Monthly Archives: November 2022

29 November 2022
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AI

The Frank Sinatra song that not even Frank Sinatra heard

Reading Time: 4 minutes

As Christmas is fast approaching, we are starting to hear the holiday classics everywhere. From All I Want for Christmas at the Supermarket to Rockin’ Around the Christmas Tree on the radio – Christmas songs are virtually unavoidable. 

But I’d like you to think of the artists behind these songs – most of Spotify’s Christmas Hits playlist[1] is comprised of songs recorded or written before the first manned mission to the Moon.

Naturally, many of the authors and performers listed in the credit sections of these songs are long gone – Bing Crosby died in 1977, Nat King Cole passed away in 1965 and Frank Sinatra departed in 1998. 

Frank Sinatra
source: http://enterate24.com/hace-104-anos-nacio-el-cantante-frank-sinatra/

It’s a shame that we won’t be able to hear any new songs from them.

But what if it doesn’t have to be that way?

That’s where OpenAI’s Jukebox comes into play.

Debuted in April 2020, the technology analysed over a million songs[2], along with their lyrics and metadata (release date, genre, mood) and is now capable of generating full tracks in the style of any well-known artist. The company shared a range of demos, designed to resemble artists such as Alan Jackson, Katy Perry, or Elvis Presley. Most notably though, the song that stands out is “Hot Tub Christmas”, in the style of Frank Sinatra. While the “recording” quality might not be perfect, the timbre of the “singer’s” voice is eerily similar to that of the legendary American singer.

Though the lyrics have been co-written by a language model and OpenAI researchers, the chord progressions and instrumental cohesion are very well replicated in the computer-generated mp3s. The team behind Jukebox is aware of the software’s faults, as “[…] the generated songs show local musical coherence, follow traditional chord patterns and can even feature impressive solos, we do not hear familiar larger musical structures such as choruses that repeat.”2

Jukebox doesn’t analyze the actual notes in the songs, but only relations between pitch over time. An upside of such an approach is the possibility of highly realistic human voice creation. For their future endeavors, OpenAI plans to integrate a note-to-MIDI technology which would detect the rhythms and exact notes, which would allow for a deeper, more natural, and precise song creation – perhaps with the use of software instruments or synthesizers for higher file and sound quality.

Jukebox, at this point, is treated by the music industry as a mere curiosity, with no real applications – even despite a new feature of creating an acapella file from user-generated lyrics being introduced. This dynamic might change in a relatively short time if Jukebox becomes able to create classically written songs, providing the notes, rhythms MIDI files behind them. With such possibilities, songwriters and producers could streamline their music creation processes and massively increase their output. 

The current market situation is visualized by the fact that most of the investments poured into creative AI come from Venture Capital and Tech Corporations – not from the Music Industry.[3]

At this point, it does not seem like any songwriter or producer jobs are endangered. High quality audio files have incredibly many timesteps which encode data – a standard 4-minute-long song in a .wav 44.1 kHz file will contain over 10 million timesteps.[4] Currently, a song needs to be almost fully produced and designed by a professional before being rendered into such a complicated audio file.

The process of AI art generation is slowly being integrated into commercial culture, with the generator Midjourney winning the Colorado State Fair Fine Arts Competition.[5] Jukebox and similar technologies are often criticized for taking away the humanity out of art, while some perceive it as an opportunity to augment their creations through technology.[6]

“Théâtre D’opéra Spatial” – the AI-generated, contest winning piece of art
source: https://edition.cnn.com/2022/09/03/tech/ai-art-fair-winner-controversy/index.html

To me, it seems inevitable that Artificial Intelligence will be widely used in the music industry – major labels will push for anything that can give them a competitive edge in business. 

We must also take into consideration the legal implications of Jukebox.[7] Our laws don’t include AI “artists” and thus, there might be copyright implications. Who is the de facto author of such a song? The AI developer, or the person who entered prompts into the technology to create a specific tune? How do we split royalties for such songs? Furthermore, is it acceptable ethically to expand dead artists’ catalogues?

