Do you agree Eric Klein?
The billionaire engineer, who also helped found the artificial intelligence research lab OpenAI in 2015, has consistently warned of the existential threat posed by advanced artificial intelligence in recent years. Despite this, he said he still feels that the issue is not properly understood.
There have been many landmarks in the history of artificial intelligence, from the formulation of the mathematical theory that inspired neural networks back in 1943, to IBM’s famous Watson AI beating two champion Jeopardy! contestants in 2011 to win a million dollar prize.
Future historians may look back at 2020 as a similarly important checkpoint on the road to AI dominance. Why? Because YouTuber Funk Turkey has created a new Led Zeppelin song using the power of AI.
Handling imbalanced datasets in machine learning is a difficult challenge, and can include topics such as payment fraud, diagnosing cancer or disease, and even cyber security attacks. What all of these have in…
Who knows what the future will bring? Well, Alan Couzens just might. In this article, he takes a look at current uses of artificial intelligence in sports and tells us where AI technology is headed and how it will help coaches in the next 10 years.
A study published today (July 27, 2020) in The Lancet Digital Health by UPMC and University of Pittsburgh researchers demonstrates the highest accuracy to date in recognizing and characterizing prostate cancer using an artificial intelligence (AI) program.
“Humans are good at recognizing anomalies, but they have their own biases or past experience,” said senior author Rajiv Dhir, M.D., M.B.A., chief pathologist and vice chair of pathology at UPMC Shadyside and professor of biomedical informatics at Pitt. “Machines are detached from the whole story. There’s definitely an element of standardizing care.”
To train the AI to recognize prostate cancer, Dhir and his colleagues provided images from more than a million parts of stained tissue slides taken from patient biopsies. Each image was labeled by expert pathologists to teach the AI how to discriminate between healthy and abnormal tissue. The algorithm was then tested on a separate set of 1,600 slides taken from 100 consecutive patients seen at UPMC for suspected prostate cancer.
As the world edges closer towards exascale computing, the University of Florida has announced a partnership with chipmaker NVIDIA that aims to create a 700-petaflop AI supercomputer next year.
So, you’ve seen some amazing GPT-3 demos on Twitter (if not, where have you been?). This mega machine learning model, created by OpenAI, can write it’s own op-eds, poems, articles, and even working code:
If you want to try out GPT-3 today, you’ll need to apply to be whitelisted by OpenAI. But the applications of this model seem endless – you could ostensibly use it to query a SQL database in plain English, automatically comment code, automatically generate code, write trendy article headlines, write viral Tweets, and a whole lot more.
StartX startup Buzz Solutions out of Stanford, California just introduced its AI solution to help utilities quickly spot powerline and grid faults so repairs can be made before wildfires start.
Their unique platform uses AI and machine vision technology to analyze millions of images of powerlines and towers from drones, helicopters, and aircraft to find dangerous faults and flaws as well as overgrown vegetation, in and around the grid infrastructure to help utilities identify problem areas and repair them before a fire starts.
This system can do the analysis at half the cost and in a fraction of the time compared to humans, hours to days not months to years.
“‘Aurora will enable us to explore new frontiers in artificial intelligence and machine learning,’ said Narayanan ‘Bobby’ Kasthuri, assistant professor of neurobiology at the University of Chicago and researcher at Argonne. ‘This will be the first time scientists have had a machine powerful enough to match the kind of computations the brain can do.’”
Super computer Aurora will help map the human brain at “quintillion—or one billion billion—calculations per second, 50 times quicker than today’s most powerful supercomputers.”
Note: the article discusses implications beyond neuroscience.
Argonne, DOE and Intel announce exascale computer built for next-generation AI and machine learning.
In a new paper, DeepMind describes an AI algorithm that was able to discover a critical programming rule in deep reinforcement learning from scratch.
