#neural-networks

#neural-networks

Bard is Google's artificial intelligence chatbot which generates responses to user-provided natural language prompts.In response to a prompt, Bard can pull information from the internet and present a response.The large language model behind Bard delivers the response in natural language - in contrast to a standard Google search, where a result consists of a snippet of information or a list of links.

The worst thing about this hyperspeed artificial intelligence race is that, even if you are used to expecting the unexpected, the bloody thing keeps surprising you by opening new cans of worms every other day.And this weekly roundup has truck-size cans overflowing with worms the size of elephant trunks among the release of Stability.ai's

Designed to help you identify the sessions that best fit your interests and learning goals, the ODSC Europe 2023 tracks highlight the data science and AI fields that are helping to build the future.You'll learn about the latest research, topics, and tools from the leading experts in their respective fields.

Fandom Fracas
Writers are threatening to pull their stories from Archive of Our Own (AO3), one of the world's largest fanfiction websites, after staff posted that they will not prohibit the publication of artificial intelligence-generated fanfiction on the website.Typifying the anger, one Twitter user wrote that they "would rather have one hundred thousand unreadably bad human-written fics added to AO3 every day than one AI fic."

On Tuesday, OpenAI published a new research paper detailing a technique that uses its GPT-4 language model to write explanations for the behavior of neurons in its older GPT-2 model, albeit imperfectly.It's a step forward for "interpretability," which is a field of AI that seeks to explain why neural networks create the outputs they do.

UI/UX design should be easy to use.This is the first and still golden rule of the UI/UX design solutions since everything gets started from the user experience and is being built in order to be comfortable and intuitive.However, it can be a tricky task and most UI/UX designers know it for sure since user groups differ a lot: in terms of age, nationality and gender.

Welcome to On Tech: A.I., a pop-up newsletter that will teach you about artificial intelligence, especially the new breed of chatbots like ChatGPT all in only five days.We'll tackle some of the big themes and questions around A.I.By the end of the week, you'll know enough to command the room at a dinner party, or impress your co-workers.

We've compiled a list of phrases and concepts useful to understanding artificial intelligence, in particular the new breed of A.I.-enabled chatbots like ChatGPT, Bing and Bard.If you don't understand these explanations, or would like to learn more, you might want to consider asking the chatbots themselves.

What if an AI could interpret your imagination, turning images in your mind's eye into reality?While that sounds like a detail in a cyberpunk novel, researchers have now accomplished exactly this, according to a recently-published paper.Researchers found that they could reconstruct high-resolution and highly accurate images from brain activity by using the popular Stable Diffusion image generation model, as outlined in a paper published in December.

A new player is ready as a bot from OpenAI has watched 70,000 hours of players on Minecraft and is ready to game.According to a report from the MIT Technology Review, a bot was trained on tens of thousands of hours of players playing the popular sandbox title.Now it's able to complete complex actions, such as crafting in-game diamond tools - a task that would take well-versed human players at least twenty minutes.

A-level computer science students are still learning about floppy disks, but not artificial intelligence (AI), Parliament was told.Labour peer Lord Knight of Weymouth, chief education adviser at TES Global Ltd, a digital education company, told peers he met an A-level student at the weekend who revealed this.

Training Day
OpenAI's finances are all over the place, but one thing is clear - not much of the money it spends or earns is going to the low-wage contract workers hired to train its AI.Two OpenAI contractors revealed to NBC News that the kind of work that goes into training large language models (LLMs) like those behind ChatGPT is very much "grunt work" - though in the case of these two individuals, they're pretty happy to be doing it.

The man once described as the father of artificial intelligence is breaking ranks with many of his contemporaries who are fearful of the AI arms race, saying what is coming is inevitable and we should learn to embrace it.Prof Jurgen Schmidhuber's work on neural networks in the 1990s was developed into language-processing models that went on to be used in technologies such as Google Translate and Apple's Siri.

The famous first image of a black hole just got two times sharper.A research team used artificial intelligence to dramatically improve upon its first image from 2019, which now shows the black hole at the center of the M87 galaxy as darker and bigger than the first image depicted.I'm an astronomer who studies and has written about cosmology, black holes, and exoplanets.

Geoffrey Hinton has left Google, joining the chorus of industry leaders warning against the race to deploy new AI models

Amidst the boom in generative tech, sentiments around AI are rapidly shifting.After OpenAI released a new version of ChatGPT in March, over a thousand leading experts in the field-including the likes of Elon Musk-signed an open letter calling for a six-month halt on further development, citing "profound risks to society and humanity."

TechnologyUnited States of America 48 minutes ago48 minutes ago Geoffrey Hinton told the NYT scientists should make sure they are in control of AI before they expand it further.The AI pioneer warned of the technology's ability to create convincing hoaxes.Artificial intelligence pioneer Geoffrey Hinton, often dubbed the "godfather of AI," has quit Google, as he attempts to shed more light on what he says are the many dangers of the technology, free of any employment restrictions.

