Lifeboat Foundation

How far away could an artificial brain be? Perhaps a very long way off still, but a working analogue to the essential element of the brain’s networks, the synapse, appears closer at hand now.

That’s because a device that draws inspiration from batteries now appears surprisingly well suited to run artificial neural networks. Called electrochemical RAM (ECRAM), it is giving traditional transistor-based AI an unexpected run for its money—and is quickly moving toward the head of the pack in the race to develop the perfect artificial synapse. Researchers recently reported a string of advances at this week’s IEEE International Electron Device Meeting (IEDM 2022) and elsewhere, including ECRAM devices that use less energy, hold memory longer, and take up less space.

The artificial neural networks that power today’s machine-learning algorithms are software that models a large collection of electronics-based “neurons,” along with their many connections, or synapses. Instead of representing neural networks in software, researchers think that faster, more energy-efficient AI would result from representing the components, especially the synapses, with real devices. This concept, called analog AI, requires a memory cell that combines a whole slew of difficult-to-obtain properties: it needs to hold a large enough range of analog values, switch between different values reliably and quickly, hold its value for a long time, and be amenable to manufacturing at scale.

Here’s why you’ve been hearing so much about ChatGPT.

Researchers at the Department of Energy’s Oak Ridge National Laboratory, the University of Tennessee and Texas A&M University demonstrated bio-inspired devices that accelerate routes to neuromorphic, or brain-like, computing.

Results published in Nature Communications report the first example of a lipid-based “memcapacitor,” a charge storage component with memory that processes information much like synapses do in the brain. Their discovery could support the emergence of computing networks modeled on biology for a sensory approach to machine learning.

“Our goal is to develop materials and computing elements that work like biological synapses and neurons—with vast interconnectivity and flexibility—to enable autonomous systems that operate differently than current computing devices and offer new functionality and learning capabilities,” said Joseph Najem, a recent postdoctoral researcher at ORNL’s Center for Nanophase Materials Sciences, a DOE Office of Science User Facility, and current assistant professor of mechanical engineering at Penn State.

To get a roundup of TechCrunch’s biggest and most important stories delivered to your inbox every day at 3 p.m. PDT, subscribe here.

Why, hello there, and welcome to your Tuesday Daily Crunch. I’ll be your host this week while Haje works from an undisclosed location where day is night and night is day. If you aren’t enjoying today’s Found podcast about tampons, we hope you at least saw stars at the TC Sessions: Space event. Let’s dig into some news! — Christine.

The new guidelines provide restrictions and regulations for creators submitting art.

Adobe has now started accepting AI-generated stock images on its platform, but with regulations. The company updated its guidelines.

Image credit: Left: Adobe Stock / Art Master, Middle: Adobe Stock /Robert Kneschke, Right: Adobe Stock / Forest Spirit.

Continue reading “Amplifying human creativity: Adobe Stock defines new guidelines for content made with generative AI” »

It can be specifically useful in the robotics and manufacturing industries.

Researchers from the University of Minnesota, Twin Cities, use ultrasound waves to move objects hands-free, according to an institutional press release.

Continue reading “An innovative method allows researchers to move objects using ultrasound waves” »

The car will allegedly have less ambitious self-driving capabilities initially and it’s debut date has been pushed back to 2026.

Apple’s ambitious electric vehicle (EV) will allegedly have fewer self-driving capabilities for its launch date, the latter of which has been pushed back by a year, from 2025 to 2026, according to a Bloomberg.

The car is still in the pipeline and is reported to be set up with more conventional car features and designs than other autonomous EVs.

Continue reading “Apple’s self-driving car debut pushed back and may be less advanced” »

The application has registered one million plus downloads since its launch.

Inquiries for OpenAI’s ChatGPT, a dialogue-based AI chatbot, are going through the roof. The rising interest in the application can be attributed to some of its entertaining responses to users’ queries, which has lately created a storm on Twitter.

ChatGPT is not your typical chatbot featured in every customer service portal corner.

Continue reading “ChatGPT; 8 coolest ways to use OpenAI’s viral application” »

The merged computing power can give rise to faster and more accurate machine learning applications.

Last month, LUMI, the fastest supercomputer in Europe, was connected to HELMI, Finland’s first quantum computer, a five-qubit system operational since 2021. This makes Finland the first country in Europe to have created such a hybrid system — it is one of the few countries worldwide to have done the same.

LUMI is famous — the supercomputer ranks third in the latest Top 500 list of the world’s fastest supercomputer and can carry out 309 petaflops. LUMI, too became operational in 2021.

Continue reading “Europe’s fastest supercomputer just connected to a quantum computer in Finland — here’s why” »