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Category: robotics/AI – Page 1,660

Can an AI-powered insect trap solve a $220 billion pest problem?

Pests destroy up to 40% of the world’s crops each year, causing $220 billion in economic losses, according to the UN Food and Agriculture Organization (FAO). Trapview is harnessing the power of AI to help tackle the problem.

The Slovenian company has developed a device that traps and identifies pests, and acts as an advance warning system by predicting how they will spread.

“We’ve built the biggest database of pictures of insects in the world, which allows us to really use modern AI-based computing vision in the most optimal way,” says Matej Štefančič, CEO of Trapview and parent company EFOS.

Deepmind’s new video game AIs learn from humans

Deepmind introduces a new research framework for AI agents in simulated environments such as video games that can interact more flexibly and naturally with humans.

AI systems have achieved great success in video games such as Dota or Starcraft, defeating human professional players. This is made possible by precise reward functions that are tuned to optimize game outcomes: Agents were trained using unique wins and losses calculated by computer code. Where such reward functions are possible, AI agents can sometimes achieve superhuman performance.

But often – especially for everyday human behaviors with open-ended outcomes – there is no such precise reward function.

Ubisoft’s New AI: Breathing Life Into Games!

11/26/22

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Microsoft Uses Transfer Learning to Train Autonomous Drones

Originally published on Towards AI the World’s Leading AI and Technology News and Media Company. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. At Towards AI, we help scale AI and technology startups. Let us help you unleash your technology to the masses.

The model is able to transfer knowledge between a simulated environment and real-world settings.

Researchers are building robots that can build themselves

Researchers at MIT’s Center for Bits and Atoms are working on an ambitious project, designing robots that effectively self-assemble. The team admits that the goal of an autonomous self-building robot is still “years away,” but the work has thus far demonstrated positive results.

At the system’s center are voxels (a term borrowed from computer graphics), which carry power and data that can be shared between pieces. The pieces form the foundation of the robot, grabbing and attaching additional voxels before moving across the grid for further assembly.

The researchers note in an associated paper published in Nature, “Our approach challenges the convention that larger constructions need larger machines to build them, and could be applied in areas that today either require substantial capital investments for fixed infrastructure or are altogether unfeasible.”

Robotics Breakthrough Builds Anything

MIT researchers have devised an algorithm using voxels robotics devices to build anything from houses to planes to cars and even other robots by using a grid system that transfers knowledge to determine when to build what, and when to build other robot builders. New Google Deepmind video game artificial intelligence develops agents that can talk, listen, ask questions, navigate, search and retrieve information, control things, and do a range of other intelligent tasks in real-time. New Non-invasive brain computer interface device transmits information through optic nerve to compete with Neuralink BCI.

Tech News Timestamps:
0:00 Robotics Breakthrough Builds Anything — Even Robots.
2:44 New Google Deepmind Video Game AI
5:25 New Neuralink BCI Competitor.

#robot #ai #neuralink

How Will AI And 5G Power the Next Wave Of Innovation?

The combined force of these disruptive technologies (AI and 5G) enables fast, secure, and ubiquitous connectivity of cost-efficient smart networks and IoT (Internet-of-Things) devices. This convergence point is essential to concepts like intelligent wireless edge.

5G and AI, the connected digital edge

Artificial intelligence and 5G are the two most critical elements that would empower futuristic innovations. These cutting-edge technologies are inherently synergistic. The rapid advancements of AI significantly improve the entire 5G ecosystem, its performance, and efficiency. Besides, 5G-connected devices’ proliferation helps drive unparalleled intelligence and new improvements in AI-based learning and inference. Moreover, the transformation of the connected, intelligent edge has commenced as on-device intelligence has garnered phenomenal traction. This transformation is critical to leveraging the full potential of 5G’s future. With these prospects, these technologies hold enough potential to transform every industry. Here’s how the combination of AI and 5G has been reshaping industries.

Google AI Introduces ‘SegCLR,’ a Self-Supervised Machine Learning Technique that Produces Highly Informative Representations of Cells Directly from 3D Electron Microscope Imagery and Segmentations

If we can analyze the organization of neural circuits, it will play a crucial role in better understanding the process of thinking. It is where the maps come into play. Maps of the nervous system contain information about the identity of individual cells, like their type, subcellular component, and connectivity of the neurons.

But how do we obtain these maps?

Volumetric nanometer-resolution imaging of brain tissue is a technique that provides the raw data needed to build these maps. But inferring all the relevant information is a laborious and challenging task because of the multiple scales of brain structures (e.g., nm for a synapse vs. mm for an axon). It requires hours of manual ground truth labeling by expert annotators.

History Of AI In 33 Breakthroughs: Digital Storage

On September 14, 1956, IBM announced the 305 and 650 RAMAC (Random Access Memory Accounting) “data processing machines,” incorporating the first-ever disk storage product. The 305 came with fifty 24-inch disks for a total capacity of 5 megabytes, weighed 1 ton, and could be leased for $3,200 per month.

In 1953, Arthur J. Critchlow, a young member of IBM’s advanced technologies research lab in San Jose, California, was assigned the task of finding a better data storage medium than punch-cards.

The information explosion (a term first used in 1941, according to the Oxford English Dictionary) has turned into the big digital data explosion. And the data explosion enabled deep learning, an advanced data analysis method, to perform today’s AI breakthroughs in image identification and natural language processing.

The RAMAC became obsolete within a few years of its introduction as the vacuum tubes powering it were replaced by transistors. Today, disk drives still serve as the primary containers for digital data, but solid-state drives (flash memory), first used in mobile devices, are fast replacing disk drives even in today’s successors of the RAMAC, supporting large-scale business operations.

Whatever form the storage takes, IBM created in 1956 new markets and businesses based on fast access to digital data. As Seagate’s Mark Kryder asserted in 2006: “Instead of Silicon Valley, they should call it Ferrous Oxide Valley. It wasn’t the microprocessor that enabled the personal video recorder, it was storage. It’s enabling new industries.”

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