In conclusion: AI is slowly entering into creative arts, especially the music industry, thus expanding songwriters’ and producers’ output and possibilities. It appears that in this case, the risk of actual people being replaced by technology is lower than in easily automated and routine operations. 

This time, I’ll ask the classic question: do you think that AI art is proper art? Should it be publicly disclosed that a song or a painting was generated through Artificial Intelligence?

Let me know what you think in the comments!

Until next time,

Jan 

[1] https://open.spotify.com/playlist/37i9dQZF1DX0Yxoavh5qJV?si=d4fa601b2c3f4418

[2] https://www.cnet.com/science/these-ai-generated-katy-perry-and-elvis-songs-sound-hauntingly-real/

[3] https://blog.songtrust.com/current-state-of-ai-what-songwriters-need-to-know

[4] https://openai.com/blog/jukebox/

[5] https://edition.cnn.com/2022/09/03/tech/ai-art-fair-winner-controversy/index.html

[6] https://fortune.com/2018/10/25/artificial-intelligence-music/

[7] https://themix.musixmatch.com/post/ai-in-songwriting-4-practical-applications

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28 November 2022
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Will Physical Money Disappear?

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Many people including me have noticed the decreasing rate of using physical cash in payments while the increasing rate of using online payments and debit/credit cards.

Who would have imagined 100 years ago that we will be paying through something called an online transaction or payment, I don’t think a lot of people anticipated this rapid sequence of development.

Pros and cons of cash:

for someone who is using cash he/she won’t have to worry about any security breaches, paying with cash protects and prevents your personal data as well as your money, because it’s always next to you, there is no risk or fear from hackers online, you have more control over your spending’s when your cash is finished its finished (you can’t spend more than what you have), you don’t go into any debts unlike when using a credit card for example. Also cash is accepted everywhere, many people tend to think that its more private and more secure.

However, using cash has its downsides as well, the most main one is that cash can be lost or stolen, more over with the world as it is headed more and more towards technology and electronic development, electronic purchases won’t be an option or rather won’t be available maybe you would miss out on some rewards or promotions online. You will also miss the opportunity to build credit. And it’s also more difficult to track your expenses and payments with cash.

Pros and cons of online payments/cards:

Basically the advantages of using electronic payment methods solve most of the downsides of using cash, it’s better to pay big amounts of money by card as its much more convenient and easier to do, you can track your balance and money received and sent, you can use more money than you have (using credit, which can also be a disadvantage), on the other side, there are also downsides when using card and online payments, as some technical problems may occur, security threat and concern, sometimes there is limitation on the amount of money you can pay, there is also expenses for the service as well as interest rate.

Throughout the last years, many people started wondering wither we will stop depending on using cash for our payments and depend completely on using online payments and cards and head towards a cashless environment.

I would say that the younger generation is headed more towards the cashless environment while the older generation is still stick to using cash, mainly because they don’t trust the online procedures, and they aren’t used to it as they have used cash as their way of buying for most of their life.

Ultimately, cash may in fact disappear. But it’s mostly a question of where and when. While it may disappear in some countries, it might remain in others.

Resources:

https://www.forbes.com/advisor/credit-cards/cash-vs-credit-which-should-i-use/

https://www.sbalynxpayment.org/post/advantages-disadvantages-of-cash-discounts-allowances

The Pros And Cons Of Cash Vs Card

28 November 2022
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Benefits of Data Storytelling

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What is Data Storytelling?

Data storytelling is the most effective method for leveraging data to produce new knowledge, new choices, or new actions. It is an interdisciplinary profession that incorporates knowledge and experience from several domains such as communication, analysis, and design. It is used to solve a variety of issues and is employed in a variety of areas.

The majority of marketers have some narrative experience. When we talk about data storytelling, we’re talking about stories in which data is the main focus. The narrative’s purpose is to explain the information and its importance. There are many different types of stories, and most of them can be conveyed with the help of photographs, but only a handful do.

The most important elements of data storytelling:

Data: The cornerstone of any data story is a thorough study of correct, full data. Data analysis employing descriptive, diagnostic, predictive, and prescriptive analysis may help you comprehend the whole picture.

