Deep learning is a type of machine learning based on artificial neural networks inspired by the human brain. The method is used to teach machines how to learn from large amounts of data through multi-layered structures of algorithms.

Deepfakes typically use a computer learning network called a variational autoencoder, a type of artificial neural network that is commonly used for face recognition.

 

Deepfake technology resembles the 21st century version of Photoshop,but is far more dangerous. It carries many negative implications as it continues to advance the field of artificial intelligence. Deepfake is often controlled by a group of cybercriminals who have the ability to convincingly mimic other humans. Additionally, this platform is used to create numerous manipulated videos that look very real.

In a recent incident, a group of cyber criminals created a fake video with the face of Rashmika Mandan, a South Indian actress, and the body of Zara Patel, a British-Indian girl. This video caused a wave of reactions in the Bollywood community.

When was it first discovered, and what did it do?

Deepfake technology first surfaced in 2017 on the online platform Reddit. Initially, it gained notoriety for swapping the faces of celebrities such as Gal Gadot, Scarlett Johansson, Taylor Swift, and others, primarily for creating explicit content. This face-swapping was accomplished through the use of a machine employing deep learning algorithms. One key element in this process was an AI algorithm known as an “encoder.”

What is an encoder?

An “encoder” serves as a crucial component in the deepfake process. It enables machines to discern commonalities between two faces, reducing them to their shared features by compressing the facial images.

With the aid of an encoder, erroneous images are superimposed to manipulate the source content, while another algorithm, called the “decoder,” reconstructs the face with the desired orientation and expressions.

What does Deepfake technology do to original videos and photos?

Deepfake technology adeptly alters and manipulates the voices and faces of characters within various videos, frequently with explicit content.

Deepfake usage?

Primarily, deepfake technology finds application in unsavory edits, notably within pornographic video content. However, there have been instances, especially during elections, where politicians’ video clips were digitally altered and disseminated with falsely attributed statements.

Prominently, even well-known individuals with significant public profiles have fallen victim to deepfake videos. An example includes former US President Barack Obama, who was featured in a deepfake video where he appeared to refer to Donald Trump as a derogatory term. This video garnered widespread attention.

Furthermore, even Mark Zuckerberg, Meta’s chief, was depicted in various deepfake videos making claims about having “total control of billions of people’s stolen data.”

An AI firm named Deeptrace was also identified, which had cataloged 15,000 deepfake videos by September 2019.

What do experts have to say about deepfake creators?

Experts, including Danielle Citron, a professor of law at Boston University, have voiced serious concerns about the detrimental uses of deepfake technology. Citron highlighted the fact that deepfake technology has been weaponized against women, and recent incidents like the one involving actress Rashmika raise further safety concerns.

What else can deepfake do besides creating videos?

Deepfake technology extends beyond crafting AI-driven videos. It can also generate entirely fabricated images from scratch. Additionally, it has the capacity to create fictitious profiles and characters, complete with fictional names and accompanying videos.

Who is creating deepfake videos presently?

According to a report from The Guardian, a wide range of individuals, from industrial and academic researchers to amateur enthusiasts, can create deepfake videos. Visual effects studios and even porn producers also harness this technology for the manipulation and creation of content.

The FTC has already filed suit to block the $68.7 billion acquisition, opting to file a lawsuit before a domestic administrative judge. Through this trial-like process, the judge will make an initial decision that can be appealed to the full commission for a vote. Microsoft can then appeal to federal court if the decision is not in its favor. The case is due to be heard by an administrative judge in August.

“We welcome the opportunity to present our case in federal court. We believe expediting the legal process in the U.S. will ultimately lead to more choice and competition in the marketplace.”

said Microsoft President Brad Smith.

An appeal against the UK Competition and Markets Authority’s decision to block the merger is also planned for this summer, shortly after the acquisition deadline.

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According to Google, this update has increased the accuracy of calculation-based word and math problems in their internal challenge datasets by 30%.

The tech giant claims that Bard should be able to provide information such as simple odds of numbers in the millions, the rate of increase in savings, and what words like “lollipop” look like in reverse (this is the strongest weapon the tool has against the competition).

Google also announced a feature that allows the data Bard produces to be edited and manipulated in Sheets. This is the perfect update for people who hate spreadsheets.

The startup announced $26 million in funding, which includes a previously unannounced $5 million seed round and a newer $21 million Series A. At the same time, DevZero also announced the general availability of its cloud development platform.

The company’s co-founder and CEO Debo Ray says his goal is to make the development process easier for engineers while allowing them to freely choose the tools they will use.

“When a developer wants to do work, whatever they want to do, how can I give them an environment to actively code and test where they can immediately just get to build it, focusing only on the revenue generating parts of the business and letting DevZero take care of the underlying developer infrastructure,”

Ray told TechCrunch.

According to him, most of the developers’ work is done on laptops, and compiling in particular can be time-consuming when the developer’s machine is engaged for large chunks of time. By moving the development environment to the cloud, more resources are made available for the build process, allowing developers to get back to work faster.

Today, the startup has 21 employees and is hiring new ones in the meantime. For Ray, building a diverse organization is important and he believes it will ultimately lead to a better product.