Lifeboat Foundation

The losses for short-sellers betting against Elon Musk’s electric vehicle company have ballooned to $7.6 billion over the past month, making it the least profitable short position for hedge funds, according to data from S3 Partners.

The swift one-month surge in Tesla stock has wiped out about half of the gains short-sellers made last year betting against the company. At the end of December, short-sellers had made a $15 billion profit in 2022, making Tesla the most profitable short of the year.

Shares of Tesla have been on a rollercoaster following vehicle price cuts and a weaker-than-expected fourth-quarter delivery number. But on the company’s most recent earnings call, Musk reaffirmed the company’s long-term growth target of 50%.

Google chief evangelist and “father of the internet” Vint Cerf has a message for executives looking to rush business deals on chat artificial intelligence: “Don’t.”

Cerf pleaded with attendees at a Mountain View, California, conference on Monday not to scramble to invest in conversational AI just because “it’s a hot topic.” The warning comes amid a burst in popularity for ChatGPT.

After decades of speculation, real-world artificial intelligence has finally hit a tipping point. Now that we know what AI models like ChatGPT and DALL-E can do, should we be worried?

Summary: Tracking hippocampal neurons in mice as they watched a movie revealed novel ways to improve artificial intelligence and track neurological disorders associated with memory and learning deficits.

Source: UCLA

Even the legendary filmmaker Orson Welles couldn’t have imagined such a plot twist.

Not going to happen unless some “doomsdayers” decide to take man back to analog. Perish the thought!

Which brings us to Big Blue – not Big Brother – and its move to take artificial intelligence into the cloud minus all the hardware.

Yes, IBM (and let’s not leave out Red Hat, IBM’s core cloud player) has found another way to tout its cloud computing business by creating what it calls an artificial intelligence-focused supercomputer that exists in the cloud.

Imagine you’re a young engineer whose boss drops by one morning with a sheaf of complicated fluid dynamics equations. “We need you to design a system to solve these equations for the latest fighter jet,” bossman intones, and although you groan as you recall the hell of your fluid dynamics courses, you realize that it should be easy enough to whip up a program to do the job. But then you remember that it’s like 1950, and that digital computers — at least ones that can fit in an airplane — haven’t been invented yet, and that you’re going to have to do this the hard way.

The scenario is obviously contrived, but this peek inside the Bendix MG-1 Central Air Data Computer reveals the engineer’s nightmare fuel that was needed to accomplish some pretty complex computations in a severely resource-constrained environment. As [Ken Shirriff] explains, this particular device was used aboard USAF fighter aircraft in the mid-50s, when the complexities of supersonic flight were beginning to outpace the instrumentation needed to safely fly in that regime. Thanks to the way air behaves near the speed of sound, a simple pitot tube system for measuring airspeed was no longer enough; analog computers like the MG-1 were designed to deal with these changes and integrate them into a host of other measurements critical to the pilot.

Continue reading “1950s Fighter Jet Air Computer Shows What Analog Could Do” »

After Russia launched a nearly unstoppable missile, America is hitting back with a bomber that can travel at Mach 10.

A key algorithm that quietly empowers and simplifies our electronics is the Fourier transform, which turns the graph of a signal varying in time into a graph that describes it in terms of its frequencies.

Packaging signals that represent sounds or images in terms of their frequencies allows us to analyze and adjust sound and image files, Richard Stern, professor of electrical and computer engineering at Carnegie Mellon University, tells Popular Mechanics. This mathematical operation also makes it possible for us to store data efficiently.

The invention of color TV is a great example of this, Stern explains. In the 1950s, television was just black and white. Engineers at RCA developed color television, and used Fourier transforms to simplify the data transmission so that the industry could introduce color without tripling the demands on the channels by adding data for red, green, and blue light. Viewers with black-and-white TVs could continue to see the same images as they saw before, while viewers with color TVs could now see the images in color.

One question for Brad Ringeisen, a chemist and executive director of the Innovative Genomics Institute. Founded by Nobel Prize-winning biochemist Jennifer Doudna, it aims to bridge revolutionary gene-editing tool development to affordable and accessible solutions in human health and climate.

Will CRISPR cure cancer?

We’re always thinking about: What are those targets in the future? Cancer is one of those things. The biggest impact is going to be what’s called systemic delivery, or in vivo delivery. There’s been one example of this in the community right now—to treat a liver disease. Intellia Therapeutics, a biotech company, has shown that you can actually intravenously apply CRISPR-Cas9 treatment. (CRISPR is the guide RNA, the targeting molecule, and Cas9 is the cutting molecule that edits DNA.) It can go to the liver and target the liver cells, and make edits at a high enough efficacy to treat genetic liver disease. The problem is that the liver is the easiest. It’s like the garbage can of the body. Pretty much anything that you put into the body is ultimately going to find its way to the liver. So that’s absolutely the easiest tissue to deliver to. But trying to deliver to a solid tumor, or to the brain, is much more difficult.