Narrative: A tale, also known as a verbal or written narrative, is used to express insights drawn from data, the context around it, and actions you advocate and hope to inspire in your audience.

Visualizations: Visual representations of your data and narrative may help you tell your message in a clear and memorable way. These might take the form of charts, graphs, diagrams.

The benefits of data storytelling

Data storytelling is comparable to human storytelling, but it includes deeper insights and supporting facts in the form of graphs and charts. Data storytelling simplifies complex information so that your audience can connect with your content and make key decisions more quickly and confidently.

Creating a data story that inspires others to act may be a really effective technique. People and your business may benefit from effective data storytelling. Some of the advantages of effective data storytelling include:

  • Increasing the value of your data and insights;
  • Interpreting difficult information and emphasising vital elements for the audience;
  • Giving your data a personal touch;
  • Adding value to your target audience and industry;
  • Developing your reputation as an industry and issue thought leader.

What makes a great data story?

It must be meaningful
This means that the information (including copy and images) must be appropriate for the audience’s present level of understanding and must assist them in achieving some sort of goal.


Perhaps your audience is internal, such as a presentation to leadership about the need of investing in a certain strategy or method. Or they might be external, such as a campaign to get them to test your solution.

In any case, consider what is important to them. The finest stories are those that appeal directly to people, and the more particular the person, the better.

It must have accurate data
This means that the data should come from a reliable source and/or be gathered in a method that accurately depicts what is required to convey a true tale.


Data made public by government institutions, intergovernmental organizations, university researchers, and established analysts are not only more accessible, but also transparent and verified.


The facts you utilize should assist you in telling the truth. It should be relevant to the audience’s needs and assist them in understanding just what they need to know to make an important decision.

A clear narrative is crucial
When it comes to narrative, we are all accustomed to the standard three-act structure with a beginning, middle, and finish.

For data storytelling, this typically implies that you need to learn about the issue first before diving into the data. You must also finish with a particular call to action—another distinction between a data story and a basic report.


Also, if your audience is not an expert, use clear language to avoid losing them in tricky jargon or complicated acronyms.

It should incorporate deliberate graphics

It implies that your graphics, whether images, graphs, or charts, should help your audience grasp what the data means.

What are your thoughts on data storytelling?

References:

https://www.analyticssteps.com/blogs/introduction-data-storytelling

https://online.hbs.edu/blog/post/data-storytelling

https://powerbi.microsoft.com/en-us/data-storytelling/

https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/?sh=7874148052ad

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28 November 2022
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Challenges of self driving cars

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While the arrival of self-driving automobiles has many potential benefits, it also has its own set of challenges. Technology is never flawless, and computers may be hacked. Furthermore, while autonomous cars will make our roads safer, they may also have unexpected societal implications, such as greater unemployment rates.

Some possible issues with self-driving automobiles are inherent in the existing layout and use of our highway infrastructure. Existing road conditions and signs, for example, as well as the transition phase in which some drivers on the road will use autonomous vehicles and others, will use traditional vehicles, might all provide substantial challenges to the adoption of self-driving cars.

Road conditions

Road conditions can be exceedingly variable and vary from location to location. There are smooth and well-marked wide roadways in certain situations. In other areas, the road is severely eroded, with no lane markings. Lanes are not well defined, there are potholes, hilly and tunnel routes with unclear external cues for orientation, and so forth.

Weather conditions

Another stumbling block is the weather. The weather might be bright and clear or wet and stormy. Autonomous vehicles should be able to operate in any weather situations. There is no possibility of failure or downtime.

Traffic conditions

Autonomous vehicles would have to enter the road and drive under a variety of traffic scenarios. They would have to share the road with other autonomous vehicles as well as a large number of humans. There are a lot of emotions involved whenever people are involved. The flow of traffic might be greatly monitored and self-regulated. However, there are times when someone may be breaching driving laws. An item may appear in unforeseen circumstances. Even a few centimeters per minute of movement matters in tight traffic. One cannot wait indefinitely for traffic to clear and for some prerequisite to begin moving. If there are more of these automobiles on the road waiting for traffic to move, it might lead to a heavy traffic.

