Lifeboat Foundation

The biggest computer chip in the world is so fast and powerful it can predict future actions “faster than the laws of physics produce the same result.”

That’s according to a post by Cerebras Systems, a startup company that made the claim at the online SC20 supercomputing conference this week.

Working with the U.S. Department of Energy’s National Energy Technology Laboratory, Cerebras designed what it calls “the world’s most powerful AI compute system.” It created a massive chip 8.5 inch-square chip, the Cerebras CS-1, housed in a refrigerator-sized computer in an effort to improve on deep-learning training models.

Here’s what the world’s space agencies hope to learn about the Red planet.

Code Unto Caesar

Durendal’s algorithm wrote scripture about three topics: “the plague,” “Caesar,” and “the end of days.” So it’s not surprising that things took a grim turn. The full text is full of glitches characteristic of AI-written texts, like excerpts where over half of the nouns are “Lord.” But some passages are more coherent and read like bizarre doomsday prophecies.

For example, from the plague section: “O LORD of hosts, the God of Israel; When they saw the angel of the Lord above all the brethren which were in the wilderness, and the soldiers of the prophets shall be ashamed of men.”

The feature could save YouTube creators from having to manually add chapters to the descriptions of their videos.

Whole-body positron emission tomography combined with computed tomography (PET/CT) is a cornerstone in the management of lymphoma (cancer in the lymphatic system). PET/CT scans are used to diagnose disease and then to monitor how well patients respond to therapy. However, accurately classifying every single lymph node in a scan as healthy or cancerous is a complex and time-consuming process. Because of this, detailed quantitative treatment monitoring is often not feasible in clinical day-to-day practice.

Researchers at the University of Wisconsin-Madison have recently developed a deep-learning model that can perform this task automatically. This could free up valuable physician time and make quantitative PET/CT treatment monitoring possible for a larger number of patients.

To acquire PET/CT scans, patients are injected with a sugar molecule marked with radioactive fluorine-18 (¹⁸ F-fluorodeoxyglucose). When the fluorine atom decays, it emits a positron that instantly annihilates with an electron in its immediate vicinity. This annihilation process emits two back-to-back photons, which the scanner detects and uses to infer the location of the radioactive decay.

Artificial intelligence is being developed that can analyze whether it’s own decision or prediction is reliable.

…An AI that is aware/determine or analyze it’s own weaknesses. Basically, it should help doctors or passengers of the AI know quickly the risk involved.

How might The Terminator have played out if Skynet had decided it probably wasn’t responsible enough to hold the keys to the entire US nuclear arsenal? As it turns out, scientists may just have saved us from such a future AI-led apocalypse, by creating neural networks that know when they’re untrustworthy.

Continue reading “Artificial Intelligence Is Now Smart Enough to Know When It Can’t Be Trusted” »

😃 KFC now has self driving 5G trucks? 😃

Autonomous 5G vehicles are getting more popular and closer to your neighborhood… Read about KFC’s trucks here.

Scholars have a nifty way of alerting colleagues to lengthy treatises that they find simply not worth their time to read.

They tag such documents “tl;dr”—too long, didn’t read.

It’s kind of a 21st century spin on the 420-year-old notion Shakespeare’s Polonius relayed to the king and queen in “Hamlet”: “Brevity,” he suggested, “is the soul of wit.”

Another great advantage is the ability to incorporate AI at early stages of image acquisition. Among other things, this enables us to reduce the amount of radiation needed to acquire a high-resolution CT or shorten the duration needed for an MRI scan. And this leads to patient welfare improvements as well as healthcare cost reductions.

AI applications

In recent years there has been tremendous work in this field mainly focusing on cardiovascular, ophthalmology, neurology, and cancer detection.