Air Combat Evolution) program and its first phase, in which air combat is studied in the context of e.g. machine learning.
DARPA’s Air Combat Evolution (ACE) program is half way through Phase 1 and has notched several key accomplishments in anticipation of live subscale aircraft dogfights in Phase 2 later this year
“Our biggest focus at the end of Phase 1 is on the simulation-to-real transition of the AI algorithms as we prepare for live-fly sub-scale aircraft scenarios in late 2021,” said Col. Dan “Animal” Javorsek, program manager in DARPA’s Strategic Technology Office. “Managing this transition to the real world is a critical test for most AI algorithms. In fact, prior efforts have been brittle to just these types of transitions because some solutions can be over-reliant on digital artefacts from the simulation environment.”
Watch the short movie about “Phase 1” on the YouTube channel, DARPAtv !!!
According to DARPA, the goal of the program is to create a trusted, scalable AI-managed air combat autonomy system that would also be the result of human-machine collaboration. As you can see in the video below, which explains the entire test, two F-16 fighters were to knock down the enemy plane.
Let me add that the US military has recently also tested new tools for fighting in cyberspace – and there it apparently needs more ways to conduct battles. The US Army also intends to buy 40,000. ultramodern goggles, which include they will allow you to “see through the walls”.
The Americans will spend several hundred million dollars for this purpose, but it will probably be money well invested. The goggles will offer some impressive possibilities, including “seeing through walls”.
They have been working on IVAS goggles for quite a few years and want to buy as much as 40,000 pieces of this equipment that will be used by soldiers around the world. These are mainly to be infantry units, which, thanks to IVAS goggles, will receive much better understanding on the battlefield.
The goggles are able to receive images from cameras placed around the armored transport vehicle, thanks to which soldiers who are inside the machine and equipped with goggles can look through its walls, seeing what is happening outside the vehicle. The goggles will also offer other possibilities, e.g. looking around the corners of a building or a corridor, providing the soldier with an image from a webcam attached to his weapon. The goggles can also receive an image from a thermal imaging telescope, offering the soldier a better view of the battlefield at night.
The general assumption is that the goggles work similarly to a fighter pilot’s helmet, offering soldiers a range of information in the form of a digital display, e.g. a map with GPS coordinates. The American command assumed that it would spend 40,000 on the purchase. IVAS goggles $ 1.1 billion, and Congress cut that amount by twenty per cent. This does not change the fact that soldiers are already training with this type of devices and their implementation into active service units seems to be a matter of time.
Sources: – https://bit.ly/3fcfLSK – photo 1 DARPA’s logo – https://bit.ly/2Pq6wDK – photo 2 and article from DARPA – https://bit.ly/3fa272p – photo 3
You can now pay for Tesla cars with bitcoin cryptocurrency.
E-car maker Tesla has begun to accept bitcoin, according to a Twitter message from Elon Musk. This is a new milestone in the cryptocurrency adoption process.
The company will not exchange bitcoins for FIAT.
“Tesla only uses internal and open source software and supports Bitcoin nodes directly,” added Musk in another reply. “Bitcoin paid to Tesla will be kept as bitcoin, not converted to fiat currency.”
The tweets appeared shortly after some Twitter users began noticing bitcoin support as a payment option in the company’s US stores for its electric car models.
Musk commented that bitcoin payment is available in the US for now. “Bitcoin payment option available outside the United States later this year,” he added.
The address where the bitcoins for the cars will go.
Based on the bitcoin payment details that The Block editors were able to see even before removing the option, the company provided this BTC address as a receiving address.
Tesla informed users that it does not currently accept payments in digital assets other than bitcoin. Potential car purchase transactions are to take place at the indicated address in one transaction.
It had to happen!
Already at the time of submitting the 10-K documents to the US Securities and Exchange Commission in early February regarding the 1.5 billion investment in BTC, Tesla announced that it would soon start accepting bitcoin as a form of payment for its products.
With BTC, you can now buy models from the manufacturer’s extensive fleet of electric cars (Model S, Model Y, Model 3 and Model X).
In most parts of the world, the Internet is usually associated with freedom of speech and expression. However, it also can be utilized as a method of direct propaganda and strict censorship.
In this article, you will learn how the Internet censorship system works in China.
In recent years, the Chinese leadership has devoted more and more resources to controlling content online. First of all, there are topics on the Chinese internet that became taboo from the very beginning. There are not so many of them: everything related to separatism, questions about the independence of Tibet and Xinjiang, protests in Tiananmen Square in 1989, everything related to the Falun Gong movement, and, of course, any criticism of the Chinese Communist Party and central authorities. However, it is not forbidden to point out any problems on a local level.
