AI Language models are taking over the world by storm. Every other day, we hear research being conducted using ChatGPT-based models. For instance, an engineer recently integrated ChatGPT with Boston Dynamics’ Robot Dog, Spot. In another piece of news, an AI based on the GPT-4 model was being used to plan Defense and War Strategies.

The Breakthrough can help Patients with Locked-in Syndrome

Now, another recent breakthrough achieved by researchers at the University of Texas at Austin in decoding functional magnetic resonance imaging (fMRI) signals of the human brain using a neural network marked a significant step forward in the field of neuroscience. The use of GPT-1 model in analyzing fMRI data and decoding cortical semantic representation of continuous language opens up new avenues for the development of non-invasive methods of exploring the brain’s neural activity.

This research has great potential to help patients with conditions such as locked-in syndrome, where patients are unable to communicate due to paralysis. The use of non-invasive methods for decoding the neural activity of the brain could provide a means for patients to communicate with others and express their thoughts, thereby enhancing their quality of life.

Furthermore, this research also has the potential to revolutionize the field of artificial intelligence by enabling machines to better understand human language and communication. The ability of the neural network to decode the brain’s semantic representation of language could have far-reaching implications for natural language processing and the development of conversational AI.

The breakthrough achieved by the researchers at the University of Texas at Austin is a significant step forward in the field of neuroscience and has the potential to benefit both patients and the development of artificial intelligence. The use of non-invasive methods for decoding neural activity in the brain has enormous potential for future research and could lead to significant advancements in our understanding of the brain and its functions.

RELATED:

• Microsoft plans to sell private ChatGPT to businesses, a pricey but secure alternative
• ChatGPT returns to Italy after addressing data privacy concerns
• Best ChatGPT Prompts for Web Developers

(Via)

The post GPT-based AI Neural Network Decodes Brain Activity without Surgery appeared first on Gizmochina.

Artificial intelligence has come a long way since its inception, but it still has a long way to go before it can truly replicate human intelligence. However, recent breakthroughs in nanotechnology have paved the way for the development of AI systems that are capable of learning and remembering in ways that were previously thought to be exclusive to the human brain. Memories are stored in the brain as patterns of activity across these neural networks. When a memory is formed, certain neurons are activated and connections between them are strengthened. When the memory is recalled, those same neurons are activated again, reactivating the same pattern of neural activity. The brain also has the ability to consolidate memories over time, strengthening the connections between neurons and making memories more resistant to decay. The exact mechanisms of memory formation and recall are still not fully understood, but advances in neuroscience and AI research are shedding new light on this complex process.

Researchers try to Mimic Neural Networks for Nanowire Tech

Researchers at the University of Sydney have found that nanowire networks have the ability to simulate high-level cognitive functions that are typically associated with the human brain. The networks, made up of highly conductive silver wires that are covered in plastic material and formed into a network that can self-assemble into a dynamically complex network with memory and processing capabilities, were able to learn and remember like the human brain in tests. By manipulating the voltages in the networks, the researchers enhanced their memory capacity and accuracy to the point where they were able to “remember” the endpoint of seven steps ahead in the circuit, comparable to human memory.

This breakthrough could have a wide range of applications in AI, from the development of autonomous vehicles to the creation of more advanced healthcare systems. However, it also raises important ethical questions about the future of AI and the role that technology will play in our lives. As AI systems become more advanced, it is important to consider the potential risks and benefits of these technologies and to ensure that they are developed in a responsible and ethical manner.

RELATED:

• ChatGPT Makes Waves in Yokosuka: First AI Chatbot Used in Japanese Municipality Offices
• Xiaomi 13 Ultra Repairs Come with a Hefty Price Tag
• Best Keyboard for iPad 2023 – Apple, Logitech & More

(Via)

The post Nanowire AI Networks Mimic Human Brain’s Learning and Memory Abilities appeared first on Gizmochina.

U.S fabless chipmaker Qualcomm first announced its new Snapdragon 700 series at MWC 2018 with the Snapdragon 710 being the first of the series to find its way into smartphones. The new SDM700 series lies in between the flagship Snapdragon 800 series and the premium mid-range Snapdragon 600 series. It draws a number of advanced features from the former and is very suitable for high-end models.

Apart from the Snapdragon 710, little is known of other members of the series but a new rumour has emerged which deals with the Snapdragon 720. While there is presently no information on the specification of the Snapdragon 720, it is only known to be an enhanced version of the Snapdragon 710. However, the SDM720 is said to have a Neural Processing Unit (NPU) similar to Huawei’s Kirin 970 which is dedicated to AI acceleration. If this turns out to be true, it will be the first time Qualcomm as the current Snapdragon platform doesn’t have a dedicated AI hardware unit but rather relies on the Artificial Intelligence Engine(AIE). This is software-based and the efficiency in the specific AI scene is still low.

In addition to Snapdragon 720, there had been a leaked poster that appeared a few months back containing details of the Snapdragon 730. The earlier leak tipped that Qualcomm’s SDM730 will be manufactured using a Samsung 8nm LPP process (10nm upgrade), integrating two Kryo 4xx 2.3GHz, six Kryo 4xx 1.8 GHz CPU core and specially equipped with NPU 120 unit!

Related: Mysterious Snapdragon 680 Appears on Geekbench with Impressive Scores

Finally, the new rumour also includes that at least three mobile phone manufacturers are currently developing Snapdragon 720-powered models, of which Samsung is expected to be the first to utilise the chipset on its mid-range Galaxy series.

(source)

The post Snapdragon 720 rumoured to feature a dedicated NPU for AI just like Kirin 970! appeared first on Gizmochina.