Accident Liability

Accident liability is the most significant feature of self-driving automobiles. In the case of self-driving automobiles, the software will be the primary component that will operate the vehicle and make all critical choices. While the earliest concepts had a human physically stationed behind the steering wheel. Furthermore, owing to the nature of autonomous vehicles, the occupants will be primarily relaxed and may not be paying careful attention to road conditions. In instances where their attention is required, it may be too late to act by the time they need to.

Radar Interference

Lasers and radar are used for navigation in self-driving automobiles. The lasers are installed on the roof, while the sensors are located on the vehicle’s body. Radar operates by detecting radio wave reflections from nearby objects. When a car is on the road, it emits radio frequency waves that are reflected by other automobiles and things in the vicinity. The time required for the reflection is calculated to determine the distance between the automobile and the object. Based on the radar data, appropriate action is subsequently performed. Radar operates by detecting radio wave reflections from nearby objects. When a car is on the road, it emits radio frequency waves that are reflected by other automobiles and things in the vicinity. The time required for the reflection is calculated to determine the distance between the automobile and the object. Based on the radar data, appropriate action is subsequently performed. Will a car be able to discern between its own (reflected) signal and the signal (reflected or transmitted) from another vehicle when this technology is utilized for hundreds of cars on the road? Even if numerous radio frequencies are available for radar, it is doubtful that this frequency range would be insufficient for all cars made.

What are your thoughts on the self-driven cars? 

Are they going to become the reality?

References:

https://www.johndaylegal.com/potential-problems.html

https://www.vox.com/2016/4/21/11447838/self-driving-cars-challenges-obstacles

https://www.livescience.com/50841-future-of-driverless-cars.html

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28 November 2022
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AI agent that can collaborate and negotiate with humans

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While artificial intelligence has mastered chess, go, and poker, it has yet to win games reliant on language and comprehending the other person’s intentions. According to Meta, the company’s artificial intelligence group has recently built a model capable of comprehending and acquiring human trust, which has boosted the rankings of the popular game Diplomacy.

Even though the Meta Platforms conglomerate is best recognized for owning and developing social networks such as Facebook, Instagram, and WhatsApp, as well as pioneering virtual reality, Meta is also actively working on artificial intelligence research. The results of this work include artificial intelligence capable of translating from languages that have no written form. Today, Meta introduces another milestone in the evolution of artificial intelligence: Cicero, an AI agent that negotiates, persuades and collaborates with people. It accomplishes this through the popular game Diplomacy.

For decades, games against actual humans have served as not only a training ground for artificial intelligence, but also a means of demonstrating how far technology has progressed. Deep Blue astonished the world by defeating chess grandmaster Garry Kasparov in 1997. In 2015, AlphaGo became the first computer program to defeat a professional at the ancient Chinese board game go. Both chess and go have a set of principles that can be instilled into an artificial intelligence using data from hundreds of games. And with hundreds more, teach it human-level strategy and decision-making.

Diplomacy is a game that has long been considered to be impossible for an artificial intelligence to learn. The game needs the computer to recognize the plans, outlook on the game, and motivations of the other players rather than a mathematical comprehension of the actions done on the board. The AI must then convert this comprehension into natural language signals that persuade the human participants that it is correct. Meta created the Cicero agent by combining two types of artificial intelligence models: a strategic thinking model (similar to AlphaGo and Deep Blue) and a natural language processing model (similar to GPT-3).

The strategic thinking model’s abilities enabled Cicero to make the best decisions for himself, while natural language processing enabled the AI to communicate naturally with the players. It was trained using a BART-type language model with 2.7 billion parameters gathered from various sorts of internet documents, then modified with training data from 40,000 online games involving human players on WebDiplomacy.net.

Cicero was able to become one of the finest players of the browser version of Diplomacy, scoring “more than double the average score” and getting into the top 10 players who have played more than one game as a result of such training. 

Although Cicero can only play Diplomacy, the technology used to construct the AI agent has many real-world applications, as Meta claims. Controlling natural language generation through planning and reinforcement learning, according to Meta AI, can help break down communication barriers between humans and AI-powered agents.

