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Artificial Intelligence

Algorithm can paint like Van Gogh or other famous painter

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For a long time humans have been able to create artistic images, turning their visual experiences into paintings, using dozens of personal styles. Scientists have failed to make a computer or a robot learn how to paint, until now…

A team of German researchers from the University of Tubingen have created an algorithm that can turn visual experiences into paintings, by learning and using the painting styles of famous painters. This algorithm uses an artificial neural network of computers to accurately learn how to paint.

Artificial neural networks are statistical learning computers that use models inspired by biological neural networks, more precisely the human brain. These networks are designed to simulate how a network of neurons behave under a certain sensory input, like an image. This technology is used in hand and speech recognition, weather predictions or medical diagnosis.

The German researchers designed a deep learning algorithm that is able to understand the personal painting styles of world-renowned painters such as Vicent Van Gogh, J.M.Turner, Pablo Picasso or Edvard Munch. The computers are fed with images of the paintings and also a random photograph.

The algorithm teaches the computer to combine the photo with a certain image of a famous painting and then transforms that photo into an image that has the signature style of the painter. The algorithm is so smart that the background objects, or the layout remains the same, while the colors, technique and brush strokes of the painter are emulated into the overall picture.

The paintings used so far are Starry night by Van Gogh, The Scream by Munch, The Shipwreck of the Minotaur by Turner and Femme nue assise by Picasso. “The system uses neural representations to separate and recombine content and style of arbitrary images, providing a neural algorithm for the creation of artistic images”, said the researchers.

These findings can offer “a path forward to an algorithmic understanding of how humans create and perceive artistic imagery” emphasized the German scientists. The findings have been published in a paper entitled “A Neural Algorithm of Artistic Style” in the Cornell University Library depository.

 

Who doesn’t enjoy listening to a good story. Personally I love reading about the people who inspire me and what it took for them to achieve their success. As I am a bit of a self confessed tech geek I think there is no better way to discover these stories than by reading every day some articles or the newspaper . My bookcases are filled with good tech biographies, they remind me that anyone can be a success. So even if you come from an underprivileged part of society or you aren’t the smartest person in the room we all have a chance to reach the top. The same message shines in my beliefs. All it takes to succeed is a good idea, a little risk and a lot of hard work and any geek can become a success. VENI VIDI VICI .

Artificial Intelligence

The company pcTattletale, which develops spyware, has announced that it is ceasing operations and shutting down following a data breach

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The creator of the spyware application pcTattletale declared that his company is now defunct and permanently closed due to a recent data breach that occurred over the weekend.

The shutdown occurred shortly after a hacker vandalized the spyware manufacturer’s website and shared links containing substantial quantities of data from pcTattletale’s servers, including databases of customer information and some stolen data from victims.

pcTattletale was a covert surveillance application, commonly referred to as “stalkerware,” due to its capability to monitor individuals without their awareness. This app enabled the user to remotely access screenshots of the target’s Android or Windows device, as well as their confidential information, from any location worldwide. pcTattletale marketed its spyware application as a means to monitor employees while also openly endorsing its capability to surreptitiously observe spouses and domestic partners without their consent, which is a violation of the law.

According to the data breach notification site Have I Been Pwned, the app, which is no longer in operation, had a total of 138,000 customers who had registered to use the service.

The hacker claimed on the vandalized website that pcTattletale’s servers could be manipulated to disclose the private keys for its Amazon Web Services account. These keys were utilized by the spyware manufacturer to store a vast number of screenshots of the devices on which the spyware was installed.

pcTattletale’s website is currently inaccessible

Bryan Fleming, the founder of pcTattletale, informed me via text message on Tuesday that he no longer possesses the ability to access the Amazon Web Services account of the company.

Fleming stated that they deleted all data as a precautionary measure due to the potential risk of a data breach that could have compromised their customers’ information.

Fleming stated that the account has been closed and the servers have been deleted.

An examination of the compromised data reveals that pcTattletale stored over 300 million screenshots of victims’ devices on its Amazon S3 storage server, spanning several years. I verified that there were screenshots from pcTattletale-monitored devices available to the public.

Amazon appears to have taken measures against the manufacturer of spyware. The Amazon S3 storage server pcTattletale previously utilized for storing device screenshots now displays an error code, “AllAccessDisabled,” which is employed by Amazon to restrict all access to a customer’s account. This includes the customer themselves, who can only seek resolution by contacting Amazon for additional support. Nevertheless, Fleming refrained from providing an answer regarding whether AWS had terminated the service, and AWS spokesperson Grant Milne also declined to comment.

Fleming stated that he did not retain a duplicate of the data and did not provide an explanation for the company’s deletion of the data without prior notification to those individuals whose information was compromised in the data breach. He ceased to reply to our inquiries.