At the same time, it is not so important for the Chinese authorities to tightly close access to foreign media. If someone really wants to read the New York Times, Facebook or Twitter, they can. The policy is different: to make the bulk of the population to consume content from local resources controlled by the Communist Party. Therefore, almost all local analogues of existing world services were created: there is an analogue of Twitter (Weibo), there is an analogue of Facebook (Wechat), of YouTube (Youku), and so on, even an analogue of the Quora question-answer service (Zhihu) and the search engine for scientific works Google Scholar (Baidu Wenku). All these resources are obviously under the tight control of the Communist Party.
All bloggers are also strictly controlled. In the early 2010s, there was no compulsory state registration for Chinese bloggers if they are not well-known personalities and do not represent any structures or legal entities. But already in the mid-2010s, all bloggers were obliged to register using real names and identity documents. In addition, in 2013, there was a responsibility for the publication of compromising information, the so-called law on rumors and speculation. Any criticism of the central authorities, of course, fell into this category. Under this law comes criminal liability when a message is republished more than 500 times or when the number of views is more than 5000. You also should keep in mind that 500 reposts on the scale of the Chinese Internet is nothing. This law covers almost any post on Chinese social networks with information that is not necessarily unreliable, but disliked by the authorities.
This is exactly what happened to the famous Chinese doctor Li Wenliang, who tried to warn colleagues that a new infection, very similar to the SARS virus, appeared to be a new COVID19, was spreading in the country. He started to have problems exactly with the law on rumors and speculation. He was summoned to the relevant authorities where he was forced to give explanations and then publicly admit that he was guilty of publishing false information. As we already know the information turned out to be reliable and Li Wenliang himself died from the coronavirus infection that he was trying to warn everyone about.
Already in the beginning of 2021, the State Chancellery for Internet Information Affairs published new rules according to which Internet users, including bloggers, are not allowed to independently publish information about politics, the military sphere, the economy and social sphere without appropriate accreditation as a media. This is another step towards tightening censorship. In fact, apart from pictures of cats and food, there are less and less topics in the Chinese blogosphere that you can discuss relatively freely.
That is why streaming services are gaining popularity in China now – precisely because communication takes place live and content moderation is difficult. However, artificial intelligence technologies now make it possible to recognize live speech and extract keywords from it. If the algorithm marks the stream as suspicious, then the moderator receives a signal and starts checking this stream manually. If he notices any forbidden or politically unreliable topics, then the broadcast is forcibly stopped, and the user who started it is restricted from accessing the platform.
As technology is constantly evolving, uncensored conversation becomes more and more difficult. When Clubhouse appeared on the internet, the first week in China, it was wildly popular. It seemed as a new form of free communication. However, the Chinese authorities quickly banned it.
For the international community, Beijing’s cyber-policy is a sign of the challenge that a more powerful China presents to the liberal world order, which prioritises values such as freedom of speech. It also reflects the paradox inherent in China’s efforts to promote itself as a champion of globalisation, while simultaneously advocating a model of internet sovereignty and closing its cyber-world to information and investment from abroad.
Sodinokibi, also known as REvil (short for Ransomware Evil) is a ransomware threat group gaining more and more notoriety. Similar to some other ransomware families, REvil is what is called a Ransomware-as-a-Service (RaaS). Ransomware-as-a-Service is where a group of people maintain the code and another group, known as affiliates, spread the ransomware. Such RaaS models allow affiliates to distribute REvil ransomware in various ways, such as phishing campaigns or by uploading tools and scripts allowing them to execute the ransomware in the internal network of a victim.
Sodinokibi hacks organizations by infecting them with a file blocking virus, which encrypts files after infection and discards a ransom request message. In the message, Sodinokibi explains that the victim needs to pay a ransom in bitcoins or else the files will be leaked.
The group recently made headlines when they targeted Acer, a Taiwanese electronics company. On March 19th 2021, Acer was the subject of a hacker attack. The attackers, who are the REvil group, demanded the biggest known ransom to date in the history of cyber-attacks – $50 million. The hackers gave Acer until the 28th of March to pay the ransom, or all the stolen data will be released to the public. As of March 20th, Acer did not acknowledge that they were the victim of a security breach.