References:

https://arstechnica.com/information-technology/2022/11/meta-researchers-create-ai-that-masters-diplomacy-tricking-human-players/

https://gizmodo.com/meta-ai-cicero-diplomacy-gaming-1849811840

28 November 2022
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AI in Emotion Recognition

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Emotion recognition is one of the various facial recognition systems that have evolved through time. Currently, facial emotion recognition software is utilized to allow a specific program to inspect and process human facial expressions. Using complex image dispensation, this program acts like a human brain, allowing it to recognize emotions as well.

AI identifies and examines various facial expressions to use them with extra information. This is beneficial for a number of purposes, including investigations and interviews, and enables authorities to identify a person’s emotions using just technology.

What emotions can be recognised by AI system?

  • Anger
  • Joy
  • Surprise
  • Fear
  • Sadness

How does face recognition works?

Every year, facial expression-detecting technology becomes increasingly advanced. The AI used recognizes and examines facial expressions based on a variety of parameters to determine what emotion the individual is displaying. Factors like:

  1. Using Metrics:

    When a person exhibits a certain feeling or expression (for example, a grin) together with a level of confidence. It may be conceived of as a detector by employing metrics: The score climbs from 0 (no expression) to 100 (expression fully present) when the emotion or facial expression arises and strengthns .
  1. Using Datasets:

    The data consists of grayscale pictures of faces with 48×48 pixels. The faces have been automatically positioned such that they are about centered and take up around the same amount of area in each image. The aim is to categorize each face depending on the emotion expressed in the facial expression (0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral).
  1. Using ParralleDots:

ParralleDots has developed an AI-based solution that developers may utilize after training on a specified data set to detect images.

The process of developing an emotion detection model, like any other AI project, begins with project planning and data collecting. More information on the steps of an AI project and the collecting of datasets may be found in our dedicated articles.

Let’s take a break from the data acquired for an emotion identification model. It is a vital (and time-consuming) component of the future algorithm since it must be gathered, analyzed, safeguarded, and annotated. This data is necessary to train the emotion recognition model, which is essentially a procedure that teaches the machine how to interpret the data you provide it.

Finally, is important to understand that there are unsolved issues and hazards associated with emotion detection. The intellectual underpinning of this technology is dubious at best, and privacy concerns have caused a few big cities in the United States to ban its usage by the police. However, there is no need to be disappointed by these flaws. Emotion recognition is still in its early stages, but it will get stronger, more accurate, and more secure. With high-quality data and annotation, cultural understanding, and privacy restrictions in place, emotion detection algorithms might be among the most useful technologies of our time.

What do you think about such innovation?

References:

https://recfaces.com/articles/emotion-recognition

https://tudip.com/blog-post/what-is-emotion-recognition/

https://link.springer.com/article/10.1007/s10919-020-00340-4

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28 November 2022
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Apps, Business, Software

Why Maro should be compulsory in middle school and high school education.

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Daily, parents are faced with uncomfortable or difficult topics that eventually must be discussed with their children, whether it be regarding puberty, mental health or empathy and diversity. For that reason, Kenzie Butera Davis has created a start-up called “Maro” with an aim to help parents who do not know how to begin such important conversations. 

If children knew more about puberty and mental health, starting from a younger age (for example 10y/o), many unnecessary actions could’ve been avoided without worsening anyones mental state. Many young girls find puberty a taboo topic and feel embarrassed when someone points out completely normal and natural things such as menstrual cycles, acne or overall hormonal changes. In the US, for example, this oftentimes creates a mental block in their head, which transforms to anxiety (a mental disorder) as they can get picked on or ‘bullied’.

Maro’s purpose is to educate younger generations (and not only!) regarding various situations that they’ll be faced with every day as they get older. A lot of parents don’t see the urgent need to educate their children regarding such mature topics even though they’re vital to know, especially during their pre-teen age. The focus of this app is the education regarding mental health, as that is something that many are struggling with nowadays, especially after the pandemic, and yet still fail to realise its seriousness.