According to The New York Times, AI pioneer Dr. Geoffrey Hinton has resigned from Google so he can "speak freely" about potential risks posed by AI.Hinton, who helped create some of the fundamental technology behind today's generative AI systems, fears that the tech industry's drive to develop AI products could result in dangerous consequences-from misinformation to job loss or even a threat to humanity.

To help illustrate our cover story on how the AI arms race is changing the world, we reached out to award-winning AI artist Pindar Van Arman, who uses artificial intelligence to create his art.Van Arman, who built his first painting robot 15 years ago, uses deep learning neural networks, artificial intelligence, feedback loops, and computational creativity to guide his newer robots.

Have you ever wondered what people listen to when undergoing MDMA-assisted therapy?I'm guessing you probably haven't.If you have, then wow what an inquisitive mind you have.But maybe you aren't even aware how MDMA-trials work.I'll tell you.A short while ago, VICE interviewed Petra Skeffington, an Associate Professor of Psychology at Perth's Murdoch University, who's currently one of the researchers behind Australia's first MDMA-Assisted therapy trial.

Massachusetts Institute of Technology researchers determined that the brain's demand and language systems encode specific code properties that correlate with machine-learned representations.The researchers performed functional magnetic resonance imaging (fMRI) scans of programmers' brains as they processed computer program elements and saw a difference in encoding properties related to dynamic analysis, in which information is encoded much better in the brain's multiple demand network compared to the language processing center.

Editor's note: Chakri Cherukuri is a speaker for ODSC Europe 2023 this June.Be sure to check out his talk, "Fast Option Pricing Using Deep Learning Methods," there!In finance, options are financial instruments that give the holder the right to buy ( Call option) or sell ( Put option) the underlying asset (price S) at a fixed price (Strike K) on (or before) a fixed date (Maturity T).

The core of an artificial intelligence program like ChatGPT is something called a large language model: an algorithm that mimics the form of written language.While the inner workings of these algorithms are notoriously difficult to decipher, the basic idea behind them is surprisingly simple.They are trained on mountains of internet text, by going through them a few sentences or paragraphs at a time, repeatedly guessing the next word (or word fragment) and then grading themselves against the real thing.

Drip God
Did they fool you?Those mega-viral images of Pope Francis looking fresh to death in a pristine white puffer are AI-generated fakes.As Snopes reports, that pic of Il Papa that went viral over the weekend is, as lots of people suspected, a fake - and, as always, the debunking site has the receipts to prove it.

IGphotography via Getty Images  Last year, MIT developed an AI/ML algorithm capable of learning and adapting to new information while on the job, not just during its initial training phase.These "liquid" neural networks (in the sense) literally play 4D chess - their models requiring time-series data to operate - which makes them ideal for use in time-sensitive tasks like pacemaker monitoring, weather forecasting, investment forecasting, or autonomous vehicle navigation.

The success of ChatGPT and its competitors is based on what's termed emergent behaviors.These systems, called large language models (LLMs), weren't trained to output natural-sounding language (or effective malware); they were simply tasked with tracking the statistics of word usage.But, given a large enough training set of language samples and a sufficiently complex neural network, their training resulted in an internal representation that "understood" English usage and a large compendium of facts.

Artificial intelligence researchers have celebrated a string of successes with neural networks, computer programs that roughly mimic how our brains are organized.But despite rapid progress, neural networks remain relatively inflexible, with little ability to change on the fly or adjust to unfamiliar circumstances.

A brain-imitating neural network that employs photons instead of electrons could rapidly analyze vast amounts of data by running many computations simultaneously using thousands of wavelengths of light, a new study finds.Artificial neural networks are increasingly finding use in applications such as analyzing medical scans and supporting autonomous vehicles.

On Friday, researchers from Nvidia announced Magic3D, an AI model that can generate 3D models from text descriptions.After entering a prompt such as, "A blue poison-dart frog sitting on a water lily," Magic3D generates a 3D mesh model, complete with colored texture, in about 40 minutes.With modifications, the resulting model can be used in video games or CGI art scenes.

On Monday, Cerebras Systems unveiled its 13.5 million core Andromeda AI supercomputer for deep learning, reports Reuters.According Cerebras, Andromeda delivers over one 1 exaflop (1 quintillion operations per second) of AI computational power at 16-bit half precision.The Andromeda is itself a cluster of 16 Cerebras C-2 computers linked together.

Deep neural networks are susceptible to adversarial perturbations of their input data that can cause a sample to be incorrectly classified.These perturbations contain small variations in the pixel space that cannot be detected by a human but can change the output of a classifier.Reliably detecting attacks in a given set of inputs is of high practical relevance due to the vulnerability of neural networks to adversarial examples.

Deep Learning today is a powerful and widely used tool for Artificial Intelligence and machine learning.Compared to traditional neural networks, deep learning can more effectively model complex patterns in data.This is due to its ability to learn multiple levels of representation, from low-level features to high-level concepts.