The malware first surfaced in 2019, when it was discovered that in Oracle’s WebLogic server a serious flaw was noticed – a remote code execution bug which was remotely exploitable without authentication. This was an unusual attack from the side of the hackers, as it directly utilized the vulnerability of the server – and as researchers suggests, such attacks are typically executed with the involvement of user interactions, e.g., the act of opening an attachment to an email message or clicking on a malicious link.
Sodinokibi has subsequently targeted organizations such as celebrity law firm Grubman Shire Meiselas & Sacks, foreigner currency exchange giant Travelex, Brown Forman Corp. (the owner of the Ritz Hotel in London) and as of recently Acer.
REvil is gaining momentum and notoriety, which is evident in the way the hacking group decided to target the tech giant Acer. This cyber security breach is worth following, as the repercussions for Acer may be substantial. This unfortunate event for Acer should also serve as a reminder to all internet users that cyber security attacks keep getting more refined and complex, and that substantial security measures should always be kept in place.
Around 50 years ago it happened to be clear that the world will never be the same place again. The internet revolution has started. Today, we are continuing that process and the pace of changes is only increasing. Overall trends show that the differences between technological domains are blurring to answer the demand of modern society. The result of that is the birth of IoT applications in various domains, both on the specialized and mass market.
This in turn gives tremendous business and career opportunities for all types of specialists from various domains, because:
There is no smart city without smart sensors.
Smart sensors need an embedded AI.
Embedded AI requires data scientists.
This short scene shows the mechanism on how different technologies (in this case AI) are intertwined with the IoT. Unfortunately, this causes a high degree of uncertainty and is making business/career decisions more complex. In order to act wisely, you need a good understanding of the roots of these technologies.
Internet of Things (IoT)
As you probably might guess the Internet of things is a concept that is a little mixed up. So, I would like to divide it into two components: the internet & the things to introduce it that way.
Firstly, we need to look at the very basics and acknowledge that the existence of our universe is possible thanks to the 4 fundamental forces of nature: Gravity, The weak force, Electromagnetism, and The strong force.
For us, the most important is Electromagnetism, which throughout the past centuries we were trying to tame and benefit from. It was pretty unsuccessful, until the 19th century when we started to process the energy in more sophisticated ways.
At that time we uncover the potential of radio frequencies and made developments like electric light, transformer, wireless communication, etc.
If you are familiar with the early history of the internet you probably recognize the name ARPANET, which was a military program developed to connect the university centers in the United States. The next step was the creation of Internet Protocol (IP), soon after that the 1G cellular system was born and the rest of the story you know.
As you can see the Internet was initially created to connect specialized machines with at least a bit of computing power such as computers and in the later steps mobile devices. On the other hand, back in the ’70s, there were initial applications of machine-to-machine communication (M2M).
You might ask, how is today’s IoT different, from what it was in the past?
A great answer to this question is a quote by iotforall:
„The biggest difference between M2M and IoT is that an M2M system uses point-to-point communication. An IoT system, meanwhile, typically situates its devices within a global cloud network that allows larger-scale integration and more sophisticated applications. Scalability is another key difference between M2M and IoT. „
Let’s quickly visualize the power of IoT in practice.
Giving the example of healthcare true flawless experience might look like that: mattresses monitoring your sleep, chairs monitoring your posture, various medical devices testing your condition, microphones collecting the data about your cough to monitor lungs conditions, etc. This in turn shows that we need billions of more connections than we have today and it only is possible with the new generation of telecommunication architecture.
The answer to this demand is an improved technology of the 5th generation (5G) of cellular communication protocols, rules, and methodologies issued by IEEE (Institute of Electrical and Electronics Engineers)
It is mainly focused on:
The wide availability of the signal (enhanced mobile broadband)
Significantly decreased latency compared to 4th generation technology, especially useful for applications requiring critical reliability e.g. remote surgical operations
Enhanced machine to machine communication up to 1 mln devices per 1 square kilometer
Technology still faces many challenges both in engineering and societal aspects. As you can see many challenges addressed by the IoT advocates are not going to be solved with the rise of 5G architecture. Cellular of the fifth generation might soon become outdated and that is why various R&D departments are already working on the 6G.
It is projected that the next few decades are going to be a constant transition process between new generations of cellular technology. Henceforth, it is obvious that 4G, 5G, 6G will overlap it selves and it would be hard to talk about one of them individually in terms of predictions. That is why I would like to describe more in detail the future potential business opportunities as the result of these three.