The situation at pcTattletale is not exceptional. Spyware applications are widely recognized for their inherent software flaws and are notorious for their tendency to inadvertently disclose or release data. Inadequate security practices have led federal regulators to prohibit stalkerware makers from participating in the surveillance industry in the past.

FTC spokesperson Juliana Gruenwald Henderson declined to provide any information regarding the agency’s investigation into pcTattletale.

Other manufacturers of spyware have ceased operations following comparable security breaches. The Polish-originated espionage software LetMeSpy was terminated in June 2023 due to a cyber attack that compromised its systems and resulted in the deletion of its clients’ data. Additionally, a state of New York investigation resulted in the shutdown of the spyware programs PhoneSpector and Highster.

 

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Artificial Intelligence

Apple’s Design Award nominees focus on small businesses and independent designers, but they mostly ignore AI (except for Arc)

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Apple is honoring indie apps and startups rather than larger tech companies, including those that provide AI chatbots, through its selection of finalists for the Apple Design Awards.

Amidst scrutiny from lawmakers and regulators regarding its App Store model, Apple is now focusing on recognizing smaller developers in its annual list of the most exceptional and technologically advanced software available on its platform. ChatGPT is notably absent from Apple’s list of finalists. Apple prioritizes small to midsize app developers such as Copilot Money, SmartGym, Crouton (a recipe app), Procreate Dreams (a creative app), Gentler Streak, and others. They also give preference to venture-backed startups like Rooms (a creativity app) and Arc Search (a reimagined web browser).

The latter app has integrated artificial intelligence (AI) with an agent that performs browsing tasks on your behalf. Additionally, it includes a new feature that allows you to ask questions by simply raising the phone to your ear and saying, “Call Arc.” Notably, this app is the only one on the list that explicitly mentions the technology that has gained significant attention and popularity in the App Store and the wider tech industry in the past year.

Despite achieving high download numbers since its launch last year, ChatGPT was not designated as the “app of the year” by either Apple or Google. The ADAs would have provided Apple with another chance to acknowledge the innovation, but once again, it was disregarded.

Apple’s selection of finalists includes indie games such as Rytmos from Floppy Club, a Copenhagen-based game developer; finity, a match-three puzzle game available on Apple Arcade; The Wreck from The Pixel Hunt, an independent game studio based in Paris; The Bear from Mucks Games, a group of creative individuals from Germany; and several others.

The non-game apps highlighted by Apple this year are primarily indie efforts. For instance, India-based independent developer RhythmicWorks Software created the meditation timer Meditate. A small group of independent developers from Italy under the direction of Nicholas Mariniello created Sunlitt, a sun-tracking app. Dudel Draw, a drawing app, is developed by indie outfit Silly Little Apps in the U.S. Isuru Wanasinghe, an Australian developer, created the journaling app Gratitude. Last but not least, ex-Googlers created and a16z backed Rooms, a creative app for designing imaginative spaces in an 8-bit style. Apple has nominated Rooms in two categories, making it doubly blessed.

However, there are indeed some prominent developers included in the list, such as Neowiz from South Korea, which has been nominated for its game “Lies of P”; 505 Games’ “Death Stranding Director’s Cut”; HoYoverse, the creator of “Genshin Impact,” for their game “Honkai: Star Rail”; and Activision’s “Call of Duty: Warzone Mobile.” However, when using Apple technologies like MetalFX or optimizations created especially for its M1 and superior chips (or perhaps incorporating in-app purchases! ), Apple’s decision is at least partially influenced.

Additional titles receiving recognition this year include What the Car?, NYT Games, Hello Kitty Island Adventure, Cityscapes: Sim Builder, How We Feel, Ahead: Emotions Coach, The Bear, Lost in Play, Wavelength, Little Nightmares, and a few select apps and games specifically designed for the Vision Pro, such as Blackbox, Loóna, Synth Riders, djay, NBA, and Sky Guide. Significantly, a number of these applications were initially developed for iOS and subsequently adapted for Vision Pro.

Additionally, the presence of an “Inclusivity” section enhances Apple’s worldwide app community, which includes individuals in the European Union (EU), where the Digital Markets Act is currently being implemented. Apple nominations in this section encompass a range of applications and games. These include the app “oko” from Belgium, designed specifically for low-vision users. Another notable nomination is “Complete Anatomy 2024” from Ireland, which focuses on diversity. Additionally, the app “Tiimo” from Denmark caters to neurodivergent users. The nominated games include “Unpacking” from the digital storefront Humble Bundle, “Quadline,” developed by Kovalov Ivan from Ukraine, and “Crayola Adventures.”

