Billionaire investor and former Facebook exec Chamath Palihapitiya thinks AI will radically change the job of the venture capitalist.
In a Friday episode of the “All-In Podcast,” hosted by Palihapitiya, Jason Calacanis, David Sacks, and David Friedberg, the investor said there was a “reasonable case to make” that the VC job could even cease to exist.
He said that changes to the industry sparked by AI could lead to VCs being replaced by “an automated system of capital against objectives.”
An AI that can identify the patients most at risk of pancreatic cancer could lead to earlier detection of the deadly disease, which currently kills 88% of patients within 5 years of diagnosis.
The challenge: People with pancreatic cancer typically don’t experience any symptoms until a tumor is large or the cancer has spread to other organs. As a result, most aren’t diagnosed until their cancer is advanced and much harder to treat.
Screening people without symptoms for pancreatic cancer could lead to earlier detection, but the only tests for it are expensive or invasive. As a result, they’re reserved for the few people doctors believe are at high risk of pancreatic cancer, due to a family history of the disease, for example.
“A lot of the technologies employed offshore now are the same technologies that have been there for the last 40 or 50 years,” says Mayall.
Turning to artificial intelligence and smart tech to overhaul maritime safety, his company Zelim is working on a trio of life-saving technologies — including an autonomous, unmanned lifeboat called “Guardian.”
The Scottish startup, which Mayall founded in 2017 when he was just 22 years old, is now working with the US Coastguard and several offshore energy companies to perfect its tech, which Mayall hopes can make rescues quicker for the victims and safer for the rescuers.
Induce lucid dreams on demand to unravel the mystery of consciousness.
The combination of ultrasound and machine learning models (created using EEG & fMRI data) allows us to detect when dreamers are in REM to induce and stabilize lucid dreams.
“Dinkinesh really did live up to its name; this is marvelous,” said Hal Levison, referring to the meaning of Dinkinesh in the Amharic language, “marvelous.” Levison is principal investigator for Lucy from the Boulder, Colorado, branch of the San-Antonio-based Southwest Research Institute. “When Lucy was originally selected for flight, we planned to fly by seven asteroids. With the addition of Dinkinesh, two Trojan moons, and now this satellite, we’ve turned it up to 11.”
In the weeks prior to the spacecraft’s encounter with Dinkinesh, the Lucy team had wondered if Dinkinesh might be a binary system, given how Lucy’s instruments were seeing the asteroid’s brightness changing with time. The first images from the encounter removed all doubt. Dinkinesh is a close binary. From a preliminary analysis of the first available images, the team estimates that the larger body is approximately 0.5 miles (790 m) at its widest, while the smaller is about 0.15 miles (220 m) in size.
This encounter primarily served as an in-flight test of the spacecraft, specifically focusing on testing the system that allows Lucy to autonomously track an asteroid as it flies past at 10,000 mph, referred to as the terminal tracking system.
Hussam Amrouch has developed an AI-ready architecture that is twice as powerful as comparable in-memory computing approaches. As reported in the journal Nature, the professor at the Technical University of Munich (TUM) applies a new computational paradigm using special circuits known as ferroelectric field effect transistors (FeFETs). Within a few years, this could prove useful for generative AI, deep learning algorithms, and robotic applications.
The basic idea is simple: unlike previous chips, where only calculations were carried out on transistors, they are now the location of data storage as well. That saves time and energy.
“As a result, the performance of the chips is also boosted,” says Hussam Amrouch, a professor of AI processor design at the Technical University of Munich (TUM).
Complimentary approaches — “HighLight” and “Tailors and Swiftiles” — could boost the performance of demanding machine-learning tasks.
Researchers from MIT
MIT is an acronym for the Massachusetts Institute of Technology. It is a prestigious private research university in Cambridge, Massachusetts that was founded in 1861. It is organized into five Schools: architecture and planning; engineering; humanities, arts, and social sciences; management; and science. MIT’s impact includes many scientific breakthroughs and technological advances. Their stated goal is to make a better world through education, research, and innovation.
Some researchers see formal specifications as a way for autonomous systems to “explain themselves” to humans. But a new study finds that we aren’t understanding.
As autonomous systems and artificial intelligence become increasingly common in daily life, new methods are emerging to help humans check that these systems are behaving as expected. One method, called formal specifications, uses mathematical formulas that can be translated into natural-language expressions. Some researchers claim that this method can be used to spell out decisions an AI will make in a way that is interpretable to humans.
Research Findings on Interpretability.
OpenAI’s first DevDay was jam-packed with updates and announcements. But according to CEO Sam Altman, we’ve yet to scratch the AI surface.
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