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How These AI-Powered Chatbots Keep Getting Better
Artificial Intelligence is advancing faster than ever, with a new crop of generative AI programs that are creating art, videos, humor, fake news, and plenty of controversy. The technologies powering this latest slate of tools have been in the works for years, but the public release of these programs—particularly a new chatbot enabled by OpenAI’s GPT system—represents a big step forward for machine intelligence.
Large language models help decipher clinical notes
Electronic health records (EHRs) need a new public relations manager. Ten years ago, the U.S. government passed a law that strongly encouraged the adoption of electronic health records with the intent of improving and streamlining care. The enormous amount of information in these now-digital records could be used to answer very specific questions beyond the scope of clinical trials.
A simpler path to better computer vision
Before a machine-learning model can complete a task, such as identifying cancer in medical images, the model must be trained. Training image classification models typically involves showing the model millions of example images gathered into a massive dataset. However, using real image data can raise practical and ethical concerns: The images could run afoul of copyright laws, violate people’s privacy, or be biased against a certain racial or ethnic group
A far-sighted approach to machine learning
Picture two teams squaring off on a football field. The players can cooperate to achieve an objective and compete against other players with conflicting interests. That’s how the game works.
Creating artificial intelligence agents that can learn to compete and cooperate as effectively as humans remains a thorny problem. A key challenge is enabling AI agents to anticipate future behaviors of other agents when they are all learning simultaneously.
ChatGPT’s Most Charming Trick Is Also Its Biggest Flaw
Reddy, CEO of Abacus.AI, which develops tools for coders who use artificial intelligence, was charmed by ChatGPT’s ability to answer requests for definitions of love or creative new cocktail recipes. Her company is already exploring how to use ChatGPT to help write technical documents. “We have tested it, and it works great,” she says.
NASA researcher's AI 'eye' could help robotic data-gathering.
When it comes to making real-time decisions about unfamiliar data—say, choosing a path to hike up a mountain you've never scaled before—existing artificial intelligence and machine learning tech doesn't come close to measuring up to human skill. That's why NASA scientist John Moisan is developing an AI "eye."
Tutorial on Simple ML for sheets
With Simple ML for Sheets, also referred to as Simple ML, everyone can use Machine Learning (ML) in Google Sheets without knowing ML, without coding, and without sharing data with third parties. This tutorial takes you through the steps of using Simple ML for Sheets to solve three exercises: Predicting missing values (task 1), identifying abnormal values (task 2), and training / evaluating & understanding a model manually (task 3).
Adobe to begin selling AI-generated stock images.
In October, Shutterstock announced that it was expanding its partnership with DALL-E creator OpenAI. As part of the expanded partnership, Shutterstock will offer DALL-E images to customers. Generative AI tools have raised concerns about their potential use for things like scams and misinformation. Due to such concerns, OpenAI delayed making its tool publicly available until it was able to implement safeguards designed to prevent or mitigate such risks.
Artificial Intelligence will be the Central Theme to Transform Communication and Businesses.
This research study assesses the evolution of the connected intelligence era with the transition from 5G to 6G. Mobile communications and networks have been evolving every decade. With the launch of 5G in 2022, governments and companies have started investing in the research and development of 6G. Although the launch of the platform technology is expected by 2030, those working on 6G have drawn a clear roadmap for its development.
An AI app that can spot deepfake videos of famous people.
A pair of researchers, one with Gymnasium of Johannes Kepler, the other with the University of California, Berkley, has developed an artificial intelligence (AI) application capable of determining whether a video clip of a famous person is genuine or a deepfake. In their paper published in Proceedings of the National Academy of Sciences, Matyáš Boháček and Hany Farid describe training their AI system to recognize unique body movements of certain individuals to discern whether a video was real or not.
Soft robot detects damage, heals itself.
Our lab is always trying to make robots more enduring and agile, so they operate longer with more capabilities," said Rob Shepherd, associate professor of mechanical and aerospace engineering. "If you make robots operate for a long time, they're going to accumulate damage. And so how can we allow them to repair or deal with that damage?" For self-healing to work, Shepard says the key first step is that the robot must be able to identify that there is, in fact, something that needs to be fixed.
Artificial neural networks learn better when they spend time not learning at all.
The brain is very busy when we sleep, repeating what we have learned during the day," said Maxim Bazhenov, PhD, professor of medicine and a sleep researcher at University of California San Diego School of Medicine. "Sleep helps reorganize memories and presents them in the most efficient way." Artificial neural networks leverage the architecture of the human brain to improve numerous technologies and systems, from basic science and medicine to finance and social media.
Watch the Top 8 New Features in Microsoft Excel.
Global Natural Language Processing (NLP) Market Share, Size and Forecast till 2028
Natural Language Processing (NLP) market size is estimated to be worth USD 867.4 million in 2021 and is forecast to a readjusted size of USD 2972.1 million by 2028 with a CAGR of 19.2% during review period. The research report on the Global "Natural Language Processing (NLP) Market" includes an in-depth study of the present market environment and estimates. The study is an exceptional combination of qualitative and quantitative data, highlighting key market developments, challenges, industry assessments, and new opportunities and trends in the Natural Language Processing (NLP) Market.