Lifeboat Foundation

Earlier this year, in June 2,021 the British Ministry of Defence employed Rafael’s DRONE DOME counter-UAV system to protect world leaders during the G7 Summit in Cornwall, England from unmanned aerial threats. Three years ago, Britain’s Defence Ministry purchased several DRONE DOME systems which it has successfully employed in a multitude of operational scenarios, including for protecting both the physical site and participants of this year’s G7 summit. Rafael’s DRONE DOME is an innovative end-to-end, combat-proven counter-Unmanned Aerial System (C-UAS), providing all-weather, 360-degree rapid defence against hostile drones. Fully operational and globally deployed, DRONE DOME offers a modular, robust infrastructure comprised of electronic jammers and sensors and unique artificial intelligence algorithms to effectively secure threatened air space.

Meir Ben Shaya, Rafael EVP for Marketing and Business Development of Air Defence Systems: Rafael today recognizes two new and key trends in the field of counter-UAVs, both of which DRONE DOME can successfully defend against. The first trend is the number of drones employed during an attack, and the operational need to have the ability counter multiple, simultaneous attacks; this is a significant, practical challenge that any successful system must be able to overcome. The second trend is the type of tool being employed. Previously, air defense systems were developed to seek out conventional aircraft, large unmanned aerial vehicles, and missile, but today these defense systems must also tackle smaller, slower, low-flying threats which are becoming more and more autonomous.

Training efficiency has become a significant factor for deep learning as the neural network models, and training data size grows. GPT-3 is an excellent example to show how critical training efficiency factor could be as it takes weeks of training with thousands of GPUs to demonstrate remarkable capabilities in few-shot learning.

To address this problem, the Google AI team introduce two families of neural networks for image recognition. First is EfficientNetV2, consisting of CNN (Convolutional neural networks) with a small-scale dataset for faster training efficiency such as ImageNet1k (with 1.28 million images). Second is a hybrid model called CoAtNet, which combines convolution and self-attention to achieve higher accuracy on large-scale datasets such as ImageNet21 (with 13 million images) and JFT (with billions of images). As per the research report by Google, EfficientNetV2 and CoAtNet both are 4 to 10 times faster while achieving state-of-the-art and 90.88% top-1 accuracy on the well-established ImageNet dataset.

Is Elon right Eric Klien?

It’s been nearly five years since Musk first announced the full self driving feature and very little progress has been made on it.

❤️ Check out the Gradient Dissent podcast by Weights & Biases: http://wandb.me/gd.

📝 The paper “The Relightables: Volumetric Performance Capture of Humans with Realistic Relighting” is available here:
https://augmentedperception.github.io/therelightables/

Continue reading “This AI Makes Digital Copies of Humans! 👤” »

We talk to Anil Mankar, Co-founder and Chief Development Officer at BrainChip, about artificial intelligence and neural-networking ICs.

Aggregate of labor displacement from AI-spoiler-literally EVERYTHING.

OECD experts have calculated the probability a job will be automated, on the basis of how feasible it is for technology to perform the tasks that comprise that job.

Continue reading “Are you being automated out of work?” »

[Editorial Note] This article has been planned and published as part of a series of articles related to open-source AI models and insight sharing by Sung Chang-yeop, who is a Developer Relations Engineer at Common Computer. This is the 11th article so far and its mainly about BlenderBot 2.0, a chatbot released by Facebook AI.

Get ready.

Tesla CEO Elon Musk said the company will use personal driving data to determine whether owners who have paid for its controversial “Full Self-Driving” software can access the latest beta version that promises more automated driving functions.

Musk tweeted late Thursday night that the FSD Beta v10.0.1 software update, which has already been pushed out to a group of select owners, will become more widely available starting September 24.

Continue reading “Tesla will open controversial FSD beta software to owners with a good driving record” »

The Singularity is now in private beta. But you still have to care about syntax errors.