It is projected that by 2030 the overall telecommunication advancements will allow:
Transfer of senses like smell
I would like to disclaim that this is going to be my private observation, that with the rise of political trends and ideas to give every person a salary from the first day of birth, this will have hundreds of results (not rating good/bad) and one of them will be the increasing boredom. The rise of all sorts of gaming apps using this feature is just a marvelous way to create new experiences and disrupt the entertainment sector.
Inch perfect localization services
Space! The answer to an unbreakable internet connection all around the world. Satellite-based internet is a huge opportunity to enter growing markets like e.g. Nigeria. Many of the services that Google wanted to provide to this country failed due to low internet connection. In the next decade, it will change for the better. It is worth to mention almost everybody in Nigeria is a smartphone user.
Another aspect is the production and management of the data gathered throughout the satellites. Geospatial analytics is a great source of knowledge e.g. ability to measure the amount of gasoline in Saudi Arabian Oil Tanks and send this data to the NYC stock exchange to see how is the relation of stock prices to the real demand.
Not to mention GPS advancements that will make navigating, targeting, etc. more efficient.
How to benefit from it?
I hope that now, you have just a bit broader sense of how it all will be in the future and that now we are just starting.
Huge problems usually are followed by huge earnings if solved. Here is the list of problems and few interdependencies that might help build your future business model/career.
Connectivity — discovering the ways to establish a reliable wireless connection. As we already know, the connection is just a radio wave of a certain frequency, hence it can be modulated. This modulation could be „smart” in the future thanks to Deep Learning and Machine Learning.
Continuity — optimizing the battery life. How to predict long-term battery life by analyzing data from charge-discharge cycles?
Compliance — be up to date with evolving regulations. As AI is improving financial services compliance, it has a significant potential for smart management of constantly changing regulations.
Coexistence — billions of devices per km2 means billions of data that need to be processed. Smart sensors with embedded AI is a crucial element of industry 4.0
Cybersecurity — a secure connection is the most important part of IoT. Which technology will make it possible? Blockchain IoT has a projected 45% CAGR, what will be the successor of NFC (near-field-connection)? Many questions little answers = good business opportunity.
The transformation process will not happen overnight, 5G is very different from 2,3,4G because it is now when the Industrial revolution will be possible. Adding a coronavirus and the tendencies to move industry production from China back to Europe all give opportunities for businesses focusing on adapting Europe’s industry to new circumstances. All solutions connecting the old infrastructure with the new technologies are going to be crucial.
In the IoT world embedded AI will be used very often and a certain degree of independence requires applied algorithms to be reliable. To do that the algorithms will have to be certified. If you like law and science maybe such a research center is a good career choice.
As space will be a fundamental part of IoT systems and you would have an opportunity to work in a NewSpace company it is highly possible that you will benefit financially and you will have long-term stable employment.
Motion is everything. We are entering a time when the motion of people, cars, ships, etc. will be tracked and the data produced this way will be the new oil of our century. To benefit from it, you need to solve some issues named as 5 C’s of IoT and follow the newest media coverage about Industry 4.0 and the space race.
Wikipedia, the free encyclopedia has been used and praised for various groups, researchers, students and even tech behemoths. It has been used for free, even thought it powers many of The Big Four commercial technologies. Now, it can finally change.
Everyone knows tight partnership between Wikipedia and Google. One fuels another one with date and in exchange is winded up in search results. Other tech giants used its services as well. Many chatbots and virtual assistants such as Apple’s Siri or Amazon’s Alexa learn and use data from Wikipedia.
According to The Wired, some companies are generous enough to contribute in many donations once a while, on the other hand, there are also companies that create enormous projects based on Wikipedia data without even mentioning it to the Wikimedia board. The new project called Wikimedia Enterprise decided to finally recognize commercial users as a separate database.
Nowadays, companies hire a lot of people in order to build teams responsible for importing Wikipedia data, usually through “data dumps” happening every other week. They do it without any help from Wikipedia. This is going to change.
“They all have teams dedicated to Wikipedia management—big ones,” Becker said, adding that making the different content speak to each other required “a lot of low-level work—cleaning and managing—which is very expensive.”
That is why Wikimedia Enterprise was born. It offers kind of a premium version of the Wikipedia API, which can be used to extract data faster and in format of a choice. Wikimedia thinks that companies are going to love this function and they will eagerly pay for it, since they are already paying whole teams to clean and format data. Now, it can be done even faster and at the source.
What do you think about Enterprise? Should Wikipedia introduce more premium paid services for companies? Let me know in the comments.