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Category: robotics/AI – Page 1,424

The molecular implementation of a DNA-based artificial neural network

Molecular computing is a promising area of study aimed at using biological molecules to create programmable devices. This idea was first introduced in the mid-1990s and has since been realized by several computer scientists and physicists worldwide.

Researchers at East China Normal University and Shanghai Jiao Tong University have recently developed molecular convolutional (CNNs) based on synthetic DNA regulatory circuits. Their approach, introduced in a paper published in Nature Machine Intelligence, overcomes some of the challenges typically encountered when creating efficient artificial neural networks based on molecular components.

“The intersection of computer science and is a fertile ground for new and exciting science, especially the design of intelligent systems is a longstanding goal for scientists,” Hao Pei, one of the researchers who carried out the study, told TechXplore. “Compared to the brain, the scale and computing power of developed DNA neural networks are severely limited, due to the size limitations. The primary objective of our work was to scale up the computing power of DNA circuits by introducing a suitable model for DNA molecular systems.”

Will GPT-3 Win Oscar When it Starts Writing Movie Scripts Big Time?

Using GPT-3, Calamity AI developed a short film script called Date Night. GPT-3 is the third generation Generative Pre-trained Transformer, is a neural network ML model trained using internet data to generate any type of text. GPT-3 has been used to create articles, poetry, stories, news reports, and dialogue using just a small amount of input text that can be used to produce large amounts of quality content. Developed by OpenAI, it requires a small amount of input text to generate large volumes of relevant and sophisticated machine-generated text.

Enter Calamity AI, a pair of film students in California collaborating with an AI to write original short films and produce for YouTube. It aims to showcase the results of AI and humans working in tandem. The limitations of artificial intelligence restrict it from doing every element of the filmmaking process.

Medicine and the metaverse: New tech allows doctors to travel inside of your body

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The world of technology is rapidly shifting from flat media viewed in the third person to immersive media experienced in the first person. Recently dubbed “the metaverse,” this major transition in mainstream computing has ignited a new wave of excitement over the core technologies of virtual and augmented reality. But there is a third technology area known as telepresence that is often overlooked but will become an important part of the metaverse.

While virtual reality brings users into simulated worlds, telepresence (also called telerobotics) uses remote robots to bring users to distant places, giving them the ability to look around and perform complex tasks. This concept goes back to science fiction of the 1940s and a seminal short story by Robert A. Heinlein entitled Waldo. If we combine that concept with another classic sci-fi tale, Fantastic Voyage (1966), we can imagine tiny robotic vessels that go inside the body and swim around under the control of doctors who diagnose patients from the inside, and even perform surgical tasks.

Protein sequence design by deep learning

The design of protein sequences that can precisely fold into pre-specified 3D structures is a challenging task. A recently proposed deep-learning algorithm improves such designs when compared with traditional, physics-based protein design approaches.

ABACUS-R is trained on the task of predicting the AA at a given residue, using information about that residue’s backbone structure, and the backbone and AA of neighboring residues in space. To do this, ABACUS-R uses the Transformer neural network architecture6, which offers flexibility in representing and integrating information between different residues. Although these aspects are similar to a previous network2, ABACUS-R adds auxiliary training tasks, such as predicting secondary structures, solvent exposure and sidechain torsion angles. These outputs aren’t needed during design but help with training and increase sequence recovery by about 6%. To design a protein sequence, ABACUS-R uses an iterative ‘denoising’ process (Fig.

Tapping into the pulse of marketing with data visualization

Once datasets are cleaned, data visualization remodels them into intelligible graphics that put actionable insights on full display.

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Chances are you’ve heard the phrase “a picture is worth a thousand words.” What you may not know is that depending on the context, this can be somewhat of a misleading statement.

Hear us out. The human brain is hardwired to ingest images 60,000 times faster than text, accounting for 90% of the information we process every day being visual. These numbers make a convincing case as to why a picture deserves a little more credit than just a thousand words.