#neural-network

#neural-network

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).

Several papers discussed the importance of segmenting time series into groups and modeling each group separately to enhance forecasting accuracy overall.But what does this look like in practice?At the end of the day, why not use an AutoML package (Automated Machine Learning) or an Auto-Forecasting tool and let it do the job for you?

"A robot may not injure a human being or, through inaction, allow a human being to come to harm."Turns out the Bing AI is bizarre and that is making quite the waves at the moment.In essence, the Bing version of ChatGPT has the capability of performing internet searches and as a result will feed some extra data into itself.

A new field of research dubbed "organoid intelligence" is emerging as scientists look to build computers from lumps of brain cells grown in a petri dish.These organoids are cultured from stem cells harvested from skin samples, and are tiny lumps of brain cells containing a jumble of neurons.

The right tools for a job can make all the difference, which is certainly the case in the tech space.Many developers refer to deep learning frameworks as building blocks because they simplify the training, validating, and designing stages.This blog looks at the top nine deep learning frameworks, showcasing their advantages and key features, and how Coding Dojo is the answer to learning data science and entering the field.

Geoffrey Hinton, who alongside two other so-called "Godfathers of AI" won the 2018 Turing Award for their foundational work that led to the current boom in artificial intelligence, now says a part of him regrets his life's work.Hinton recently quit his job at Google in order to speak freely about the risks of AI, according to an interview with the 75-year-old in The New York Times.

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.

TikTok is China's "Trojan horse," according to Rob Joyce, who heads the cyber security unit of America's National Security Agency.Joyce, speaking at the Silverado Policy Accelerator's conference on Monday, called TikTok "a strategic issue."This, as opposed to the type of tactical, day-to-day cyber threats the US spy agency wards off on the regular from nation-state actors and cyber crime gangs looking to make a buck (coin?) from business email compromise or ransomware infections.

In the second of our five-part series, I'm going to explain how the technology actually works.The artificial intelligences that powers ChatGPT, Microsoft's Bing chatbot and Google's Bard can carry out humanlike conversations and write natural, fluid prose on an endless variety of topics.They can also perform complex tasks, from writing code to planning a kid's birthday party.

Google is to make its chatbot technology available to the public in the coming weeks and months as it responds to the success of ChatGPT, a Microsoft-backed artificial intelligence chatbot that has become a global phenomenon after it was made available free of charge.Sundar Pichai, the chief executive of Google's owner, Alphabet, said the use of AI had reached an inflection point and the company was extremely well positioned in the field.

by William Kherbek // Dec. 20, 2022
In the flood of writing and pondering about the advance of artificial intelligence-enabled art, the word "uncanny" keeps popping up.Writers and artists frequently describe the warped, hyper-real/hyper-cursed images programs such as DALL-E and Midjourney produce as possessed of the kind of eerie life-but-not-life effects discussed in Sigmund Freud's 1919 essay 'The Uncanny.' Freud was building on an earlier essay by another German pioneer of psychology, Ernst Jentsch, whose 1906 essay, 'On the Psychology of the Uncanny,' potentially speaks more directly to the 'machinic uncanny' of AI than Freud.

The popularity of word salad prepared by large language models (LLMs) like OpenAI's ChatGPT, Google's Bard, and Meta's LLaMa has prompted academics to look for ways to detect machine-generated text.Sadly, existing detection schemes may not be much better than flipping a coin, raising the possibility that we're destined to ingest statistically composed copy as a consequence of online content consumption.

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.

Things are moving at lighting speed in AI Land.On Friday, a software developer named Georgi Gerganov created a tool called "llama.cpp"that can run Meta's new GPT-3-class AI large language model, LLaMA, locally on a Mac laptop.Soon thereafter, people worked out how to run LLaMA on Windows as well.

By the end of 2022, AI was in the spotlight, and like many people, I was skeptical and rigorous about how it could change us as humans.But all ofmy hesitation vanished when Chat GPT was launched.In just a few weeks, I saw how this AI chatbot could provide valid and valuable responses, and my perception of AI shifted utterly.

A.I. chatbots are not sentient beings that can think their own thoughts, despite what science fiction fans might imagine.But the similarities between those chatbots and a human brain are already quite disturbing.That's the central takeaway from my colleague Kevin Roose's recent two-hour chat with the artificial intelligence software being built into Bing, Microsoft's search engine.

By the end of 2022, AI was in the spotlight, and like many people, I was skeptical and rigorous about how it could change us as humans.But all ofmy hesitation vanished when Chat GPT was launched.In just a few weeks, I saw how this AI chatbot could provide valid and valuable responses, and my perception of AI shifted utterly.

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, Meta announced a new AI-powered large language model (LLM) called LLaMA-13B that it claims can outperform OpenAI's GPT-3 model despite being "10x smaller."Smaller-sized AI models could lead to running ChatGPT-style language assistants locally on devices such as PCs and smartphones.

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.

The movie industry could be revolutionized with the help of artificial intelligence (AI) software.Technology developed by Flawless, an AI filmmaking company, uses a neural network to recreate filmed scenes of an actor's face to match newly recorded dialogue."You can't tell what's real and what's not," says Flawless co-founder Scott Mann.

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.