The issue with mental health education in schools is that it doesn’t necessarily exist. In fact, mental health is not typically taken seriously by the education systems. This usually escalates to many children being looked down upon while they’re struggling and may also be harassed by their peers by being called “weaker” or “attention-seeking”. Is this due to the children not knowing the severity of what such actions and words may cause to the ones already struggling? Perhaps. For that reason, Maro was created; with hopes to solve the said problem.

In the US alone, 1 in 5 children between the ages of 10-24 struggle with mental health that leaves them with lifelong struggles if they remain untreated. In most cases, many are unable to seek professional help, due to their or their parents’ financial state as such treatment ends up being quite costly. In fact, 8/10 that go to therapy state that such expense is a great investment, yet 40% of those people admit to needing to seek financial support in order to be able to attend. `Due to this, many are forced to deal with their problems on their own.

Most common disorders diagnosed amongst younger children in 2020 would be anxiety (with 9.2% – around 5.6 million children) and depression with 4.0%- 2.4 million). The problem here is that many believe that anxiety is not as serious as depression, and as that may be somewhat true, it is still a disorder that limits children to live their life the way they wish they could.

To summarise, Maro was created as a solution to many people’s problems. Not to forget, Maro offers various information regarding many topics other than mental health, that being puberty, sex ed, diversity and respect etc. There’s an option for schools/teachers, parents and individuals. Yes, you do have to pay a small fee, but compared to the costs generated from going to a single therapy appointment, Maro is not only affordable for a lot more people but is also giving you, and the people around you the required education and tips on how to fight your troubles or generally live a better a life.

Do you wish you had Maro growing up? Or do you believe it will be a successful startup that will change people’s lives for the better?

Sources:

Research Update: Children’s Anxiety and Depression on the Rise

Maro’s new app looks to help schools screen kids for depression and anxiety

https://www.meetmaro.com

https://www.forbes.com/sites/afdhelaziz/2021/02/04/how-innovative-app-maro-is-helping-parents-have-those-difficult-conversations-with-their-kids/?sh=6b622f4d412d

27 November 2022
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Is it possible to diagnose Parkinson’s or COVID-19 based on the user’s voice?

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It is difficult to detect Parkinson’s disease or COVID-19 in the early stages of those illnesses. Therefore there is a solution to that problem. An app called Aum detects both of those diseases in the early stages.

Dinesh Kumar, a professor at the Royal Melbourne Institute of Technology, and his colleagues conducted an experiment to discover whether the subtleties in a person’s voice could be detected by machine-learning algorithms. Therefore they invited 36 people with Parkinson’s disease and 36 without it.

The participants had to say different phenomes, which required sounds from the throat (/a/), the mouth (/o/), and the nose (/m/). The researchers recorded that with the IOS system, and then they developed and applied the algorithms which could differentiate people with Parkinson’s disease and without it. In IEEE Access, the researchers reported that their algorithm could identify people with Parkinson’s disease with 100 per cent accuracy. Kumar also said that they could differentiate between people with Parkinson’s disease who take medication and who do not.

The researchers then applied a different machine-learning algorithm to the previous one. It turned out that the features extracted from the vowel /i/ during the first three days after admittance to the hospital were the most effective at differentiating between people with a COVID-19 infection of the lungs and healthy people. The algorithm was accurate at 94 per cent.

In my opinion, Aum is beneficial for us. With that app, we can detect in the early stages illnesses like Parkinson’s or COVID-19. Therefore we can prepare for the future by buying assistive devices for a person with Parkinson’s disease or adapting our house to that person. Moreover, those people can start taking medicines from the very beginning of their disease, which may help them to slow down the effects of that illness. When it comes to COVID-19, taking medication from the beginning of that illness can make them recover. However, if the app got a diagnosis wrong, it could end badly for that person. It could cause unnecessary expenses, stress or breakdowns leading to mental health problems. I think that we should not believe the app in 100 per cent, and the researchers should continue to develop it.

Thanks for your time. Feel free to comment below 🙂

References:

https://spectrum.ieee.org/parkinsons-disease-diagnosis

https://www.youtube.com/watch?v=stL3BSSgwp0

27 November 2022
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Will AI determine if we can end our lives? Will Everyone be capable of 3D-printing suicide pods for themselves?