 

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Artificial Intelligence

AI models have preferences for certain numbers due to their ability to simulate human-like behavior

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AI models consistently astonish us, not just with their capabilities but also with their limitations and the reasons behind them. A noteworthy characteristic of these systems is that they select random numbers in a manner that resembles human behavior, albeit in a flawed manner.

However, first, what precisely does that signify? Is it not possible for individuals to select numbers in a random manner? And how can you determine if someone is accomplishing this task effectively or not? Humans possess a longstanding and widely recognized limitation: we tend to excessively analyze and misinterpret randomness.

Instruct an individual to forecast the outcome of 100 coin tosses and then contrast their predictions with the actual results of 100 coin tosses. It is typically possible to distinguish between the two sets of outcomes since, contrary to what one might expect, the actual coin tosses appear to exhibit a lesser degree of randomness. It is typical to see a string of six or seven consecutive heads or tails occurrences, which human predictors rarely include in their top 100 predictions.

Similarly, the situation remains unchanged when you want someone to select a number from the range of 0 to 100. Individuals rarely select the numbers 1 or 100. Numbers that are divisible by 5 are infrequent, as are numbers that have repeated digits such as 66 and 99. These selections do not appear to be random to us, as they possess certain qualities: tiny, large, and distinctive. Alternatively, we frequently select numbers that conclude with the digit 7, typically from a position in the center.

There are numerous instances of this type of predictability in psychology. However, the fact that AIs engage in the same behavior does not diminish its strangeness.

Indeed, a group of inquisitive engineers at Gramener conducted a casual yet captivating experiment in which they directly queried multiple prominent LLM chatbots to select a random number between the range of 0 to 100.

The outcomes were non-random, reader.

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Each of the three examined models exhibited a consistent “preferred” number that consistently emerged as their response when operating in the most deterministic mode. However, this number also occurred frequently even when the models were set to higher “temperatures,” which is a feature that enhances the diversity of their outcomes.

OpenAI’s GPT-3.5 Turbo has a strong preference for the number 47. In the past, it had a preference for the number 42, which gained popularity because to Douglas Adams’ novel, The Hitchhiker’s Guide to the Galaxy, where it was portrayed as the answer to the ultimate questions about life, the world, and everything.

The name of the product is “Anthropic’s Claude 3”. The number 42 was present with Haiku. Gemini has a preference for the number 72.

Significantly, all three models exhibited a bias similar to that of humans in the other numbers they chose, even when the temperature was high.

Everyone tended to avoid numbers that were either too low or too high. Claude, in particular, never exceeded 87 or fell below 27, and even those values were considered outliers. Numbers in the double digits, such as 33, 55, and 66, were deliberately avoided; however, a number ending in 7, namely 77, appeared. There are very few whole numbers, save for one instance when Gemini, at its maximum temperature, unexpectedly selected 0.

What is the reason for this? Artificial intelligences is not human. Why would they be concerned about something that appears to be random? Have they finally attained consciousness and is this their way of demonstrating it?

Negative. The solution, as is typically the situation with such matters, is that we are attributing human characteristics to something to an excessive extent. These models are indifferent to the distinction between what is and what is not random. They lack understanding of the concept of “randomness”. The question is answered using the same approach as for all other questions: by analyzing the training data and reproducing the most often written response following a question resembling “choose a random number.” The frequency of its appearance directly correlates with the frequency of repetition by the model.

In their training data, they would encounter the value of 100 in rare instances, as it is an infrequent response. From the perspective of the AI model, the answer of 100 is deemed unacceptable for that particular query. Lacking any cognitive capacity for reasoning and devoid of any comprehension of numerical concepts, it can only respond in a manner akin to that of a stochastic parrot. Likewise, they have shown a tendency to struggle with basic arithmetic tasks, like as multiplying a small set of numbers. This is because it is highly improbable that the specific calculation “112 multiplied by 894, then multiplied by 32 equals 3,204,096” is included in their training data. However, more recent models will detect the presence of a mathematical problem and transfer it to a subroutine.

This serves as a perfect example of LLM habits and the seeming display of humanity they can exhibit. It is important to remember that these systems have been trained to mimic human behavior, even if that was not the original purpose. Hence, the evasion or prevention of pseudanthropy is exceedingly challenging.

In the headline, I stated that these models possess the belief that they are human beings, yet that statement is somewhat deceptive. As we frequently emphasize, they lack the ability to reason. However, in their replies, they consistently mimic individuals without any requirement for knowledge or cognitive processing. Regardless of whether you’re seeking a recipe for chickpea salad, investment guidance, or a random number, the procedure remains unchanged. The results possess a human quality because they originate from human-generated information and are subsequently modified—for your convenience as well as to benefit the significant financial interests of artificial intelligence.

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