Neural Nets sound sexy and interesting.But what are they exactly?How do they achieve their magic and most importantly, can you build one without being an expert data scientist?In this article I'm going to show you the basics of neural networks and how you can implement one yourself using existing tools.

Art created using artificial intelligence (AI) is burgeoning.From commercial gallery shows-including Jon Rafman's large-scale, algorithmically generated paintings at Sprüth Magers in London ( Ebrah k'dabri, until 25 March)-to the PATH-AI artist residency organised in collaboration with London's Somerset House, AI-related art projects are springing up everywhere.

If you've scrolled through TikTok over the past week, you've probably seen a video that goes something like this: a woman looks amazed as she stares at her face in the camera.She touches her lips, her eyelids, her cheeks, as if questioning that the parts of her face could actually be real."It's not me at all," one user said.

(Image credit: University of Chicago)
With the latest generation of AI art generators riding roughshod over intellectual property rights, it was about time that someone created a tool that can protect artists' work.Sure enough, researchers have now developed a program that aims to prevent artists' styles from being copied.

Microsoft released a new version of its Bing search engine last week, and unlike an ordinary search engine it includes a chatbot that can answer questions in clear, concise prose.Since then, people have noticed that some of what the Bing chatbot generates is inaccurate, misleading and downright weird, prompting fears that it has become sentient, or aware of the world around it.

Deep learning is one of the most crucial tools for analyzing massive amounts of data.It informs decision-making in every sector, adapting to accuracy the more humans feed it with knowledge.However, there is such a prospect as too much information, as deep learning's job is to find patterns and connections between data points to inform humanity's questions and affirm assertions.

In 1923, an editorial cartoonist named H.T. Webster drew a humorous cartoon for the New York World newspaper depicting a fictional 2023 machine that would generate ideas and draw them as cartoons automatically.It presaged recent advancements in AI image synthesis, one century later, that actually can create artwork automatically.

Researchers from Los Alamos National Laboratory are working on a way to help artificial intelligence researchers comprehend neural network behavior.In doing so, they found an interesting surprise.As neural networks are being employed in more fields, understanding how and why they operate is going to become more important, especially with tools such as facial recognition, and autonomous cars, becoming more prevalent in society.

Over the past year, AI generated images have skyrocketed in popularity, even featuring on magazine covers and winning art competitions, thanks to an onslaught of new generators that can come up with new pieces of art for free or a small fee.Lensa, a new AI-powered image generating app can whip up stylized portraits from ten to 20 input images that a user uploads of themselves or somebody else, has reignited a heated debate over whether human artists are being unfairly ripped off by having their work remixed without permission.

In brief OpenAI has released a new language model named ChatGPT this week, which is designed to mimic human conversations.The model is based on the company's latest text-generation GPT-3.5 system released earlier this year.ChatGPT is more conversational than previous versions.It can ask users follow-up questions and refrain from responding to inappropriate inputs instead of just generating text.

Disney   researchers have an artificial intelligence system that seemingly makes it far easier to make an actor appear younger or older in a scene.While artists will still be able to make manual adjustments to make sure the effect looks as realistic as possible, the AI tool could take care of most of the heavy lifting.

When British director Scott Mann's latest film, Fall, was on the precipice of receiving an "R" rating from the MPAA over the number of "F" bombs dropped over its one hour and 47-minute run time, he did what any reasonable person would: he used artificial intelligence to digitally alter the actor's performances in order to change the swear words into more palatable terms.

How to Find Duplicates (and Near-Duplicates) in a Corpus with NLP In this article, we'll call the profileText action, pull down output tables, and perform duplicate identification in Python.Understanding Your Neural Network's Predictions Use this concise guide to assess your neural network's feature importance.

Utilizing neural networks in spatial data analysis
Earth Sciences need to process, often in real-time, datasets of complex internal structure, various resolutions, a multitude of formats, and significant volume.Spatial data may originate from observations made during field research, aerial and satellite imaging, wearable sensors, and more.

Every neural network needs at least one activation function to make accurate predictions.It's at the heart of the processing capabilities.Choosing the right one can result in a precise, high-performance network consistently delivering the desired results.Data scientists can use an easy process to determine what activation function is the right fit for their systems.

In the world of deep-learning AI, the ancient board game Go looms large.Until 2016, the best human Go player could still defeat the strongest Go-playing AI.That changed with DeepMind's AlphaGo, which used deep-learning neural networks to teach itself the game at a level humans cannot match.More recently, KataGo has become popular as an open source Go-playing AI that can beat top-ranking human Go players.

Self-esteem is a lot like Ikea furniture - few parents know how to build it correctly, and a lot of kids risk getting hurt because of it.Scientists suspect that the key to developing self-esteem is starting early, when children are young and their brains are still developing.This is part of the reason that low self-esteem seems to run in the family.