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Recently debate about suicide Sarco pods came back to life. We still are not sure if our lives should be put in hands of AI. Certainly, it’s hard to imagine it deciding if we are allowed to die.

The Sarco pod also known as Pegasos and has been referred to as a “suicide pod” is a euthanasia device or machine consisting of a 3D-printed detachable capsule mounted on a stand that contains a canister of liquid nitrogen to die by suicide through inert gas asphyxiation. “Sarco” is short for “sarcophagus”. It is used in conjunction with inert gas nitrogen which decreases oxygen levels rapidly and prevents panic, a sense of suffocation and struggling before unconsciousness, known as the hypercapnic alarm response caused by the presence of high carbon dioxide concentrations in the blood. The Sarco was invented by euthanasia campaigner Philip Nitschke (Founder of Exit International a non-profit organisation advocating the legalisation of voluntary euthanasia and assisted suicide) in 2017.

The inventor thinks that the mainstream medical community has completely medicalized the end-of-life process while ignoring the many social, existential, or purely cognitive criteria related to it, which he argues are equally valid. That is why Nitschke and his team are creating an online interactive program that completely deletes the human aspect, thanks to its algorithm it will be able to evaluate if a certain person can get a “free pass” which is a ticket to use the death pod. The whole process will take less than 24 hours. He says his AI will assess a person’s eligibility for suicide using the guidelines suggested by a professor of law, health and ethics at the University of Sydney named Cameron Stewart, published in the Journal of Medical Ethics in 2011.

Interestingly, Nitschke says he’s been getting a tone of requests, from people who see “no future for the planet” due to all sorts of crises like a global warning and war in Ukraine. He considers them all equally respectable and answers that

“anyone who makes a rational decision to end their lives should have the best access to the best means necessary,”

The current pod costs around €25,000 to produce, a significant reduction in cost from the first version of Sarco, which came to over €150,000. But Nitschke’s aim is to reduce the price to zero and allow anyone anywhere to download the design and print it for themselves free of charge.

So, here we are thinking about the future. Will we accept the ideology of Philip Nitschke? Will we allow an AI to determine who is fit to choose their own way of death? Will we see people in the near future printing Sarco pods for themselves? Or maybe we will totally ignore Nitschke’s ideas? What do you think?

Sources:

27 November 2022
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The Biggest Cloud Security Challenges

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What is Cloud security?

Cloud security is a branch of cyber security that focuses on safeguarding cloud computing platforms. This involves maintaining data privacy and security across internet infrastructure, apps, and platforms. The efforts of cloud providers and the clients that utilize them, whether an individual, small to medium corporation, or enterprise, are required to secure these systems.

Cloud providers use always-on internet connections to host services on their servers. Because their firm relies on consumer confidence, they deploy cloud security solutions to keep client data private and secure. However, cloud security is also partially in the hands of the customer. Understanding these aspects is critical for a successful cloud security solution.

Why Cloud security is imortant?

Business and personal data resided locally in the 1990s, and security was also local. Data would be stored on your personal PC’s internal storage and on business servers if you worked for a firm.

The introduction of cloud technology has compelled everyone to rethink cyber security. Your data and apps may be bouncing between local and distant servers — but they’re always online. If you use Google Docs on your smartphone or Salesforce software to manage your clients, the data might be stored anywhere. As a result, safeguarding it becomes more complicated than before it was only a matter of preventing unauthorized individuals from accessing your network.

Cloud security necessitates certain changes to prior IT processes, however it has grown increasingly important for two reasons:

  • Convenience over security. Cloud computing is rapidly becoming a key technique for both business and personal use. Because of innovation, new technology is being introduced faster than industry security regulations can catch up, putting additional responsibility on users and providers to address accessibility concerns.
  • Centralization and multi-tenant storage. Every component, from fundamental infrastructure to minor data such as emails and documents, may now be discovered and accessed remotely via 24/7 web-based connections. All of this data collection on the computers of a few large service providers can be quite harmful. Threat actors may now target enormous multi-organizational data centers and trigger massive data breaches 

What are the biggest Cloud security challenges?

As risks have developed and more sophisticated new assaults have emerged, it is now more vital than ever for enterprises to adopt security-first mindsets. Having said that, here are some of the most pressing difficulties we face this year, as well as how cloud security solutions may assist your firm in overcoming them.

Data Breaches

Failure to handle data properly (through purposeful encryption) exposes your company to significant compliance concerns, not to mention data breach penalties, fines, and substantial breaches of consumer confidence. Regardless of what your Service-Level Agreement (SLA) states, it is your responsibility to secure your customers’ and employees’ data.

IT workers have traditionally had extensive control over network infrastructure and physical hardware (firewalls, etc.) used to protect proprietary data. Some of those security controls are abandoned to a trusted partner in the cloud (in all scenarios, including private cloud, public cloud, and hybrid cloud scenarios), implying that cloud infrastructure might raise security concerns. Choosing the proper vendor with a proven track record of deploying robust security measures is critical to overcome this difficulty.

Compliance With Regulatory Mandates

It’s typical for corporations, particularly small and medium-sized businesses, to believe that just cooperating with a cloud solutions provider provides them with optimum security. However, there is more to it than meets the eye.

The correct cloud security solutions give the technological capability to comply with regulatory demands, but constant supervision and detailed attention to detail are required. The cloud provider provides cloud security under the responsibility model, whereas the end user provides cloud security.

Data loss

It’s natural to be concerned about the security of business-critical data when it’s moved to the cloud. Losing cloud data, whether by inadvertent deletion and human mistake, criminal manipulation including malware installation (i.e. DDoS), or a natural disaster that shuts down a cloud service provider, may be fatal for commercial businesses. A DDoS assault is frequently only a distraction for a more serious danger, such as an effort to steal or erase data.

To address this difficulty, it is critical to have a disaster recovery plan in place, as well as an integrated system to combat hostile assaults.

What types of cloud security solutions are available?

Identity and access management (IAM)

Enterprises may utilize identity and access management (IAM) technologies and services to install policy-driven enforcement methods for all users seeking to access both on-premises and cloud-based services. IAM’s fundamental capability is to generate digital identities for all users, allowing them to be actively monitored and limited as needed throughout all data exchanges.

Data loss prevention (DLP)

DLP (data loss prevention) services provide a set of tools and services designed to safeguard the security of regulated cloud data. DLP systems secure all stored data, whether at rest or in motion, by combining remediation warnings, data encryption, and other preventative measures.

Security information and event management (SIEM)

Security information and event management (SIEM) is a complete security orchestration solution for cloud-based settings that automates threat monitoring, detection, and response. SIEM technology, which uses artificial intelligence (AI)-driven technologies to correlate log data across many platforms and digital assets, enables IT professionals to successfully deploy network security policies while responding fast to any possible threats.

Business continuity and disaster recovery

Data breaches and disruptive disruptions can occur regardless of the precautionary measures that enterprises put in place for their on-premise and cloud-based infrastructures. Enterprises must be able to respond swiftly to newly identified vulnerabilities or large system failures. Disaster recovery solutions are a must-have in cloud security because they offer enterprises the tools, services, and standards needed to fast data recovery and restart regular company operations.

The security risks and challenges associated with cloud computing are not insurmountable. Enterprises may reap the benefits of cloud technology with the correct cloud service provider (CSP), technology, and planning.

The CDNetworks cloud security solution combines web speed with cutting-edge cloud security technologies. With 160 points of presence, our customers’ cloud-based assets are safeguarded with 24/7 end-to-end protection, including DDoS mitigation at the network and application levels, and their websites and cloud applications are expedited on a worldwide scale.

Resources:

https://www.skyhighsecurity.com/en-us/cybersecurity-defined/what-is-cloud-security.html

https://www.ibm.com/topics/cloud-security

https://www.kaspersky.com/resource-center/definitions/what-is-cloud-security

https://www.startus-insights.com/innovators-guide/cybersecurity-trends-innovation/

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